Radiology Research Forum

Radiology research forum is an ongoing lecture series held approximately every two weeks at our Center.

The forum rotates among lectures by distinguished visiting researchers, presentations by partners involved in collaborative projects with our faculty, and research reports by scientists from the radiology department at NYU Langone Health, which operates our Center.

Many but not all of the lectures comprise the Seminar in Biomedical Imaging (BMSC-GA 4416), part of the Biomedical Imaging and Technology PhD Training Program

Most talks are given at noon on Tuesdays or Thursdays. Unless otherwise noted, the forum is held in the conference room on the fourth floor of our headquarters at 660 First Avenue in Manhattan.

For the time being, all research lectures are conducted via Webex. To request an invitation, get in touch with Rania Assas.

Wednesday, April 7, at 12:30 p.m.

Li Feng, PhD

Assistant Professor
Icahn School of Medicine at Mount Sinai

GRASP MRI: Past, Present and Future

Abstract: The GRASP project, started from 2011, is 10 years old today! GRASP MRI represents years of innovation and efforts by a research team consisting of MRI physicists, clinician scientists and industry partners. To date, GRASP MRI has been successfully demonstrated in many clinical applications; its overall performance has been greatly improved after years of optimization; and it has also been extended to a number of new variants. In this talk, Li will take this opportunity to summarize the GRASP developments over the past decade and to discuss future directions that GRASP MRI could potentially be heading to. Of course, in the era of artificial intelligence, how to make a smart version of GRASP by incorporating the latest deep learning technology is an important question we have to think and plan. If you are interested in hearing the latest of this project, you won’t want to miss this story.

About the speaker: Dr Li Feng is currently an Assistant Professor of Radiology at the BioMedical Engineering and Imaging Institute (BMEII) at the Icahn School of Medicine at Mount Sinai, 60 blocks north of NYU. Li completed his Master and PhD studies (2008-2015) and postdoctoral training (2015-2018) all at NYU School of Medicine. Li’s research has been centered on GRASP MRI and he has been dedicated to optimizing and improving this technique since his early PhD study. Li is a Junior Fellow of ISMRM (2015) and was a winner of the Early Career Award (Young Investigator Award) from the Society for Cardiovascular Magnetic Resonance (SCMR) (2014). As an alumnus of NYU and CBI, Li is very excited to come back for a visit, and he is very much looking forward to virtually meeting all the NYU friends and colleagues

Tuesday, March 30, at noon.

Anna Chen, BS

Graduate Student, Biomedical Imaging nad Technology
Vilcek Institute of Graduate Biomedical Sciences
NYU Grossman School of Medicine
Reproducibility of 1H MRSI in Mild Traumatic Brain Injury

Abstract: Traumatic brain injury (TBI) is a global health concern, with mild TBI (mTBI) accounting for 60%-80% of cases. TBI sequelae can be histologically explained by axonal varicosities known as diffuse axonal injury, but this pathology is not detectable using conventional CT and MRI. 1H MRS is a technique sensitive to neurochemical alterations which may enable more precise evaluation of TBI severity and prognostication when macroscopic structural damage is lacking. Unfortunately, varying results in regard to which metabolite(s) are most likely to be affected and what brain region(s) should be sampled, contribute to the limited clinical use of MRS in TBI. 1H MRSI has shed light on the regional distribution of metabolite findings, but a key part of translating the new knowledge to the clinic rests on determining how reproducible are the results of any particular study. This talk will present 1) initial data from a project intending to test the reproducibility of 1H MRSI findings from previous studies with a different mTBI cohort, 2) an outlook on future directions, as well as 3) recent findings from sodium imaging.

About the speaker: Anna Chen is a second-year PhD student, advised by Ivan Kirov, PhD. She has a background in cognitive neuroscience, and is interested in using and improving MRS techniques to better understand brain metabolism in disease.

Wednesday, March 17, at 1:00 p.m.

Nima Gilani, PhD

Postdoctoral Researcher
Previously at the Department of Cognitive Neuroscience, Maastricht University
Microstructure of the cortical grey matter

Abstract: Neurodegenerative diseases such as Alzheimer’s disease cause changes and disruption to cortical microstructure and architecture. MRI could potentially be sensitive to such changes. There is a growing interest in modelling human cortical areas using a combination of quantitative MRI and 3D microscopy ex vivo. This presentation contains a brief review of MR modalities that could be used for this purpose in addition to a Monte Carlo simulation study of DWI in light fluorescence microscopy samples.

About the speaker: Nima is a multi-disciplinary researcher with a background in MR physics, electrical and nuclear engineering, and medical image analysis. He received his PhD in MRI of prostate cancer from University of East Anglia in 2016. His most recent postdoc at Maastricht University (2017-2019) was regarding microstructural characterization of the cortical grey matter using MRI and light fluorescence microscopy.

Tuesday, March 16th at noon

Jungkyu Park, MS

Doctoral Candidate, Biomedical Imaging nad Technology
Vilcek Institute of Graduate Biomedical Sciences
NYU Grossman School of Medicine
Building deep neural networks to find small lesions from hundreds of millions of pixels

Abstract: Our effort at NYU School of Medicine towards building deep neural networks for Digital Breast Tomosynthesis (DBT) volumes ranked #1 at the DBTex challenge. In this international challenge, we built an AI system to find biopsy-proven lesions from the DBT volumes collected from the Duke University Hospital. In this talk, I will discuss how our team was able to reach the best performance on the external dataset by utilizing our own private datasets at NYU Langone and how the model outputs could benefit the radiologists.

About the speaker: Speaker bio

Wednesday, March 3, at 2:00 p.m.

Galit Pelled, PhD

Chief, Division of Neuroengineering, Institute for Quantitative Health Science and Engineering
Michigan State University
East Lansing, MI
Neuromodulation technologies for restoring and augmenting neuro-performance
Tuesday, March 2, at noon

Chenyang Li, MS

Doctoral Candidate, Biomedical Imaging and Technology
Vilcek Institute of Graduate Biomedical Sciences
NYU Grossman School of Medicine
Measuring Apparent Water Exchange in Post-mortem Mouse Brains using Filter Exchange Imaging and Diffusion Time Dependent Kurtosis Imaging

Abstract: Water exchange between compartments in the brain (e.g., the vascular, ventricular, extracellular, and intracellular spaces) is a crucial biological process for maintaining homeostasis and may serve as a biomarker for diagnosis of structural and functional deficits. FEXI and DKI(t) are promising diffusion MRI techniques for measuring apparent exchange in the brain. FEXI employs a double-diffusion-encoding scheme to filter tissue compartment based on differences in diffusivities and measures the recovery in diffusion measurements over an increasing mixing time, characterized by Apparent Exchange Rate (AXR). DKI(t), on the other hand, measure apparent exchange based on its effects on the asymptotic decay of diffusion kurtosis described by the Kärger model. In this study, we investigated the relationship between FEXI and DKI(t) based measurements of apparent exchange in post-mortem mouse brains and elucidated its confounding factors in determining the desired exchange process.

About the speaker: Chenyang Li is a 3rd year PhD candidate in Vilcek Institute of Biomedical Science under the supervision of Prof. Jiangyang Zhang and Dr. Yulin Ge. He had a background in Chemical and Biomolecular Engineering before entering the field of MRI. His research interests involve using advanced MRI techniques to evaluate the microstructural integrity and vascular functions in both animal models and human studies.

Wednesday, February 24, at 2:00 p.m.

Jadranka Stojanovska, MD, MS

Clinical Assistant Professor, Radiology
Director, Cardiac MRI Service, Cardiothoracic Radiology Division
University of Michigan
Fat or Fit: Focus on Epicardial Adiposity Phenotypes

Abstract: The parallel growth of obesity and diabetes has escalated over the last four decades placing over 1.9 billion overweight and obese individuals at increased risk of developing cardiovascular disease (CVD). This risk has been attributed to the pressure of a low-grade inflammatory state, but the mechanism underlying the inflammation is unclear. An increased epicardial adipose tissue volume or thickness quantified by echocardiography, computed tomography (CT) or magnetic resonance (MR) has been shown to correlate with cardiovascular disease and diabetes independent of anthropometric measurements such as body mass index. However, in visceral obesity, epicardial adipose tissue can assume a white adipose phenotype that is hypothesized to be associated with proinflammatory markers. The white adipose tissue may precede the accumulation of fat and increase in epicardial adipose volume. The objectives for this talk are to discuss the current theories of defining cardiovascular or cardiometabolic risk, what research has been done by others and our group that could leverage future utilization of imaging as a surrogate marker of identifying patients at risk for adverse CVD outcome. We will emphasize the research performed by our group to understand the correlation between the increased epicardial edipose fat fraction quantified by water-fat imaging and coronary artery disease including tissue inflammation defined by lipidome and transcriptome profiling in patients undergoing open-heart surgery. Epicardial, extrapericardial, and subcutaneous depots expressed different imaging, lipidome and transcriptome signatures. Furthermore, increased epicardial fat fraction positively correlated with coronary artery disease, tissue ceramides, a pro-inflammatory lipids, and proinflammatory gene expressions. We will discuss research questions and future direction of utilizing epicardial fat fraction to risk stratify CVD patients and monitor therapeutic response.

About the speaker: Dr. Jadranka Stojanovska is an Assistant Professor of Radiology, a board-certified diagnostic radiologist, and a fellowship trained cardiothoracic radiologist. She holds the position of Director of Cardiovascular MR at the University of Michigan and provides excellence in patient care through collaboration with scientists, physicians, and technologists. This opportunity has allowed her to develop skill sets in building teams to solve logistic problems and address the needs of Michigan Medicine enterprise. Following her international medical training and radiology residency, she completed a post-doctoral research fellowship, a clinical cardiothoracic radiology fellowship, and a Master in Science program in Clinical Research and Statistical Design from the University of Michigan. Gearing towards physician scientist pathway, she completed competitive training grants such as General Electric Radiology Research Academic Fellowship, NIH sponsored Post-Doctoral Translational Science Program, and KL2 to study epicardial adiposity phenotypes. Her research focus is on translational imaging and disease outcomes using quantitative imaging in risk stratification and therapeutic efficacy assessment of cardiovascular diseases. She has authored and co-authored more than 50 peer-reviewed publications and more than 150 scientific abstracts. She is an avid teacher and has given numerous lectures around the world. She is a recipient of many awards including Excellence in Teaching from Radiology Residents and Medical Students. Nationally, she serves on cardiac imaging committees including ACR Appropriateness Criteria Expert Panel in Cardiac Imaging, Women in SCMR, and RSNA Scientific Abstract Committee. She serves as a reviewer for many imaging journals, PCORI, and NIH. Internationally, she facilitates building CMR programs through education, advocacy, research, and clinical excellence. She enjoys her time with family, martial arts, playing piano, and traveling.

Tuesday, February 16, at noon

Faye McKenna, MS

PhD Candidate in Biomedical Imaging & Technology
Lazar Translational Brain Imaging Lab
New York University Vilcek Institute of Graduate Biomedical Sciences
Microvascular and Microstructural Changes in Psychotic Spectrum Disorders Relate to Cognition, Disease Duration and Metabolites: A Multiparametric Imaging Study

Abstract: Previous research has suggested both perfusion and free water (FW) alterations in Psychotic Spectrum Disorders (PSD), assessed independently of each other. To study PSD neuropathology, we applied a three-compartment IVIM-FWI model which disentangles FW diffusion and perfusion along with an anisotropic diffusion tissue compartment. The estimation of each of these metrics may be affected when the effects of the other are not taken into consideration. Previous histological studies have suggested an array of microvascular and microstructural deficits likely to impact perfusion and FW in PSD, including increased inflammation, morphological differences in capillaries, and disruptions in the neurovascular unit cells and the blood brain barrier. The aim of this research was to evaluate, for the first time, if the three compartment IVIM-FWI model can describe microvascular and microstructural changes in PSD in both gray and white matter. Additionally, we examined the relationships between the IVIM-FWI derived measures of perfusion fraction (PF), FW, and fractional anisotropy of tissue (FAt) and psychosis duration, cognition, and MR spectroscopy metabolites.

About the speaker: Faye McKenna is a fourth-year PhD candidate in the Lazar Translational Brain Imaging Lab and NYU Grossman School of Medicine's Biomedical Imaging and Technology PhD Training Program. She is advised by Mariana Lazar, PhD. McKenna's research focuses on applying diffusion MRI models to better understand neuropsychiatric disease.

Thursday, December 17, at 2:00 p.m.

Tianrui Luo, MSE

PhD Candidate
Functional MRI Lab
University of Michigan
MRI reconstruction and pulse design for accelerated neuroimaging

Abstract: Pulse design and reconstruction are two important topics in MR research for enabling faster imaging. On the pulse design side, selective excitations that confine signals to be within a small ROI instead of the full imaging FOV can promote sampling sparsity in the k-space, as a direct outcome of the change of the corresponding Nyquist sampling rate.

On the reconstruction side, besides improving algorithms’ capability on restoring images from less data, another objective is to reduce the reconstruction time, particularly for dynamic imaging. This talk presents our developments on these two perspectives: The first part introduces a pulse design framework built on our efficient auto-differentiable Bloch simulator. By propagating the derivatives in an automatic way, this tool connects excitation objectives (e.g., accuracy) directly to the pulse waveforms to be designed without approximations such as the small-tip model. It enables us to address excitation losses that are previously not approachable. We apply this tool on outer volume saturated inner volume imaging, which confines imaging signals into an ROI by selectively spoiling spin magnetizations outside.

About the speaker: Tianrui Luo is a PhD student in the functional MRI lab, University of Michigan. He is advised by Dr. Jon-Fredrik Nielsen, and Dr. Douglas Noll. His research focuses on MR image reconstruction and pulse design.

Tuesday, November 24, at 10:00 a.m.

Joao Periquito, MSE

PhD Candidate
Max-Delbrück-Centrum für Molekulare Medizin
Berlin Ultrahigh Field Facility
MRI Assessment of Renal Tubular Volume Fraction with DWI-Continuum Modeling

Abstract: Renal tissue hypoxia is considered to be an important factor in the development of numerous acute and chronic kidney diseases. Blood oxygenation sensitized MRI can provide quantitative information about changes in renal blood oxygenation via mapping of T2*. Simultaneous MRI and invasive physiological measurements in rat kidneys demonstrated that changes in renal T2* do not accurately reflect renal tissue oxygenation under pathophysiological conditions. Confounding factors that should be taken into account for the interpretation of renal T2* include renal blood volume fraction and tubular volume fraction. Tubuli represent a unique structural and functional component of renal parenchyma, whose volume fraction may rapidly change, e.g., due to alterations in filtration or tubular outflow.

Diffusion-weighted imaging (DWI) provides a method for in-vivo evaluation of water mobility. In the kidneys intravoxel incoherent water motion may be linked to three different sources: i) renal tissue water diffusion, ii) blood perfusion within intrarenal microvasculature and iii) fluid in the tubules. The latter provides means to probe for changes in the tubular volume fraction. Recognizing this opportunity this presentation examines the feasibility of assessing tubular volume fraction changes using the non-negative least squares (NNLS) analysis of DWI data.

About the speaker: João Periquito is currently finishing his PhD in the field of renal MR imaging at Berlin Ultrahigh Field Facility (B.U.F.F.) - Max Delbrueck Center (MDC), Berlin, Germany. His research has focused on the development of new diagnostic techniques for renal MRI. During his PhD, he created a DW split-RARE sequence on a preclinical scanner and used it to disentangle the different components responsible for renal diffusion decay together with a continuum modelling approach. In addition to the pursuit of his PhD, he was involved in the creation of several chapters of a staple protocols book - Preclinical MRI of the Kidney: Methods and Protocols, sponsored by PARENCHIMA. João is also involved in the project Open Source Imaging Initiative (, a creative community of volunteers with the aim of facilitating medical devices to more people all around the world.

Thursday, October 29th at 9:00 a.m.

Hongyu An, PhD

Associate Professor of Radiology
MIR, Mallinckrodt Institute of Radiology
Washington University School of Medicine in St. Louis
PET/MR Attenuation Correction

About the speaker: speaker bio

Wednesday, October 28, at 2:00 p.m.

Jason Stockmann, PhD

Assistant Professor
Department of Radiology
Massachusetts General Hospital
Beyond B0 shimming: Emerging applications for local magnetic field control in MRI

Abstract: This talk will explore new ways to use local magnetic field control besides conventional “B0 shimming”. Perturbations of the main magnetic field (“B0”) due to tissue susceptibility interfaces are a long-standing obstacle in Magnetic Resonance applications. Inhomogeneous B0 fields can lead to artifacts such as geometric distortion, signal voids, poor RF pulse performance, and spectral line broadening. This has limited the use of diffusion, functional, and spectroscopic MR imaging in many regions of the brain and body. Recently, it has been shown that multi-coil arrays of independently-driven loops placed close to the body can generate nonlinear, high spatial-order field offsets to “shim out” unwanted susceptibility fields on a subject-specific basis, benefiting field homogeneity and image quality. In this talk, we explore the potential for repurposing multi-coil shim arrays for new applications that exploit their nonlinear, rapidly-switchable local field offsets. Examples include tailored field offsets for improved lipid suppression in MR spectroscopic imaging; zoomed functional MRI of target brain anatomy; flip angle correction at ultra-high field; and supplementary spatial encoding for improved parallel imaging. We will also explore ways to add local field control capability to coil arrays originally designed for other applications, such as RF receive arrays and Transcranial Magnetic Stimulation probe arrays, so that their degrees of freedom can be brought to bear.

About the speaker: speaker bio

Wednesday, October 21, 2:00 p.m.

Corree Laule, PhD

Associate Professor
University of British Columbia
Myelin Water Imaging: Past, Present & Future

Abstract: The presentation will provide a broad overview of the history of myelin water imaging in humans. Myelin water imaging is based on measurement of the short T2 component of water in brain and spinal cord tissue. What began as a lengthy single slice, single center measurement has expanded to many countries on multiple continents in just over 25 years. Important work along the way has included post-mortem validation studies in human CNS tissue, comprehensive assessment of development and normal characterization in adults, as well application to many neurological diseases including multiple sclerosis, concussion, stroke and beyond. The creation of normative atlases and development of faster analysis approaches promises to help move myelin water imaging to clinic in the coming decade.

About the speaker: Dr. Cornelia (Corree) Laule is a physicist and has been using NMR and MRI to conduct brain and spinal cord research for over two decades, with an emphasis on myelin imaging. After a PhD in MR physics, she completed a post-doctoral fellowship in neuropathology where her research focused on MRI-pathology correlation studies in multiple sclerosis (MS) brain tissue. She is now an Associate Professor at the University of British Columbia, and an Associate Director of the International Collaboration on Repair Discoveries (ICORD). She is interested in understanding the microstructural and pathological determinants which govern MRI signal changes in central nervous system (CNS) tissue. Her primary areas of research are MS and spinal cord injury, and she has extensive experience in imaging both in vivo and post mortem brain and spinal cord. She also has conducted research many other CNS applications including schizophrenia, cervical spondylotic myelopathy, PKU, Krabbe Disease, Hungtington's Disease, depression, brain tumours, vascular cognitive impairment, development, aging, dyslexia, and dyscalculia, as well the characterization of normal controls. She is particularly interested in myelin and hopes to use biochemical analysis and electron microscopy to understand how variations in myelin composition and structure may influence to MRI measures. For further information regarding Dr. Laule’s research, please visit and follow her on twitter @mripathology

Wednesday, September 30, at 2:00 p.m.

Wafaa Sweidan, MS

Ph.D. Candidate in Translational Neuroscience Program
Graduate Research Fellow
Sastry Foundation Advanced Imaging Laboratory
Department of Psychiatry and Behavioral Neurosciences
Wayne State University
Detroit, MI
Investigating Cortical Microstructure in Parkinson Disease Patients Using Diffusion Magnetic Resonance Imaging

Abstract: Parkinson disease (PD) is a neurodegenerative disorder characterized pathologically by nigrostriatal dopaminergic terminal loss and the development of Lewy pathology in surviving neurons of the substantia nigra (SN). Lewy pathology extends beyond the SN, and can be found in limbic and prefrontal cortical regions associated with cognitive decline. In vivo assessment of cortical microstructure and the extent of pathological changes will be clinically useful to monitor disease progression. For this purpose, our study used two diffusion MRI models, diffusion tensor imaging and neurite orientation dispersion and density imaging, to study the microstructural changes in the cerebral cortex of PD participants (n=18) compared to healthy controls (n=8). We demonstrate that in the absence of cortical thinning, PD pathology is associated with significant abnormalities in cortical diffusion metrics. Specifically, we found that the anterior cingulate cortex and inferior temporal lobe are consistently involved in PD through reductions in the intracellular volume fraction, fractional anisotropy (FA) and increased orientation dispersion index. FA reductions were extensive and involved more limbic areas such as entorhinal cortex, parahippocampus and insula. These findings are consistent with the presence of Lewy pathology in limbic regions and might be reflecting the earliest stages of tissue involvement in PD.

Tuesday, September 29, at 2:00 p.m.

Nicole Seiberlich, PhD

Associate Professor
Department of Radiology
University of Michigan
Cardiac Magnetic Resonance Fingerprinting

Abstract: Cardiovascular Magnetic Resonance (CMR) is a valuable tool that enables non-invasive characterization of tissue and assessment of cardiac function. Parametric mapping techniques play an important role in CMR due to their sensitivity to physiological and pathological changes in the myocardium. The capability of mapping T1 and T2 simultaneously in a single scan makes the novel cardiac Magnetic Resonance Fingerprinting (cMRF) technique a promising technology to facilitate diagnosis and treatment evaluation in various cardiac diseases. Unlike conventional parametric mapping approaches which may yield different T1 or T2 values for the same subject depending on the specifics of the MRI system hardware or pulse sequence implementation, cMRF has the potential to offer reproducible measurements of tissue properties on all MRI scanners. This talk aims to introduce the basics of the cMRF technique, including pulse sequence design, dictionary generation, and pattern matching, as well as highlighting potential applications.

About the speaker: Nicole Seiberlich is the Co-Director of the Michigan Institute for Imaging Technology and Translation and Associate Professor of Radiology at the University of Michigan in Ann Arbor. Prior to this role, she was the Elmer Lincoln Lindseth Associate Professor of Biomedical Engineering at Case Western Reserve University. She received her BS in Chemistry from Yale University in 2001, and completed her PhD thesis at the University of Wuerzburg on the topic of novel Magnetic Resonance Imaging techniques in 2008. Her work in rapid MRI is funded by the NIH and NSF. Nicole is a member of the Editorial Board for Magnetic Resonance in Medicine and serves as an Associate Editor for IEEE Transactions in Medical Imaging. She has been a member of the Board of Trustees of the ISMRM since 2016, and has served on and chaired multiple committees for both the ISMRM and the SCMR. Most recently Nicole has been selected as the Program Chair for the ISMRM Annual Meeting in 2021, to be held in Vancouver, Canada. She has published more than 60 peer-reviewed manuscripts on the topics of rapid and quantitative MRI, and has been invited to give more than 75 lectures, including the ISMRM/NIBIB New Horizons Lecture. In addition to her professional activities, she has won a number of awards for teaching and mentorship, including the CWRU Diekhoff Award for Excellence in Graduate Mentorship.

Wednesday, September 22, at 2:00 p.m.

Andrew Webb, PhD

Professor, Director C.J.Gorter Center for High Field MRI
Department of Radiology
Leiden University Medical Center
Low field MRI: hardware, data acquisition, image processing, sustainability and in vivo applications

Abstract: Commercial magnetic resonance imaging (MRI) systems cost millions of euros to purchase, require large electromagnetically shielded spaces to house, are extremely expensive to maintain and require highly trained technicians to operate. These factors together means that their distribution is confined to centrally-located medical centres in large towns and cities. Globally over 70% of the world’s population has absolutely no access to MRI, and clinical conditions which could benefit from even very simple scans cannot be treated. In the financially developed world, although MRI is diagnostically very important, the high cost and fixed nature prohibits any type of role in widespread health screening, for example. The magnetic fields typically used are very high, which means that there are severe contraindications so that, for example, MRI cannot currently be used in the emergency room. From the considerations above it is clear that if low-field MRI could be made more portable, accessible and sustainable then it would open up new opportunities in both developed and developing countries.

Rather than designing a highly sophisticated and expensive piece of equipment that can be used for all types of scanning, we use the philosophy of tailored design, such that we can design much more inexpensive systems for specific medical applications. Thus rather than one large MRI, the model is similar to having tens of different mobile ultrasound machines in a medical facility. In order to achieve portability, we design systems that use thousands of very small low-cost permanent magnets, arranged in designs which have no fringe field and therefore very easy siting requirements. The low magnetic fields allow scanning of patients with implants, and the scanner could potentially be transported on an ambulance for differentiation of hemorrhagic or ischemic stroke, for example. This talk will cover aspects of magnet, gradient and RF coil design for low fields (~50 mT) , as well as corrections for gradient- and B0-distortions, and present the latest in vivo results as well as an outlook on future developments.

About the speaker: Andrew Webb graduated from the University of Bristol with a bachelors degree in Chemistry and obtained his PhD from the University of Cambridge. After a postdoc in the Department of Radiology at the University of Florida, he joined the faculty of the Department of Electrical and Computer Engineering at the University of Illinois Urbana-Champaign. He was appointed full professor in 2000, and worked for three years in the Department of Physics at the University of Wurzburg on a Humboldt Fellowship. In 2008 he was appointed to run the newly-formed C.J.Gorter Centre in the Department of Radiology at Leiden University Medical Center. His main research areas are RF design for high field MRI, and translation of new engineering concepts into the clinic supported by an ERC Advanced Grant. Recently his lab has moved into the area of sustainable open-source low field MRI for developing countries funded by the Simon Stevin Preis in 2017. In addition to over 300 peer-reviewed publications he has authored four academic text books on medical imaging and biomedical instrumentation. He is an Associate Editor for Magnetic Resonance in Medicine and on the editorial board of several other MR journals. In 2020 he will be President of the European Society of Magnetic Resonance in Medicine and Biology. In 2010 he founded the Nadine Barrie Smith trust which supports four student fellowships per year for women in science and engineering.

Wednesday, August 5, at 2:00 p.m.

Farah Shamout, DPhil

Assistant Professor/Emerging Scholar of Electrical and Computer Engineering
Engineering Division
NYU Abu Dhabi
Artificial Intelligence System for Predicting the Deterioration of Patients with COVID-19 in the Emergency Department

Abstract: There is a pressing need to identify deterioration amongst patients with COVID-19 in order to avoid life-threatening adverse events. Chest radiographs are frequently collected from patients presenting with COVID-19 upon arrival to the emergency department, since it is considered as a first-line triage tool and the disease primarily manifests as a respiratory illness. In this talk, I will discuss the AI prognosis system we developed using data collected at NYU Langone Health to predict in-hospital deterioration, defined as the occurrence of intubation, mortality, or ICU admission. In particular, our system consists of an ensemble of an interpretable deep learning model to learn from chest X-ray images and a gradient boosting model to learn from routinely collected clinical variables, e.g. vital signs and laboratory tests. The system also computes deterioration risk curves to summarise how the risk is expected to evolve over time. The results of retrospective validation on the held-out test set, the reader study, and silent deployment in the hospital infrastructure highlight the promise of our AI system in assisting front-line workers through real-time assessment of prognosis.

About the speaker: Farah Shamout is an Assistant Professor Emerging Scholar in Computer Engineering at NYU Abu Dhabi and a visiting research scholar at the NYU Center for Data Science. Her research expertise is in machine learning for healthcare, data analytics for large-scale multi-modal data, and model interpretability. Her projects focus on real-world clinical problems to inform decision-making, including diagnosis and prognosis using electronic health records and medical imaging. Previously, Farah completed her doctoral studies in Engineering Science at the University of Oxford as a Rhodes Scholar.

Wednesday, July 22, at 2:00 p.m.

Susie Y. Huang, MD, PhD

Assistant Professor
Athinoula A. Martinos Center for Biomedical Imaging
Department of Radiology
Massachusetts General Hospital, Harvard Medical School
Characterizing tissue microstructure in the living human brain using high-gradient diffusion MRI and ultrafast susceptibility-weighted Imaging

Abstract: Less is known about the structure-function relationship in the human brain than in any other organ system. The challenge of studying brain structure is that brain networks span multiple spatial scales, from individual neurons all the way to whole-brain systems. Diffusion magnetic resonance imaging (MRI) holds great promise among noninvasive imaging methods for probing cellular structure of any depth and location in the living human brain. Robust methods for in vivo mapping of tissue microstructure by diffusion MRI remain elusive due to the demand for fast and strong diffusion-encoding gradients. I will present an overview of our group’s efforts to advance MR hardware, biophysical modeling, and validation of microstructural metrics derived from diffusion MRI in order to probe the structure of the human brain across multiple scales. I will review current progress and applications of these methods to study axonal microstructure in the normal and aging human brain and assess axonal damage in multiple sclerosis.

To bridge the divide between the neuroscientific and clinical use of MRI in probing tissue microstructure, this presentation will also provide an overview of our ongoing efforts to optimize, translate and validate novel encoding and reconstruction techniques for the ultrafast acquisition of high-resolution, multi-contrast MR images in a clinical setting. These efforts are exemplified in our recent work exploring the benefits of improved speed and resolution of ultrafast susceptibility-weighted imaging to study microvascular injury in patients with severe COVID-19 using radiologic-pathologic correlative examinations.

About the speaker: speaker bio

Wendesday, July 15, at 2:00 p.m.

Elena Vinogradov, PhD

Associate Professor
Radiology Department and Advanced Imaging Research Center
UT Southwestern Medical Center
Chemical Exchange Saturation Transfer (CEST) and Inhomogeneous Magnetization Transfer (ihMT) for Molecular and Microstructural Contrast in Human MRI

Abstract: Recently, methods employing single- and dual-frequency saturation are gaining recognition to detect events on microstructural and molecular level. Specifically, Chemical Exchange Saturation Transfer (CEST) employs selective saturation of the exchanging protons and subsequent detection of the water signal decrease to create images that are weighted by the presence of a metabolite or pH1. Here, we will describe aspects of translating CEST to reliable clinical applications at 3Tesla and discuss its potential uses in human oncology, specifically breast cancer. Second, we will discuss a method called inhomogeneous Magnetization Transfer2 (ihMT), which employs dual-frequency saturation to create contrast originating from the residual dipolar couplings and thus specific to microstructure. We will focus on principles of ihMT, its comparison to other white matter metrics (diffusion) and the methods application to the detection of myelin in brain and spinal cord.

1. J. Zhou,, Nat. Med., 9,1085-1090 (2003).
2. G. Varma,, MRM, 73, 614-622 (2015).

About the speaker: speaker bio

Wednesday, May 27, at 11:00 a.m.

Nikolai Avdievitch, PhD

Senior Research Scientist
High-Field MR Center
Max Planck Institute for Biological Cybernetics
Tubingen, Germany
Bent Folded-End Dipole Head Array for Ultra-High-Field Magnetic Resonance Imaging Turns “Dielectric Resonance” from an Enemy to a Friend

Abstract: Due to a substantial shortening of the RF wave length (below 15 cm at 7T), RF magnetic field at UHF has a specific transmit (Tx) excitation pattern with strongly decreased (more than 2 times) values at the periphery of a human head. This effect is seen not only in the transversal slice but also in the coronal and sagittal slices, which considerably limits the longitudinal Tx-coverage (along the magnet’s axis) of conventional surface loop head arrays. In this work, we developed a novel human head UHF array consisted of 8 transceiver folded-end dipole antennas circumscribing a head. Due to the asymmetrical shape of the dipoles (bending and folding) and the presence of an RF shield near the folded portion, the array simultaneously excites two modes, i.e. a circular polarized mode of the array itself, and the TE mode (“dielectric resonance”) of the human head. Mode mixing can be easily controlled by changing the length of the folded portion. Due to this mixing, the new dipole array improves longitudinal coverage as compared to unfolded dipoles. By optimizing the length of the folded portion, we can also minimize the peak local SAR value and decouple adjacent dipole elements.

About the speaker: speaker bio

Wednesday, May 20, at 2:00 p.m.

Georgeann McGuinness, MD

Associate Dean for Mentoring and Professional Development
Professor and Senior Vice Chair of Radiology
Vice Chair of Academic Affairs
Director, Clinical Faculty Mentoring
NYU Langone Health
COVID-19: The Evolving Role of Chest Imaging

Abstract: This lecture will provide a brief clinical overview of SARS-CoV-2 infection and COVID-19 manifestations in the lungs. Imaging findings in the chest will be defined and literature reports summarized. Our evolving clinical experience will be described, including the subacute and chronic manifestations of COVID-19 lung disease we are now seeing. Finally, completed and ongoing thoracic COVID research projects will be presented.

Wednesday, May 13, at 2:00 p.m.

Merry Mani, PhD

Director, Microstructure Imaging Lab
Assistant Professor of Radiology – Division of Neuroradiology
University of Iowa
Computational Approaches for Efficient MRI: Applications in Neuroscience Research

Abstract: Magnetic Resonance Imaging has revolutionized the field of neuroscience by providing a non-invasive means to study the brain, to understand its organization, specialization and anomalies in an unprecedented manner. Despite the rapid advances in MRI instrumentation, it is still challenging to achieve high quality data in an efficient manner for several MR imaging modalities, especially for those modalities involving multi-dimensional imaging. In this talk, I will discuss several computational approaches that we have developed to achieve high efficiency MR imaging to enable many applications. These approaches strive to achieve high resolution, high SNR and artifact-free MRI by jointly optimizing the contribution of MR acquisition, the signal modeling under investigation and the reconstruction methods to provide meaningful information in an efficient manner. In this talk, I will focus the discussion mainly on diffusion magnetic resonance imaging and our work towards improving the efficiency of this modality.

About the speaker: Merry Mani received her PhD in 2014 from the University of Rochester, NY. Later in 2014, she joined the Magnetic Resonance Research Facility at the University of Iowa as a post-doctoral research fellow, where she developed new imaging methods on the 7T MRI. In 2019, she became an Assistant Professor in the department of Radiology, Carver College of Medicine, University of Iowa. Her lab focus on integrating cross-disciplinary tools such as signal modeling and signal processing with imaging physics and image analysis tools to enable high efficiency MRI. These include the development of novel pulse sequences and optimization of sampling trajectories and reconstruction methods for maximum performance.

Wednesday, May 6, at 2:00 p.m.

Gigi Galiana, PhD

Associate Professor
Radiology and Biomedical Imaging
Yale University, School of Medicine
Nonlinear gradients for spatial encoding and contrast

Abstract: Like standard gradients, nonlinear gradients modulate the magnitude of Bz as a function of position; the difference is that the magnitude as a function of position is generally not linear or unidirectional. One important consequence of gradient nonlinearity is that the modulation of spins is no longer sinusoidal, so MR data do not correspond to points in k-space. Therefore, early encoding strategies focused on optimizing sequences by considering encoding in the spatial domain. However, a k-space analysis of nonlinear encoding provides significant insights on sequence design and suggests novel strategies, such as FRONSAC encoding. With FRONSAC, most of the encoding comes from a standard linear trajectory (e.g. Cartesian, radial or spiral), but nonlinear gradients are used to effectively increase the width of the k-space trajectory. For an undersampled scan, the additional width reduces gaps in k-space and improves reconstructions, but most other properties of the underlying linear method are unchanged. For example, Cartesian-FRONSAC retains features like insensitivity to off-resonance spins and timing delays, ease of changing FOV, resolution, and orientation, and relatively simple contrast behavior, while still allowing for higher undersampling factors. This versatile approach can be added to nearly any sequence, improving undersampling artifacts even for low channel arrays, as we have shown by acquiring a full FRONSAC-enhanced brain protocol in a cohort of healthy subjects.

An additional emerging application of nonlinear gradients is in generating diffusion contrast. In some sense, a linear gradient is the maximally egalitarian way to distribute a ΔB(x): it generates the same Gx (d(ΔB)/dx) everywhere, but the peak Gx across the FOV is the lowest possible. By allowing nonlinearity, Gx is different at each voxel, but it can be concentrated to certain regions of interest. Thus, for specialized applications, it may be possible to achieve massive gradients strengths and very high diffusion weightings using simple equipment. For example, for prostate DWI, we propose an inside-out nonlinear gradient, which simulations suggest will ultimately double CNR in ADC maps.

Wednesday, April 29, at 2:00 p.m.

Zhen Xu, PhD

Associate Professor and Associate Chair of Graduate Education
Department of Biomedical Engineering
University of Michigan
Histotripsy: Image-guided Ultrasound Therapy for Non-invasive Surgery

Abstract: Wouldn’t it be great to perform a surgery without incision or bleeding? “Histotripsy” is the first non-invasive, non-ionizing, and non-thermal ablation technique that is invented by Dr. Xu and her colleagues at the University of Michigan. Using ultrasound pulses applied from outside the body and focused to the target diseased tissue, histotripsy produces a cluster of energetic microbubbles at the target tissue using the endogenous gas pockets with millimeter accuracy. These microbubbles, each similar in size to individual cells, function as “mini-scalpels” to mechanically fractionate cells to acellular debris in the target tissue. The acellular debris is absorbed over time via metabolism, resulting in effective tissue removal. Off-target tissue remains undamaged and no incision is needed. Thus histotripsy can perform non-invasive surgery guided by real-time imaging. Histotripsy has potential for many clinical applications where non-invasive tissue removal is desired. Recent research in Dr. Xu’s lab also shows potent immune response and abscopal effects induced by histotripsy and its potential for immunotherapy. Dr. Xu will talk about the mechanism and instrumentation development of histotripsy as well as the latest pre-clinical and clinical studies of histotripsy for cancer, neurological, cardiovascular, and immunotherapy applications.

About the speaker: Zhen Xu is a tenured Associate Professor and Associate Chair of Graduate Education at the Department of Biomedical Engineering at the University of Michigan, Ann Arbor, MI. She received the Ph.D. degree in biomedical engineering from the University of Michigan in 2005. Her research focuses on ultrasound therapy and imaging, particularly histotripsy. She received the IEEE Ultrasonics, Ferroelectrics, and Frequency Control (UFFC) Outstanding Paper Award in 2006; National Institute of Health (NIH) New Investigator Award at the First National Institute of Biomedical Imaging and Bioengineering (NIBIB) Edward C. Nagy New Investigator Symposium in 2011, The Federic Lizzi Early Career Award from The International Society of Therapeutic Ultrasound (ISTU) in 2015, the Fellow of American Institute of Medicine and Bioengineering in 2019, and The Lockhart Memorial Prize for Cancer Research in 2020. She is an associate editor for IEEE Transactions on UFFC and Frontiers in Bioengineering and Biotechnology, Deputy VP of UFFC Ultrasonics Standing Committee, and an elected board member of ISTU. She is a principal investigator of grants funded by NIH, Office of Navy Research, American Cancer Association, and Focused Ultrasound Foundation. She is also co-founder of HistoSonics, a startup company developing histotripsy for oncological applications.

Wednesday, April 22, at 2:00 p.m.

Ulas Bagci, PhD

Principal Investigator
Center for Research in Computer Vision (CRCV)
University of Central Florida
A Collaborative CAD System (C-CAD) for Radiological Applications with Eye-Tracking, Sparse Attentional Model, and Deep Learning

Abstract: Vision researchers have been analyzing behaviors of radiologists during screening to understand how and why they miss tumors or misdiagnose. In this regard, eye-trackers have been instrumental in understanding visual search processes of radiologists. However, most relevant studies in this aspect are not compatible with realistic radiology reading rooms. In this talk, I will share our unique experience for developing a paradigm shifting computer aided diagnosis (CAD) system, called collaborative CAD (C-CAD), that unifies CAD and eye-tracking systems in realistic radiology room settings. In other words, we are creating artificial intelligence (AI) tools that get benefits from human cognition and improve over complementary powers of AI and human intelligence. We first developed an eye-tracking interface providing radiologists with a real radiology reading room experience. Second, we proposed a novel computer algorithm that unifies eye-tracking data and a CAD system. The proposed C-CAD collaborates with radiologists via eye-tracking technology and helps them to improve their diagnostic decisions. The proposed C-CAD system has been tested in a lung and prostate cancer screening experiment with multiple radiologists. More recently, we also experimented brain tumor segmentation with the proposed technology leading to promising results. In the last part of my talk, I will describe how to develop AI algorithms which are trusted by clinicians, namely “explainable AI algorithms". By embedding explainability into black box nature of deep learning algorithms, it will be possible to deploy AI tools into clinical workflow, and leading into more intelligent and less artificial algorithms available in radiology rooms.

About the speaker: Bagci is a faculty member at the Center for Research in Computer Vision (CRCV), University of Central Florida. His research interests are artificial intelligence, machine learning and their applications in biomedical and clinical imaging. Previously, he was a staff scientist and the lab co-manager at the NIH's Center for Infectious Disease Imaging (CIDI) Lab, department of Radiology and Imaging Sciences (RAD&IS). Dr. Bagci had also been the leading scientist (image analyst) in biosafety/bioterrorism project initiated jointly by NIAID and IRF. Dr. Bagci obtained his PhD degree from Computer Science, University of Nottingham (UK) in collaboration with University of Pennsylvania. Dr. Bagci is senior member of IEEE and RSNA, and member of scientific organizations such as SNMMI, ASA, RSS, AAAS, and MICCAI. Dr. Bagci is the recipient of many awards including NIH's FARE award (twice), RSNA Merit Awards (5+ times), best paper awards, poster prizes, and several highlights in journal covers, media, and news. Dr. Bagci was co-chair of Image Processing Track of SPIE Medical Imaging Conference, 2017, and technical committee member of MICCAI for several years. Dr. Bagci is the principal investigator of R01 grants from NIH/NCI.

Wednesday, April 15, at 2:00 p.m.

Anastasia Yendiki, PhD

Associate Professor, Harvard Medical School
Associate Investigator, Massachusetts General Hospital
Athinoula A. Martinos Center for Biomedical Imaging
Towards improved inference on connectional anatomy from diffusion MRI

Abstract: This talk will provide an overview of work that our group has done on mapping connectional anatomy from diffusion MRI, and a preview of where this path might lead us next. First, I will discuss our previously developed algorithms for reconstructing white-matter pathways from diffusion MRI. These include both supervised and unsupervised methods with a common theme: like neuroanatomists, they define white-matter bundles based on relative position with respect to neighboring anatomical structures, rather than based on absolute coordinates in a template space. This makes them robust to individual variability and to the effects of disease or healthy development and aging.

Second, I will present results from recent post mortem validation studies, where we have evaluated the accuracy of diffusion MRI with respect to polarization-sensitive optical coherence tomography in human samples, or chemical tracing in non-human primates. Our results suggest that existing methods for inferring the orientation of axon bundles from diffusion MRI do not benefit substantially from very high b-values. This implies that our analysis tools have not kept up with the rapid progress of our hardware, and that new tools are needed to fully take advantage of the data that can be acquired by today's ultra-high-gradient MRI scanners. I will end the talk by discussing how we may be able to address this, by using the post mortem data not only to evaluate existing methods but to engineer the next generation of tractography algorithms.

About the speaker: Faculty bio

Wednesday, April 8, at 2:00 p.m.

Yu Veronica Sui, MA

PhD Student
Biomedical Imaging and Technology Program
Sackler Institute of Graduate Biomedical Sciences
NYU Langone Health
Characterization of Cortical Myelin Deficits in Schizophrenia Spectrum Disorders using Quantitative Magnetization Transfer Imaging

Abstract: Myelin abnormalities in schizophrenia spectrum disorders have been suggested by histological studies, which have shown aberrations in myelin lamellae, oligodendrocyte structure, and myelin- and oligodendrocyte-related gene expression. However, in vivo examination of myelin content, especially the intra-cortical myeloarchitecture remains limited. In our current project, we employ magnetization transfer imaging to derive macromolecular proton fraction (MPF), a quantitative estimate of myelin content. This talk will focus on data suggesting a flattening of the cortical myelin profile in patients with schizophrenia spectrum disorders and an association of cortical myelin alterations with illness progression and cognitive outcomes. Preliminary findings on whole-brain myeloarchitectural similarity changes in schizophrenia will also be presented.

About the speaker: Yu Veronica Sui is a second-year graduate student in Sackler Institute’s Biomedical Imaging and Technology training program working with Mariana Lazar. She has a background in cognitive psychology and is interested in developing and employing new imaging and analytics methods to characterize the neural bases of psychiatric disorders. Her focus in Lazar Lab is psychosis-related pathological changes in the brain, including both microstructural and connectivity abnormalities.

Tuesday, March 3, at noon

Mark Does, PhD

Professor of Biomedical Engineering
Vanderbilt University
Nashville, TN
Adventures in Quantitative Magnetic Resonance Imaging

Abstract: An alluring feature of magnetic resonance imaging (MRI) is its potential to provide quantitative and specific characterizations of tissue. However, the barriers to the realization of quantitative MRI (qMRI) are many and progress has been slow. This presentation will include vignettes of technical, experimental, and translational efforts to develop and utilize qMRI, with primary applications being the characterization of white matter micro-structure/composition and bone fracture risk.

About the speaker: Faculty bio

Tuesday, February 11, at noon

Sarah Shaykevich

PhD Student
Biomedical Imaging and Technology PhD Training Program
Sackler Institute of Graduate Biomedical Sciences
NYU Langone Health
Functional Optoacoustic Neuro-Tomography
Friday, February 7, at noon

Adrienne Campbell-Washburn, PhD

Director, MRI Program
National Heart, Lung, and Blood Institute (National Institutes of Health)
Opportunities in clinical imaging using a high-performance 0.55T MRI system

Abstract: Lower field strength MRI systems paired with high-performance hardware and advanced imaging methods offer unique opportunities for clinical imaging. Specifically, this system configuration offers improved safety for MRI-guided invasive procedures, improved imaging in high-susceptibility regions including the lung, and advantages for efficient image acquisitions. In light of developments in MRI engineering and available computational power, and as well as the drive to reduce MRI costs, there is significant value in revisiting lower field MRI in the context of modern clinical imaging. This talk will describe the experience of the NHLBI imaging patients on a ramped down 0.55T system for 2 years.

About the speaker: Dr. Adrienne Campbell-Washburn is the Director of the MRI Technology Program at the National Heart, Lung, and Blood Institute (National Institutes of Health). Her research focuses on the development of MRI technology for cardiac imaging, lung imaging, and MRI-guided interventions. She works on developing advanced MRI acquisitions that leverage non-Cartesian sampling and reconstruction methods using state-of-the-art computational resources in the clinical environment. Her research aims to improve SNR-efficiency, imaging speed, interventional procedural guidance including device safety and visibility, motion robustness, quantification, and clinical integration.

Tuesday, January 28, at noon

Bruce Berkowitz, PhD

Wayne State University School of Medicine
Treating oxidative stress in aging and disease: Moving from art to science

Abstract: Imaging biomarkers that bridge neuronal abnormalities in vivo and behavior, and animal models and human patients, are urgently needed to quicken discovery and application of novel disease-modifying therapy, but are not yet available. I will be discussing novel MRI and OCT approaches for measuring sustained and excessive production of free radicals (i.e., oxidative stress) in neuronal laminae without a contrast agent in untreatable neurodegenerative disease. These studies set the stage for translating and managing anti-oxidant treatment in patients for the first time.

Tuesday, January 21, at noon

Frank Ong, PhD

Postdoctoral Fellow
Stanford University
Modernizing Medical Imaging with Large-scale Computational Algorithms

Abstract: Existing clinical infrastructures severely under-utilize modern computation resources, leading to costly errors, slow workflows and limited research opportunities. However, trends in cloud computing and machine learning are rapidly changing this landscape. Tech companies, such as Amazon, Google and Microsoft, are now racing to integrate high performance computing into clinical settings. Medical imaging stands to gain tremendously from advances in computing power, which will enable many previously unthinkable applications.

In this talk, I will focus on three directions on leveraging these emerging computing resources to improve medical imaging: 1) reconstructions of high dimensional volumetric dynamic MRI on the order of 100GBs; 2) continuous learning and image quality improvement from undersampled datasets; 3) optimizing end-to-end systems across clinical workflow.

Tuesday, January 14, at noon

Zhengnan Huang, MSc

PhD Student, Biomedical Imaging and Technology
Sackler Institute of Graduate Biomedical Sciences
NYU Grossman School of Medicine
Temporal Regularization with Machine Learning for Dynamic Image Reconstruction

Abstract: Dynamic MR image quality is limited by the temporal and spatial resolution trade-off. Adopting machine learning in the reconstruction network provide alternative method to reconstruct the image of better quality. This presentation will focus on our work using Recurrent Neural Networks(RNN) as regularizer in our dynamic MR reconstruction network. The regularizer is designed to take time series of kspace with flexible length and use it to reconstruct image series. I will show how we design simulation to get ground truth images for model training. Then I will show the output of the trained network on simulated breast perfusion MR data with comparison to other reconstruction methods.

About the speaker: Zhengnan Huang joined Florian Knoll's lab in 2018. He has educational background in bioinformatics. His research interest is MR image reconstruction and machine learning application.

Wednesday, December 18, at noon

Stefano B. Blumberg

PhD Student
University College London
Three Deep Learning Techniques for 3D diffusion MRI Image Enhancement

Abstract: In this talk, we discuss three deep learning techniques to improve the image quality of 3D diffusion MRI Images. We first introduce a novel low-memory method, which allows us to control the GPU memory usage during training therefore allowing us to handle the processing of 3-dimensional, high-resolution, multi-channeled medical images. Secondly we present the first multi-task learning approach in data harmonization, where we integrate information from multiple acquisitions to improve the predictive performance and learning efficiency of the training procedure. Thirdly we present an extension of the transposed convolution, where we learn both the offsets of target locations and a blur to interpolate the fractional positions. All three techniques can be applied in other image-related paradigms.

Tuesday, December 17, at noon

Ansel Hillmer, PhD

Assistant Professor
Departments of Radiology & Biomedical Imaging, Psychiatry, and Biomedical Engineering
Yale University
PET Imaging of Immune Function in Psychiatric Disorders

Abstract: Dysregulated immune signaling contributes to many neuropsychiatric conditions. Brain PET imaging can measure neuroimmune factors that inform treatment development for such conditions. This talk will focus on PET imaging of the 18-kDa translocator protein (TSPO). Preclinical work informing the interpretation of TSPO signal, including imaging dynamic responses to endotoxin, an acute immune stimulus, will first be presented. Next, human data imaging TSPO in tobacco smoking, alcohol use disorder, and Alzheimer’s disease will be presented to demonstrate diverse applications of these techniques. Whole body imaging of TSPO following acute alcohol administration as an immune stimulus will also be presented. Finally, work characterizing new radiotracers that complement TSPO measures in immune signaling will be presented. This work depicts ways in which PET imaging can be leveraged to study immune function in the context of neuropsychiatric disorders.

About the speaker: Dr. Ansel Hillmer is an Assistant Professor in the Departments of Radiology & Biomedical Imaging, Psychiatry, and Biomedical Engineering at Yale University, and Associate Director of Imaging at the Yale PET Center. He received his Ph.D. in Medical Physics from the University of Wisconsin, Madison in 2014. His research focuses on the characterization and application of PET imaging paradigms to study psychiatric (and other) diseases, with particular emphasis on applications to substance use (alcohol, tobacco, cannabis). Active research projects include assessing dynamic responses of neuroimmune and glutamate signaling to alcohol challenge, preclinical characterization of novel radiotracers targeting immune mechanisms, and the development of multimodal data integration approaches.

Friday, December 13, at noon

Galina Pavlovskaya, PhD

Associate Professor
University of Nottingham
Validation of rheo-markers in ex-vivo human cartilage for early OA detection using multiscale MRI

Abstract: A novel investigation of rheo-markers (proton T2* and sodium multiple quantum filtering) shows the potential for multi-nuclear MRI biomarkers in mechanically loaded joints with good evidence of a dynamic 23Na environment during compression which may be useful for early OA detection before symptoms occur.

About the speaker: Galina Pavlovskaya is a MR physicist with the expertise in sodium MRI and microimaging (UTE, MQF) at ultra-high field (9.4T), particularly in applying these techniques in exploring new imaging markers in diseases associated with physical stresses i.e. arthritis and injuries in sports medicine. Galina studied for her undergraduate (Soft Condensed Matter Physics) degree at Lomonosov Moscow State University, Moscow, Russia and postgraduate (PhD, Chemical Physics) degree at Clark University, Massachusetts, USA. From there she moved to a post-doctoral position at the National High Magnetic Field Laboratory, Tallahassee, Florida, USA working on MRI of fluid flows in tissues following a second post-doctoral post in MRI of bio-fluid flow in stenotic geometries at Lawrence Berkeley National Laboratory, University of California, Berkeley, USA. She continued as an independent Researcher at Colorado State University developing hyperpolarised MRI methodology for lung studies and sodium MRI methodology for soft tissues characterisation. In 2009 she was appointed as an Assistant Professor at the University of Nottingham, where she continued to work on hyperpolarisation techniques and sodium methodology developments. She was promoted to an Associate Professor in 2017, her research is currently funded by MRC, BBSRC, EPSRC and charities and targets development of sodium MRI for healthcare applications.

Tuesday, December 10, at noon

Matthew Koff, PhD

Associate Scientist, Department of Radiology and Imaging
Associate Professor of Biomedical Imaging in Orthapaedic Surgery
Weill Cornell Medical College of Cornell University
New York, NY
MRI for Monitoring Health of Total Hip Arthroplasty

Abstract: A majority of primary total hip arthroplasty (THA) devices function well but implant failures occur. This presentation will cover our long standing efforts to utilize MRI in identifying patients needing premature implant revision due to adverse local tissue reactions (ALTRs). The utility of advanced multi-spectral imaging to reduce metallic susceptibility artifact and visualize synovitis, osteolysis, and tendon tears near arthroplasty will be displayed. I will also show results from our on-going studies using MRI to evaluate patients with different THA bearing materials to determine which factors are predictive of abnormal synovial reaction. Finally, data will be shown regarding the longitudinal prevalence of MRI detected ALTRs in a cohort of high functioning THA patients.

About the speaker: Dr. Koff is a biomedical engineer whose work focuses on using novel magnetic resonance imaging (MRI) acquisition techniques and analyses for musculoskeletal applications. He uses quantitative MRI (qMRI) as a biomarker to evaluate: 1) bone-implant integration and biologic reactions due the implant, using multi-acquisition variable resonance image combination (MAVRIC) for total hip, knee, and shoulder arthroplasty and other orthopaedic hardware; 2) the initiation and progression of degenerative joint disease in articular cartilage using T2 and T1ρ mapping; 3) meniscal tears and the post-operative healing process, using ultra-short echo (UTE) imaging and T2* mapping.

He has been the PI of NIH funded studies and involved in foundation supported studies which necessitate coordination across numerous sites while performing longitudinal imaging image acquisition and data analysis. These studies have been performed in conjunction with orthopaedic surgeons, radiologists, MRI physicists, biomedical engineers, physical therapists, and statisticians. He enjoys working as part of a multi-disciplinary team comprised of clinical and basic science researchers to perform clinically relevant and translational research.

Thursday, December 5, at noon

Robia Pautler, PhD

Associate Professor
Departments of Molecular Physiology and Biophysics, Neuroscience and Radiology
Baylor College of Medicine
Houston, TX
Protective effects of Intranasally Administered Nanoantioxidants in the Olfactory System in Mouse Models of Alzheimer’s Disease

Abstract: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by the neuropathological accumulation of amyloid beta (Ab) plaques and neurofibrillary tangles comprised of hyperphosphorylated tau. Tau is a microtubule-associated protein involved in microtubule stability and when tau is hyperphosphorylated, microtubules become destabilized which leads to impaired axonal transport. Axonal transport is an important cellular process that shuttles vesicles, neurotransmitters, and mitochondria from the soma to the synapse. Perturbations in axonal transport disrupt neuronal activity by reducing the transport of mitochondria, increasing reactive oxygen species (ROS) and diminishing the formation of active zones at the synapse. Axonal transport deficits are thought to occur early and continue to progress in AD. Thus, there is a significant need and strong scientific premise to identify the mechanisms by which axonal transport deficits occur and also can be improved in AD.

Olfactory receptor neurons are the only part of the central nervous system (CNS) with direct access to the outside world. They lie at the beginning of a neural network which projects to the olfactory bulb followed by the piriform olfactory cortex (primary olfactory cortex), the entorhinal cortex (secondary olfactory cortex). The olfactory system is also the first system affected in AD patients and mouse models of AD before cognitive deficits develop. Indeed, using Manganese Enhanced MRI (MEMRI), we have shown that axonal transport deficits in the olfactory receptor neurons occur before the appearance of learning and memory deficits appear and are reversed when we reduce ROS levels by overexpressing superoxide dismutase 2 (SOD-2) in AD mice. Here, we describe our current efforts with reducing oxidative stress in the olfactory structures in mouse models of AD with intranasally applied nanoantioxidants.

About the speaker: Robia G. Pautler is an Associate Professor in the Departments of Molecular Physiology and Biophysics, Neuroscience and Radiology at Baylor College of Medicine. She also directs the Small Animal MRI imaging facilities at BCM and also Texas Children’s Hospital. She is known for her work in mouse models of Alzheimer’s Disease and oxidative stress. Dr. Pautler received her BS from Colorado State University, her PhD from Carnegie Mellon University, working with Dr. Alan Koretsky, and did a postdoctoral fellowship with Drs. Scott Fraser and Russ Jacobs at Caltech. She joined the faculty at Baylor College of Medicine in 2003 and is currently a tenured Associate Professor. She has earned multiple NIH and Foundation grants and has over 65 publications. In addition to her work in research, she is very active in educational endeavors -- she was the Co-Director of the Graduate Education Program for Physiology for 7 years, she is on the Faculty Operating Committee for the MD/PhD program, she has served as the Chair of multiple educational committees and has mentored numerous trainees ranging from the high school to junior faculty level. She is a staunch advocate for Diversity in the Sciences and Education in general. She spearheaded the formation of the Women in MR group at the ISMRM as part of her Annual Program Meeting Committee endeavors. She is also currently pursuing her certification as a Special Education Advocate.

Thursday, December 5, at 10:00 a.m.

Itamar Kahn, PhD

Associate Professor
Department of Neuroscience
Ruth and Bruce Rappaport Faculty of Medicine
Technion – Israel Institute of Technology
Whole-brain fMRI of the behaving mouse

Abstract: Functional MRI is used extensively in human brain research, enabling characterization of distributed brain activity underlying complex perceptual and cognitive processes. However, it has been limited in utility in rodents. I will present the work we have done to establish awake mouse MRI, characterize the properties of the hemodynamic response function as different from humans and how these two aspect enabled us to conduct whole-brain fMRI of the behaving animal. I will expand on recent work using whole-brain functional imaging of head-fixed mice performing odor discrimination and conclude by showing additional behavioral modalities we develop with the goal to establish this approach as a platform to be used extensively in the field.

About the speaker: Dr. Itamar Kahn is an associate professor of neuroscience at the Ruth and Bruce Rappaport Faculty of Medicine, Technion – Israel Institute of Technology. Dr. Kahn received his bachelor of science degree from Ben-Gurion University of the Negev in Mathematics and Computer Science. For his doctoral training, Dr. Kahn went to Massachusetts Institute of Technology (MIT) where he studied long-term memory function at the Brain and Cognitive Sciences department under the supervision of Anthony Wagner, and then went on to become a post-doctoral associate at the Howard Hughes Medical Institute at Harvard University from 2006-2010 under the joint supervision of Profs. Randy Buckner, Chris Moore and Ed Boyden, studying functional connectivity in rodents using optogenetics, electrophysiology and functional magnetic resonance imaging (fMRI).

Monday, November 25, at noon

Sebastian Flassbeck, PhD

Postdoctoral Fellow
Division of Medical Physics in Radiology
German Cancer Research Center
Simultaneous Quantification of Flow Velocities and Relaxation Constants Through MRF

Abstract: A novel imaging technique is presented, capable of simultaneously quantifying time-resolved blood flow velocities and the relaxation constants of static tissue. This is accomplished through the use of a Magnetic Resonance Fingerprinting (MRF) based approach. The developed technique, termed “Flow-MRF”, allows accurate mapping of velocities and relaxation constants in measurement times up to 4-fold shorter than conventional MRI-based velocimetry techniques.

About the speaker: Sebastian Flassbeck is a postdoc in the division of medical physics in radiology at the German Cancer Research Center. He received his doctorate in physics from the Heidelberg University in May 2019. His research is focused on the development of quantitative imaging techniques at ultra-high fields.

Thursday, November 21, at noon

Xiang Xu, PhD

Assistant Professor
Department of Radiology
Johns Hopkins University
glucoCEST MRI: en route to Translation

Abstract: Chemical exchange saturation transfer (CEST) is a relatively new type of MRI contrast that indirectly detects low concentration labile protons through water signal with enhanced sensitivity. In this presentation, I will explain the principles of CEST imaging and its applications. I will show results from using CEST to image D-glucose (glucoCEST) in vivo, first on brain tumor mouse model at ultra-high magnetic field, then on human brain tumor patient on 7T system. Our recent effort of translating the technique to clinical field strength and the promise and challenges of glucoCEST at clinical field strength will be also be discussed.

About the speaker: Dr. Xiang Xu is an Assistant Professor at the Johns Hopkins University in the Department of Radiology. Xiang completed her PhD at New York University and her undergraduate studies at Jilin University, China. Her research interests include developing new NMR and MRI technologies ranging from signal enhancement to imaging techniques. Currently, she focuses on method development and the application of chemical exchange saturation transfer (CEST) techniques both on pre-clinical and clinical MRI scanners. She is developing methodologies that would enable the imaging of D-glucose in vivo using CEST.

Tuesday, November 12, at noon

Juan Fortea, PhD

Sant Pau Memory Unit
Barcelona, Spain
Multimodal biomarker studies to understand Alzheimer´s disease: biochemical & imaging biomarkers in sporadic AD and AD in Down syndrome

Abstract: CSF, PET and MRI multimodal studies enable the early diagnosis of Alzheimer's Disease. We have proposed a model in which interactions between biomarkers in preclinical AD result in a two-phase phenomenon: an initial phase of cortical thickening due to amyloid-related inflammation, followed by a cortical atrophy phase which occurs once tau biomarkers become abnormal. These results have implications in the selection of patients for clinical trials and the use of MRI as a surrogate marker of efficacy. We will also present data showing the potential of studying the cortical microstructure with DTI to assess these early changes and in the diagnosis of other neurodegenerative diseases.

About the speaker: Juan Fortea is a behavioral neurologist and a dementia expert, and leads the Alzheimer Down Unit and the neuroimaging core of the Memory Unit at the hospital of Sant Pau in Barcelona. His research interest is in the early diagnosis of neurodegenerative diseases and AD natural history through CSF, PET and MRI multimodal studies.

Thursday, October 24, at noon

Xin Yu, PhD

Research Group Leader
Department High-field Magnetic Resonance
Max Planck Institute
Bridge the functional and hemodynamic brain mapping with the multi-modal fMRI

Abstract: In this talk, I will introduce the combination of the advanced fMRI method with the emerging neuro-techniques to decipher the neuro-glial-vascular (NGV) coupling basis of brain state dynamics. First, we will see through the large voxel acquired from conventional fMRI to decipher the contribution from distinct vascular components to the fMRI signal. A newly developed single-vessel fMRI method allows identifying the activity-evoked hemodynamic signal propagation through the cerebrovasculature in the brain with either sensory inputs or optogenetic activation. Second, we will combine the fMRI with the optical fiber-mediated calcium recordings to decipher the cell-type-specific contribution to the fMRI signal from neurons and astrocytes. Meanwhile, we will also show how extracellular glutamate can be recorded simultaneously to mediate NGV interaction. Finally, we are going to present how the global fMRI signal fluctuation can be linked to the brain state changes. We merge the pupillometry with the multi-modal fMRI to examine the detailed arousal index by pupil dynamics and fMRI fluctuation. In summary, we hope to provide a novel perspective to under brain function with multi-modal fMRI across different scales.

About the speaker: I got my Bachelor's Degree in Microbiology and Immunology at Wuhan University in 2000. Then, I came to the US for a Mater training at Seton Hall University, working on effect of morphine on mu-opioid receptor expression in the Hippocampal-pituitary-adrenal gland of a drug-abused rat model. I, for the first time, learned about the brain function mapping in contrast to c-fos based immunohistochemistry. Then, I decided to work on MRI for brain mapping. Luckily, I got to work in Dr. Daniel Turnbull’s group at NYUMC on Manganese-enhanced MRI, in collaboration with Dr. Dan Sanes on the tonotopy mapping in mice and with Dr. Eric Lang and Dr. Rodolf Llinas on activity-dependent Mn tract-tracing from inferior olivary nucleus to cerebellum. After finishing my Ph.D. in 2007, I joined Dr. Alan Koretsky’s lab at NINDS to study brain plasticity by combining BOLD-fMRI and electrophysiology, as well as developing novel high spatiotemporal resolution fMRI methods. After 6 years postdoctoral training, I joined Max Planck Institute for Biological Cybernetics to build my own group to build a high field multi-modal fMRI laboratory with a fixed contract.

Tuesday, October 15, at noon

Aviv Mezer, PhD

Assistant Professor
Human Brain Biophysics Lab
Edmond and Lily Safra Center for Brain Sciences (ELSC)
The Hebrew University of Jerusalem
Disentangling molecular alterations from water-content changes in the aging human brain using quantitative MRI

Abstract: Quantitative MRI (qMRI) parameters such as T1 provide physical parametric measurements crucial for clinical and scientific studies. However, an important challenge in applying qMRI measurements is their biological specificity, as they change in response to both molecular composition and water content. I will discuss an approach that disentangles these two important biological quantities and allows for decoding of the molecular composition from the qMRI signal. I will demonstrate that this approach can reveal the molecular composition of lipid samples. Furthermore, we identify region-specific molecular signatures in the human brain that have been validated against histological measurements. Last, we exploit our method to reveal region-specific molecular changes in the aging human brain. I suggest that the ability to disentangle molecular signatures from water-related changes opens the door to a quantitative and specific characterization of the human brain.

Tuesday, October 8, at noon

Ray Razlighi, PhD

Assistant Professor
Department of Neurology, Columbia University
Department of Biomedical Engineering, Columbia University
Taub Institute for Research on Alzheimer’s Disease and the Ageing Brain
Hierarchical Structure of the Human Brain’s Macro-scale Networks

Abstract: This talk will start with a brief introduction of what is negative BOLD response in fMRI data and what are its characteristics. It continues by categorizing different types of negative BOLD signal according to their properties and outlines the optimal techniques used to extract negative BOLD response.

About the speaker: The applications of negative BOLD response are unlimited, however, three on-going research projects in our lab which extensively rely on negative BOLD response will be presented. First project uses negative BOLD response to demonstrate how spontaneous activity and task-evoked activity in the brain give rise to two spatially overlapping but temporally dissociable signals which both are manifested in fMRI data. Using these findings, the second project attempts to use negative BOLD response to demonstrate evidences for the hierarchical structure in the human brain functional networks. This is done by demonstrating that task-evoked negative BOLD response in the Default mode network is modulated by switching attention whereas the functional connectivity between the same network of regions remain intact. Finally, we introduce negative BOLD response as a new brain biomarker that could potentially differentiate between normal and pathological ageing brains.

Friday, October 4, at noon

Ricardo Coronado Leija, PhD

Postdoctoral Fellow
Universidad Nacional Autónoma de México
Instituto de Neurobiología Laboratorio de Conectividad Cerebral
A biological framework for the evaluation of per-bundle water diffusion metrics within a region of fiber crossing

Abstract: Several multiple fiber methods have been proposed that seem to overcome the limitations of the diffusion tensor and methodologies aimed to provide information from the diffusion signal, but that are mostly suited for single fiber population regions. Although the majority of these multiple fiber methods where created with the primary purpose of improving tractography results, some of them are able to provide per-bundle dMRI derived metrics. However, biological interpretations of such metrics are limited by the lack of histological confirmation.

To this end, we developed a straightforward biological validation framework. Unilateral retinal ischemia was induced in ten rats, which resulted in axonal (Wallerian) degeneration of the corresponding optic nerve, while the contralateral was left intact; the intact and injured axonal populations meet at the optic chiasm as they cross the midline, generating a fiber crossing region in which each population has different diffusion properties. Five rats served as controls. High-resolution ex vivo dMRI was acquired five weeks after experimental procedures.

We correlated and compared histology derived information to per-bundle descriptors obtained from three multiple fiber methodologies for dMRI analysis: constrained spherical deconvolution (CSD) and two multi-tensor (MT) representations. We found a tight correlation between axonal density (as evaluated through automatic segmentation of histological sections) with per-bundle apparent fiber density (from CSD) and fractional anisotropy (derived from the MT methods). The multiple fiber methods explored were able to correctly identify the damaged fiber populations in a region of fiber crossings (chiasm). Our results provide validation of metrics that bring substantial and clinically useful information about white-matter tissue at crossing fiber regions.

Our proposed framework is useful to validate other current and future dMRI multiple fiber methods; it also can be extended for the analysis of other pathological conditions, such as inflammation and demyelination, in order to evaluate the capabilities of these dMRI methods to differentiate between.

About the speaker: Dr. Coronado Leija has received his PhD in computer science at CIMAT, Mexico, under supervision of Drs Jose Zaleta and Alonso Manzanares, and is currently a postdoctoral fellow at UNAM with Dr Luis Concha. He is also a visiting scholar at Boston Children’s Hospital, where he is collaborating with Dr Benoit Scherrer on white matter degeneration in rats.

Tuesday, October 1, at noon

Patryk Filipiak, PhD

Postdoctoral Researcher
Athena Lab
Inria Sophia Antipolis, France
Bridging Brain Structure and Function by Correlating Structural Connectivity and Cortico-Cortical Transmission

Abstract: Elucidating the relationship between the structure and function of the brain is one of the main open questions in neuroscience. The capabilities of diffusion MRI-based (dMRI) techniques to quantify connectivity strength between brain areas, referred to as structural connectivity, in combination with modalities to quantify brain function such as electrocorticography (ECoG) have enabled advances in this field.

The aim of the project that I will talk about is to establish a relationship between dMRI-based structural connectivity and effective connectivity maps based on the propagation of Cortico-Cortical Evoked Potentials (CCEPs). To this end, we applied direct electrical stimulation of the cortex during awake surgery of brain tumor patients and recorded the induced electrophysiological activity with subdural ECoG electrodes.

I will briefly summarize our study of seven patients. For each of them, we correlated dMRI-based structural connectivity measures, including streamline counts and lengths, with delays and amplitudes of CCEPs. In addition, we used the structural information to predict the CCEP propagation with a linear regression model.

About the speaker: Patryk Filipiak is a post-doc researcher at the Athena Lab (Inria Sophia Antipolis, France) interested in the structural and effective brain connectivity and acquisition of MR images, working in a collaboration with the clinicians from l'Hopital Pasteur in Nice. He obtained his PhD in Computer Science from the University of Wroclaw (Poland) in December 2016. Simultaneously, he was hired as a researcher and software developer at Neurosoft GmbH (Bergisch Gladbach, Germany) in the project applying computational intelligence and statistical learning techniques to the vehicle traffic analysis.

Thursday, September 19, at noon

Lirong Yan, PhD

Assistant Professor of Neurology
USC Stevens Neuroimaging and Informatics Institute
Keck School of Medicine
University of Southern California
Advanced arterial spin labeling in cerebrovascular imaging

Abstract: Arterial spin labeling (ASL) is a non-invasive MRI technique for cerebral blood flow (CBF) measurement by using magnetically labeled blood spins as endogenous tracers. The recent development of ASL has promoted it as a useful imaging tool for tissue perfusion assessment in cerebrovascular disorders. For perfusion imaging, after spin tagging, images are generally acquired at a relatively long post-labeling delay time (~1.8s) when the labeled blood from labeling plane reaches capillaries/tissue. Additional physiological information can be derived during the passage of labeled blood through the cerebral arterial trees into capillaries and tissue, such as dynamic MR angiography, vascular territorial mapping, cerebral blood volume (CBV) and vascular compliance et al, all of which also provide useful information in the diagnosis and treatment of cerebrovascular disease. In this talk, I will introduce my work about these recent advances in ASL beyond CBF measurement.

About the speaker: My research interest focuses on the development of novel MRI techniques and clinical translations in noninvasive cerebral vascular and perfusion imaging. In particular, my research has been focused on the technical development of arterial spin labeling (ASL) based perfusion MRI, and dynamic intracranial MR angiography techniques as well as cerebral hemodynamic quantification. I developed a high spatial and temporal non-contrast enhanced 4-dimensional MR angiography (4D MRA) technique with cutting-edge fast imaging methods (e.g. golden angle radial with KWIC and CS reconstruction). I also proposed a noninvasive quantitative method for estimating arterial cerebral blood volume (CBV) using dynamic ASL technique and developed a noninvasive MRI technique to assess intracranial vascular compliance (VC). I have been working on Siemens platform for over 13 years and developed a couple of sequences including 4D MRA, concurrent BOLD/ASL with dual-echo EPI, random vessel-encoded ASL. Currently I serve as the principal investigator (PI) of an AHA Scientist Development Grant and an NIH K25 grant.

Thursday, September 5, at noon

Inge Brinkmann, PhD

Siemens Healthcare GmbH
Diagnostic Imaging
Inge at a glance

Abstract: Inge will be giving an overview of her work at Siemens Healthineers.

Tuesday, September 3, at noon

Fidel Guerrero Pena

PhD Candidate
Computer Science
Federal University of Pernambuco
Recife, Brazil
Loss Function Modeling for Deep Neural Networks Applied to Pixel-level Tasks

Abstract: In recent years, deep convolutional neural networks have overcome several challenges in the field of computer vision and image processing. In particular, pixel-level tasks such as image segmentation, restoration, generation, enhancement, and inpainting, showed significant improvements thanks to advances in the technique. In general, the supervised training of a neural network entails solving a high dimensional non-convex optimization problem whose objective is to transform the vectors of the input domain to a prescribed output. However, due to the high dimensionality of the parameter space and the presence of saddle points and large flat regions on the error surface, the process of training a neural network is extraordinarily challenging. We propose modeling new loss functions to facilitate training while improving the generalization of models for pixel-level regression and classification tasks. Our newly introduced loss functions modify the optimization landscape to achieve better results in regions which are notoriously more prone to failure. They increase the overall optimization performance and accelerate convergence. We applied our formulations to instance segmentation of cells with full and weak supervision and tested them on challenging biological images with isolated and cluttered cells. We also propose a new pixel-level regression loss function applied to the multi-focus image fusion problem resulting in the joint learning of activity level measurement and fusion rule. New pre-processing and post-processing techniques to help improve the solutions are also introduced. Our methods have shown significant improvements in the segmentation and image restoration tasks as reported by a diverse set of metrics and visual inspections.

About the speaker: Fidel Alejandro Guerrero Pena received the B.Sc. degree in Computer Science from the Universidad de Oriente, Cuba (2013) and the M.Sc. degree in Computer Science from the Center for Informatics (CIn) of the Federal University of Pernambuco, Brazil (2017). In the period 2013-2015 worked as a lecturer in Artificial Intelligence at Universidad de Oriente, Cuba. Since November 2016 work as a Computational Scientist in Motorola LLC/CIn partnership, Brazil. Currently is a Ph.D. student in Computer Science at the Federal University of Pernambuco and a Special Visiting Ph.D. student at the Biology and Biological Engineering division of the California Institute of Technology, USA. His research interests include Image Processing, Computer Vision, Machine Learning, and Deep Learning.

Thursday, August 29, at noon

Mijung Kim, PhD Candidate

Computer Science Engineering
Ghent University
Deep-Learning-Assisted Disease Diagnosis and Detection

Abstract: Recent achievement of deep learning algorithms using convolutional neural networks (CNNs) yields high performance of image classification and segmentation. The algorithms have been applied to assist doctor’s medical decision more efficiently and effectively. In this talk, I will introduce deep learning applications to rotator cuff tears, glaucoma, and intraocular pressure relations with daily diet pattern.

About the speaker: Mijung Kim is a PhD candidate in Computer Science Engineering at Ghent University, Belgium since September 2015. Actively collaborating with domain experts, i.e. orthopedists, ophthalmologists, and radiologists, she has been researching on computer aided disease diagnosis such as Glaucoma and Rotator Cuff Tear using deep learning algorithms over medical imaging such as fundus, X-rays, and magnetic resonance (MR) images. Current research is focusing on tackling data imbalance issue for classification and weakly supervised localization of medical imaging data.

Tuesday, August 27, at noon

Amparo Ruiz, PhD

Senior Research Scientist
Co-Director of OLE! (Osteoarthritis Lab for Experimental Imaging)
Department of Radiology
NYU Langone Health
A Molecular Imaging Approach to Study, Diagnose and Treat Osteoarthritis

Abstract: Osteoarthritis (OA) is the most common form of arthritis, affecting millions of people in the US for which only palliative treatments are available until joint replacement surgery. The elusiveness of effective OA treatments is the consequence of OA being a complex disease. OA is a multifactorial disease with inflammatory, metabolic, and mechanical causes involving all tissues of the joint. Thus, we still lack understanding on OA pathogenesis, in part due to the lack of diagnostic biomarkers that can detect early pathological changes in the joint and monitor therapy. A major barrier in OA research is to see and understand the interplay between OA factors to both be able to phenotype OA and provide patient-specific treatments. At OLE! (Osteoarthritis Lab for Experimental !maging), we aim to solve this technological problem by developing advanced imaging technology that can monitor in vivo of the influence of OA factors and treat them. We have established an innovative research program for in vivo molecular imaging of the degenerative joint. We are developing imaging probes with theragnostic potential that combine the specificity of biochemical assays with anatomical and tissue-specific assessment of early degenerative changes.

Thursday, August 22, at noon

Mahesh B. Keerthivasan

Postdoctoral Research Scientist
Mahesh B Keerthivasan
Non-Cartesian Techniques for Quantitative Parameter Mapping

Abstract: Conventional T1- and T2- weighted pulse sequences are routinely used in the clinic for the diagnosis of a variety of pathologies. Quantatative estimation of tissue relaxation times can be used to further improve the quality of diagnosis in applications including cardiac, abdominal, and musculoskeletal imaging. In this talk, I will introduce a radial Turbo Spin Echo (RADTSE) pulse sequence for simultaneous T2w imaging and T2 mapping. Specifically, I will present a RADTSE pulse sequence with very long echo train lengths and variable refocusing flip angles for improved slice coverage in abdominal breath-held imaging. I will also discuss a simultaneous multi-slice excitation technique to improve the slice and SNR efficiency of double inversion RADTSE for cardiac imaging. Finally, I will give an overview of my ongoing research on quantitative T1 mapping and the use of artificial intelligence for analysis of deep brain structures.

About the speaker: Mahesh is currently a Postdoctoral Research Scientist at Siemens Healthineers USA. He received a B.Eng. from Anna University, India in 2009 and an M.S. from University of Arizona in 2012. In August 2018, he earned his PhD in Electrical and Computer Engineering from the University of Arizona, under the mentorship of Dr. Diego Martin and Dr. Maria Altbach. His research focus has been on the development of pulse sequences and computational methods for quantitative MR imaging.

Tuesday, August 20, at noon

Assaf Tal, PhD

Principal Investigator
Department of Chemical Physics
Weizmann Institute of Science
Magnetic Resonance Spectroscopy: From Multiparametric to Functional

Abstract: Magnetic Resonance Spectroscopy (MRS) is used to non-invasively monitor the in-vivo biochemistry of tissue, by quantifying the concentrations of several prominent metabolites, including glutamate, choline, GABA and creatine, among others. Conventional MRS produces static estimates of concentrations. In this talk, I will present two recent advances in MRS methodology which provide a more dynamic information. First, I will discuss our work on multiparametric MRS, which simultaneously quantifies metabolite concentrations and relaxation times (T1, T2). Both T1 and T2 provide information about the molecular microenvironment of the metabolites via their microscopic dynamics. In the second part of the talk, I will discuss our work on functional MRS, which examines the temporal changes to several prominent metabolites in response to external stimuli, and discuss some of our interpretations to the changes measured in this unsolved, fascinating puzzle.

Tuesday, August 13, at noon

Fei Gao, PhD

Staff Scientist
Research Department at Siemens Molecular Imaging
Knoxville, TN
Innovation from Image Formation to Post-processing

Abstract: In this talk, I will introduce my recent research activities from image formation to post processing using examples of whole body scatter estimation and image reconstruction for Biograph mMR and a deep learning powered lung analysis post processing application. For the Biograph mMR, we designed a new method to process step and shoot sinogram to simulate a whole body sinogram and reconstruct the whole body image directly, which increases the quantitative accuracy of scatter estimation and improves performance of image reconstruction. For post-processing, I will showcase several AI predevelopment activities, focusing on the lung ventilation / perfusion application. Here, deep learning-based lung lobe segmentation has been developed to enable a potentially fully automated workflow for lung analysis. This prototype is available on the Siemens Frontier platform, offering a seamless integration to syngo.

About the speaker: Fei Gao, Ph.D. is currently a staff scientist in the research department at Siemens Molecular Imaging in Knoxville, Tennessee. He has a wide range of experiences from image formation to post-processing, having worked on many Siemens scanners and postprocessing environments, i.e. PET/CT, PET/MR, SPECT/CT and syngo.via. His research interests cover image reconstruction, data correction, clinical application, as well as using artificial intelligence to improve workflow and user experiences.

Tuesday, August 6, at 4:00 p.m.

Tullie Murrel

Applied Research Scientist
Facebook AI Research (FAIR)

Abstract: fastMRI is a collaborative research project between Facebook AI Research (FAIR) and NYU Langone Health. The aim is to investigate the use of AI to improve acceleration and robustness of MRI scans. In this talk, Tullie, a Research Engineer at FAIR, will give an overview of the work done on knee image reconstruction and reinforcement learning based active sampling. He will cover the plans going forward to investigate brain image reconstruction, motion robust reconstructions for Dynamic MRI and extensions to the active sampling work.

Tuesday, August 6th, at noon

Jose Maria Carazo

Head, Bio-Computing Unit (BCU)
National Center of Biotechnology
Madrid, Spain
Analyzing and enhancing cryo EM maps using local directional resolution

Abstract: Expecting to fully engage equally deep Physicists and Biologists, I will introduce the notion of "how good a macromolecular CyoEM map is", addressing this question in a totally new way in the field, by providing a "resolution tensor" per CryoEM voxel map (instead of just a number, the so-called "local resolution"). The mathematical beauty of this tensor representation will immediately open a new university of opportunities for experimentalists in CryoEM (clearly impacting Pharma), with the capability to assess the quality of the map from the map itself (without the images), the alignement errors, the presence of problematic directions..... and much more.

About the speaker: I was born in the beautiful town of Granada, Spain. It was in this University where I finished my Master in Physics. I then moved to the IBM Madrid Scientific Center, where I was confronted with the image processing challenges behind the emerging techniques, at the time, of three-dimensional electron microscopy (3D-EM) and the different atomic scanning techniques in whose development IBM was engaged. I defended my PhD in Molecular Biology at the University Autonoma of Madrid (UAM) in 1984. I left for Albany, New York, in 1986, to join the Wadsworth Center of the NYS Department of Health, to work under the direction of Dr. Joachim Frank. My coming back to Madrid happened in 1989, setting up the BioComputing Unit of the newly established National Center for Biotechnology (CNB), nowadays the largest Center of the Spanish High Research Council (CSIC), located in the campus of the UAM. Currently I keep busy in Madrid, fully engaged in my activities at the CNB and Instruct, after a period in which I was deeply involved in technology transfer, spinning of, maturing and finally selling to Perkin Elmer (PKI) our bioinformatics company Integromics.

Thursday, August 1, at noon

Andrew Alexander, PhD

Professor of Medical Physics and Psychiatry
Co-Director of Waisman Brain Imaging Lab
University of Wisconsin-Madison
Efficient Motion-Corrected Multiple Contrast MRI with MPnRAGE

Abstract: T1-weighted structural imaging with MP-RAGE is a cornerstone of brain imaging studies for both clinical and research applications. However it is sensitive to head motion, RF inhomogeneities, and provides only a single image contrast. Recently, we developed MPnRAGE which combines inversion magnetization preparation with a 3D radial rapid gradient echo readout. This sampling enables the simultaneous acquisition of n inversion recovery contrasts, which may be used to generate one or more application specific contrast images, and generate high resolution, whole-brain T1 relaxometry images. The 3D radial sampling is also highly amenable to self-navigated motion correction during the reconstruction, which provides robust and reliable high quality T1-weighted and quantitative T1 images of the brain. This technique is highly promising for brain imaging studies of children, aging and brain pathology.

About the speaker: Dr. Andy Alexander is Professor of Medical Physics and Psychiatry at the University of Wisconsin – Madison and is Co-Director of the Waisman Brain Imaging Laboratory. He received his PhD in Optical Sciences from the University of Arizona and did postdoctoral training in MRI at the University of Utah. His research program is focused on quantitative MRI using diffusion and relaxometry methods for characterizing the brain across the lifespan with a focus on neurodevelopment and intellectual and developmental disorders. Dr. Alexander’s current research includes studies of autism, pediatric brain injury, infant brain development, Down syndrome, and aging.

Tuesday, July 23, at noon

Kawin Setsompop, PhD

Associate Professor
Harvard Medical School
New directions in MRI through tailored acquisitions

Abstract: A synergistic approach in developing MRI acquisition through utilizing the interplay between hardware design, software algorithm development, and MR physics has dramatically increased MRI’s spatiotemporal resolution capability. IN this talk, I will cover some of these tailored acquisition strategies which are being pioneered by my group, focusing particularly on applications in rapid imaging, diffusion, & fMRI, and quantitative and multidimensional/time-resolved imaging of the brain. The overarching theme is in radically improving the speed, sensitivity, and specificity of in vivo brain imaging, with the goal in providing more detailed information about the brain both in health and disease.

Tuesday, July 16, at noon

Jimin Ren, PhD

Associate Professor, Advanced Imaging Research Center
Associate Professor, Department of Radiology
University of Texas Southwestern Medical Center
Imaging Metabolic Processes and Identifying Biomarkers of Diseases at 7 Tesla

Abstract: Dr. Ren will discuss a series of studies using dynamic and kinetic MRS, that have identified cellular energetic activities in multiple pathways. He will also demonstrate how 7T 31P MRS can serve as a powerful tool to capture aberrant brain events in remote skeletal muscle.

About the speaker: Dr. Ren’s motivating interest is in energy metabolism and especially in understanding how different metabolic pathways interact to meet body’s energy demand and maintain homeostasis. His research centers on developing technical protocol and methods for imaging metabolic processes and identifying biomarkers of diseases by 1H/13C/31P MR spectroscopy at ultrahigh field 7T. Dr. Ren has wide collaboration with on- and off-campus investigators of a variety of interests and background, with hands-on experience of scanning >1000 subjects for metabolic imaging of brain, liver and skeletal muscle.

Monday, July 15, at noon

Nastaren Abad, MS

PhD Candidate
Florida State University
Chasing the trinity: Characterization of acute migraine

Abstract: Migraine is a disabling, multifactorial recurrent neurological disorder. Affecting approximately 38 million people in the United States alone, migraine is recognized by the World Health Organization as the 7th most disabling condition, due to the sufferer’s inability to perform everyday activities. The characterization, classification and diagnosis of migraine is complex due to the tremendous cohort of variable clinical triggers and symptoms reported. Collectively, the symptoms accompanying migraine implicate multiple neural networks and processes functioning abnormally. A mechanistic search for a common denominator based on the symptoms in migraine potentially involves the recruitment of the thalamic region (fatigue, depression, irritability, food cravings), brainstem (muscle tenderness, neck stiffness), cortex (sensitivity to photo and phono) and limbic response (depression anhedonia).

The prevailing consensus in the migraine community appears to indicate a combination of neuronal and vascular involvement with the trigeminal vascular system (TGVS) complicit in the progression of migraine. Broadly, various triggers initiate migraine to differing degrees and treatment methodologies target a variety of pathways with varied results; the fundamental mechanism driving change is unclear. In the absence of an identifiable locus for anatomical, biochemical or pathological change in common clinical migraine, a fundamental question remains unanswered: What endogenous media and pathways link the stimulus to perception of migraine and potentially pain?

The goal of this talk is to highlight progress made in the characterization of acute triggered migraine. To elucidate this neurovascular coupled system, two fundamental mechanisms complicit in neuronal disorders are explored, namely ionic fluxes using sodium MRI and metabolic changes by utilizing proton spectroscopy as well as ongoing efforts to characterize cerebral perfusion—with and without pharmaceutical prophylaxis.

About the speaker: Nastaren Abad is a graduate student at Florida State University and the National High Magnetic Field Laboratory, under the mentorship of Dr. Samuel C. Grant. She has a BS degree in Chemical Engineering, with an MS degree in Biomedical Engineering. Her PhD dissertation in Biomedical Engineering is due to be defended in Fall 2019. Her research focuses on utilizing MR Imaging and Spectroscopic techniques for the characterization of neurological diseases and disorders.

Wednesday, June 26, at noon

Elena Sizikova

PhD Student and NSF Graduate Fellow
3D Vision Lab
Princeton University
Structure-Aware Shape Analysis in Medical Imaging

Abstract: Automatic delineation and measurement of main organs is one of the critical steps for assessment of disease, planning and postoperative or treatment follow-up. Internal human anatomy is composed of complex shapes that exhibit a large degree of variation, which is challenging to capture using existing modeling tools. We observe that complex shapes can be learned by neural networks from large amounts of examples and summarized using a coarsely defined structure, which is consistent and robust across variety of observations. Further, shape structure can be used in the synthesis process to improve the quality of generated shapes. We study medical applications of 3D organ reconstruction from topograms and synthetic X-ray prediction and propose several ways of incorporating structure into the synthesis process, and. We also show compelling quantitative results on 3D liver shape reconstruction and volume estimation on 2129 CT scans.

About the speaker: Elena is a PhD student and an NSF Graduate Fellow in the 3D Vision Lab in Princeton University, advised by Prof. Thomas Funkhouser. Her research interests lie at the intersection of computer vision applications to medical imaging and perception, shape analysis, and computer graphics. She received best paper awards in EUROGRAPHICS Workshop on Graphics and Cultural Heritage (GCH) in 2016 for her work on archeological shape reconstruction, and in ECCV Virtual/Augmented Reality for Visual Artificial Intelligence (AVRVAI) in 2016 for her work on neural place recognition. During her PhD, she spent time in Vision Technologies and Solutions (VTS) group in Siemens Healthcare and in Adobe Research. She will be starting as a Moore-Sloan Faculty Fellow/Assistant Professor in the NYU Center for Data Science (CDS) in September 2019.

Tuesday, June 11, at noon

Simone A. Winkler, PhD

Weill Cornell Medicine
MRI Research Institute
Ultra High-Field MRI
The essential role of multidisciplinary engineering in Ultra High-Field MRI

Abstract: Magnetic Resonance Imaging (MRI) has emerged as one of the most powerful and informative diagnostic tools in modern medicine. While most clinical MR studies use magnetic field strengths of 1.5T or 3T, leading research is pushing these magnetic field strengths to 7T and beyond. These new ultra high‐field (UHF) technologies promise images with higher spatial resolution, higher sensitivity to subtle change, and novel contrasts, which will in turn improve our basic understanding of anatomy and physiology in both healthy tissue and disease. However, there are substantial hurdles to surmount before we will reap the promised benefits of UHF MRI in clinical applications. This talk will introduce some of the major challenges faced in UHF MRI and will summarize a number of concepts in engineering and multiphysics that are being researched to overcome these issues.

About the speaker: Dr. Simone Angela Winkler is a Stanford-trained and NIH K99/R00 funded assistant professor at Weill Cornell Medicine. Her research focuses on Ultra High-Field MRI and multidisciplinary engineering applied to medicine and medical imaging.

Wednesday, May 22, at noon

Michael T. McMahon, PhD

Associate Professor
F.M. Kirby Research Center for Functional Brain Imaging
Kennedy Krieger Institute, JHU
Monitoring progression in kidney disease using pH and perfusion MRI

Abstract: Chronic Kidney Disease (CKD) is a cardinal feature of methylmalonic acidemia (MMA), a prototypic organic acidemia. Impaired growth, low activity, and protein restriction affect muscle mass and lower serum creatinine concentrations, which can delay the diagnosis and management of renal disease in this patient population. We have designed a general alternative strategy for monitoring renal function based on administration of a pH sensitive MRI contrast agents to acquire functional information. We have tested our methods in a mouse model of MMA, and detected robust differences in the perfusion fraction and pH maps we produce between groups with severe, mild, and no renal disease. Our results demonstrate that MRI contrast agents can be used for early detection and monitoring of CKD, particularly in disorders that alter renal pH and perfusion such as MMA.

About the speaker: Dr. Michael T. McMahon is an Associate Professor in The Russell H. Morgan Department of Radiology and Radiological Sciences at the Johns Hopkins School of Medicine and an affiliated faculty in the F.M. Kirby Research Center for Functional Brain Imaging at the Kennedy Krieger Institute. He received his BS in Physics from the University of Richmond and PhD in Physical Chemistry from the University of Illinois at Urbana-Champaign where he worked under Eric Oldfield on solid state NMR. He was further trained in magnetic resonance as a postdoctoral fellow in Robert Griffin’s laboratory at the Francis Bitter Magnet Laboratory at the Massachusetts Institute of Technology and joined the faculty at the Johns Hopkins School of Medicine and the Kennedy Krieger Institute where he has remained for the last 15 years. Dr. McMahon’s group has made many contributions to the field of MRI with this work involving the interplay between chemistry, biomaterials, and imaging. His group has developed MR imaging agents using Chemical Exchange Saturation Transfer (CEST), hyperpolarization, fluorine and a major emphasis of his group is on using contrast agents for functional imaging of the kidneys. He has received predoctoral and postdoctoral fellowships from the National Institutes of Health, a President’s International Fellowship from the Chinese Academy of Sciences, and has been recognized as a Distinguished Reviewer by Magnetic Resonance in Medicine from 2010-2017 and a Top Reviewer of 2018 by the Journal of Magnetic Resonance.

Tuesday, May 21, at noon

Alex T. L. Leong, PhD

Research Assistant Professor
Department of Electrical and Electronic Engineering
The University of Hong Kong
Window to Understanding Multisensory Large-scale Brain Networks through Optogenetic Functional MRI (fMRI)

Abstract: One grand challenge for the 21st century is to achieve an integrated understanding of brain circuits and networks, particularly the spatiotemporal patterns of neural activity that give rise to functions and behavior. Brains form highly complex circuits where circuit elements communicate using electrical and/or chemical signals. Such communications are typically facilitated through long-range projections that interconnect numerous regions, giving rise to a network-like property in the brain. Despite their importance, the functions of long-range projections remain poorly understood. Here, I will show you our recent developments in deploying multimodal techniques in-vivo on rodents to interrogate multisensory brain networks; leveraging on the strengths of optogenetics to enable cell-type specific neuromodulation, functional MRI (fMRI) to visualize brain-wide neural activity, and electrophysiology to explore the neural mechanism(s) that underlie our observations. I will present key findings from our work in the multisensory thalamo-cortical, cortico-cortical, and cortical-subcortical circuits, including the unique dynamic spatiotemporal response properties of multisensory pathways as well as their functional relevance. From this talk, I aim to show you how utilization of multimodal brain imaging techniques can be vital in our quest to achieving an integrated and systemic understanding of large-scale brain-wide multisensory interactions.

About the speaker: Alex T. L. Leong is currently a Research Assistant Professor in the Department of Electrical and Electronic Engineering, The University of Hong Kong. He received his doctorate in electrical and electronic engineering (MRI neuroimaging) from the same university, under the supervision of Prof. Ed X. Wu. For his Ph.D., he worked on combining optogenetics with fMRI in the study of spatiotemporal properties that govern neural activity propagations and interactions in the sensory thalamo-cortical network and the neural underpinnings of brain-wide functional connectivity as measured with resting-state fMRI. He received numerous awards in recognition of his work in functional neuroimaging, including ISMRM's Junior Fellow Award and OCSMRM’s Young Investigator Award. His current research interests include the use of neuroimaging, particularly MRI, to visualize complex and poorly understood brain networks in preclinical animal models; and develop novel non-invasive neuromodulation techniques that can be translated for therapeutic use.

Thursday, May 9, at noon

Frank Ong, PhD

Postdoctoral Researcher
Stanford University
Extreme MRI: Reconstructing Hundred-Gigabyte Volumetric Dynamic MRI from Non-Gated Acquisitions

Abstract: In this talk, I will present techniques to reconstruct 3D dynamic MRI of ~100 GBs from non-gated acquisitions. The problem considered is vastly undetermined and demanding of computation and memory. I will introduce a multi scale low rank matrix model to compactly represent dynamic image sequence. This enables compressed storage, which in combination with a stochastic optimization approach, renders the reconstruction of 100s of GBs of images feasible. The proposed method is applied to dynamic contrast enhanced MRI and free breathing lung MRI, with reconstruction resolution of near millimeter spatially, and sub-second temporally. The attached animated gif shows a 3D rendered result from this talk.
(Joint work with Xucheng Zhu, Joseph Cheng, Peder Larson, Shreyas Vasanawala, and Michael Lustig)

About the speaker: Frank Ong is a post-doctoral researcher at Stanford University, working with Prof. Shreyas Vasanawala and Prof. John Pauly. His research focuses on computational imaging methods in medical imaging, particularly in MRI. He received his PhD degree from UC Berkeley in Fall 2018, under the mentorship of Prof. Michael Lustig.

Friday, May 3, at noon

Sandip Biswal, MD

Associate Professor
Department of Radiology
Stanford University School of Medicine
Imaging Pain: Pinpointing the site of pain generation using clinical molecular imaging and PET/MRI

Abstract: Pain is now the #1 clinical problem in the world and, yet, our current imaging methods to correctly identify pain generators remain woefully innacurate. The fact that meniscal tears, herniated discs, arthritis and rotator cuff tears are seen in asymptomatic individuals supports the disturbing fact that standard-of-care imaging techniques are extremely poor at pinpointing the exact site of pain generation. This dearth of unreliable diagnostic tools necessarily facilitates significant misdiagnosis, mismanagement, rampant use of opioids and unhelpful surgeries. Thankfully, relatively recent developments in clinical molecular imaging (MI) are affording the opportunity to pinpoint the exact site(s) of pain generation due to advances in biomarker discovery, imaging technology and radiotracer design. Our group has developed a highly specific 18F-labeled positron emission tomography (PET) radiotracer for imaging the sigma-1 receptor (S1R), a master regulator of ion channel activity and molecular biomarker of pain generation. Additionally, we have repurposed 18F-fluordeoxyglucose (FDG) as a marker of inflammation by virtue of its proclivity for metabolically active processes. Here, we will describe our experience using these radiotracers in our ongoing PET/MRI clinical trials of patients with chronic pain. Importantly, we will illustrate how this new imaging method is enabling more accurate identification and localization of pain generators and is starting to positively impact the way we treat pain.

Michelle James, PhD

Stanford University School of Medicine
Imaging the brain on fire – PET tracer design and development for visualizing neuroinflammation

Abstract: Neuroinflammation is a key pathological feature of many central nervous system (CNS) diseases. Although extensive work in preclinical rodent models demonstrate a significant role for both the innate and adaptive immune response in the initiation and progression of neurological diseases, our understanding of these responses and their contribution to human disease remains very limited. ​Additionally, ​both beneficial and toxic inflammatory processes are associated with progression and remission of neurological disease, and the spatiotemporal course of these complex responses remain a mystery especially in the clinical setting. Molecular imaging using positron emission tomography (PET) has enormous potential as a translatable technique to enhance our understanding of neuroinflammation in CNS diseases. Our experience with developing new PET radioligands for visualizing the neuroinflammatory component of Alzheimer’s disease, multiple sclerosis, and stroke will be described. I will provide examples regarding our work on d​esigning radioligands for the translator protein 18 kDa (TSPO), triggering receptor expressed on myeloid cells 1 (TREM1), and two B lymphocyte surface antigens. Specifically, the in vivo role, spatiotemporal dynamics, ​peripheral contribution and different functional phenotypes of innate and adaptive immune cells throughout the progression of CNS diseases will be shown. Moreover, I will describe how we are starting to apply these tools to track disease progression, guide therapeutic selection for individual patients, and serve as surrogate endpoints in clinical trials.

Tuesday, April 30, at noon

Marios Georgiadis, PhD

SNSF Post-Doctoral Fellow
NYU Langone Medical Center
Combining MRI with X-rays to Assess Tissue Microstructure

Abstract: Although both MRI and CT resolutions are limited, different MRI and X-ray modalities offer possibilities for tissue microstructure analyses. Diffusion MRI is sensitive to proton displacement in the micrometer scale, whereas X-ray photons scatter off the sample’s micro- and nano-structure.

Recently, we developed techniques based on X-ray scattering that allow tomographic investigations of the sample’s fiber orientations. In brain, these techniques also allow quantifying myelin content, due to myelin’s repetitive structure.

In this talk I will give an overview of my work in CBI in the past two years; I will present applications of these techniques to mouse and human CNS, to derive fiber orientations and myelin content in healthy, diseased and treated tissue, and comparison to diffusion MRI metrics.

About the speaker: Marios has been part of the Fieremans-Novikov group for the past two years, looking into CNS microstructure. He is a mechanical engineer by training (School of Mechanical Engineering, National Technical University of Athens, Greece). He obtained his MSc in Biomedical Engineering from ETH Zurich (Swiss Federal Institute of Technology), receiving the ETH medal for his thesis. He did his PhD in Bone Biomechanics in the lab of Ralph Muller in ETH Zurich, earning the 2nd Student Award from the European Society for Biomechanics in 2015 for developing X-ray scattering-based methods to investigate bone microstructure in 3D. He then switched to neuroscience, doing a post-doc in the lab of Markus Rudin, in ETH Zurich, where he started looking into combining DTI with X-ray scattering for studying rodent brain. He is recipient of the Early Postdoc Mobility and Postdoc Mobility Fellowships from the Swiss National Science Foundation. He will next move to Stanford University, to work with Michael Zeineh on the study of diseased CNS tissue.

Thursday, April 25, at noon

Mami IIMA, MD, PhD

Department of Radiology
Institute for Advancement of Clinical and Translational Science
Kyoto University Hospital, Kyoto, Japan
Breast DWI: ADC and beyond

Abstract: Diffusion MR imaging has become an important clinical imaging modality in breast imaging, for the detection of malignant lesions and metastases, as well as for therapy monitoring. Some studies have shown that pretreatment ADC has might be a useful biomarker to predict response to breast cancer therapy. However, non-Gaussian diffusion might potentially extract more microstructural information than the ADC, as with a high degree diffusion weighting (high b values) one increases the effects of obstacles to free diffusion present in tissues, notably cell membranes. Indeed, the “kurtosis” which reflects diffusion non-gaussianity is high in malignant lesions compared to benign lesions. Still, a particularly challenging problem for breast diffusion MRI is the detection of the non-mass enhancing lesions seen on contrast-enhanced MRI, such as with DCIS. High-resolution images using readout- segmented EPI might overcome the low sensitivity of such lesions. On the other hand, tissue perfusion which is also available from diffusion MRI images (IVIM effect) gives information on the blood fraction which appears correlated with vessel density. The IVIM fraction is usually high in malignant lesions, but there seems to be a large overlap with benign lesions. Combination of non-Gaussian diffusion and IVIM parameters appears to boost diagnosis accuracy. Still, the results have been sometimes inconsistent in the literature partly due to differences in study design (choice of b values and acquisition methods, data analysis approaches, differences in patient population), and the standardization of acquisition protocols and processing methods used for quantitative DWI analysis is a very important step for for diffusion MR imaging to become a clinically recognized biomarker.

The investigations on the relationship between the IVIM/diffusion parameters and the underlying tissue structure at microscopic level, as well as changes induced by therapy, must be pursued using animal models, MRI of specimens at ultra-high resolution and validation with histology. Reliability and reproducibility of diffusion MRI results must also be assessed to facilitate monitoring disease progression or response to therapy in individual patients.

About the speaker: Mami Iima is a radiologist and assistant professor of Department of Radiology, and Institute for Advancement of Clinical and Translational Science at Kyoto University Hospital, Japan. She holds an MD and a PhD and has published important articles about IVIM and diffusion MRI mainly in the breast and is a coeditor of the first textbook published on IVIM MRI. She has received the awards, including Kyoto University President Award, JSPS Ikushi Prize by Japanese Emperor and Empress, the Most Outstanding Female Researcher award at Kyoto University, and Magna Cum Laude of ISMRM.

Thursday, April 25, at 10:30 a.m.

Denis Le Bihan, MD, PhD

NeuroSpin, CEA-Saclay Center, Gif-sur-Yvette, France
NIPS, Okazaki, Japan
Human Brain Research Center, Kyoto University, Kyoto, Japan
From molecules to mind: MRI’s potential for future’s medicine

Abstract: The understanding of the human brain is one of the main scientific challenges of the 21st century. Unraveling the biological mechanisms of our mental life should help us understanding neurological or psychiatric diseases to allow early diagnosis and treatment of patients, with obvious economical counterparts. In this quest of the human brain neuroimaging and especially MRI has become an inescapable pathway because it allows getting maps of brain structure and function in situ, non-invasively, in patients or normal volunteers of any age. MRI allows brain anatomy of individuals to be visualized in 3 dimensions with great details, as well as networks of brain regions activated by high order cognitive functions, together with stunning images of the connections between those areas. Still, images remain at a macroscopic scale (millions of brain cells), while invasive techniques in animals and tissues explore very small ensembles of neurons. This large gap must be bridged to understand how the brain works, as interaction and synergy exist between all brain levels. One approach is to rely on diffusion MRI, a concept which has been develop from the mid-1980s based on Einstein’s framework to probe tissue structure at a microscopic scale while images remain at millimeter scale through parametrization or modeling, providing unique information on the functional architecture of tissues. Since then, diffusion MRI has become a pillar of modern clinical imaging. Diffusion MRI has mainly been used to investigate neurological disorders, but is now also rapidly expanding in oncology, to detect, characterize or even stage malignant lesions, especially for breast or prostate cancer. In the brain diffusion MRI even allows to reveal dynamic changes occurring in tissue microstructure intimately linked to the neuronal activation mechanisms. On the other hand, outstanding instruments operating to field of 11.7 teslas or above are now emerging to boost the spatial and temporal resolution to not only allow us to "better" see inside our brain, confirming or invalidating our current assumptions on how it works, but also to generate new assumptions and elaborate a kind of “Gauge Theory” to help us decode the functioning of our brain.

About the speaker: Denis Le Bihan holds an M.D. (Neurosurgery and Radiology) and a Ph.D. in Physics (Nuclear and Elementary Particles). Since 1987 he has hold positions in the USA (NIH, Bethesda, Maryland and Georgetown University, Washington, DC) France (CEA) and Japan (Kyoto University). In 2007 De. Le Bihan became the Founding Director of NeuroSpin, a new Institute of the French CEA aimed at developing and using ultra high field Magnetic Resonance to understand the brain. Dr. Le Bihan is especially credited with inventing, developing and introducing into research and clinical practice the concept of diffusion MRI, a new and powerful approach to study normal and diseased brain anatomy and function, as well as brain wiring. Le Bihan has received many awards, such as the Gold Medal of the International Society for Magnetic Resonance in Medicine, the Lounsbery Award from the National Academy of Sciences (USA) and French Academy of Sciences, the Louis D. Award of the “Institut de France”, the Honda Prize and Louis Jeantet Foundation Award. Dr. Le Bihan is a full member of the French Academy of Sciences and of the Academy of Technologies, and an Associate Member of the National Academy of Pharmacy and a corresponding member of the National Academy of Medicine.

Tuesday, April 16, at noon

Ida Haggstrom, PhD

Postdoctoral Research Fellow
Memorial Sloan Kettering Cancer Center
The Thomas Fuchs Lab
DeepPET: A deep encoder–decoder network for directly solving the PET image reconstruction inverse problem

Abstract: To overcome the lack of automation and long computational times for advanced PET image reconstruction methods, we present a novel encoder-decoder architecture that quickly reconstructs high quality images directly from PET sinogram data. DeepPET is trained and evaluated on realistic, simulated data, and resulting images have higher quality than conventional techniques, and takes a fraction of the time to generate.

Tuesday, April 9, at noon

Carlotta Ianniello, MS

PhD Candidate
Biomedical imaging program
Sackler Institute of Biomedical Science
NYU Langone Health
Sodium (23Na) MRI in breast at 7T

Abstract: Sodium (23Na) MRI has shown promise for monitoring neoadjuvant chemotherapy (NACT) response in breast cancer. Unfortunately, due to low sodium content in the body, its low MR sensitivity and short relaxation times in biological tissues, 23Na MRI suffers from intrinsically low signal-to-noise ratio (SNR), which can be up to 20,000 times lower than that of proton. Such low SNR translates into low spatial resolution and long acquisition times. Efforts to alleviate these challenges generally utilize high field systems (≥ 3 T), ultra-short echo time (UTE) acquisition methods, and tailored radiofrequency coils to boost the baseline SNR. Our focus is the coil design aspect. Specifically, we present a dual-tuned multichannel 1H/23Na bilateral breast coil consisting of volume transmit/receive (Tx/Rx) 1H coils, volume 23Na transmit coils and an 8-channel 23Na receive array for 7 T MRI which enabled sodium imaging in vivo with 2.8 mm isotropic nominal resolution (~5 mm real resolution) in 9:36 min. The proposed coil could enable access to even more specific biomarkers of cellular metabolism such as intracellular sodium concentration, and cellular density such as extracellular volume fraction that are still largely unexplored due to the challenges associated with 23Na MRI.

About the speaker: Carlotta Ianniello received her Bachelor and Master degree in biomedical engineering from Federico II University in Naples (Italy). She is currently a PhD candidate working with Ryan Brown and Guillaume Madelin at NYU Langone Health. Carlotta’s focus is hardware development for sodium 23Na MRI in the breast.

Monday, April 8, at noon

Spencer Brinker, PhD

Yale School of Medicine
Transcranial Ultrasound and Monitoring Devices for Brain Stimulation: Benchtop to Human-Scale Prototype Development in the Lab

Transcranial Ultrasound and Monitoring Devices for Brain Stimulation: Benchtop to Human-Scale Prototype Development in the Lab

Abstract: Transcranial Ultrasound (TUS) is an emerging field with a vast range of new potential clinical applications. Here, a series of new human scale TUS devices and the novel benchtop strategies used to develop them in the laboratory will be presented. These devices are intended for brain tumor cancer therapy and for treating neurological disorders such as epilepsy, pain, depression, and essential tremor. The presentation will include the latest developments for: 1) A neuronavigation-guided single-element transducer platform for delivering multi-target pulsed low-intensity TUS to human brain. 2) An integrated scalp sensor for simultaneous electroencephalography and acoustic emission detection. 3) A 3D passive acoustic mapping array device compatible with the FDA approved ExAblate 4000 system for localizing microbubble cavitation. Highlights of each technique relevant to current clinical investigations and future directions of each strategy will be discussed.

About the speaker: Spencer Brinker, PhD. is a postdoctoral associate in the Department of Anesthesiology at the Yale School of Medicine. His primary research is developing innovative transcranial ultrasound methods and technologies for human use to treat brain disorders. Other aspects of his research include using preclinical MRI and other non-invasive techniques to measure the propagation of mechanical waves in the brain to better understand their influence on brain physiology. Dr. Brinker received his PhD. in Mechanical Engineering from the University of Illinois at Chicago where he specialized in experimental Magnetic Resonance Elastography. Following that, he completed postdoctoral fellowship in the Focused Ultrasound Laboratory at Brigham & Women’s Hospital, Harvard Medical School and was a Research Fellow in the Ferenc Jolesz National Center for Image-Guided Therapy Multidisciplinary Program.

Tuesday, April 2, at noon

Zidan Yu, MS

PhD Candidate
Biomedical imaging program
Sackler Institute of Biomedical Science
NYU Langone Health
Simultaneous proton MRF and sodium MRI

Abstract: Sodium(23Na) MRI can provide unique metabolic information to study the human body and its afflictions. However, the low intrinsic SNR of sodium MRI limits the resolution of the images to 3-5 mm isotropic and necessitates long acquisition times (~10-20 min). Moreover, the necessity to perform 1H and 23Na acquisitions sequentially prolongs the total scan time, which impedes the wide spread adoption of sodium imaging. In this talk, we will present a technique to simultaneously acquire sodium images and multi-parametric proton maps in one single scan.

About the speaker: Zidan Yu received her Bachelor in biological science from Wuhan University in China and then completed her Master in biomedical engineering at the NYU Tandon School of Engineering. She is currently a PhD candidate working with Martijn A. Cloos and Daniel K. Sodickson at the NYU School of Medicine. Zidan’s research interests are MR sequence design, Sodium MRI, and MR at ultra-high field.

Tuesday, March 26, at noon

Faye McKenna, MS

Lazar Translational Brain Imaging Lab
New York University Sackler Institute of Graduate Biomedical Sciences
PhD Student in Biomedical Imaging
Diffusional Kurtosis Imaging of Gray Matter Neuropathology: Schizophrenia and Autism Spectrum Disorder

Abstract: Prior histological post-mortem studies have highlighted gray matter (GM) microstructural abnormalities as a pathological feature of both schizophrenia (SZ) and autism spectrum disorder (ASD). However, these histological studies were limited by the small sample sizes and focus on restricted brain areas. In this talk, we present our work examining the feasibility of diffusional kurtosis imaging (DKI) to describe gray matter microstructural abnormalities in SZ and ASD non-invasively and in vivo. DKI is an extension of diffusion tensor imaging that accounts for non-Gaussian water diffusion contributions to the diffusion MRI signal and provides several kurtosis indices that reflect tissue microstructural complexity. The talk will review existing research investigating DKI’s use to describe GM microstructure pathology in several clinical populations and animal disease models, as well as our recent findings showing significant differences in kurtosis intensity and lateralization metrics in SZ and ASD populations

About the speaker: Faye McKenna is in her 2nd year of PhD training at New York University Sackler Institute of Graduate Biomedical Sciences’ Biomedical Imaging program. Her research focuses on using multi-modal MRI to quantify and better understand neuropathology in psychotic and autism spectrum disorders. She holds a BA in behavioral neuroscience and a MS in Bioimaging.

Tuesday, March 19, at noon

Emilie McKinnon

PhD Candidate
Medical University South Carolina
Where to go beyond DTI: Diffusion MRI advantages at high b-values

Abstract: Diffusion MRI (dMRI) has the unique ability to study brain microstructure at a resolution much smaller than the MRI voxel itself. The strength of diffusion weighting (i.e., the b-value) strongly impacts what information is contained in the dMRI signal. Since modern scanners have much stronger gradients, high b-value dMRI is becoming more feasible, and its utilization is likely to increase. High b-value acquisitions provide information beyond what is attainable with DTI and have proven useful for fiber tractography and for calculating diffusion measures that have greater biological specificity. This presentation will revisit a high b-value technique known as fiber ball imaging (FBI) but will mostly focus on how it can be used in combination with diffusion kurtosis imaging (DKI) to estimate microstructural parameters, such as compartmental water fractions and diffusion tensors. In addition, FBI provides the opportunity to calculate compartmental transverse relaxation times (T2) while avoiding multi-exponential fitting schemes.

Thursday, March 14, at noon

Ju Qiao, PhD

Nanomedicine Science and Technology Center
Department of Mechanical and Industrial Engineering
Northeastern University, Boston, MA
Quantitative Magnetic Resonance Imaging for Neurology and Cancer

Abstract: Magnetic Resonance Imaging (MRI) is an invaluable diagnostic tool for imaging the human body, diagnosing and characterizing diseases, and developing new treatments. In this work, we describe two applications of a novel MRI technique, Quantitative Ultra-short Time-to-echo Contrast-Enhanced (QUTE-CE) MRI to brain disease.

In a first application, QUTE-CE is employed to quantify nanoparticle accumulation in tumors, which is of great clinical interest for stratifying cancer patients who may benefit from therapeutic nanoparticles. Using FDA-approved superparamagnetic iron oxide nanoparticle (SPION) ferumoxytol in QUTE-CE MRI, we produce quantitative measurement of contrast and delineate clear, positive-contrast brain/tumor vasculature image in mice and rats. QUTE-CE MRI is shown to improve contrast and contrast efficiency compared to conventional high-resolution T1- and T2-weighted imaging. QUTE-CE is ideally suited for non-invasive visualization and quantification of tumor nanoparticle uptake, and accordingly, it can potentially be used for identifying cancer patients who can respond to treatment with therapeutic nanoparticles.

In a second application, QUTE-CE is employed to characterize traumatic brain injury (TBI). TBI is a prevalent risk of death and disability in young people with about 1.6 million cases reported per year in the US. Some of the most devastating injuries from brain trauma are the rupturing of arteries between the dura and the skull in an epidural hematoma (blood brain barrier disruption), as well as tears in emissary veins, resulting in hemorrhagic contusions seen in subdural hematomas. This accumulation of blood can squeeze and increase pressure on the brain. Here, we introduce a novel application of QUTE-CE to image blood accumulation and detect microbleeds in mild TBI animals. Rats which underwent 3 mild concussions showed significant difference in QUTE-CE MRI measure of ferumoxytol accumulation in extravascular space indicating blood brain barrier damage following TBI. These differences were observed primarily in cortex, hypothalamus, basal ganglia, cerebellum and brainstem. This study demonstrates that QUTE-CE MRI can be used to detect blood brain barrier disruption and microbleeds in mild TBI rats.

About the speaker: Dr. Qiao has finished her PhD training in December 2018 at Northeastern University. Her research is focused on quantitative MRI of neurodegenerative diseases and tumors. In addition to her PhD, she holds a BS in Physics and a MS in Biophysics.

Thursday, March 7, at noon

Prof. Dr. Martin Uecker

German Centre for Cardiovascular Research
University Medical Center Gottingen
Nonlinear Image Reconstruction Methods
Tuesday, March 5, at noon

Sanjeev Chawla, PhD

Research Assistant Professor
Department of Radiology
Perelman School of Medicine at University of Pennsylvania
Metabolic and Physiologic MR Imaging in Evaluating Treatment Response in Patients with Glioblastomas

Abstract: Glioblastoma (GBM) is the most common primary malignant brain tumor in adults with poor prognosis. The standard of care for patients with GBM includes maximal surgical resection and concurrent chemo-radiation therapy followed by 6 to 12 cycles of adjuvant temozolomide (TMZ). Standard therapeutic approaches provide modest improvement in progression-free and overall survival, necessitating the investigation of novel therapies. Recently, FDA approved the use of tumor-treating fields for the treatment of patients with GBM. Additionally, several immunotherapeutic modalities such as chimeric antigen T cell receptors, check-point inhibitors and dendric cell vaccines hold much promise in the future treatment paradigms for these patients. In this presentation, I will discuss the potential roles of 3D-echoplanar spectroscopic imaging, diffusion and perfusion MR imaging techniques in evaluating treatment response in patients with GBM receiving established and novel treatment modalities. As non-invasive identification of patients harboring isocitrate dehydrogenase (IDH) mutant gliomas can have significant clinical implications, I will also present our initial experience on the utility of 2D-correlational spectroscopy in identifying glioma patients with IDH mutation.

About the speaker: Sanjeev Chawla, PhD is working as a Research Assistant Professor in the Department of Radiology, Perelman School of Medicine at University of Pennsylvania, Philadelphia. Sanjeev’s research interest includes development and application of advanced MR imaging and spectroscopy methods to study brain tumors. Sanjeev has authored numerous peer-reviewed original research/review articles and book chapters. He has presented his work at regional, national, and international cancer conferences and symposia. Sanjeev has also qualified part-I and II examinations conducted by American Board of Medical Physics. Recently, Sanjeev’s group was awarded a grant from Penn Center for Precision Medicine (PCPM) on evaluating tumor infiltration in glioblastomas using ultrahigh field MR imaging techniques. Among academic roles, Sanjeev has participated as an instructor for a Bio-Engineering course (BE546) with emphasis on fundamental techniques in imaging and spectroscopy for three years, he has mentored several visiting fellows, and he is a member of search committee for appointment of clinical fellows in the Neuroradiology Division of Hospital of University of Pennsylvania. He also possesses extensive editorial experience and got opportunities to work as a lead guest editor for special issues of journals such as Contrast Media & Molecular Imaging and Journal of Oncology

Tuesday, February 12, at noon

Hong-Hsi Lee, MD, MS

PhD Candidate
Biomedical Imaging Program
Sackler Institute of Biomedical Sciences
NYU Langone Health
Time-Dependent Diffusion in the Brain

Abstract: Diffusion MRI is sensitive to the length scale of tens of microns, which coincides to the scale of microstructure in the human brain tissue. By varying the diffusion time, we can evaluate the brain micro-geometry via time-dependent diffusion measurements and the biophysical modeling. To validate our model, we segmented 3-dimensional realistic microstructure of the mouse brain white matter and performed Monte Carlo simulations of the diffusion in segmented axons. This talk will focus on the time dependence either along or perpendicular to white matter axons and corresponding micro-geometries, such as axonal diameter variation.

About the speaker: After finishing the major in Medicine and Physics in Taiwan, Hong-Hsi Lee is working with Dmitry S. Novikov and Els Fieremans as a PhD candidate in the biomedical imaging program at the Sackler Institute of Biomedical Sciences. Hong-Hsi’s recent focus is on Monte Carlo simulations of the diffusion in 3-dimensional realistic microstructure and image processing, such as denoising and super-resolution.

Tuesday, January 29, at noon

Jens Jensen, PhD

Professor of Neuroscience
Associate Director of the Center for Biomedical Imaging
Charleston, SC
Fiber Ball Imaging

Abstract: Fiber Ball Imaging (FBI) is a diffusion MRI method that estimates the orientation of axonal fibers in white matter from an inverse Funk transform. This approach avoids the need for numerical fitting to a signal model and for a fiber response function. FBI also yields predictions for certain microstructural parameters, including the fraction anisotropy axonal. When combined with triple diffusion encoding MRI, FBI can also be used to find the intra-axonal diffusivity and the axonal water fraction. This talk will focus on the basic concepts that underlie FBI but will also show data that support its validity and illustrate its application.

About the speaker: Dr. Jens H. Jensen received his PhD in physics from Princeton University. After several years at the New York University School of Medicine, he joined the faculty of MUSC in 2011. He is currently Professor of Neuroscience and Associate Director of the Center for Biomedical Imaging. His research focuses on applications of MRI to neurological disorders, including Alzheimer’s disease, epilepsy, and stroke.

Friday, January 25

Niek Van Overberghe

International Sales Manager
Exploring the CUBES - expanding PET SPECT and CT imaging capabilities to accelerate translational research

Abstract: Niek Van Overberghe (International Sales Manager @ MOLECUBES) will present on the unique technology at the core of the β-,γ and X-CUBE, preclinical imagers for PET, SPECT and CT. This new generation of in vivo imaging systems makes use of monolithic crystals coupled to solid state siPMs taking imaging one step further, combined with an in vivo CT system that ensures fast and low dose acquisitions. Thanks to this new technology, researchers can now inject lower activities, scan for a shorter time, hereby reducing the stress level on animals, increasing throughput, lowering radiotracer cost, and lowering the dose of the operator. Because of their unique bench top size, the instruments can be used in any lab around the world without needing building modifications. In addition, Niek will present on different applications that highlight the superior capabilities of these bench top modular systems compared to older systems.

About the speaker: "Niek Van Overberghe completed his masters in Biomedical Engineering at the University of Ghent and KU Leuven, Belgium in conjunction with international exchange projects at the University of Helsinki and the University of Valencia. Complementing these studies with an education in Business Administration at EHSAL management school, Niek started his career as key account manager at Sigma-Aldrich. In 2017, he decided to join a promising start-up company from Ghent University: MOLECUBES. Niek is currently heading the global sales and marketing at Molecubes, promoting their bench top high-end preclinical PET SPECT and CT imagers world wide.

Thursday, December 20, at noon

Nick Pawlowski

PhD Candidate
Biomedical Imaga Analysis Group Imperial College London
Outlier Detection using Bayesian Deep Learning

Abstract: Regardless of improved accuracy scores and other metrics, deep learning methods tend to be overconfident on unseen data or even when predicting the wrong label. Bayesian deep learning offers a framework to alleviate some of these concerns by modeling the uncertainty over the weights generating those predictions. This talk will introduce Bayesian deep learning and present the use of Bayesian NNs for outlier detection in the medical imaging domain, particularly the application of Brain lesion detection.

About the speaker: Nick is a PhD student in the Biomedical Image Analysis group at Imperial College London, supervised by Ben Glocker. He works on methods to integrate and use uncertainty with deep learning methods. Recently he worked on Bayesian neural networks and their use for outlier detection. Nick is currently a Research Intern at Facebook AI Research Montreal and a main developer of DLTK, a toolkit for deep learning for medical imaging. During this summer he was a Machine Learning resident at Google X.

Tuesday, December 18, at noon

Thomas Witzel, PhD

Instructor in Radiology, Harvard Medical School
Assistant in Biomedical Engineering, Massachusetts General Hospital
Director Human MR Imaging Core, Athinoula A. Martinos Center for Biomedical Imaging
Democratizing Magnetic Resonance Imaging; Open Source MRI Scanners for Education, Innovation, and Accessible Radiology

Abstract: Since its inception 45 years ago, development of MRI systems has been predominantly driven by commercial entities and innovation is centered on the commercial interests of these vendors. In a relatively small ecosystem of MRI manufacturers that compete in a low quantity, high profit margin market, innovation is effectively controlled by the manufacturer's openness to outside access and is often limited by the manufacturer’s market needs. The possibilities are even more limited when it comes to disruptive modifications of the scanner hardware. In my presentation, I’ll discuss the need for and show the prospects of an open-source MRI system for education, disruptive innovation, and accessible healthcare and will show the results of educational work with a $500 fully open-source MRI spectrometer.

About the speaker: I received my Ph.D. from Massachusetts Institute of Technology (MIT) in 2011, and I have since worked as Head Physicist of the Martinos Center and since 2013 also as Director of the Human MRI Core of the Martinos Center.

Wednesday, December 12, at noon

Ozan Öktem, PhD

Associate Professor
Department of Mathematics
KTH-Royal Institute of Technology
Stockholm, Sweden
Recent Advances in Using Machine Learning for Image Reconstruction

Abstract: The talk will outline recent approaches for using (deep) convolutional neural networks to solve a wide range of inverse problems, such as image reconstruction in medical tomography. A key element is to use a neural network architecture for reconstruction that includes physics based models that describe how data is generated as well as its statistical properties. Another is the possibility to integrate complex task related a priori information and elements of decision making into the reconstruction procedure. The resulting approach outperforms current state-of-the-art in terms of 'quality', computational speed and there is no need to manually set parameters as with variational methods. Furthermore, the amount of training data and network size can be kept surprisingly small. The talk will also touch upon further developments based on using generative adversarial networks for uncertainty quantification.

About the speaker: Dr. Öktem is an Associate Professor in Mathematics at the Department of Mathematics, KTH - Royal Institute of Technology, Stockholm. He specializes in theory and algorithms for solving severely ill-posed inverse problems with emphasis on tomographic imaging. Prior to joining his current affiliation in 2008, he worked as an applied mathematician for more than 13 years in industry. His research combines methods from mathematical analysis, differential geometry, and mathematical statistics with techniques from machine learning. Focus lately has been on combining model-based approaches with deep neural networks for uncertainty quantification and task adapted reconstruction in large scale inverse problems. The research is spearheaded by concrete challenges in imaging applications from various scientific fields, like 3D electron and fluorescence microscopy in bioimaging, low-dose clinical CT and spatiotemporal PET/CT, x-ray phase contrast tomography for bioimaging and material sciences, and lately seismic tomography for geophysical prospecting.

Tuesday, December 11, at noon

Ritse M. Mann, MD, PhD

Department of Radiology and Nuclear Medicine, Radboud University Medical Centre, Nijmegen, the Netherlands
Department of Radiology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
Future Directions of Breast MRI—Potential of Deep Learning Tools

Abstract: Ultrafast breast MRI provides excellent data for automated breast lesion classification. Incorporating morphology, T2 and DWI using various automated approaches, improves the classification task slightly, but late phase dynamics seem redundant. Since about a 3rd of detected breast cancers are missed on prior breast MRI while in retrospect clearly visible, there is a strong incentive for the development of systems that not only classify, but automatically detect breast lesions in MRI volumes. Using a deep learning system about 70% of these cancers can be marked at 2 false positives per volume. Since automated detection also demands automated segmentation of the breast and the fibroglandular tissue to determine the search space, these algorithms may potentially also be used for risk prediction and prognostication based upon qualified measures of fibroglandular tissue and background parenchymal enhancement.

Tuesday, December 4

Itamar Ronen, PhD

Associate Professor of Radiology
C.J. Gorter Center for High Field MRI Research
Leiden University Medical Cente
The Netherlands
Diffusion of Intracellular Metabolites: a Compartment Specific Probe for Microstructure and Physiology

Abstract: Intracellular metabolites that give rise to quantifiable MR resonances are unique structural probes for the intracellular space, and are oftentimes specific, or preferential enough to a certain cell type to provide information that is also cell-type specific. In the brain, N-acetylaspartate (NAA) and glutamate (Glu) are predominantly neuronal/axonal in nature, whereas soluble choline compounds (tCho), myo-inositol (mI) and glutamine (Gln) are predominantly glial. The diffusion properties of these metabolites, examined by diffusion weighted MR spectroscopy (DWS) exclusively reflect properties of the intracellular milieu, thus reflecting properties such as cytosolic viscosity, macromolecular crowding, tortuosity of the intracellular space, the integrity of the cytoskeleton and other intracellular structures, and in some cases – intracellular sub-compartmentation and exchange.

The presentation will introduce some of the methodological concepts of DWS and the particular challenges of acquiring robust DWS for accurate estimation of metabolite diffusion properties. Subsequently, the unique ability of DWS to characterize cell-type specific structural and physiological features will be demonstrated, focusing on combining DTI/DWI and DWS in a combined analysis framework aimed at better characterizing tissue microstructural properties, as well as acquisition strategies aimed at characterizing compartment-specific microscopic anisotropy (µFA) in tissue. Also presented are applications of DWS to discern cell-type specific intracellular damage in disease.

About the speaker: Itamar Ronen studied chemistry at the School of Chemistry in Tel Aviv University, and obtained his PhD under the supervision of Prof. Gil Navon on proton-detected 17O-NMR. Subsequently he was a post-doctoral fellow at the center for magnetic resonance research (CMRR) at the University of Minnesota with Dr. Dae-Shik Kim. Most of his work since then has been directed at developing compartment-specific diffusion methods for evaluating tissue microstructure in neuroanatomical and clinical investigations. In 2003 he moved to Boston University, where together with Dr. Dae-Shik Kim he co-founded the Center for Biomedical Imaging and served 6 years as Assistant Professor of Anatomy and Neurobiology. Currently he is Associate Professor of Radiology at the Leiden University Medical Center and a principal investigator at the C. J. Gorter Center for High Field MRI.

Monday, November 19, at noon

Jana Hutter, PhD

Research Fellow
Centre for Biomedical Engineering & Centre for the Developing Brain
King’s College London
Acquisition Advances for Efficient & Joint Diffusion-Relaxometry MRI

Abstract: Emerging novel analysis techniques offering insights into microstructure and tissue properties require more and more eloquent data. This talk will introduce some of our recent advances on the acquisition side, presenting multi-parametric diffusion acquisitions - extending the parameter space to allow integrated T1, T2* and Diffusion sampling (b-value,b-vector, b-shape) within reasonable imaging times. Combination with Multiband imaging and sampling strategies in this multi-dimensional space will be discussed and exploratory data-driven analysis results presented.

Tuesday, November 13, at noon

Li Yao, PhD

Lead Data Scientist
Enlitic, San Francisco, CA
Excitement and Challenges in Building Medical Imaging Products in the Real World with Artificial Intelligence

Abstract: AI, in its much misinterpreted form, holds the promise of revolutionizing medical imaging in healthcare. In practice, however, many challenges remain. This talk presents some of the challenges that we, as a company, have recognized on the way of building better tools for radiologists. In particular, Dr. Li Yao, the Lead Data Scientist at Enlitic, will share with the audience three project stories, one with Chest X-ray, one with Chest CT, and one with medical text reports, each of which highlights unique excitement and challenge in the real world clinical context. The talk will be overall technical on AI and machine learning side.

n Tuesday, November 6, at noon

Maciej Mazurowski, PhD

Associate Professor of Radiology
Electrical and Computer Engineering, Biostatistics and Bioinformatics
Duke University
Machine learning and Computer Vision in Radiology

Abstract: The terms artificial intelligence, machine learning, deep learning, or computer vision are mentioned increasingly often in the radiology community. In this talk, Dr. Mazurowski will talk about how these methods can help radiologists in their clinical practice as well as how they can advance science by improving our understanding of cancer. The talk will be concluded with more general thoughts on the future of the radiology profession in the advent of human-level artificial intelligence. Dr. Mazurowski is an Associate Professor of Radiology, Electrical and Computer Engineering, and Biostatistics and Bioinformatics and Duke University. He leads a research laboratory with focus on applications of machine learning to cancer imaging.

Tuesday, October 23, at noon

Sune Jespersen, PhD

CFIN/MindLab and Deptartment of Physics and Astronomy
Aarhus University, Denmark
Towards MRI Virtual Tissue Microscopy with Diffusion MRI: the Aarhus Perspective

Abstract: Being sensitive to tissue structural features on the micrometer level (microstructure), diffusion MRI combined with biophysical modeling has the potential to map relevant biological properties on scales far below the nominal voxel resolution. In the brain and spinal cord, much work in this direction has been based on a relatively simple biophysical model of diffusion, recently dubbed “the standard model”. This model characterizes the diffusion signal in terms of a handful of relevant parameters: neurite volume fraction, intra-neurite and extra-neurite diffusivity, and the neurite or fiber orientation distribution. In this talk, I will give some background for the standard model and an overview of our work with it, covering our efforts to validate the model in animal model systems including some comparison with histology. I will also outline some current problems with the model and ongoing attempts to overcome them.

Tuesday, October 16, at noon

Ryutaro Tanno

PhD student in Machine Learning and Medical Imaging
University College London, UK
Centre for Medical Image Computing, Department of Computer Science
Learning from Noisy Data: How to Teach Machines when Doctors Disagree with Each Other

Abstract: Access to clean and voluminous datasets is a piece of luxury confined to academic research for many machine learning applications. In practice, such datasets are hard to come by, and consequently limit the performance of deployed machine learning systems. This problem is pervasive in medical imaging applications where the cost of data acquisition and labelling is high. In this talk, I will present a method that is capable of learning more intelligently from such noisy data by modelling the human annotation process. This is particularly relevant in situations where data is labelled by multiple annotators of varying skill levels and biases.

Tuesday, October , at noon

Prof. Dr. Damijan Miklavcic

Faculty of Electrical Engineering
University of Ljubljana
Electroporation-based Technologies and Treatments

Abstract: When cells are exposed to high voltage electric pulses their membranes become transiently permeable, i.e. molecules otherwise deprived of transmembrane transport molecules can gain access into the cytosol. This phenomenon is called electroporation. It can be reversible - cells survive or irreversible, if cells die. The former is used to introduce genes into cells for gene therapy and DNA vaccination (gene electrotransfer) or to increase effectiveness of some chemotherapeutic drugs (electrochemotherapy), while the latter is used as a non-thermal tissue ablation method.

Electroporation of cells depends on local electric field to which cells are exposed. In vivo in tissue electric field is impossible to measure directly. Therefore current density imaging and magnetic resonance impedance tomography have been used to elucidate electric field distribution and was correlated with cell membrane permeabilisation.

Tuesday, October 2, at noon

Kristine Glunde, MS, PhD

Professor of Radiology and Radiological Science
Johns Hopkins University School of Medicine
Unraveling Breast Cancer with Multimodal Molecular Imaging

Abstract: Novel molecular imaging techniques are allowing us to visualize breast tumor biology in unprecedented molecular detail. These include the use of magnetic resonance spectroscopic imaging, mass spectrometric imaging, and Raman imaging for mapping molecular and metabolic pathways in breast cancer. Applications of these molecular imaging techniques are improving our understanding of metabolic and oncogenic signaling in breast cancer progression, metastasis, and response to therapy. Finally, we are also investigating the processes that lead to “molecular priming” of metastatic target organs prior to the arrival of the first metastasizing cancer cells.

September 11, at noon

Chamith S. Rajapakse, PhD

Assistant Professor of Radiology
University of Pennsylvania
Imaging-Based Methods for Assessment of Metabolic Bone Disease

Abstract: Millions of people worldwide suffer from metabolic bone diseases, predisposing them to bone fractures and devastating consequences. Within a year of a hip fracture, for example, 20-30% of patients die and 50% lose the ability to walk. Medical imaging plays an important role in the diagnosis of bone disease, staging, fracture risk assessment, and monitoring of treatment. Radiographs and dual energy X-ray absorptiometry (DXA), which provides semi-quantitative assessment, are the modalities of choice for clinical management of metabolic bone diseases. Recent advances in medical imaging technologies and analysis techniques have enabled novel non-invasive approaches for quantification of bone quality. For example, it is now possible to obtain three-dimensional high-resolution images depicting the trabecular and cortical microstructure in human subjects. Ability of obtain high resolution images has paved the way for elegant image analysis algorithms for extracting information about various aspects of bone quality not feasible previously. For example, it is now possible to characterize trabecular bone microarchitecture using multi-row detector CT and the tensor scale algorithm or estimate the hip fracture strength using high-resolution imaging based finite element analysis. More recently, MRI, CT, ultrasound, and PET techniques have been developed for extracting novel biomarkers related to bone strength. For example, bone water assessed by MRI has been proposed as a new biomarker for bone quality. Many of these imaging-based techniques could provide early differential diagnosis, periodic monitoring, and a comprehensive assessment of bone quality thereby potentially changing the way metabolic bone diseases are managed in the future.

Tuesday, August 28, at noon

Kim Butts Pauly, PhD

Stanford University
Bringing MR-Guided Focused Ultrasound into Focus
Tuesday, August 21, at noon

Prof. Yonina Eldar

Department of Electrical Engineering
Technion, Israel Institute of Technology
Fast Analog to Digital Compression for High Resolution Imaging

Abstract: The famous Shannon-Nyquist theorem has become a landmark in the development of digital signal processing. However, in many modern applications, the signal bandwidths have increased tremendously, while the acquisition capabilities have not scaled sufficiently fast. Consequently, conversion to digital has become a serious bottleneck. Furthermore, the resulting high rate digital data requires storage, communication and processing at very high rates which is computationally expensive and requires large amounts of power. In the context of medical imaging sampling at high rates often translates to high radiation dosages, increased scanning times, bulky medical devices, and limited resolution.

In this talk, we present a framework for sampling and processing a wide class of wideband analog signals at rates far below Nyquist by exploiting signal structure and the processing task and show several demos of real-time sub-Nyquist prototypes. We then consider applications of these ideas to a variety of problems in medical and optical imaging including fast and quantitative MRI, wireless ultrasound, fast Doppler imaging, and correlation based super-resolution in microscopy and ultrasound which combines high spatial resolution with short integration time. We end by discussing several modern methods for structure-based phase retrieval which has applications in several areas of optical imaging.

Tuesday, August 7, at noon

Moriah E. Thomason, PhD

Associate Professor, Department of Child and Adolescent Psychiatry
NYU School of Medicine
Emergent Functional Connectomics in Human Fetal Brain Networks

Abstract: While we possess rather detailed understanding of select micro- and macroscopic processes of normal human brain development, we know far less about how brain changes relate to behavioral changes over the course of life from the prenatal period to early adulthood. This lack of understanding is especially pronounced in very early years of human life, years where change is most rapid, and vulnerability heightened. The primary objective of our research is to characterize fundamental properties of human brain macroscale neural system development, and examine how early experiences, beginning in utero, influence life-long learning and neurological health. We are testing models in which early psychosocial stress and concomitant toxin exposure influence development of neural systems, particularly those that support the establishment of cognitive control and regulatory processes in childhood. Rigorous evaluation of emergent self-regulatory processes and their neurological and biobehavioral bases has potential to inform educational strategies and lead to biologically-informed behavioral interventions for those with enhanced risk.

About the speaker: Moriah Thomason is an Associate Professor of Child and Adolescent Psychiatry in the New York University School of Medicine, and a Research Assistant Professor at the Survey Research Center in the Institute for Social Research at the University of Michigan. She formerly served as Director of the Perinatal Neural Connectivity Unit within the intramural Perinatology Research Branch of NICHD/NIH. Her published research addresses principals of neural development beginning in utero. Her current NIH grants examine environmental factors with potential to influence functional neurocircuitry of the developing brain. She received her undergraduate training at UC Berkeley, and her graduate and postdoctoral training at Stanford and MIT in Neuroscience. Her work has been featured on NPR's All Things Considered, BBC World Service, The Huffington Post, MIT Technology Review, New Scientist, and most recently, in Science, Nature Medicine and National Geographic.

Tuesday, July 24, at noon

Daniel Nunes, PhD

Neuroplasticity and Neural Activity Lab
Center Champalimaud for the Unknown
Lisbon, Portugal
Imaging Microstructural Dynamics Using Diffusion MRI
Tuesday, July 10, at noon

Valerij G. Kiselev, PhD

University Medical Center Freiburg
Freiburg, Germany
What Do We Really Measure with the MRI Signal Phase?

Abstract: Decade-old measurements of the MRI signal phase in the human brain white matter ignited a still-ongoing discussion of how to calculate the Larmor frequency of NMR-visible spins in magnetically heterogeneous media. While this discussion has somewhat decoupled from the original biomedical context going deep into NMR physics and questioning the assumptions behind the Lorentz cavity construction, its practical implications may significantly limit the applicability of quantitative susceptibility mapping (QSM). This talk will give an overview of the biophysical origins of the Larmor frequency offset. A simple model, which remains in the debate focus, is used to illustrate the relation between the microstructure and the Larmor frequency. A closed-form analytical solution for this model is obtained in the practically relevant limit of fast diffusion. This solution illustrates the microstructural correlates of the recent empirical nerve tissue description, adds to the discussion of the Lorentz cavity construction in heterogenous media, and formulates the major challenge for the QSM. The talk will conclude with a discussion of the unresolved problems on the way to building realistic models for white matter magnetic microstructure.

Tuesday, June 12, at noon

Rebecca Feldman, PhD

Senior Scientist
Translational and Molecular Imaging Institute
Icahn School of Medicine at Mount Sinai
Magnetic Resonance Spectroscopic Imaging of Epilepsy

Abstract: Epilepsy affects approximately 2.2 million people in the United States. Thirty percent of epilepsy is refractory to pharmacotherapy, and surgical treatment of refractory epilepsy can often be the most effective treatment option. Investigations of the resected tissue of MRI-negative subjects suggest that there exist focal epileptogenic lesions, amenable to resection, that are not detectable using current clinical MRI protocols.

Magnetic resonance spectroscopic imaging (MRSI) provides metabolic information which is complimentary to structural imaging. We have developed a novel B1-insensitive semi-adiabatic spectral-spatial imaging sequence (SASSI) which was designed to overcome many of the limitations of MRSI at ultra-high fields, enabling effective acquisition of high resolution grids of spectra. We have used SASSI to detect metabolic alterations in the head and body of the hippocampus of patients with focal epilepsy who were non-lesional or inconclusive in their clinical MRI exams.

Friday, May 25, at noon

Matthew Rosen, PhD

Director, Low Field MRI and Hyperpolarized Media Laboratory
Co-Director, Center for Machine Learning
MGH/Martinos Center for Biomedical Imaging
Harvard Medical School
Life at the Bottom: Deconstructing MRI at 6.5 mT with Physics, AI, and Nanodiamonds Too
Friday, May 18, at noon

Yuan Wang, PhD

Department of Electrical and Computer Engineering
Tandon School of Engineering, NYU
Biophysically Interpretable Recurrent Neural Network for Functional Magnetic Resonance Imaging Analysis

Abstract: Dynamic Causal Modelling (DCM) is an advanced biophysical model which explicitly describes the entire process from experimental stimuli to functional magnetic resonance imaging (fMRI) signals via neural activity and cerebral hemodynamics. To conduct a DCM study, one needs to represent the experimental stimuli as a compact vector-valued function of time, which is hard in complex tasks such as book reading and natural movie watching. Deep learning provides the state-of-the-art signal representation solution, encoding complex signals into compact dense vectors while preserving the essence of the original signals. There is growing interest in using Recurrent Neural Networks (RNNs), a major family of deep learning techniques, in fMRI modeling. However, the generic RNNs used in existing studies work as black boxes, making the interpretation of results in a neuroscience context difficult and obscure.

In this paper, we propose a new biophysically interpretable RNN built on DCM, DCM-RNN. We generalize the vanilla RNN and show that DCM can be cast faithfully as a special form of the generalized RNN. DCM-RNN uses back propagation for parameter estimation. We believe DCM-RNN is a promising tool for neuroscience. It can fit seamlessly into classical DCM studies. We demonstrate face validity of DCM-RNN in two principal applications of DCM: causal brain architecture hypotheses testing and effective connectivity estimation. We also demonstrate construct validity of DCM-RNN in an attention-visual experiment. Moreover, DCM-RNN enables end-to-end training of DCM and representation learning deep neural networks, extending DCM studies to complex tasks.

Thursday, May 17, at 13:30 p.m.

Youngwook Kee , PhD

NY Postdoctoral Associate in Radiology
Weill Cornell Medical College, New York
Various Roles of Total Variation Regularization for Low-Level Vision and Inverse Problems in MRI

Abstract: In this talk, I will present 3 different roles of total variation (TV) regularization in variational methods for unsupervised image segmentation in computer vision, deconvolution in quantitative susceptibility mapping (QSM), and image reconstruction for fast multicontrast MRI. First, TV as a measure of the perimeter of a candidate partition encoded by the indicator function of a set. In unsupervised image segmentation, the total length of region boundaries is often minimized to obtain a compact partition that likely matches the way humans perceive. A statistical distance between color distributions of distinctive regions in a candidate partition is maximized with the minimization of TV for unsupervised image partitioning. Second, TV as a measure of the amount of streaking artifacts in QSM deconvolution. QSM is a noninvasive MRI method for a quantitative study of the tissue magnetic susceptibility distribution by solving magnetic field to susceptibility source inversion problem. A major challenge in the ill-posed inverse problem is streaking artifacts from noise in the field which propagates at the complementary magic angle. These artifacts can be selectively reduced by weighted TV regularization that makes use of anatomical information of the corresponding magnitude image. Lastly, TV as a measure of undersampling artifacts in image reconstruction for multicontrast MRI. In clinical MRI, multiple contrasts such as T1w, T2w, and FLAIR are sequentially acquired, consequently taking a long scan time. To shorten such a long scan time, structural information that exists between contrasts is extracted from T1w and is incorporated into the TV term as an orthogonal projector in the model-based image reconstruction for the subsequent contrasts that are highly undersampled.

About the speaker: Youngwook Kee received the B.S. in Electrical Engineering from Ajou University in 2008, the M.S. in Computational Science from Seoul National University in 2010, and the Ph.D. in Electrical Engineering from Korea Advanced Institute of Science and Technology in 2015. Since 2015 he has been carrying out MRI research as Postdoctoral Associate in Radiology at Weill Cornell Medical College. During 2012 to 2013, he was a graduate student in the Computer Vision Group at Technical University of Munich on a Erasmus-Mundus BEAM fellowship.

Tuesday, May 15, at noon

Piotr Walczak, MD

Associate Professor
Johns Hopkins Medicine
Department of Radiology
MRI-guided Targeting of Therapeutics to the Brain at High Precision

Abstract: Dr. Piotr Walczak is an Associate Professor in the Johns Hopkins Medicine Department of Radiology and Radiological Science. He specializes in magnetic resonance research and neuroradiology, with an emphasis on image-guided delivery of therapeutic agents to the brain. He is developing techniques for stem cell transplantation-based restoration of white matter damage in a variety of neurological disorders.

Dr. Walczak received his M.D. in 2002 from the Medical University of Warsaw in Poland. He then completed a research fellowship in cell-based therapy for neurodegenerative disorders at the University of South Florida. After a fellowship in cellular imaging at Johns Hopkins University School of Medicine, Dr. Walczak joined the faculty of Johns Hopkins in 2008.

He is an affiliated faculty member at the Kennedy Krieger Institute’s F.M. Kirby Research Center and he holds a Visiting Professor appointment in the department of Neurology and Neurosurgery Collegium Medicum University of Warmia and Mazury in Olsztyn, Poland.

Friday, May 11, at noon

Alexey Tonyushkin, PhD

Research Assistant Professor and Director of Technical Operations
University of Massachusetts Boston
Magnetic Particle Imaging: Introduction to Physics and Instrumentation

Abstract: Magnetic Particle Imaging (MPI) is a new tomographic imaging modality that offers high spatial and temporal resolutions. Compared to the other imaging modalities such as MRI/CT/PET, MPI is non-toxic, more sensitive, and fully quantitative technique. MPI addresses clinical and research needs for safe diagnostic and therapeutic applications such as cancer screening, cell tracking, and angiography. To date, a few small-bore MPI systems have been developed, however, human-size MPI scanner has yet to be built. The major challenge of scaling up of MPI is in high power consumption that is associated with the traditional approach to designing the scanner. In my talk, I will overview the basics of MPI, specifically, physics and instrumentation that includes two fundamental types of MPI topologies: field-free-point and field-free-line. Then I will describe my approach to designing MPI scanner and also will show how traditional MPI can be blended with atom optics to incorporate an atomic magnetometer as a very sensitive way of detecting the signal.

Wednesday, May 2, at 10:30 a.m.

Joachim A. Behar, PhD

Postdoctoral Fellow
Department of Biomedical Engineering
Technion Israel Institute of Technology
Physiologically Informed Diagnosis Using Cardiac Mobile Health Systems

Abstract: With billions of mobile devices worldwide and the low cost of connected medical hardware, recording and transmitting medical data has become easier than ever. However, this ‘wealth’ of physiological data has not yet been harnessed to provide actionable clinical information. This is due to the lack of smart algorithms that can exploit the information encrypted within these ‘big databases’ of biomedical time series and take individual variability into account. Exploiting these data necessitates an in depth understanding of the physiology underlying these biomedical time series, the use of advanced digital signal processing and machine learning tools to recognize and extract characteristic patterns of health function, and the ability to translate these patterns into clinically actionable information.

In this talk I will present my research in electrophysiology, namely the “Fetal Holter AI” and “Cardio AI” projects. For these two research projects I leverage state-of-the-art signal processing and machine-learning techniques to harness physiological information contained in biomedical time series and provide clinically actionable information. The “Fetal Holter AI” project aims to create a novel intelligent non-invasive fetal Holter electrocardiogram system to diagnose for fetal arrhythmias and remotely monitor the fetal cardiac health. The “Cardio AI” project has two aims: (1) to better understand the physiological information contained in the heart rate variability i.e. the time interval variation between consecutive heartbeats. I will present a new software, PhysioZoo, which we developed in our laboratory at the Technion for analyzing the heart rate variability from animal models; (2) to create an artificial intelligence system which can identify cardiac pathologies from the electrocardiogram with accuracy similar to the cardiologist’s direct interpretation. I will finish my presentation by briefly mentioning the “SmartCare Sleep AI” project which aims at creating a single channel screening test for obstructive sleep apnea. I will present my work in elaborating this test using patterns recognition from the oximetry time series in order to recognize individuals with this medical condition.

Wednesday, May 2, at noon

Audrey Fan, PhD

Instructor, Radiology
Stanford University
Imaging Insights into the Vascular Nature of Brain Disorders

Abstract: Our brain depends on continuous blood flow to deliver the oxygen and nutrients it needs to function. Disruption to this oxygen supply, as in cerebrovascular diseases, has devastating consequences, most strikingly in acute stroke. Noninvasive imaging of brain blood flow and metabolism is technically challenging, but would provide critical information to diagnose and select therapies for patients.

My mission is to engineer new imaging biomarkers of brain physiology to address this need. In this talk, I describe development of a novel magnetic resonance imaging (MRI) technique to quantify oxygenation in cerebral blood vessels. I also validated MRI methods to measure cerebral blood flow against the reference standard by positron emission tomography (PET), using state-of-the-art simultaneous PET/MRI hardware. I performed these studies in challenging cerebrovascular patient cases, including Moyamoya disease, and used imaging to inform our basic understanding of disease pathophysiology.

In the long term, the imaging tools I develop will establish a vascular “fingerprint” that succinctly captures the metabolic health of an individual, and alerts us to a broad set of neurological diseases in its earliest stages.

Tuesday, May 1, at noon

Greg Zaharchuk, MD, PhD

Associate Professor of Radiology, Neurosciences Institute
Stanford University, California
The Deep Learning Revolution: Implications for Radiologists

Abstract: Greg Zaharchuk is an associate professor in radiology at Stanford University and a neuroradiologist at Stanford Hospital. His research interests include deep learning applications in neuroimaging, imaging of cerebral hemodynamics with MRI and CT, noninvasive oxygenation measurement with MRI, clinical imaging of cerebrovascular disease, imaging of cervical artery dissection, MR/PET in neuroradiology, and resting-state fMRI for perfusion imaging and stroke.

Friday, April 27, at noon

Dan Ma, PhD

Research Scientist
Department of Radiology
Case Western Reserve University
Magnetic Resonance Fingerprinting: A Flexible Framework for Fast Quantitative MRI

Abstract: Current clinical MRI often consists of a series of qualitative or weighted measurements of tissue properties, such as T1-weighted or T2-weighted images. These qualitative measurements have some inherent limitations. The relative contrasts from these images may change depending on the set-up of the acquisitions, the type of the scanners and so on. The interpretation of images thus only relies on subjective assessment or morphological measurement. This limits the ability to diagnose pathology in a reproducible and reliable manner, to characterize tissues and lesions and to longitudinally follow up lesions or to assess response to novel therapies. The weighted contrast from multiple underlying tissue properties may also reduce the sensitivity and specificity to detect and characterize subtle and diffuse diseases. Although these limitations could be overcome by collecting fully quantitative tissue maps using quantitative MRI techniques, the adoption of quantitative MRI in clinical practice is hampered due to its long scan time, low repeatability and lack of robustness.

This talk will introduce the concept and technical advances of magnetic resonance fingerprinting (MRF), which is a robust and flexible framework for fast, multi-parametric quantitative MRI. This technology allows quantification of multiple key tissue properties, such as T1, T2, T2*, and perfusion in a clinically feasible time and with high repeatability, which overcomes the barrier of clinical adoption of quantitative MRI. Since MRF is a dictionary based method that has no requirement of the encoding methods and signal shapes, this technology also allows flexible sequence designs for various clinical applications, and flexible numerical simulation for sophisticated physical and physiological settings. Both features contribute to more robust and accurate quantitative results. Finally, the talk will discuss some clinical applications of MRF, demonstrating promising clinical translation of this technology.

Wednesday, April 18, at noon

Peng Hu, PhD

Associate Professor
Department of Radiological Sciences
David Geffen School of Medicine
University of California, Los Angeles, California
Recent Developments in Cardiovascular MRI and MR-guided Radiation Therapy

Abstract: MRI with ferumxotyol as a intravascular contrast agent holds great promises for a number of clinical applications. In this talk, Dr. Hu will discuss translational ferumoxytol-enhanced cardiovascular MRI techniques that enables new paradigms for imaging congenital heart disease and beyond. In the second half of the talk, Dr. Hu will discuss his recent work in developing MRI techniques for guiding radiation therapy with regard to anatomical tracking and tumor response assessment.

Tuesday, April 3, at noon

Richard Dortch, PhD

Research Assistant Professor
Radiology and Radiological Sciences
Vanderbilt University
Quantitative Neuroimaging of the Peripheral Nervous System

Abstract: The peripheral nervous system is primarily composed of nerves that transmit motor and sensory information between the spinal cord and the body. Damage to these nerves results in a wide array of symptoms, ranging from temporary numbness, tingling, and pricking sensations to burning pain, muscle weakness, paralysis, organ failure, and death. Although clinicians have tools for assessing peripheral neuropathies (e.g., nerve conduction studies), they provide limited information in proximal and/or transected nerves. Quantitative MRI techniques (e.g., diffusion and magnetization transfer) may overcome these limitations by providing assays of myelin and axon pathologies throughout the peripheral nervous system. Unfortunately, few studies have applied quantitative MRI techniques to study peripheral neuropathies in humans in vivo. This can be attributed to the technical challenges associated with peripheral nerve MRI, including the need for higher spatial resolution in feasible scan times, a lack of contrast on standard anatomical images, and the influence of surrounding fat. In this talk, Dr. Dortch will discuss i) methods to overcome the technical challenges associated with peripheral nerve MRI and ii) applications of quantitative MRI methods in inherited neuropathies and trauma.

Tuesday, March 27, at noon

Christin Sander, PhD

A.A. Martinos Center of Biomedical Imaging
Department of Radiology, Massachusetts General Hospital, Harvard Medical School
Neuroreceptors at Work: Imaging Molecular Dynamics & Signaling with PET/fMRI

Abstract: Advances in simultaneous positron emission tomography (PET) and magnetic resonance imaging (MRI) have enabled novel approaches for in vivo functional brain mapping. The complementary nature of the imaging signals acquired by PET and functional MRI (fMRI) permits new insights into neurotransmission of the living brain: fMRI localizes changes in brain activity, whereas PET captures the underlying molecular and receptor-specific dynamics. One of the potentials of this technology is to provide new clinical biomarkers for the evaluation of dynamic receptor function and therapeutic interventions.

This talk will describe how simultaneous functional imaging with PET/fMRI leads to novel mechanistic insights through neuromodulation of brain function. The focus will be on interventions that target the dopamine receptor system, either through pharmacological or direct electrical stimulation. I will show that neurovascular coupling to receptors as identified by PET/fMRI can be used to classify drug properties in vivo. Together with biological and pharmacokinetic models, mechanistic insight into receptor adaptations over time can be gained. I will then talk about the in vivo effects of deep brain stimulation, and how the combined use of experimental approaches allows us to unravel receptor subtype contributions to observed signal changes. Finally, I will show how PET and fMRI can be used for evaluating the effects of flow, and how the combination of both modalities can provide alternative approaches for evaluating radiotracer probes of novel in vivo receptor targets.

About the speaker: r. Christin Sander is an instructor at the A. A. Martinos Center of Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School. She completed her PhD in Electrical Engineering at MIT in 2014, and received an MEng and MSc from Imperial College and University College London. She is currently funded by an NIH K99 Career Award from the National Institute of Drug Abuse.

Friday, March 23, at noon

Bruce Berkowitz, PhD

Professor, Department of Anatomy & Cell Biology
Professor, Department of Ophthalmology
Director of Small Animal MRI Facility
Wayne State University School of Medicine
Detroit, Michigan
Oxidative Stress and its Functional Consequences Measured In Vivo by MRI

Abstract: Dr. Berkowitz has established a body of work that highlights new functions for MRI in the context of evaluating early treatment of prodromal neurodegenerative disease. His current pioneering efforts uses MRI to measure neuronal oxidative stress without a contrast agent in Alzheimer’s disease and genetic forms of blindness to personalize antioxidant treatment in order to modify the course of these devastating diseases.

Friday, March 23, at 10:30 a.m.

Shu Zhang, MSc

PhD candidate
The University of Texas Southwestern Medical Center
Dallas, TX
Novel Detection Methods for Chemical Exchange and Their Applications

Abstract: Chemical exchange saturation transfer (CEST) and the closely related off-resonance T1ρ methods are gaining popularity for their ability to visualize chemical exchange process between protons bound to solutes and surrounding bulk water, thus providing a contrast based on proton exchange sites with different chemical shifts. The contrast is also influenced by pH, temperature and molecule concentration. Therefore, CEST/T1ρ can provide molecular level information which reflects biochemical composition of tissues and their microenvironments. As a result, many promising applications of CEST imaging are explored, including but not limited to brain tumor imaging, brain ischemia, prostate cancer, breast cancer, kidney pH measurement and cartilage quality assessment. In the meanwhile, a lot of efforts are made to develop fast and quantitative CEST imaging methods to push CEST techniques toward clinical use.

To accelerate quantitative CEST imaging, we have developed a method based on the balanced steady-state free precession sequence as an alternative way for chemical exchange detection (bSSFPX). The feasibly of bSSFPX for chemical exchange detection was proved both theoretically and experimentally on phantoms. Mathematical models for bSSFPX were developed for quantitative measurements of T1ρ and exchange rate. bSSFPX was applied in the human brain. While the exact origin of the contrast is still under investigation, we hypothesize it is due to the chemical exchange from fast exchanging metabolites with resonance frequencies close to water. Detection of these metabolites is challenging for standard CEST imaging methods at 3T.

While application of CEST to brain malignancy is increasing, its application in body imaging is still challenging. One of the difficulties is the presence of large lipid signals. We have studied the influence of non-exchanging fat on CEST imaging using simulation, phantoms, and in vivo studies at different fat fractions and echo times. To remove the fat influence on body CEST imaging, we have developed a CEST-Dixon imaging sequence for fat free CEST imaging and applied it to human breast malignancy characterization at 3T. We have demonstrated that the CEST-Dixon sequence eliminates lipid contamination robustly in breast CEST imaging. The results display a potential for improved non-invasive characterization of human breast lesions at 3T using CEST, potentially differentiating more aggressive from less aggressive tumors.

Tuesday, March 20, at noon

Jelle Veraart, PhD

Champalimaud Center of the Unknown, Lisbon, Portugal
Biophysical Modeling of the White Matter: From Preclinical Validation to Clinical Perspective

Abstract: The morphology of the white matter&once referred to as nature’s finest masterpiece&is intricately coupled with brain function. Being able to measure the white matter structure, and its pathological changes, in vivo and non-invasively would promote the study of brain function and the more specific diagnosis of brain disorders. Despite a limited spatial resolution, the sensitivity of diffusion MRI to the Brownian motion of protons restricted by cellular structures, such as axons, provides an exciting avenue to reveal the microscopic architecture. However, bridging the length-scale gap requires the development and validation of a biophysical white matter model that decomposes the signal in components that probe specific features of the underlying microstructure, e.g. axon diameters. During this talk, I will focus on my recent work on the mapping of micrometer-thin axons using MRI, from preclinical validation to a clinical perspective.

Tuesday, March 13, at noon

Demian Wassermann, PhD

Associate Research Professor
Parietal Team
INRIA Saclay Ile-de-France
Computational Neuroanatomy of the Human Brain White Matter and Beyond

Abstract: The motivation of this talk is the computational encoding of neuroanatomy in terms of tissue characteristics as well as classical neuroanatomical knowledge.

The first problem to address will be the in vivo dissection of the human brain's white matter from diffusion magnetic resonance imaging. We address this through representing current anatomical knowledge computationally. In this talk I will introduce computational tools to represent human anatomy. More precisely, I will introduce a domain specific programming language to represent and automatically extract the major white matter structures in the human brain’s white matter, the white matter query language (WMQL) as well as applications of these techniques to dyscalculia and schizophrenia.

Then I will move on to presenting techniques to perform group-based studies to parcel the cortical mantle based on white matter connectivity. Specifically, I will show how leveraging a consistent mathematical model of axonal-based cortical connectivity we are able to separate subject and parcel-specific characteristics in a random effects model. In particular, the motor and sensory cortex are subdivided in agreement with the human homunculus of Penfield. We illustrate this by comparing our resulting parcels with the motor strip mapping included in the Human Connectome Project data.

Finally, I will provide a prospective view on NeuroLang, project that has the goal of extending the concepts explored in the previous to takes to computational neuroanatomy of the white matter to the bulk of human neuroanatomy.

About the speaker: Demian Wassermann, PhD is an Associate Research Professor at Inria Saclay Île-de-France within the Parietal laboratory. Since 2014, he has joined the INRIA to study computational representations of brain anatomy at the micro- and meso-scopic scale through MRI.

Demian graduated from the University of Buenos Aires, Argentina, where he obtained his B.Sc in computer science. He obtained his PhD at theAthena research team at the INRIA Sophia Antipolis under the supervision of Professor Rachid Deriche. In his PhD he focused on the analysis of white matter fibers traced from Diffusion MRI, aiming at providing a sound mathematical framework for automatic dissection and statistical analysis of the structures of the human brain's white matter. Between 2010 and 2013 demian worked at the Harvard Medical School and the Brigham and Women's Hospital developing tools for the computational analysis and representation of human anatomy with an emphasis in neuroanatomy of the white matter.

Wednesday, March 7, at noon

Jason Stockmann, PhD

Instructor in Radiology
A. A. Martinos Center for Biomedical Imaging
Massachusetts General Hospital & Harvard Medical School
Breaking the Mold of Conventional Gradients and Shims: New MRI Hardware for 70 mT and 7 Tesla

Abstract: Conventional gradient and shim coils for MRI generate pure spherical harmonic "B0" magnetic fields for shimming and spatial encoding, simplifying the image acquisition process. Unfortunately, these coils are difficult to build and impose high demands for space, cooling, and power consumption. In this talk, I will discuss a recent trend toward flexible spatial encoding and field control methods that use non-orthogonal magnetic field basis sets or alternative encoding mechanisms. As an example of this trend, I will discuss progress at MGH on a portable brain scanner that uses a rotating permanent magnet array with a built-in spatial encoding field to perform imaging without conventional B0 gradient coils, greatly reducing cost, weight, and power consumption. In this approach, imperfections in the linear encoding field are accounted for in the encoding matrix during image reconstruction, shifting the engineering burden away from complex hardware and into software. As a second example of flexible spatial encoding, I will show how spatial encoding can also be performed using lightweight, tailored radiofrequency coils whose "B1+" transmit field has a linear phase variation over space, enabling phase-encoded imaging in spin echo train sequences. Finally, I will review progress on multi-coil arrays of shim coils that use a non-orthogonal basis set to dynamically null localized, high-spatial order patterns of B0 inhomogeneity in the body. I will further show how multi-coil shimming can be physically integrated with the RF receive array to save space near the body. I'll then demonstrate how multi-coil shimming can benefit echo planar imaging, MR spectroscopy, and selective excitation, overcoming some of the limitations of conventional spherical harmonic shim coils.

Friday, March 9, at noon

Zhipeng Cao, PhD

Research Assistant Professor
Biomedical Engineering
Vanderbilt Universtiy
Advances in Parallel Transmission and Temperature Reconstruction for High Field MRI

Abstract: In recent years there is an increased interest to build massively parallel transmit (pTx) systems for high spatial-temperal resolution MR imaging. A novel pTx pulse compression method (array-compressed pTx, acpTx) is proposed, validated, and implemented that allows a many-element parallel transmit array to be driven by only a few power amplifiers without significantly degrading the pulse performance. AcpTx provides a new insight into pTx array design by synergistically integrating both Maxwell and Bloch principles. By maximizing the pulse performance for a pTx system with limited number of power amplifiers, acpTx can further improve highly accelerated MR imaging with multichannel reception. Specifically, acpTx is shown to improve the motion and phase errors of multi-shot EPI that would enable short TE fMRI and dMRI applications compared to single-shot EPI. In addition, the presentation will also include recent advances in improved multichannel compressed sensing reconstruction for PRF temperature imaging for MRgHIFU and high field RF heating monitoring, as well as a novel application of dielectric materials to accelerate abdominal imaging.

About the speaker: Zhipeng Cao is currently a research assistant professor at the Biomedical Engineering, Vanderbilt University, Nashville, TN. He completed his undergraduate degree (2006) in Nuclear Engineering from Tsinghua University, Beijing, China, and obtained his Ph.D degree (2013) in Biomedical Engineering from Pennsylvania State University, University Park, PA. Between 2013 and 2015, he worked as a postdoctorate research fellow at the Vanderbilt University Institute of Imaging Science (VUIIS).

His research focusses on technological development for magnetic resonance imaging at ultra-high field (7T) to improve image quality and ensure RF safety, involving topics in Bloch MR system simulation, multichannel transmit pulse design, multichannel compressed sensing image reconstruction, PRF temperature imaging, and dielectric materials.

Wednesday, February 28, at noon

Luis Angel, MD

Professor of Medicine
Director of Lung Transplantation
NYU Langone Medical Center
Update in Lung Transplantation and Predicting Chronic Rejection
Tuesday, February 27, at noon

Seena Dehkharghani, MD

Associate Professor of Radiology
Director, Stroke and Cerebrovascular Imaging
Department of Radiology
NYU School of Medicine
Cerebral MR Thermometry in Neurovascular Ischemia

Abstract: Cerebral thermoregulation is poorly understood but critical to brain homeostasis and viability. Temperature disturbances strongly potentiate cerebrovascular and other CNS injury, and represent potent targets for neuroprotection. Interrogation of brain temperature has historically been limited to costly and highly invasive implantable probes, and pragmatic approaches to measuring spatiotemporal temperature gradients are lacking. Cerebral MR thermometry may provide safe, non-invasive, and reproducible characterization of brain temperatures across physiologic, ischemic, and other pathologic disease states. This presentation will discuss initial experience with chemical shift thermometry as a biomarker of cerebrovascular injury in human and nonhuman primates, emphasizing the critical role of brain temperature at the intersection of perfusion, metabolism, and cytotoxic injury.

About the speaker: Seena Dehkharghani is an Associate Professor in the NYU Langone Department of Radiology and Director of Stroke and Cerebrovascular Imaging. He joined NYU following six years at the Emory University School of Medicine where he was an Assistant Professor in Radiology and Imaging Sciences and Neurology, and Director of the Stroke Imaging program.

Dr. Dehkharghani’s research interests include the neuroimaging of cerebrovascular ischemia, brain viability, and metabolism. He was awarded the Foundation of the American Society of Neuroradiology Scholar Award in Neuroradiology Research in 2012-2013 and 2013-2014 for the project “Investigating the Utility of MR Thermometry and Perfusion in the Evaluation of Cerebrovascular Ischemia: Applications to the Ischemic Penumbra Model of Neurovascular Injury.” He was further supported by the Stroke Trials Network of the National Institute of Neurological Disorders and Stroke, and was a coinvestigator in several multicenter stroke trials including the recent CRISP and DAWN trials. He is currently a recipient of the Empire Clinical Research Investigator Program fellowship in the multidisciplinary study, “Performance, Imaging, and Biological Markers for Sports-Related Concussion.”

February 26, at noon

Berkin Bilgic, PhD

Instructor in Radiology
Harvard Medical School
Faster MRI through Optimized Encoding and Reconstruction

Abstract: Our research focuses on developing techniques that dramatically improve the efficiency of MRI by collecting/deriving more information from each unit time of data acquisition. The overarching goal in creating these strategies is twofold:

  • pushing the limits of spatial/temporal resolution and CNR of MRI to make it a better neuroscientific tool
  • improving throughput, motion robustness and efficiency of clinical exams to make MRI more cost effective and more widely used in the clinic.

We are pursuing these goals in a number of areas, including structural, diffusion and spectroscopic imaging, as well as the quantitative techniques of MR fingerprinting, susceptibility mapping and myelin imaging. The order of magnitude efficiency gain we achieved for these acquisitions has been possible through a joint design approach that combines new hardware capabilities, new sequence and readout design, and novel image reconstruction exploiting sparsity, mutual information and deep learning.

About the speaker: Berkin Bilgic is an Instructor in Radiology at Harvard Medical School and faculty at Martinos Center for Biomedical Imaging, where he also completed his post-doctoral training in 2016. Prior to earning his PhD’13 and SM’10 degrees in EECS from MIT, he doubled in EE and Physics to obtain BS’08 degrees from Bogazici University. His research resides on the intersection of MR physics, signal processing, inverse problems and data-driven methods, with applications in fast data acquisition and quantitative imaging.

Friday, February 23, at noon

Özlem İpek

Postdoctoral Fellow & Managing Director RF Lab
Centre d’imagerie biom ́edicale (CIBM)
Ecole Polytechnique Federale de Lausanne (EPFL)
Lausanne, Switzerland
RF Coil Designs for Ultra-High-Field Magnetic Resonance in Humans

Abstract: To acquire high-resolution and –sensitivity images at ultra-high field magnetic resonance (MR) scanner, various hardware solutions can be utilized: dedicated RF coil design for a certain anatomical region of the human brain, merging high dielectric constant materials with the existing RF coil concepts, use of multi-channel transmit RF coil arrays on a parallel transmit system to steer any signal amplitude or phase. Besides these solutions, MR safety limitations have been wisely investigated, i.e. simultaneous EEG-fMRI setup at 7 T MR is simulated with finite difference time domain method to assess its RF safety. My talk will address various RF hardware solutions for 7 Tesla human proton and multi nuclei MR imaging and spectroscopy.

About the speaker: Özlem Ipek is a scientist and managing director of the RF lab at Centre d’Imagerie BioMédicale (CIBM) at EPFL, Lausanne, Switzerland. She completed her undergraduate education in Physics (2005) at the Middle East Technical University (METU), Ankara, Turkey, and obtained her diploma and master′s degree (2008) in Applied Physics at Eindhoven University of Technology (TU/e), Eindhoven, Netherlands. Between 2008 and 2012, she worked on her PhD project at the Department of Radiotherapy and Radiology at the University Medical Hospital Utrecht, and she received her PhD from Utrecht University, Utrecht, Netherlands. Her research focusses on technological development for clinical needs and advancements of human magnetic resonance (MR) imaging at ultra-high field (7T). Specifically, she works on novel MR hardware designs and methods to assess the safety of radiofrequency antennas and MR compatible devices within MR environment as well as to facilitate high-resolution human head imaging and spectroscopy as a way to investigate brain metabolism.

Friday, February 16, at noon

Fang Liu, PhD

Assistant Scientist, Department of Radiology
University of Wisconsin, Madison
The Deep Learning: Revolution in Medical Imaging

Abstract: This talk will present an overview of Deep Learning (DL) and discuss some recent successful applications in medical imaging. One aim is to draw connections between DL methods such as convolutional neural network (CNN), convolutional encoder-decoder (CED), cycle-consistent adversarial neural network (Cycle-GAN) and medical applications including image reconstruction, multi-modality image synthesis and image analysis. Dr. Liu will present some of his recent work using DL for medical imaging applications and will discuss relevant DL methods and their strengths and limitations. The talk will conclude with a discussion of open problems in DL that are particularly relevant in medical imaging and the potential challenges of DL in this emerging field.

Thursday, February 15, at noon

Sung-Min Sohn

Assistant Professor
Department of Radiology
University of Minnesota Medical School
Title: RF/Mixed-Signal Circuits and Systems toward Next-Generation MRI

Abstract: Magnetic Resonance Imaging (MRI) is one of the most state-of-the-art technologies to non-invasively acquire structural, functional, and biochemical information in the human body. Dr. Sohn will present his research topics to overcome technical barriers to increase the accessibility of MRI and improve the quality of MR imaging for next-generation MRI that realizes ultra-low RF power, miniaturization, lightweight, low cost, and safety. Most of his researches are related to the oscillating field (B1) of RF coils and interface circuits between RF coils and RF signal chains in transmit (Tx) and receive (Rx). Especially, he is focusing on the development of RF/mixed-signal circuits for simultaneous transmit and receive (STAR) and automatic correction systems of frequency tuning, impedance matching, and RF coupling as well as novel RF coil structures. His research results show the ultra-low RF peak power capability and replacement of manual adjustments to obtain human MR images. These RF hardware-engineering approaches can contribute to a wide variety of MRI researches and industries.

About the speaker: Sung-Min Sohn is currently an assistant professor (research track) in Department of Radiology at University of Minnesota, Medical School. He received his Ph.D. degree from Department of Electrical and Computer Engineering at the University of Minnesota in 2013. His current research interests lie in MRI hardware and applications, especially MRI-compatible RF/mixed-signal electronics, novel RF coils and interface circuits. He was awarded a K99/R00 Pathway to Independence Award from NIH (NIBIB) in 2016.

Monday, February 5, at noon

J.G. Fletcher, MD

Consultant, Department of Radiology
Professor of Radiology
Medical Director of the CT Innovation Center
Mayo Clinic
Making Every Photon Count: Photon Counting and Dose/Iodine Reduction at Mayo Clinic
Tuesday, January 23, at noon

Stella Kang, MD

Assistant Professor
Department of Radiology
NYU Langone Health
Outcomes Research for Imaging: Theory and Design

Abstract: Medical imaging has been targeted as a source of inordinate -- and sometimes unnecessary -- health care spending. Cross-sectional imaging use has increased markedly over recent decades, and yet the contribution of imaging to overall care has not been well characterized. Rather than parsimony, the goal of our system is to improve evidence-based clinical practice so that the right patients receive the right interventions. Outcomes research is necessary to drive this effort. In this talk, I will discuss the ways in which outcomes research can underscore the value of imaging, and review study designs that explore the best uses of imaging tests. MRI techniques that may perform better than available tests or offer similar performance at lower costs can be evaluated using intermediate health outcomes. Meanwhile, techniques for which larger, prospective studies are available can be evaluated for population-level benefits and harms. Finally, I will discuss some of the ongoing efforts at NYU to bridge the use of MRI to patient health outcomes and decision-making.

About the speaker: Stella Kang obtained her medical degree at Cornell Medical College in 2007 and was a diagnostic radiology resident at NYU. In 2013, she completed a clinical fellowship in abdominal imaging as well as comparative effectiveness research training at Massachusetts General Hospital. Also in 2013, she served as a teaching fellow at Erasmus Medical Center in Rotterdam, Netherlands, and at the Harvard School of Public Health in Advanced Medical Decision Making. At NYU, Stella has focused on the role of imaging in medical decision making for cancers and incidental imaging findings, with support of the AUR GE-Radiology Research Academic Fellowship, as well as an NCI K award. Her research interests in imaging outcomes include comparative effectiveness studies, cost effectiveness analysis, quality of life and patient reported outcome measures, and the development of decision-making tools.

Tuesday, January 16, at noon

Udunna Anazodo, PhD

PET/MR Physicist, Lawson Health Research Institute
St Joseph's Healthcare, London, Ontario
Assistant Professor, Department of Medical Biophysics
Schulich School of Medicine and Dentistry
Western University, London, Ontario, Canada
PET and MR Imaging in Management of Medically Refractory Epilepsy

Abstract: Patients with epilepsy uncontrolled by medications are potential candidates for epilepsy surgery. Surgical removal of an epileptic lesion can lead to alleviation or elimination of seizures. Majority of epileptic lesion(s) can be detected as structural abnormalities on anatomical (1.5T) MRI scans. However, anatomical MRI scans in a significant proportion of medically refractory epilepsies can be ambiguous or negative. In these non-lesional patients, PET-FDG is indicated for detection of the epileptic focus. Recent technological advances in medical imaging have led to the development of hybrid PET/MRI scanners which combine the two versatile imaging modalities in one scanner. It is predicted that PET/MRI will allow higher rates of lesion localization in medically refractory epilepsies, leading to improved surgical outcomes. In Ontario, access to PET/MRI scanners have improved from one scanner in 2012 to four scanners by the end of 2018. In this talk, I will share experiences from the Epilepsy Imaging Program at London Health Sciences Center in establishing indications for the use of PET/MRI in clinical management of medically refractory epilepsy in Ontario. In addition, I will briefly discuss some of the technical developments in advanced MRI (7T, BOLD-fMRI, DTI) that are implemented in London for clinical epilepsy imaging.

About the speaker: Dr. Udunna Anazodo completed her doctoral studies in Medical Biophysics in 2015 at Western University (formerly The University of Western Ontario) in London, Ontario, Canada. She was a Mitcas Accelerate postdoctoral fellow at Lawson Health Research Institute in London, Ontario, where she worked on translational PET/MRI projects. She is currently the PET/MR physicist at Lawson Health Research Institute and an Assistant Professor at the Departments of Medical Biophysics and Clinical Neurological Sciences, Western University. Her research focuses on developing non-invasive advanced PET and MRI techniques for clinical brain imaging, with emphasis in epilepsy, dementias and other neurodegenerative diseases.

Thursday, December 21st, noon

Bin Zheng, PhD

School of Electrical and Computer Engineering and Stephenson Cancer Center
University of Oklahoma
Developing New Quantitative Imaging Markers to Assist Cancer Risk and Prognosis Assessment

Abstract: Developing precision medicine requires accurate prediction markers and/or models to identify the personalized disease (e.g., cancer) risk and prognosis or response to the different treatment. Radiographic medical imaging is widely used in clinical practice and carries much useful information to phenotype disease risk and prognosis. However, how to reliably and quantitatively extract and compute the useful image features, which can be used to develop new and highly performed clinical prediction models remain a very challenged and hot research topic in the biomedical imaging and informatics field. In this presentation, I will discuss the general concept of applying the quantitative image feature analysis in this research field and report several research work recently conducted in our laboratory to identify new quantitative imaging markers and apply machine learning technology to develop new prediction models, which include (1) using a new imaging marker based on the bilateral mammographic density asymmetry computed from the negative mammograms to predict risk of cancer detection in the next subsequent mammography screening; (2) extracting image features from breast MR images to predict complete response (CR) of breast tumors to the neoadjuvant chemotherapy; (3) using tumor density heterogeneity features computed from lung CT images to build a prediction model to assess lung cancer recurrence risk after surgery; and (4) using image features computed from abdominal CT images to predict response of ovarian cancer patients to chemotherapy at the early stage of the clinical trials.

Tuesday, December 19th, noon

Andrew Webb, PhD

Professor, Director C.J.Gorter Center for High Field MRI
Leiden University Medical Center
Applying New Magnetic Resonance Concepts and Techniques to Human Scanning

Abstract: This talk will describe recent developments in several areas of magnetic resonance hardware and sequences which have been applied to clinical research and patient scanning at field strengths between 1.5 and 7 Tesla. Topics will include the design of very high permittivity materials/metamaterials for improved magnetic field homogeneity and lower power deposition, new ceramic-based resonators for multi-element transmit arrays, methods for the rapid non-invasive estimation of tissue conductivity, high resolution motion-free imaging of the eye, and whole-body optical-based measurement of temperature changes. Clinical applications include studies of patients with eye tumours, epilepsy, early-onset Alzheimers as well as muscular and neuromuscular dystrophies.

Friday, December 15th, noon

Partha P. Mitra, PhD

Professor at Cold Spring Harbor Laboratory
Cold Spring Harbor, NY
Tipping points in network performance: Phase transitions in machine learning and distributed control

Abstract: In 2016, it is estimated that internet IP traffic reached 10^21 bits – within striking distance of the Avogadro number. Given that data sizes are reaching thermodynamic proportions, and that relevant calculations have often to be performed in a distributed manner, it can be expected that phenomena and methods from the statistical physics of many particle systems are relevant.

This talk will examine a couple of examples where phase-transition like phenomena occur, with network performance going from a “good” to a “bad” phase sharply as a function of a relevant global parameter. The examples include the so called network consensus problem, and feature selection in multivariate regression using an L1 norm.

About the speaker

Thursday, December 14th, 11:00 a.m.

Gopal Nataraj

PhD Candidate
University of Michigan, Ann Arbor
Learning-Inspired Quantitative MRI: Acquisition, Estimation, and Application

Abstract: In quantitative MRI (QMRI), one seeks to accurately and rapidly localize biomarkers (i.e., measurable tissue properties) using MR data. One key challenge of QMRI is that ‘accurate’ and ‘rapid’ are often competing goals: more physically accurate MR signal models typically depend on more biomarkers, but estimating more markers usually requires longer acquisitions and greater computation. In this talk, I will discuss two recently developed methods to systematically limit these QMRI resource burdens. First, I will describe a method to assemble fast, statistically informative acquisitions that enable min-max optimally precise biomarker estimation. Second, I will describe a machine-learning inspired method to “learn” an extremely fast and scalable biomarker estimator from purely simulated training data. Finally, I will describe our ongoing efforts to apply these methods for fast, accurate myelin water fraction imaging. This talk discusses joint works with Prof. Jeffrey Fessler, Dr. Jon-Fredrik Nielsen, and Prof. Clayton Scott, all at the University of Michigan.

Tuesday, December 12th, noon

Enhao Gong

PhD Candidate in Electrical Engineering
Stanford University
Seminar: Deep Learning and Generative Adversarial Network for improved MRI Reconstruction

Abstract: Compressed Sensing (CS) MRI enables fast imaging. Conventional CS MRI reconstruction algorithms are time-consuming and often lead in undesired over-smoothing or artifacts. Recently, various methods have been proposed to apply Deep Learning models for more efficient and accurate MRI reconstruction. However, there are still open question on how to ensure realistic and consistent Deep Reconstruction. In this talk, a MRI reconstruction technique using Deep Learning and Generative

Adversarial Network (GAN) is introduced. Evaluated on clinical MRI datasets with both quantitative metrics and radiologists’ ratings, the proposed method demonstrates superior performance compared with conventional iterative reconstruction and Deep Learning models trained with pixel-wise loss. Similar deep learning models can also be applied for PET reconstruction and quantitative MRI.

About the speaker: Enhao Gong is a PhD Candidate in Electrical Engineering at Stanford. His research focus is on applying machine learning, deep learning and optimization for medical imaging reconstruction and processing. Specifically, he is working on fast Magnetic Resonance Imaging (MRI) techniques and multi-contrast neuroimaging applications

(MRI, PET/MR). He is advised by Professor John Pauly in Electrical Engineering and Professor Greg Zaharchuk in Radiology at Stanford.

Recently he is working to bridge deep learning methods with MRI reconstruction, such as enhancing image quality with Deep Learning and multi-contrast information, solving quantitative imaging (water-fat separation, QSM, parameter mapping) using Deep Learning framework as well as using Generative Adversarial Network (GAN) for Compressed Sensing MRI.

Wednesday, December 6th, noon

Thomas Küstner

Universität Stuttgart, Germany
Respiratory and cardiac PET/MR motion correction for the application in clinical practice
Tuesday, December 5th, noon

Filip Szczepankiewicz, PhD

Chief Research Coordinator and Technical Specialist
Random Walk Imaging (RWI)
Multidimensional diffusion MRI: unraveling new features of microstructure by clever gradient waveform design

Abstract: Evidence that conventional (linear) diffusion encoding is not enough to probe all relevant features of microstructure has accumulated for 20 years. Recent developments have seen the canonical Stejskal-Tanner experiment complemented with techniques that all contribute more specific information about the underlying structure. The lecture will survey several methods based on diffusion encoding with non-conventional gradient waveforms, and what microstructural features that they can resolve.

About the speaker: Dr. Filip Szczepankiewicz is the Chief Research Coordinator and Technical Specialist at Random Walk Imaging (RWI), and a guest researcher at Lund University. He has a PhD in Medical Radiation Physics from Lund University, and utilizes his knowledge in physics to develop and implement novel techniques for diffusion-weighted imaging. Currently, Dr. Szczepankiewicz explores non-conventional encoding to probe tissue microstructure, using NMR/MRI methods that are part of the RWI portfolio.

Tuesday, November 14th, 12:30 p.m.

Bin Lou, PhD

Senior research Scientist
Siemens Healthcare Technology Center
Medical Imaging Technologies
Siemens Medical Solutions USA, Inc.
Siemens Healthineers
Princeton, New Jersey
Part II: Toward a universal decoder of linguistic meaning from brain activation

Abstract: Technology leaders have recently announced the goal of translating thoughts into text directly from brain recordings. Existing work on decoding linguistic meaning from imaging data has been largely limited to concrete nouns, and trained and tested with similar stimuli from a few semantic categories. I will present a new approach for building a brain decoding system, based on a procedure for broadly sampling a semantic space constructed from massive text corpora. By efficiently selecting training stimuli shown to subjects, we ensure the ability to generalize to new meanings from limited imaging data. To validate this approach, we trained the system on imaging data of individual concepts, and showed it can decode imaging data of sentences from a wide variety of concrete and abstract topics in two separate datasets.

Tuesday, November 14th, noon

Carol L. Novak, PhD

Siemens Healthcare Technology Center
Medical Imaging Technologies
Siemens Medical Solutions USA, Inc.
Siemens Healthineers
Princeton, New Jersey
Part I: Overview of research activities at Siemens Medical Imaging Technologies in Princeton

Abstract: Brief overview of the current research activities at Siemens Healthcare Technology Center, Medical Imaging Technologies. Located in Princeton, NJ, we are the central research and development lab of Siemens Healthineers. Our team of over 80 research scientists and software engineers specializes in using large collections of data to build artificial intelligence solutions for healthcare. We also work closely with Siemens’ customers in submitting grant proposals to government funding agencies. Our research has resulted in multiple scientific contributions in the fields of medical imaging, modeling, and image-guided therapy and has been incorporated into many clinical products.

Friday, November 10th, noon

Sudhir Pathak, PhD
Walter Schneider, PhD

University of Pittsburgh
Idealized Axon Phantom for Validation & Calibration of dMRI: Testing Compartmental Models and Fiber Tractography

Abstract: The advancement of diffusion MR imaging (dMRI) acquisition, post-processing, and clinical diagnostic precision would be accelerated with a cross-laboratory anisotropic diffusion phantom providing paramedic control of shape geometry, packing density and routing. Our group is developing such a phantom matched to histology geometry on a 1 to 1 scale. We have created idealized axons (iAxons) that are textile-based hollow fibers at nanometer scale. They provide controlled geometrical configurations and packing density patterns. The iAxons have a diameter range from 0.2 to 36 microns filled with water covering and exceeding the biological range allowing parametric tests of dMRI precision. We create Standard iAxon Fasciculi (SIF) that contains 950-nanometer internal diameter water filled tubes with a density of a million per mm2. We can create cortical networks such as the eye to LGN of millions of iAxons with precise 50 micron routing positional control. We use non-MRI measurement with Micro CT, light, and electron microscope imaging of iAxons to to quantify dMRI precision. We are creating matched histology and phantoms for pig harvested and human cadaver tissue. We are testing bio-physical models like NODDI or spherical mean techniques (SMT) for packing density pattern and amount of iAxons. We have found the intra-cellular volume fraction correlates with a number of iAxons (r = 0.96). For geometrical configuration, we have tested Constrained Spherical Deconvolution techniques which show promising results to resolve more than 45-degree crossing. We will also present the effect of small/big delta on diffusivities at multiple packing densities of the iAxon bundle. We plan to provide phantoms across laboratories and release public data sets to drive MRI-based quantitative calibration and discovery of improved techniques. We have done cross instrument measurement and found large systematic errors in measurement (35%) across instruments at five sites. We are developing correction methods for clinical scanners. We expect the phantoms to provide a set of ground truth challenges to advance MRI diffusion physics and tractography.

Tuesday, October 31st, noon

Yoav Medan, PhD

Science and Technology Explorer
Focused Ultrasound Foundation
Past, Present and Future of MR-guided Focused Ultrasound

Abstract: Focused Ultrasound is a novel treatment modality that displaces (minimally) invasive surgery with a totally non-invasive approach using a focused beam of ultrasound energy. Depending on the parameters used, the effect at the focal point can be purely mechanical, thermal or a combination thereof. Coupled with real-time feedback of MRI enables to accomplish a spatio-thermal closed-loop procedure, which may lend itself to automation.

In my talk I will review the history of MRgFUS, the current clinical indications it is being used for and some new emerging applications. I will also describe the role of the Focused Ultrasound Foundation, a non-profit aimed at accelerating clinical adoption, in how NYU may benefit from research grants provided by the Foundation.

About the speaker: Dr. Yoav Medan, a social and technology entrepreneur, is currently a visiting scientist and an adjunct lecturer at the Technion Faculties of Electrical Engineering and Biomedical Engineering. Joining the Technion Faculty in 2012 after a lengthy career in industry as a visiting associate professor in Biomedical Engineering, Dr. Medan also teaches a course on entrepreneurship to engineering undergraduates, as part of a new minor degree track in Entrepreneurship. In addition, Dr. Medan is a mentor to entrepreneurs in the medical device field through the Technion for Life Alumni program, the Technion BizTec and MassChallenge programs. Prior to that Dr. Medan served as Vice President, Chief Systems Architect (1999-2011) of InSightec Ltd, A medical device company pioneering non-invasive MR- Guided Focused Ultrasound surgery. From 1984 through 1998 Dr. Medan held various senior research and management positions at the IBM Haifa Research Laboratory. In 2013 Dr. Medan founded Haifa3D, a new non-profit open hub for 3D digital fabrication, hosted by the Tiltan College at the Haifa Port Campus. In 2014 he cofounded NiniSpeech Ltd., a startup company developing a real-time mobile biofeedback solution for people who stutter.

Friday, October 27th, 9:00 a.m.

Prof. Lucio Frydman

Director, The Helen and Martin Kimmel Institute in Magnetic Resonance
The Bertha and Isadore Gudelsky Professorial Chair
Head, Department of Chemical and Biological Physics
Weizmann Institute, Israel
Principles and progress in spatiotemporally encoded MRI
Tuesday, October 17th, noon

Len Luyt, PhD

Associate Professor
University of Western Ontario, Canada

Dr. Mark Milne

Research Associate
Lawson Health Research Institute
1) Peptide-based Molecular Imaging Probes 2) Examining the structural variations in T1, T2 and ParaCEST MRI contrast agents
Monday, October 16th, noon

Eddy Solomon, PhD

Postdoctoral Fellow
Weizmann Institute of Science, Israel
Diffusive and Perfusive Effects in SPatio-temporal ENcoding (SPEN) Nuclear Magnetic Resonance Imaging
Friday, October 13th, noon

Francesco Grussu, PhD

University College London
Quantitative MRI of the spinal cord: challenges, feasibility and future perspectives

Abstract: Quantitative Magnetic Resonance Imaging (qMRI) enables the non-invasive measurement of microstructural properties of living tissue, thus providing useful imaging biomarkers with strong clinical potential. In practice, while qMRI is rather popular and successful in the brain, qMRI of the spinal cord is more difficult due its proneness to noise, field inhomogeneity and phyisological artifacts, which hamper the clinical translation of most qMRI methods. In this talk, I will provide an overview of spinal cord qMRI and illustrate its challenges and report on recent developments. In particular, the talk will focus on recent spinal cord qMRI approaches for neuronal morphology and myelin measurement, which hold promise for more accurate diagnosis and prognosis in conditions such as multiple sclerosis.

Tuesday, October 10th, noon

Nicolas A. Karakatsanis, PhD, DABSNM

Assistant Professor of Biomedical Engineering
Department of Radiology, Weill Cornell Medicine, New York, NY
Multi-Parametric PET/CT and PET/MR Molecular Imaging: Towards Enhanced Quantification and Diagnosis in the Clinic

Abstract: Positron Emission Tomography (PET) has been nowadays established as a molecular imaging modality capable of providing non-invasive, diagnostic and treatment response assessments of the activity of specific molecular processes underlying a spectrum of oncologic, cardiovascular and neurologic diseases. In the first part of this talk we will introduce a clinically adoptable WB dynamic 18F-FDG PET/CT scan protocol coupled with a family of robust direct 4D PET image reconstruction methods to enable for the first time WB multi-parametric PET imaging in humans. The presented framework exploits current state-of-the-art clinical PET systems technologies, such as Time-of-Flight and Resolution modeling, to also support combined WB static and parametric PET imaging from only the standard-of-care scan time window to deliver to clinic additional and highly quantitative information content beyond the standardized uptake value (SUV) metric. Later in the talk, we will also present a novel dual-tracer 18F-FDG:18F-NaF PET/MR imaging framework designed to improve PET attenuation correction in PET/MR studies by robustly segmenting the bone tissues from the 18F-NaF kinetic analysis. Finally, we will demonstrate a clinically adoptable dual-tracer dual-modality imaging protocol for the simultaneous and co-registered anatomical and molecular assessment of both inflammation and micro-calcification, two major molecular mechanisms considered to be associated with atherosclerosis, in human carotid vessel walls.

About the speaker: Dr. Nicolas (Nikolaos) A. Karakatsanis is currently an Assistant Professor in Biomedical Engineering at the Department of Radiology at Weill Cornell Medicine, Cornell University in New York, NY. His current interests focus mainly on quantitative PET/MR and PET/CT imaging utilizing advanced PET tracer kinetic modeling and MR-driven motion compensation strategies for enhancing the theranostic value of molecular imaging in cardiology, oncology and neurology. Previously, Nicolas was appointed as a senior research scientist at the Translational and Molecular Imaging Institute in the Icahn School of Medicine at Mount Sinai, New York (2015-2017). In addition, he had previously attended postdoctoral research fellow position in the Divisions of Nuclear Medicine and Molecular Imaging at University Hospital of Geneva, Switzerland (2014-2015) and Johns Hopkins University Hospital, Baltimore, MD, USA (2011-2013). Dr. Karakatsanis received his Master’s degree as well as his Ph.D. in Electrical and Computer Engineering in 2005 and 2010, respectively, from the National Technical University of Athens, Greece. His PhD thesis was on the optimization of preclinical and clinical PET imaging systems performance and data acquisition protocols using Monte Carlo simulations. He has authored and co-authored more than 20 peer-reviewed articles in scientific journals and over 70 refereed proceedings in international meetings and conferences. Dr. Karakatsanis is a member of the Nuclear Medicine and Molecular Imaging (SNMMI) organization and the elected intern (2017-2019) of the society’s Computer and Instrumentation Council (CaIC). Nicolas is also a Senior Member of the Institute of Electrical and Electronic Engineers (IEEE) and elected (2017-2020) in the Nuclear Medical Imaging Sciences Council (NMISC) of the IEEE Nuclear Plasma and Sciences (NPSS) society. Dr. Karakatsanis has been certified by the American Board of Science in Nuclear Medicine (ABSNM) with a specialization in Nuclear Medicine Physics and Instrumentation.

Tuesday, October 3rd, noon

Zahi A. Fayad, MD

Vice Chair for Research, Department of Radiology
Professor of Radiology and Medicine (Cardiology)
Director, Translational and Molecular Imaging Institute
Director, Cardiovascular Imaging
Icahn School of Medicine at Mount Sinai, New York, NY
Stress and Atherosclerotic Plaque Macrophages—A Systems Biology Approach

Abstract: Chronic social stress is an integral part of our busy contemporary lives. Abundant data show that severe chronic psychosocial stress is a risk factor for cardiovascular disease and a predictor of myocardial infarction and stroke. The mechanisms by which stress contributes to the higher cardiovascular event rates are primarily attributed to secondary effects on behavior, including smoking or food intake. How stress’ effect on the brain can directly impact cardiovascular disease is uncharted territory.

Preclinical data describe a direct causal link between social stress, neural signals, and atherosclerosis, the lipid-driven chronic inflammatory disease that is the underlying cause of myocardial infarction and stroke. The key connecting component is the macrophage, a large phagocytic leukocyte that originates in the bone marrow and accumulates in atherosclerotic lesions. Informed by abundant published and unpublished data, we hypothesize that chronic variable stress aggravates cardiovascular disease by interfering with macrophage dynamics.

Specifically, we wish to (i) understand how stress biologically affects macrophage dynamics in atherosclerosis; (ii) develop technology that monitors macrophage dynamics non-invasively; and (iii) elucidate the mechanism by which post-traumatic stress disorder (PTSD) leads to atherosclerosis.

This work is based on technological developments (such as motion compensation and fast imaging) in biomedical imaging and systems imaging using PET/MR and using novel targeted approaches (such as molecular imaging and nanomedicine) to study and treatment of inflammation in preclinical and clinical studies. I will describe our overarching and long-term goal is to collectively institute a sound scientific foundation for the biomedical and clinical community as how the link between stress and cardiovascular disease can be best approached and integrated in patient care.

  1. Systems biology and noninvasive imaging of atherosclerosis. ATVB 2016; 36:e1-e8.
  2. Relation between resting amygdalar activity and cardiovascular events: a longitudinal and cohort study. Lancet 2017; 389: 834-845.
  3. Imaging systemic inflammatory networks in ischemic heart disease. JACC 2015; 65: 1583-1591.

About the speaker: Dr. Fayad serves as professor of Radiology and Medicine (Cardiology) at the Mount Sinai School of Medicine. He is the founding Director of the Translational and Molecular Imaging Institute; Vice chair for Research, Department of Radiology at the Icahn School of Medicine at Mount Sinai. Dr. Fayad’s interdisciplinary and discipline bridging research – from engineering to biology and from pre-clinical to clinical investigations – has been dedicated to the detection and prevention of cardiovascular disease with many seminal contributions in the field of multimodality biomedical imaging (MR, CT, PET and PET/MR) and nanomedicine. His work has recently expanded in understanding the effect of stress on the immune system and cardiovascular disease. He has authored more than 500 peer-reviewed publications (h-index of 84 accessed 06/01/2017 on Google Scholar), 50 book chapters, and over 500 meeting presentations. He is currently the Principal Investigator (PI) of 5 federal grants (4 R01s and 1 P01) funded by the National Institutes of Health’s National Heart, Lung and Blood Institute and National institute of Biomedical Imaging and Bioengineering. He is also PI on three NIH sub-contracts with UCSD, Columbia and the Brigham and Women’s Hospital. In addition, he serves as Principal Investigator of the Imaging Core of the Mount Sinai National Institute of Health (NIH)/Clinical and Translational Science Awards (CTSA). He is a PI of one of the 3 projects in the Strategically Focused Prevention Research Network Center grant funded by the American Heart Association (AHA) to promote cardiovascular health among high-risk New York City children, and their parents, living in Harlem and the Bronx. Moreover, he currently leads four pharmaceutically funded multicenter clinical trials for the evaluation of novel cardiovascular drugs.

He is Associate Editor and overall Guest Editor for the Journal of the American College of Cardiology Imaging (JACC Imaging), Section Editor for Journal of the American College of Cardiology (JACC), Consulting Editor for Arteriosclerosis Thrombosis and Vascular Biology (ATVB), Guest Editor for the Journal of Cardiovascular Magnetic Resonance (JCMR) and past Associate Editor of Magnetic Resonance in Medicine (MRM). From 2013-2017, he served as Charter Member, NIH Center of Scientific Review, Clinical Molecular Imaging and Probe Development Study Section. In 2015, he chaired the Scientific Advisory Board of the Institut National de la Santé et de la Recherche Médicale (INSERM) PARCC program at the HEGP in Paris.

Dr. Fayad had his engineering trainings at Bradley University (BS, Electrical Engineering ’89), the Johns Hopkins University (MS, Biomedical Engineering ‘91) and at the University of Pennsylvania (PhD. Bioengineering ’96). From 1996 to 1997 he was junior faculty in the Department of Radiology at the University of Pennsylvania. In 1997 he joined the faculty at Mount Sinai School of Medicine.

Dr. Fayad is the recipient of multiple prestigious awards. In 2007 he was given the John Paul II Medal from Krakow, Poland in recognition for the potential of his work on humankind. As a teacher and mentor, Dr. Fayad has been also extremely successful. He has trained over 100 postdoctoral fellows, clinical fellows and students. His trainees have received major awards, fellowships, and positions in academia and industry. In 2008, he received the Outstanding Teacher Award from the International Society of Magnetic Resonance in Medicine (ISMRM) for his teaching on cardiovascular imaging and molecular imaging. In 2009 he was awarded the title of Honorary Professor in Nanomedicine at Aarhus University in Denmark. Recently, he was one of opening speakers at the 2011 97th Scientific Assembly and Scientific meeting of the Radiological Society of North America (RSNA). In 2012, he was invited to give the Henry I Russek Lecture at the 45th Anniversary of the ACCF New York Cardiovascular Symposium. In 2013, he was elected Fellow of the International Society of Magnetic Resonance In Medicine, Magnetic Resonance Imaging, received a Distinguished Reviewer from Magnetic Resonance in Medicine and was selected as an Academy of Radiology Research, Distinguished Investigator In 2014 he received the Centurion Society award from his alma matter (highest award) Bradley University for his bringing national and international credit to his alma matter. In 2014, he received the Editor’s Recognition Award, from the Journal Radiology. In 2015, he was the Dr. Joseph Dvorkin Memorial Lecturer at the Cardiac Research Day of the Mazankowski Alberta Heart Institute, University of Alberta, Edmonton, Canada. In 2015, he became the Mount Sinai Endowed Professor in Medical Imaging and Bioengineering. The Mount Sinai Professorships were established in 2007 by the Mount Sinai Boards of Trustees to honor the achievements and contributions of some of Icahn School of Medicine’s most outstanding faculty. A total of eight Mount Sinai Professorships have been awarded to date in Alzheimer’s Research, Diabetes and Aging, Gene Medicine, Medical Imaging and Bioengineering, Orthopaedics, Orthopaedic Research, Psychiatric Genomics, and Structural Biology. In 2016, he was the Heart & Stroke/Richard Lewar lecturer at the Center of Excellence in Cardiovascular Research in Toronto.

He is married to Monique P. Fayad, MBA and is the proud father of Chloé (15 year old) and Christophe (11 year old) and after spending seven years in Manhattan now lives in Larchmont, runs in Central Park and participates regularly in New York Road Runners races. He also enjoys regular sailing and stand-up board paddling in Larchmont, New York, Connecticut, Rhode Island, Cape Cod, Martha’s Vineyard, Nantucket, the Caribbean Islands and beyond. He also practices all type of daily fitness regimens that include strength, cardiovascular, core, flexibility and high intensity interval trainings for fun.

Tuesday, September 26th, noon

Gadi Goelman, PhD

Hadassah Medical Center
The Hebrew University of Jerusalem
Directed functional pathways of information flow in the visual and motor systems

Abstract: I will introduce a novel analytical method based on high order statistics and nonlinear coherences that enables to obtain directed pathways of signal progression among coupled time-series. Assuming a consistent phase relationship between neuronal and MRI signals, the method is demonstrated in the human brain with resting-state fMRI data. Pathways in the visual and the motor systems were characterized by appealing to a hierarchy based upon temporal or phase differences. I will describe the different organizations of the ventral and dorsal visual systems, the frequency dependency of the thalamo-cortical connections and how it changes with age.

Tuesday, September 19th, noon

Prof. dr. Freek J. Beekman

Section Leader, Delft University of Technology, Radboud University Nijmegen, Netherlands
Founder & CEO MILabs
Hexa-modal integrated sub-mm PET-SPECT, sub-quarter mm SPECT, high performance X-ray CT and Optical imaging

Abstract: In biomedical preclinical research we have dreamt about a magnifying glass that would allow us to e.g. see neurotransmitters in action, that would simultaneously quantify mechanical function, perfusion and various local cell functions in the heart, and in cancer research for (simultaneous) detailed dynamic distributions of pharmaceuticals and indicators of tumor response. In recent years many groups have been involved in the development of pinhole imaging SPECT systems for imaging rodents.

At MILabs and TU-Delft, a ultra-high resolution Single Photon Emission Computed Tomography (U-SPECT-CT) has been developed that can quantify tracers in 0.15 mm structures, enable low dose imaging (sub-MBq), or visualize extremely fast tracer dynamics (sub-second time frames) by developing highly advanced imaging geometries, novel image acquisition and reconstruction. An option on this system to perform 0.6 mm Positron Emission Tomography (PET) simultaneous with 0.4mm SPECT (VECTorTM) was developed. It also enables for the first time ultra-high energy SPECT (up to 1MeV) and imaging of sub-mm resolution of theranostic isotopes to real time monitor and steer cancer therapy.

In this presentation, scientific results recorded by worldwide users of a full integrated platform combining SPECT, PET, ultra-fast and ultra-high resolution CT, Cherenkov, bioluminescence and fluorescence imaging will be discussed. Finally the results of translating U-SPECT technology into a clinical device (G-SPECT: WMIS Innovation of the Year 2015), an Ultra-fast, Ultra-high resolution (<3 mm resolution) will be presented.

About the speaker: Prof. Frederik J. Beekman heads the section Radiation, Detection and Medical Imaging at TU Delft University. He co-authored over 140 journal papers and is the inventor on 31 patents. Dr. Beekman was honored with several awards for his contributions to SPECT and PET technology and its application in biomedical research (2013 FOM valorization prize, 2015 WMIS Innovation of the year, SNMMI 2017 Edward Hoffman Memorial Award). His research interests include radiation technology applied to medicine and biomedical science and image reconstruction from projections. He is an associate editor of several journals and board member of Physics in Medicine and Biology. He is also founder and CEO/CSO of MILabs ( that develops and markets high performance molecular imaging systems.

Friday, September 8th, noon

Daniel Topgaard, PhD

Division of Physical Chemistry
Lund University, Sweden
Multidimensional diffusion MRI

Abstract: Diffusion MRI is an excellent method for detecting microscopic changes of the living human brain, but often fails in assigning the observed changes to a specific structural property such as cell density, size, shape, or orientation. When attempting to solve this problem, we have decided to simply ignore the entire field of diffusion MRI, and instead translate data acquisition and processing schemes from multidimensional solid-state NMR spectroscopy. Key elements of our approach are q-vector trajectories and correlations between isotropic and directional diffusion encoding. To emphasize the origin of the new methods, we have selected the name “Multidimensional diffusion MRI.” Assuming that the water molecules within a voxel can be divided into groups exhibiting approximately Gaussian anisotropic diffusion, the composition of the voxel can be reported as a diffusion tensor distribution where each component of the distribution is directly related to a specific tissue environment. Our new methods yield estimates of the complete diffusion tensor distribution or well-defined statistical properties thereof, such as the mean and variance of isotropic diffusivities, mean-square anisotropy, and orientational order parameter, which are straight-forwardly related to cell densities, shapes, and orientations. This presentation will give an overview of the multidimensional diffusion MRI methods, including basic physical principles, pulse sequences, data processing, and examples of applications in healthy and diseased brain.

Tuesday, September 5th, noon

Peter Kochunov, PhD

Professor of Psychiatry
Professor of Psychiatry
White matter and core neurocognitive deficits in schizophrenia

Abstract: Disconnections of cortical networks may underlie various cognitive deficits that take severe clinical tolls on patients with schizophrenia. Historically, the neuropsychopharmacology of cognitive deficits is mostly conceptualized and studied in terms of neurons, neurotransmitters and synaptic receptors. We hypothesized that the dynamics of the extended lifetime development trajectory of the brain’s white matter, and the consistency of connectivity deficits in schizophrenia, posit white matter as the key loci responsible for these cognitive deficits. Using novel diffusion weighted imaging (DWI) techniques and a milestone development of identifying key white matter tracks most relevant to schizophrenia, we are now able to show that specific white matter pathways are responsible for shared vs. unique contributions to some of the key cognitive deficits in schizophrenia.

About the speaker: Dr. Kochunov is a professor of psychiatry at the University of Maryland School of Medicine, Baltimore. His interests include understanding genetic and environmental risk factors for complex polygenic mental disorders.

Wednesday, August 16th, 10:00 a.m.

Davide Piccini, PhD

Advanced Clinical Imaging Technology
Siemens Healthineers, Lausanne, Switzerland
Cardiac MRI in the era of compressed sensing and machine learning

About the speaker: “Since December 2011, Davide Piccini is an employee of Siemens Switzerland and is responsible for research projects at CIBM/CVMR as part of a collaboration between academia and industry. Davide graduated in Biomedical Engineering at the University of Padova, in Italy, in 2007. In 2008 he completed his internship at Siemens Corporate Research (SCR) in Princeton, NJ, USA, working on the development of post-processing tools for 4D visualization of cardiac cine MRI data and for semi-quantitative analyses of myocardial perfusion MRI, under the supervision of Dr. Jens Guehring. In 2011 he completed his PhD project at the University of Erlangen-Nuremberg, Germany, in the team of Prof. Dr. Joachim Hornegger on the development of algorithms for respiratory motion compensation and self-navigation in 3D whole-heart coronary MRI. His PhD project was part of a collaboration with the cardiovascular development team at the Siemens headquarters in Erlangen, Germany, and was co-supervised by Dr. Michael O. Zenge and Dr. Arne Littmann.

His main research interests are focused on the development of advanced cardiac MRI techniques, including fast cardiac MRI using compressed sensing, motion compensation for MRI, pediatric and fetal cardiac MRI, quantitative myocardial motion analysis using MR tagging, and recently on applying machine learning to cardiac MRI.

Tuesday, August 8th, noon

Aaron K. Grant, PhD

Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA
Hyperpolarized Carbon-13 for Imaging of Perfusion and Metabolism

Abstract: Hyperpolarized contrast media prepared via dissolution dynamic nuclear polarization or parahydrogen-induced polarization provide tremendous in vivo signal enhancements for dilute tracer molecules labeled with nuclei such as 13C or 15N. These signal enhancements provide a tool for monitoring tissue function and metabolism, particularly in cancer and cardiac disease. In pre-clinical models of lung, prostate and breast cancer, hyperpolarized pyruvate can detect tumor response to therapy within hours of the onset of treatment, potentially providing a new tool for personalized medicine by rapidly identifying the best therapy for each patient. Clinical translation of hyperpolarized imaging will require new approaches to MR spectroscopic imaging. Spectroscopically selective balanced steady-state techniques offer improved sensitivity and speed relative to conventional echo-planar spectroscopic methods that can be leveraged for imaging in patients.

Thursday, August 3rd, noon

Petrik Galvosas

MacDiarmid Institute for Advanced Materials and Nanotechnology, SCPS
Victoria University of Wellington, New Zealand
Magnetic Resonance in the GP’s Clinic: A vision of low field NMR for medical screening and diagnosis

Abstract: Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI) is common in medical research and widely used for medical diagnosis. However, NMR and MRI systems are expensive to install and cause substantial maintenance costs. Its use is often restricted to radiology centres or hospitals in larger cities. Here we report on recent research which may help to turn inexpensive, mobile low field NMR systems into medical devices. One challenge in low field NMR is the magnetic field inhomogeneity. It introduces a distribution of Larmor frequencies and magnetic field gradients. However, field distributions can be determined (see Fig. 1 left) and may be corrected for, thus enabling these magnet systems for the use in NMR diffusometry [1]. Another challenge is the reduced signal-to-noise ratio at lower magnetic fields. Therefore, conventional imaging approaches may not be feasible. We have shown that the sample averaged fractional anisotropy (FA) can be determined without the use of imaging [2]. However, if imaging is needed, the amount of acquired data may be reduced dramatically using prior knowledge [3]. More recently we have also demonstrated that single sided NMR systems such as the NMR MOUSE [4] can be used (see Fig. 1 right) for the determination of the total volume-to-bone volume ratio, a parameter linked to the micro structure of bones and therefore to the risk factor for osteoporosis [5]. We anticipate the use of mobile low field NMR systems as diagnosis and screening tools, affordable for general practitioners as well as mobile point-of-care medical devices on the bedside, in ambulances, operational theatres and ICU’s.

Tuesday, August 1st, noon

Kimberly Brewer, PhD

Research Scientist, Biomedical Translational Imaging Centre (BIOTIC), IWK Health Centre and QEII Health Sciences Centre
Assistant Professor, Departments of Diagnostic Radiology, Physics and Atmospheric Science, Microbiology and Immunology
School of Biomedical Engineering, Dalhousie University, Halifax, Nova Scotia, Canada
The Potential of MR Molecular Imaging for Investigation and Evaluation of Immunotherapies

Abstract: Immunotherapies are becoming increasingly important for improved treatment of a variety of cancer types. However, the development of these novel therapies has outstripped our understanding of underlying mechanisms and how best to apply them. It is therefore crucial that we use tools such as MRI, and other molecular imaging techniques, to evaluate immunotherapies in both the clinic and in preclinical studies, and develop new probes and biomarkers to increase their efficacy. Studies have shown high degrees of variability in individual response to cancer, increasing the necessity of a more personalized approach, and optimized methods for combinations of multiple therapies are not well understood.

This talk will touch on a number of molecular imaging methods used to study immunotherapy response, including the use of MRI cell tracking for monitoring both adoptive cell immunotherapies, and immune cell population migration in response to other immunotherapy subtypes. Other techniques to be discussed include use of PET (using standard FDG imaging, and novel probes specifically developed for immunotherapies) and PET/MRI multimodal imaging for monitoring both anatomical and functional changes with MRI (using DCE, T1/T2-weighted imaging, etc.)

Tuesday, July 25th, noon

Michelle Krogsgaard, PhD

Associate Professor of Pathology
Department of Pathology, Perlmutter Cancer Center
NYU School of Medicine
Mechanisms of Primary Resistance to Cancer Immunotherapies

Abstract: Although much clinical progress has been made in harnessing the immune system to recognize and target cancer, there is still a significant lack of an understanding of how tumors evade immune recognition and the mechanisms that drive tumor resistance to both T cell and checkpoint blockade immunotherapy. Our objective is to understand how tumor-mediated signaling through inhibitory receptors, including PD-1, combine to affect the process of T cell recognition of tumor antigen and activation signaling, with the goal of understanding the basis of resistance to PD-1 blockade and the potential identification of new molecular targets to enable T cells to overcome dysfunction mediated by multiple inhibitory receptors. Potential combinatorial immunotherapeutic strategies of combining T-cell therapy strategies with checkpoint blockade will also be discussed.

Thursday, July 20th, noon

Ipshita Bhattacharya

Computational Biomedical Imaging Group
University of Iowa
Pushing the limits of spectroscopic imaging using low-rank based reconstruction
Wednesday, July 19th, noon

Stefan Posse, Dr. Phil. Nat. Habil.

Professor of Neurology
Professor of Electrical and Computer Engineering
Professor of Physics and Astronomy
University of New Mexico
On the Detection of High Frequency Connectivity and Development of Presurgical Mapping using High-Speed Resting State fMRI

Abstract: Functional connectomics using resting state fMRI (rsfMRI) is a rapidly expanding task-free approach, which has the potential to complement task-based fMRI for presurgical mapping in patients with neurological disease. However, high sensitivity to head movement and physiological noise, the low frequency range of rsfMRI (< 0.2 Hz), and considerable spatial-temporal non-stationarity compromise mapping of resting state networks (RSNs).

Recently, several studies using volumetric and multi-band high-speed fMRI have reported resting state connectivity at much higher frequencies (up to 5 Hz). This approach has the potential for addressing principal limitations of mapping low frequency resting state connectivity, such as high sensitivity to signal drifts and long scan time necessary for separating major RSNs in single subjects. However, other studies have been more cautious regarding the possible signal sources or were unable to replicate the findings.

The first part of this talk will discuss recently developed ultra-high speed fMRI and confound-tolerant seed-based resting-state fMRI analysis methodology that enabled sensitive detection of high frequency signal fluctuations in auditory cortex and default mode network. Experimental findings were validated by analyzing non-physiological signal sources using simulations of auto-correlations in Rician image noise. The second part of the talk will describe initial experience using high-speed resting state fMRI for presurgical mapping in patients with brain tumors, arteriovenous malformation and epilepsy, and integration of this approach with multi-modal diagnostic imaging.

About the speaker:

Tuesday, July 18th, noon

Nicole Seiberlich, PhD

Associate Professor
Department of Biomedical Engineering
Case Western Reserve University
Advances in Rapid MRI: Magnetic Resonance Fingerprinting and Real-Time Imaging of the Heart and Abdomen

Abstract: The focus of the Seiberlich Lab is to develop MR imaging techniques to capture structural and functional information from moving organs, specifically in the abdomen and heart. This lecture will cover the recent developments using Magnetic Resonance Fingerprinting for quantitative tissue property mapping of the myocardium. Additionally, work on real-time cardiac and abdominal imaging using non-Cartesian parallel imaging techniques in conjunction with Gadgetron will be discussed.

Thursday, June 29th, 10:00 a.m.

Priti Balchandani, PhD

Assistant Professor, Radiology and Neuroscience
Translational and Molecular Imaging Institute
Icahn School of Medicine at Mount Sinai
Visualizing the brain at 7 Tesla: Technical Developments and Clinical Applications

Abstract: This talk will cover some novel radio frequency pulse and pulse sequence designs to overcome some of the main limitations of operating at high magnetic fields, thereby enabling high-resolution whole-brain anatomical, spectroscopic and diffusion imaging. Translation of these techniques to improve diagnosis, treatment and surgical planning for a range of neurological diseases and disorders will be discussed. Specific clinical applications that will be covered include: Improved localization of epileptogenic foci; imaging to reveal the neurobiology of depression; and development of imaging methods to better guide neurosurgical resection of brain tumors.

Tuesday, June 27th, at noon

Ed X. Wu, PhD

Lam Woo Professor and Chair of Biomedical Engineering
University of Hong Kong
Optogenetic fMRI Dissection of Long-Range Brain Networks

Abstract: Functional MRI (fMRI) provides the most versatile imaging platform for mapping the brain activities in vivo. More recently, resting-state fMRI (rsfMRI) has emerged as a valuable tool for mapping large-scale and long-range brain networks. However, both methods only reflect the gross outcome of the complex and cascaded activities of various cell types and networks, posing limitations when dissecting brain networks. Optogenetics technology can provide spatiotemporally precise modulation of genetically defined neuronal populations in vivo. Here we combine fMRI with optogenetic perturbations and electrophysiology to capture and analyze whole brain activity and long-range circuits with much improved specificity and causality. We deploy this capability to interrogate the spatiotemporal response properties of two distinct long-range networks, namely, thalamo-cortical and hippocampal-cortical networks. We examine the functional effects of low-frequency optogenetic stimulation within these two networks on brain responses to external sensory stimuli, on brain-wide functional connectivity at resting-state, and on cognitive behaviors. Our findings reveal that low frequency activity governs large-scale, brain-wide connectivity and interactions through long-range excitatory projections to coordinate the functional integration of remote brain regions. This low frequency phenomenon contributes to the neural basis of long-range functional connectivity as measured by rsfMRI. I this talk, I will also briefly introduce our recent diffusion MRI works in brain and MSK, including diffusion MR spectroscopy.

About the speaker: Dr. Wu is the Lam Woo Professor and Chair of Biomedical Engineering at the University of Hong Kong (HKU). From 1990 to 2003, Dr. Wu worked in Columbia University on the 3D PET and high-field MRI system engineering, first as an Assistant Professor and later as an Associate Professor of Radiology and Biomedical Engineering. Dr. Wu joined HKU in 2003. His present research focus is to develop MRI methodologies for in vivo functional and microstructural characterization of biological systems, particularly the CNS systems, in rodent models. Dr. Wu is an elected Fellow of ISMRM, IEEE, and AIMBE. He is the Asia Pacific Editor of NMR in Biomedicine since 2011.

Friday, June 16, 12:45 p.m.

Laurence Dierickx, MD

Institut Claudius Regaud
Service de médicine nucléaire
Toulouse, France
Functional testicular evaluation using PET/CT with 18F FDG?

Abstract: The aim of this presentation is to evaluate the use of PET/CT with 18F-FDG for an assessment of the testicular function and to optimise and standardise the acquisition protocol and the testicular volume analysis in order to do that. By ways of introduction there will be a literature overview where we establish why the 18F-FDG uptake is correlated with the spermatogenesis. There will follow an overview of the public health problem of male infertility where the different possible clinical applications for testicular functional imaging with PET/CT will be addressed.

In the second part of the talk we’ll discuss the correlation between 18F-FDG uptake in terms of intensity and volume of uptake and the testicular function via the parameters of the sperm analysis based on the published article of our group.

The third part of the presentation will be on the subject of some of the technical issues where the focus will be on the standardisation of the acquisition protocol for this specific indication. In the last part of the presentation, we’ll address the overall important subject, and even more so in this andrological context, of the radioprotection related issues of a PET/CT with 18F-FDG.

Finally, there’ll be an overview of some of the issues still to be addressed and the future perspectives.

Monday, June 12th, at noon

Edwin J.R. van Beek MD PhD MEd FRCPE FRCR

SINAPSE Chair of Clinical Radiology
University of Edinburgh
Pulmonary MRI - what's new in context of multimodality approaches
Tuesday, May 30th, at noon

Marios Georgiadis, PhD

Post-doctoral Fellow
NYU School of Medicine
X-ray scattering for investigating tissue microstructure: Collagen directionality in bone, neuronal directionality and myelin content in brain, and comparison with MRI, histology and CLARITY

Abstract: Small-angle X-ray scattering (SAXS) occurs when part of the X-ray beam that probes a sample is scattered at small angles, due to differences in electron density distributions within the sample. Moreover, it gives a particularly strong signal in the presence of ordered and periodic systems. The recently developed small-angle X-ray scattering tensor tomography (SAXSTT) takes X-ray tomography a step further: it uses two sample rotation axes and an iterative reconstruction algorithm to tomographically reconstruct local tissue anisotropy. The method was demonstrated for reconstructing the orientation of mineralized collagen fibrils in bone trabeculae of human vertebrae, based on the 65-nm D-spacing of collagen. Similar experiments have also very recently been performed in mouse brain, taking advantage of the ~17.5 nm spacing of the myelin sheath. Providing directly structural information, SASTT was used to derive neuronal fiber directionality and myelin content in a quantitative way. The results are being compared with MRI methods such as diffusion-weighted imaging and magnetization transfer, as well as with 2D and 3D histology (CLARITY).

About the speaker: Marios Georgiadis received his mechanical engineering diploma from the National Technical University of Athens, Greece. He did his Masters studies in Biomedical Engineering at ETH Zurich, Switzerland, with his master thesis being awarded the ETH medal. In his PhD at the Institute for Biomechanics of ETH Zurich he developed methods for investigating tissue anisotropy using X-ray scattering, and applied that to bone tissue. He was runner-up for the Student Award of the European Society of Biomechanics in 2015. In his first post-doc at the Institute for Biomedical Engineering of ETH and University of Zurich, he looked at the microstructural properties of brain tissue using X-ray scattering and MRI. He recently joined the NYU Medical Center where he will continue investigating brain tissue with X-ray scattering and MRI, supported by a Swiss National Science Foundation fellowship.

Thursday, May 25th at 10:00 am

Peder Larson, PhD

Associate Professor, Principal Investagor
University of California, San Francisco
MRI of Ultra-fast relaxing spins for PET/MRI, Lung imaging, and Myelin Imaging

Abstract: MRI has historically performed poorly when imaging ultra-fast relaxing tissues such as bone, lung tissue, and tendons as well as components of other connective tissues including cartilage and myelin. Specialized pulse sequences such as ultrashort echo time (UTE) and zero echo time (ZTE) MRI offer the potential to image these tissues, and have several promising new applications that will broaden the capability of MRI. These include
1. PET/MRI – Hybrid PET/MRI systems require attenuation correction for accurate PET reconstructions, which should include estimates of bone density. This talk will present work using ZTE MRI for generating pseudo/synthetic CT images that include bone density estimates in the head and pelvis. Most recently, we have applied Deep Learning for this synthetic image generation task.
2. Lung Imaging – Pulmonary MRI has been very challenging due to the short T2* of lung parenchyma and motion, but is important for assessing pulmonary nodules in PET/MRI and for dose reduction in pediatric populations. This talk will present an approach using UTE MRI, where self-navigation is achieved through a local low-rank reconstruction of dynamic 3D image navigators and motion-corrected images are reconstructed similarly to XD-GRASP.
3. Myelin Imaging – Myelin facilitates crucial long-range communication across the brain, and is typically assessed in MRI through diffusion-weighting, magnetization transfer, and myelin water imaging. It has been shown through ex vivo studies that there are fast relaxing components in myelin associated with protons in the myelin phospholipid membranes, which are not captured in these conventional approaches. This talk will present in vivo characterizations of the ultrashort-T2* components in the brain that have the potential to provide a more direct measurement of myelination.

About the speaker: Peder Larson, PhD, is an Associate Professor in Residence and a Principal Investigator in the Department of Radiology and Biomedical Imaging at the University of California, San Francisco. Dr. Larson's research program is primarily centered around developing new MRI scanning and reconstruction technology for improved clinical outcomes.

Tuesday, May 16th at noon

Hong-Hsi Lee

PhD Candidate
Sackler Institute of Biomedical Sciences
NYU School of Medicine
Time-Dependent Diffusion in the Brain

Abstract: Diffusion MRI is sensitive to the length scale of tens of microns, which coincides to the scale of microstructure in the human brain tissue. By changing the diffusion time or diffusion gradient pulse width, we can probe the brain micro-geometry via time-dependent diffusion measurements. To increase the sensitivity to the microstructure, STEAM sequence is often used for extending the range of diffusion time. However, water exchange between myelin water and intra-/extra-axonal water may bias the parameter estimations. This talk will focus on the time dependence either along or perpendicular to white matter axons and corresponding micro-geometries, and the correction for the time dependence measured by STEAM.

About the speaker: After finishing the major in Medicine and Physics in Taiwan, Hong-Hsi Lee is working with Dmitry S. Novikov and Els Fieremans as a PhD candidate in the biomedical imaging program at the Sackler Institute of Biomedical Sciences. Hong-Hsi’s recent focus is on the Monte Carlo simulation of the diffusion and water exchange phenomenon between highly aligned, randomly packed, myelinated axons.

Tuesday, May 9th at noon

Gregory Lemberskiy

PhD Candidate
Sackler Institute of Biomedical Sciences
NYU School of Medicine
Time-Dependent Diffusion in the Body

Abstract: Diffusion of water molecules is directly influenced by the mountainous landscape of biological tissue. By modeling time-dependent diffusion, it is possible to reverse engineer various features of this landscape. The proposed model will depend on the underlying tissue microstructure, which poses an additional challenge of model selection. This talk will focus on the efforts of modeling diffusion time-dependence in the prostate, which embodies modeling problems, which concern partial volume and model selection, as well as imaging problems, such as geometric distortion and low SNR.

About the speaker: Greg attended NYU as an undergrad, where he studied Physics. After briefly working in astronomical imaging, he decided to try his hand at medical imaging under the guidance of Dmitry S. Novikov and Els Fieremans. Greg is currently a PhD candidate in the biomedical imaging program at the Sackler Institute of Biomedical Sciences. Most of his work focuses on the development of time-dependent diffusion applications “outside-the-brain.”

Tuesday, April 18th at noon

Giuseppe Carlucci, PhD

Assistant Professor of Radiology
NYU School of Medicine
Novel agents for PET targeted imaging and theranostics

Abstract: PET radiochemistry can be a great resource for imaging, treatment and point-of-care response/monitoring in Cancer and Cardiovascular disease. A novel small molecule targeting the cyclin-dependent kinases CDK4/6 and a series of radiolabeled nanobodies and peptides for atherosclerotic plaques imaging will be presented. The seminar will also focus on the fundamentals of Radiochemistry and how the newly established CAi2R Radiochemistry facility will operate.

About the speaker: Dr. Giuseppe Carlucci is assistant professor of Radiology at NYU School of Medicine. Dr. Carlucci completed his postdoctoral training in radiochemistry at the Memorial Sloan Kettering Cancer Center, and his PhD degree at Rijksuniversiteit - University of Groningen (The Netherlands). Dr. Carlucci research program revolves around the development and validation of novel imaging tracers. This involves small molecule–, peptide-, and nanoparticle-based probes for both optical and PET imaging. His work is focused on the design of companion imaging agents for determining drug susceptibility and target engagement in the preclinical and translational setting.

Friday, April 14th at noon

Nikola Stikov, PhD

Assistant Professor of Biomedical Engineering
Co-director, NeuroPoly, École Polytechnique, University of Montreal
Producer of MRM Highlights and founder of OHBM blog
To microstructural imaging and beyond: separating the signal from the noise

Abstract: Over the past decade, the number of microstructural imaging papers has been doubling every 2.7 years. With such growth, it is becoming increasingly difficult to perform a fair comparison between competing approaches. Some simplify the tissue modelling and overlook physiological constraints. Others overparametrize the models and amplify the noise. The outcome is a field of research with great promise, but few checks and balances.
This lecture will introduce several frameworks for interpreting, validating and communicating microstructural imaging data. Examples will be drawn from myelin imaging in the brain, focusing on the challenges associated with mapping the longitudinal relaxation time (T1), the axon caliber, and the myelin thickness (g-ratio). The last part of the lecture will put these frameworks in a broader science communication context, discussing how medical imaging researchers can set new standards for reviewing, publishing, and publicizing their findings.

About the speaker: Dr. Nikola Stikov is assistant professor of Biomedical Engineering, a researcher at the Montreal Heart Institute, and co-director of NeuroPoly, the Neuroimaging Research Laboratory at École Polytechnique, University of Montreal. His research runs the gamut of quantitative magnetic resonance imaging, from basic issues of standardization and accuracy, to biophysical modelling, microstructural imaging, and clinical applications. Prior to joining the Polytechnique faculty, Dr. Stikov completed his postdoctoral training at the Montreal Neurological Institute, and his B.S., M.S., and PhD degree at Stanford University. In 2014 Dr. Stikov was elected Junior Fellow of the International Society for Magnetic Resonance in Medicine (ISMRM), and in 2015 he joined the Editorial Board of the journal Magnetic Resonance in Medicine (MRM), spearheading the journal's Highlights initiative. Continuing with his science outreach activities, in 2016 Dr. Stikov established the official blog of the Organization for Human Brain Mapping (OHBM).

Monday, April 10 at noon

Guanshu Liu, PhD

Assistant Professor of Radiology
Johns Hopkins University
MRI-guided drug delivery without chemical labeling

Abstract: Recently, Chemical Exchange Saturation Transfer (CEST) has emerged as an attractive MRI contrast mechanism. In CEST, the MRI contrast is generated by transferring the magnetic labeled water-exchanging protons (OH, NH, or NH2) from a CEST agent to its surrounding water molecules. Many natural biological compounds naturally carry exchangeable protons, making them possibly detected by CEST MRI directly in a “label-free” manner. In our studies, we utilized this unique feature to directly detect drugs and drugs carriers, which makes MRI-guided drug delivery possible even without any chemical labeling, a strategy we called “natural labeling”. This new MRI labeling strategy in principle can be tailored to many existing drug delivery systems, and portends a new path to safe, rapid clinical translation of image-guided drug delivery.

Tuesday, April 4th at noon

Harikrishna Rallapalli, BS

Graduate Student
NYU School of Medicine
A High Throughput, MEMRI-Based Imaging Pipeline to Study Mouse Models of Sporadic Human Cancer

Abstract: A high-throughput imaging pipeline is presented to characterize the heterogeneity in longitudinal disease progression in mouse models of human brain cancer and to test the efficacy of novel anti-cancer therapeutics in accurate mouse models of sporadic human cancer.

About the speaker: Hari Rallapalli is a graduate student in the Turnbull lab. He received his BS in Biomedical Engineering from the University of California, Davis.

Tuesday, March 28th at noon

Ines Blockx, PhD

Assistant Research Scientist
Center for Biomedical Imaging
Department of Radiology
NYU Langone Medical Center
In vivo characterization of rat models of Huntington’s disease using Diffusion Imaging

Abstract: Huntington disease (HD) is a dominantly inherited and progressive neurodegenerative disorder, caused by a CAG trinucleotide repeat expansion (≥ 39 repeats) within the HD gene. The median age at which HD occurs, is around 40 years and the disease progresses over time and is invariably fatal 15–20 years after the onset of the first symptoms. The major goals of current HD research are to improve early detection and monitor pathological changes in individuals both at early and advanced stages of the disease. Animal models of inherited neurological diseases provide an opportunity to test potential biomarkers of disease onset and progression and evaluate treatments for translation to clinical care. Using several diffusion MR techniques we studied two different rat models of HD. In this talk I will present data that shows that diffusion MRI is a sensitive and quantitative method to detect HD related neurodegenerative changes, at both microstructural and subcellular levels.

About the speaker: Ines Blockx holds a master in biomedical sciences and graduated at the University of Antwerp, Belgium. After her master degree in 2007, she was rewarded with an IWT (agency for innovation by science and technology) PhD research grant and had the opportunity to start a PhD at the Bio-Imaging lab (University of Antwerp - Belgium) under supervision of Prof. Dr. Annemie Van der Linden for. An important focus of her PhD was the identification of symptom-independent biomarkers of Huntington’s disease neuropathology and progression using in vivo MRI in different rodent models. After receiving her PhD in 2011, she started working as a postdoctoral researcher at the Bio-Imaging lab. During her postdoctoral career, she was the coordinating scientist and key player in an industrial research grant (Janssen Alzheimer Immunotherapy project) where she focussed on the Exploration of multiple MRI modalities to study cerebral vascular dynamics and blood-brain-barrier integrity (BBB) in a mouse model of Alzheimer disease. Currently she is working as an assistant research scientist at the Centre for Biomedical imaging at NYU, where she has the opportunity to expand her research field from preclinical to clinical neuroimaging. Here she is involved in the research of Dr. Mariana Lazar, focussing on MR spectroscopy in Schizophrenia.

Tuesday, March 7th at noon

Richard Spencer, MD, PhD

Chief, Magnetic Resonance Imaging and Spectroscopy Section
NIH/National Institute on Aging
Magnetic Resonance Relaxometry and Macromolecular Mapping: An Inverse Problem Framework

Abstract: There is an ongoing need for non-invasive identification of macromolecular changes in tissue. An important application is to the diagnosis of early osteoarthritis (OA). Our work in this area combines basic science studies in magnetic resonance imaging and relaxometry with emerging methodologies that carry translational potential. We will discuss multi-exponential transverse relaxation analysis as a means to identify underlying macromolecular compartments in normal and degraded cartilage, as well as important extensions of this work, based on higher dimensional relaxometry and compressed sensing. We will describe the mathematical setting for this work as a linear inverse problem. Further work in human subjects requires introduction of a nonlinear model system. We will describe several approaches to these problems and indicate the potential for improved detection of early cartilage degradation. Our methods are also applicable to directly mapping myelin in the brain, and we have obtained results showing myelination pattern alterations with age and in cognitive impairment. All of these studies are centered around the clinical goal of improving the ability of magnetic resonance methods to diagnose pathology and to monitor disease progression.

Tuesday, February 14th at noon

Eric E. Sigmund, PhD

Associate Professor of Radiology
New York University School of Medicine
Simultaneous PET/MRI in Advanced Breast Cancer : Initial Experiences and Future Potential

Abstract: Separately, PET and MRI have longstanding roles in diagnosis, prognosis and monitoring of breast cancer. Since the recent advent of the simultaneous PET/MRI platform, intense research has taken place to identify unrealized applications of their fusion. Initial work around the world has included study of a range of practical advantages (feasibility, efficiency, patient retention, physiologic simultaneity, co-registration), but always with an eye toward future 'breakout' applications beyond those with separate scans. I will describe efforts within our breast cancer research group that pursue both practical and fundamental benefits with the unique capabilities in our research center. Whole body evaluation of metastatic breast cancer patients is nearly equivalently done with PET/MRI as with PET/CT but with half the radiation dose. Dynamic contrast enhanced (DCE) MRI and intra-voxel incoherent motion (IVIM) MRI offer a range of quantitative characterizations of the primary tumor microenvironment (cellularity, vascular volume, vascular permeability).
that when combined with fluorodeoxyglucose (FDG) uptake provide a comprehensive characterization of malignancy in one imaging session. Simultaneity also supports detailed intralesional correlations that may increase classification ability even further. Finally, future planned work with more specific microenvironment tracers and integrated PET and MRI pharmacokinetic modeling holds remarkable potential for oncologic management with noninvasive imaging.

Monday, February 6th at noon

Markus H¨llebrand

Fraunhofer MEVIS
Bremen, Germany
Multi Cycle analysis of cardiac function in real-time

Abstract: Analyzing moving organs such as the heart in MRI is a challenging task. In clinical routine images are acquired over several heartbeats to reconstruct all contraction phases of one representative cardiac cycle using ECG-gating and breath-hold techniques.
Real-time MRI techniques allow the acquisition of serial 2D images with a temporal resolution of up to 20 ms under free breathing. The analysis of real-time MRI sequences, however, requires adapted segmentation techniques as well as an advanced analysis providing information about temporal evolution of parameters during individual heart cycles in amulti cycle analysis workflow.

Wednesday, February 1st at noon

Giulio Ferrazzi, PhD

Research Associate
Biomedical Engineering Department
King’s College London, UK
Imaging the fetus and the neonate using MR
Tuesday, January 24th at noon

Dr. Timothy Shepherd

Assistant Professor, Director of Brain Mapping
Department of Radiology
New York University School of Medicine
Integrated PET-MRI for current clinical neuroradiology dilemmas—a CAI2R perspective
January 23rd at noon

Jeffrey Fessler, PhD

William L. Root Professor of EECS
University of Michigan
Optimal first-order convex minimization methods with applications to image reconstruction and machine learning

Abstract: Many problems in signal and image processing, machine learning, and estimation require optimization of convex cost functions. For convex cost functions with Lipschitz continuous gradients, Nesterov's fast gradient method decreases the cost function at least as fast as the square of the number of iterations, a rate order that is optimal. This talk describes a new first-order optimization method called the optimized gradient method (OGM) that converges twice as fast as Nesterov's famous method yet has a remarkably similar simple implementation. Interestingly, Drori recently showed that OGM has optimal complexity among first-order methods. I will discuss other recent extensions and show examples in machine learning and X-ray computed tomography (CT). Combining OGM with ordered subsets provides particularly fast reconstruction for CT. This work is joint with Donghwan Kim.

About the speaker: Jeff Fessler is the William L. Root Professor of EECS at the University of Michigan. He received the BSEE degree from Purdue University in 1985, the MSEE degree from Stanford University in 1986, and the M.S. degree in Statistics from Stanford University in 1989. From 1985 to 1988 he was a National Science Foundation Graduate Fellow at Stanford, where he earned a Ph.D. in electrical engineering in 1990. He has worked at the University of Michigan since then. From 1991 to 1992 he was a Department of Energy Alexander Hollaender Post-Doctoral Fellow in the Division of Nuclear Medicine. From 1993 to 1995 he was an Assistant Professor in Nuclear Medicine and the Bioengineering Program. He is now a Professor in the Departments of Electrical Engineering and Computer Science, Radiology, and Biomedical Engineering. He became a Fellow of the IEEE in 2006, for contributions to the theory and practice of image reconstruction. He received the Francois Erbsmann award for his IPMI93 presentation, and the Edward Hoffman Medical Imaging Scientist Award in 2013. He has served as an associate editor for IEEE Transactions on Medical Imaging, the IEEE Signal Processing Letters, and the IEEE Transactions on Image Processing, and is currently serving as an associate editor for the IEEE Transactions on Computational Imaging. He has chaired the IEEE T-MI Steering Committee and the ISBI Steering Committee. He was co-chair of the 1997 SPIE conference on Image Reconstruction and Restoration, technical program co-chair of the 2002 IEEE International Symposium on Biomedical Imaging (ISBI), and general chair of ISBI 2007. His research interests are in statistical aspects of imaging problems, and he has supervised doctoral research in PET, SPECT, X-ray CT, MRI, and optical imaging problems.

Tuesday, January 10th at noon

Gadi Wollstein, MD

Professor of Ophthalmology
Director, Ophthalmic Imaging Research Laboratory
Vice Chair for Clinical Research
NYU Langone Medical Center

Joel Schuman, MD

Professor and Chairman of Ophthalmology
Professor of Neuroscience and Physiology
NYU Langone Medical Center
Professor of Electrical and Computer Engineering
NYU Tandon School of Engineering

Hiroshi Ishikawa, MD

Professor of Ophthalmology
Director, Ocular Imaging Center
NYU Langone Medical Center
Part II: In-vivo High Resolution Ocular Imaging - Innovative Technologies and Clinical Challenges

Summary: In recent years ocular imaging has become the cornerstone for clinical diagnosis and disease monitoring as well as a primary research tool in ophthalmology. In this presentation we will discuss state-of-the-art, in-vivo, high resolution ocular imaging technologies. We will present the utility and challenges of the technologies to advance clinical practice and research of glaucoma - a leading cause of blindness and visual morbidity.

Friday, January 6th at noon

Alexander P. Lin, PhD

Director, Center for Clinical Spectroscopy
Department of Radiology, Brigham and Women’s Hospital
Assistant Professor, Harvard Medical School
The Virtual Biopsy: Magnetic Resonance Spectroscopy of Traumatic Brain Injury

Abstract: Advances in neuroimaging provide us with greater insight to brain injury than ever before. Magnetic resonance spectroscopy is a non-invasive method of measuring brain chemistry altered by bran injury using readily available MRI, thus providing a virtual biopsy of concussions. A review of the technology and current findings from the acute to chronic stages of mild brain injury, including the rising concern of chronic traumatic encephalopathy in sports and military-related repetitive brain trauma, will be discussed.

About the speaker: Alexander P. Lin, PhD is an assistant professor at Harvard Medical School and director of the Center for Clinical Spectroscopy at Brigham and Women’s Hospital. Dr. Lin earned his doctorate in Molecular Biochemistry and Biophysics from the California Institute of Technology. He has been involved in magnetic resonance spectroscopy since 1997 both from a research and clinical perspective. His primary research focus is on sports and military-related brain injury which has been featured by the media and funded by that National Institutes of Health and Department of Defense.

Tuesday, December 13th at noon

Gadi Wollstein, MD

Professor of Ophthalmology
Director, Ophthalmic Imaging Research Laboratory
Vice Chair for Clinical Research
NYU Langone Medical Center

Joel Schuman, MD

Professor and Chairman of Ophthalmology
Professor of Neuroscience and Physiology
NYU Langone Medical Center
Professor of Electrical and Computer Engineering
NYU Tandon School of Engineering

Hiroshi Ishikawa, MD

Professor of Ophthalmology
Director, Ocular Imaging Center
NYU Langone Medical Center
Part I: In-vivo High Resolution Ocular Imaging - Innovative Technologies and Clinical Challenges

Summary: In recent years ocular imaging has become the cornerstone for clinical diagnosis and disease monitoring as well as a primary research tool in ophthalmology. In this presentation we will discuss state-of-the-art, in-vivo, high resolution ocular imaging technologies. We will present the utility and challenges of the technologies to advance clinical practice and research of glaucoma - a leading cause of blindness and visual morbidity.

Monday, November 21st at noon

Martin Burger, PhD

Institute for Computational and Applied Mathematics
University of Münster
Variational Methods for Motion-Corrected Image Reconstruction

Abstract: In this talk we discuss the use of advanced physical modeling to build successful image reconstruction approaches for dynamic imaging including motion, noise, and undersampling. The variational approach is based on minimizing energy functionals in a spatio-temporal domain including advanced models of the image formation process, noise, and motion. For the latter hyperelastic or fluid-dynamic constraints are used in order estimate feasible motion vectors jointly with the image sequence. We present the potential use of the methods for dynamic PET and highly undersampled dynamic CT. Finally we comment on extensions to include cross-modality information such as available in PET-MR. We discuss potential issues when using pre-estimated motion vectors from the MR sequence and propose a mathematical model to overcome those.

About the speaker: Martin Burger received a MS (Diplom) in Mathematics (1998) and a Ph.D. in Mathematics (2000) from the Johannes Kepler University Linz. After a period as CAM assistant professor at UCLA he returned to Johannes Kepler University, where he did his habilitation in Mathematics (2005). Briefly afterwards, he was offered a full professor position in applied mathematics at the Westfälische Wilhelms-Universität Münster, where he moved in 2006. Since then he heads the mathematical imaging group and has contributed strongly to building up interdisciplinary research structures related to biomedical imaging. In particular, he serves as PI, executive board member, and research area coordinator for the Cluster of Excellence "Cells in Motion" funded by the German Science Foundation (DFG). He received several awards and recognitions, including the Calderon Prize 2009 by the Inverse Problems International Association, an ERC consolidator grant 2013, and an offer to become director of the Weierstrass Institute for Applied Analysis and Stochastic in Berlin. His research is centered around mathematical imaging and inverse problems, currently with a strong focus on dynamic and high-dimensional image reconstruction.

Friday, November 18th at noon

Thomas Benkert, PhD, (NYU Langone Medical Center) and Bjorn Stemkens (Utrecht University Medical Center)

Advanced methods for motion-robust free-breathing MRI

Abstract: MRI of motion-sensitive applications such as abdominal examinations usually relies on strict breath-holding. However, breath-holding can fail especially for sick, elderly, or pediatric patients, which can render image quality non-diagnostic. Furthermore, sudden motion events such as global body shifts, bulk motion, or coughing may induce further artifacts.
This talk presents methods which solve these problems and enable motion-robust free-breathing MR acquisitions. First, recent advances for comprehensive one-stop shop free-breathing imaging are presented by Thomas Benkert. Second, a technique to automatically detect and exclude bulk motion is described by Bjorn Stemkens. In summary, the presented techniques have the potential to increase patient comfort, improve clinical workflow, and eliminate the risk for failed exams caused by imperfect breath-holding or sudden patient movements.

About the speakers: Dr. Thomas Benkert obtained his PhD in Physics at the University of Wuerzburg, where he worked on novel steady-state techniques for fast MRI under the supervision of Dr. Felix Breuer. In August 2015, he joined CBI as a postdoctoral researcher in the team of Dr. Tobias Block, where he is developing methods for comprehensive free-breathing imaging.
Bjorn Stemkens is a PhD candidate at the department of Radiotherapy at the University Medical Center in Utrecht where he is working on the implementation of novel MRI applications for MRI-guided radiotherapy, with a focus on abdominal treatments. In July he started a 4-month internship at CBI in the team of Dr. Tobias Block to develop a technique to detect bulk motion for robust free-breathing abdominal imaging.

Tuesday, November 15th at noon

Bruce Berkowitz, PhD

Professor, Department of Ophthalmology
Director, Small-Animal MRI Facility
Wayne State University School of Medicine
Oxidative Stress and its Functional Consequences Measured In Vivo by MRI

Abstract: In 1992, it was not obvious that MRI, a relatively insensitive and still developing imaging method, would be useful for examining the retina, one of the thinnest organs in the body. Since then, Dr. Berkowitz has established a body of work that highlights MRI as a surprisingly useful discovery tool in vision research. These methods have been successful transitioned into cancer and brain research areas, and are used by drug companies and other investigators world-wide. Improvements in resolution and methodology have even allowed us to measure the physiology of sub-compartments within rod cells in vivo. These data are spatially grounded based on optical coherence tomography images and compared to visual performance using optokinetic tracking. His current pioneering efforts uses MRI to measure neuronal oxidative stress without a contrast agent in untreatable neurodegenerative disease, including Alzheimer’s disease, to optimize antioxidant treatment in vivo.

Tuesday, November 8th at noon

Haris Sair, MD

Assistant professor of Radiology
Johns Hopkins University School of Medicine
Presurgical brain mapping using resting state fMRI – promises and challenges

Abstract: Assessment of intrinsic brain networks using resting state functional MRI (rs-fMRI) has resulted in a paradigm shift in evaluating brain function. Changes in functional connectivity have been described in numerous disorders, and normal intrinsic brain networks characterized in thousands of subjects. Several studies have examined the use of rs-fMRI in presurgical brain mapping. Following an overview of rs-fMRI basics, the benefits of rs-fMRI over task-fMRI in presurgical brain mapping will be discussed. Challenges in characterizing rs-fMRI at the single subject level for presurgical brain mapping will be reviewed.

About the speaker: Haris Sair MD is Assistant Professor of Radiology in the Department of Radiology at Johns Hopkins University School of Medicine. He completed a 2 year fellowship in Neuroradiology at the Massachusetts General Hospital, where he developed an interest in clinical functional MRI. His primary research interest is in application of resting state fMRI at the single subject level for clinical use, concentrating on presurgical brain mapping, but also including development of rs-fMRI based prediction models in disease and outcome.

Tuesday, October 25th at noon

Christoph Juchem, PhD

Departments of Biomedical Engineering and Radiology
Columbia University in the City of New York
Magnetic Resonance Engineering – from Bench to Bedside

Abstract: My laboratory pursues technology and method developments in the fields of magnetic resonance imaging (MRI) and spectroscopy (MRS) to advance their clinical potential for the study of multiple sclerosis (MS) and other neurological disorders. MRI and MRS allow the non-invasive measurement of brain anatomy and physiology, but excellent B0 magnetic field homogeneity is required for meaningful results. In the first part of my talk, I will present a technique for magnetic field modeling and correction, i.e. shimming, that is based on the combination of fields generated by an ensemble of individual, generic coils. This multi-coil approach enables the accurate generation of simple and complex magnetic field shapes in a flexible fashion. B0 shimming with the dynamic multi-coil technique (DYNAMITE) is shown to outperform conventional methods based on spherical harmonic (SH) functions and provides unrivaled magnetic field homogeneity in mouse, rat and human brain.
MS is a chronic disorder of the central nervous system that leads to demyelination and neurodegeneration. Its underlying pathobiochemical mechanisms, however, remain poorly understood. MRS promises non-invasive access to the brain's biochemistry in vivo, but suffers from methodological limitations and experimental imperfections. The goal of our work is to establish MRS as a clinical research tool towards in vivo metabolomics of the pathogenesis of MS through a combination of ultra-high 7 Tesla field, state-of-the-art B0/B1 shimming and optimized MRS methods. The second part of my talk will focus on the specific MRS infrastructure and implementations that enables us to assess pathological changes from the earliest stage of the disease.

Tuesday, October 18th at noon

Jullie Pan, MD, PhD

Professor of Neurology
University of Pittsburgh School of Medicine
7T and 3T Imaging in Epilepsy

Abstract: This talk will focus on Dr. Pan's work in the development and application of high field imaging approaches to better understand the metabolic and functional pathophysiology of epilepsy. These methods include high degree B0 shimming, high resolution MRSI and in vivo detection of amino acids and will discuss some of her results from 7T and 3T.

Tuesday, October 4th at noon

Ivan Kirov, PhD

Assistant Professor of Radiology
Center for Biomedical Imagign
Department of
Proton MR spectroscopy of lesion evolution in Multiple Sclerosis: steady-state metabolism and its relationship to conventional imaging

Abstract: Although MRI assessment of white matter lesions is essential for the clinical management of multiple sclerosis, the processes leading to the formation of lesions and underlying their subsequent MRI appearance are incompletely understood. We used proton MR spectroscopy to study the evolution of N-acetyl-aspartate (NAA), creatine (Cr), choline (Cho) and myo-inositol (mI) in pre-lesional tissue, persistent and transient new lesions, as well as in chronic lesions, and related the results to quantitative MRI measures of T1-hypointensity and T2-volume. Within 10 patients with relapsing-remitting course, there were 180 regions-of-interest consisting of up to seven semi-annual follow-ups of normal-appearing white matter (NAWM, n=10), pre-lesional tissue giving rise to acute lesions which resolved (n=3) or persisted (n=3), and of moderately (n=9) and severely hypointense (n=6) chronic lesions. Compared to NAWM, pre-lesional tissue had higher Cr and Cho, while compared to lesions, pre-lesional tissue had higher NAA. Resolving acute lesions showed similar NAA levels pre- and post-formation, suggesting no long-term axonal damage. In chronic lesions, there was an increase in mI, suggesting accumulating astrogliosis. Lesion volume was a better predictor of axonal health than T1-hypointensity, with lesions larger than 1.5 cm3 uniformly exhibiting very low (<4.5 millimolar) NAA concentrations. A positive correlation between longitudinal changes in Cho and in lesion volume in moderately hypointense lesions implied that lesion size is mediated by chronic inflammation. These and other results are integrated in a discussion on the steady state metabolism of lesion evolution in Multiple Sclerosis, viewed in the context of conventional MRI measures.

About the speaker: Ivan Kirov received his Bachelor of Science in Biology from University of California, Irvine. After graduation, he worked for 2 years as a molecular biologist on retinal stem cells. In 2004 he entered the Ph.D. program at the Sackler Institute at NYU, graduating in 2009 from the program in Physiology and Neuroscience. He then completed a post-doctoral fellowship under Oded Gonen, training on applications of proton MR spectroscopy. Ivan has been an independent investigator since 2014 as an Assistant Professor with research interests mainly in Traumatic Brain Injury and Multiple Sclerosis.

Tuesday, September 20th at noon

Teodora Chitiboi, PhD

Postodctoral Associate
Center for Biomedical Imaging
Department of Radiology
NYU School of Medicine
Myocardium Segmentation and Motion Analysis from Time-varying Cardiac Magnetic Resonance Imaging

Abstract: Magnetic Resonance Imaging (MRI) is a reference method for noninvasive examination of the global and local cardiac function. Using the latest real-time MRI sequences, cardiac function can be monitored over multiple consecutive heart beats, enabling the study of cardiac cycle variability, for example, in patients with arrhythmia. An essential precondition for the analysis of cardiac functional is the segmentation of the heart muscle (myocardium). To address this task, a hierarchical object-based segmentation approach was devised, which combines bottom-up region grouping with a top-down optimization strategy. This principle takes steps towards bridging the semantic gap between low-level image features and high-level, complex and heterogeneous structures. This algorithm is part of a comprehensive pipeline for automatic segmentation of the myocardium from short-axis MRI. Furthermore, tissue phase mapping (TPM) offers the means to inspect local cardiac motion by acquiring the velocity of individual myocardium voxels. This talk presents a semi-automatic probabilistic segmentation approach for TPM that combines contour displacement with particle tracing for estimating the uncertainty of the segmentation result. An automatic quantification method was additionally developed to compute global myocardial torsion.

About the speaker: Teodora Chitiboi received her PhD in Computer Science from Jacobs University Bremen, after having received a Bachelor and Master in Computer Science. Teodora was a researcher at Fraunhofer MEVIS in Bremen where she contributed to the development of an object-based image analysis (OBIA) library and was part of the group for Cardiovascular Research and Development. Her research interests are medical image analysis, visualization and image segmentation.


Taehoon Shin, PhD

Assistant Professor
Department of Diagnostic Radiology and Nuclear Medicine
University of Maryland, Baltimore
Advanced Magnetic Resonance Imaging Methods for Cardiovascular Applications

Abstract: This talk presents advanced MRI methods for two cardiovascular applications: non-contrast-enhanced (NCE) angiography and cardiac late gadolinium enhanced (LGE) imaging. First I will present new NCE MRA methods using Fourier based velocity-selective (VS) magnetization preparation which can generate positive vessel contrast in single acquisition with high spatial resolution in all three dimensions. The principle of VS excitation is explained under excitation k-space formalism, followed by a few designs with improved B0 and B1 immunity, and applications for various vascular territories. Second, I will present 3D LGE MRI methods based on stack-of-spirals acquisitions. Two strategies will be shown, including single breath-hold whole-heart LGE using parallel imaging acceleration, and free-breathing near-isotropic resolution LGE using outer-volume-suppressed projection-based navigator.

July 25th at noon

Pål Erik Goa, PhD

Associate Professor
Department of Physics
Norwegian University of Science and Technology
Diffusion Weighted MRI in Breast Cancer and the link to Tissue Microstructure

Abstract: Diffusion-weighted MRI (DWI) has become a standard component in most clinical breast MRI protocols. The main reason for this is the reduced apparent diffusion coefficient (ADC) observed in cancer tissue compared to healthy fibroglandular tissue and benign lesions. This effect is loosely attributed to increased cellularity and reduced extracellular volume in cancer tissue. Other flavours of DWI, like diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM) and most recently stimulated echo diffusion imaging (STE-DWI), have also been applied in breast cancer MRI. Each of these methods show some interesting results, including differences between malignant and benign tissues.
Since DWI draws its contrast from the microscopic structural features of the tissue, the link between DWI and specific microstructural parameters has always been a topic of interest. However, due to the non-unique mapping from DWI-signal to microstructure, this has proven very difficult in practice. As an example, only weak correlation between cellularity and ADC has been shown in breast cancer. A biophysical interpretation of the DWI signal is therefore often avoided, and the results from DWI are analysed with respect to its link with other parameters, like malignancy/grade or molecular subtype.
In this presentation we will discuss this issue in some detail, looking at the structure of healthy and malignant tissues together with results from the various methods in DWI.

About the speaker: Pål Erik Goa obtained his PhD in Physics at the University of Oslo, Norway, in 2002, after building the first microscope capable to capturing the live motion of quantized magnetic flux-lines in a superconductor. After working on remote sensing applications for the Norwegian Defence Research Establishment for a couple of years, he and his family moved to Trondheim in 2005, and he started on a new career in the field of medical imaging. In the period 2006-2013 he worked as MR-physicist at the Department of Radiology and Nuclear Medicine, St.Olavs Hospital, and in 2013 he took up the position as Associate Professor in Medical Physics at NTNU. Goa has been involved in a wide variety or research projects in MRI, both clinical and pre-clinical, ranging from retro-gated cardiac MRI in mice to the development of new sequences for BOLD-fMRI at 7 T. His current research interest is focused on the application of different methods of Diffusion-Weighted MRi in Cancer Management.

Tuesday, June 14th at noon

Alexandra Badea, PhD

Assistant Professor of Radiology
Center for In Vivo Microscopy
Duke Medical Center, Durham, NC
Learning from Small Animal Models of Neurological Conditions – An MR-Based Phenotyping Approach

Abstract: The rich contrast and flexibility of MR offers the possibility of quantifying multiple image based biomarkers in small animal models of neurological and psychiatric conditions. This talk focuses on a mouse model of Alzheimer’s disease (AD). Mouse models provide opportunities to study characteristics of AD in well-controlled environments and can facilitate early interventions. Multivariate biomarkers are needed for detecting AD, helping to understand its etiology, and quantifying the effect of therapies. The CVN-AD mouse model replicates multiple AD hallmark pathologies, and we identified multivariate biomarkers characterizing a brain circuit disruption predictive of cognitive decline. We used manganese-enhanced MRI to locate areas of differential uptake of manganese in CVN mice relative to age matched controls, and in association with learning and memory deficits. In vivo and ex vivo MRI revealed that CVN-AD mice replicate the hippocampal atrophy (6%), characteristic of humans with AD, and also present changes in subcortical areas. The largest effect was in the fornix (23% smaller), which connects the septum, hippocampus, and hypothalamus. In characterizing the fornix with diffusion tensor imaging, fractional anisotropy was most sensitive (20% reduction), followed by radial (15%), and axial diffusivity (2%) in detecting pathological changes. These findings were strengthened by optical microscopy and ultrastructural analyses. CD68 staining showed that white matter pathology could be secondary to neuronal degeneration or due to direct microglial attack. In conclusion, these findings strengthen the hypothesis that the fornix plays a role in AD, and can be used as a disease biomarker and as a target for therapy.

About the speaker: Dr. Badea is an Assistant Professor in the Department of Radiology at Duke, and a member of the Center for In Vivo Microscopy, where she co-directs the Visual Informatics Core, while maintaining her focus on models of neurodegenerative conditions. She was born in Romania, where she studied Physics for her BSc. She graduated with a PhD in Biomedical Engineering from the University of Patras, Greece, where she has learned to love working with images, and in particular brain images. Her interest in computational imaging has led to the development of image processing pipelines for structural and diffusion imaging. She uses such pipelines with the aim to understand the lessons that small mouse models can teach us about human neurological and psychiatric conditions.

May 31st at noon

Kerstin Hammernik

Doctoral Candidate
Research Assistant
Graz University of Technology
Insights into deep learning for MRI reconstruction

Abstract: Compressed sensing techniques allow MRI reconstruction from under sampled k-space data. However, most reconstruction methods suffer from high computational costs and are limited to low acceleration factors for non-dynamic 2D imaging protocols. Furthermore, existing image reconstruction methods are based on simple regularizers such as sparsity in the wavelet domain or Total Variation (TV). However, these simple and handcrafted regularizers make assumptions on the underlying image statistics and the reconstructed images appear unnatural. In this work, we propose a novel and efficient approach to overcome these limitations by learning a sequence of optimal regularizers that removes typical undersampling artifacts while keeping important details in the imaged objects and preserving the natural appearance of anatomical structures. We test our approach on patient data and show that we achieve superior results in terms of both runtime and image quality compared to commonly used reconstruction methods.

About the speaker: Kerstin Hammernik received a BSc and MSc in Biomedical Engineering from Graz University of Technology in 2011 and 2015, respectively. Currently,she is a research assistant and PhD student supervised by Dr. Thomas Pock at the Institute of Computer Graphics and Vision, Graz University of Technology. Her current research interests include optimization and learning of variational models with application to medical inverse problems such as magnetic resonance (MR) and photo acoustic image reconstruction.

Special Seminar: May 27th at noon

William Grissom, PhD

Assistant Professor of Biomedical Engineering
Vanderbilt University Institute of Imaging Science (VUIIS)
Nashville, TN
Array-Compressed Parallel Transmit MRI

Abstract: Many-coil transmit arrays are desirable in parallel transmission (pTx), since with many coils multidimensional pulses can be shortened, more uniform radiofrequency shims can be produced, and specific absorption rate can be more effectively controlled. However, the high cost and the large physical footprint and cabling requirements of the corresponding power amplifiers required to drive many-coil arrays has limited the number of transmit coils/channels that are used in practice, and most ultra-high field MR scanners in use today have only eight transmit channels. Inspired by recent work in MRI receive array compression, we proposed array-compressed pTx (acpTx) to overcome these limitations. In acpTx, a large number of coils is connected to a small number of channels via a virtual or physical array compression network that splits the input pulse waveforms to the coils and applies attenuations and phase shifts that are optimized jointly with the pulse waveforms. In this way, the excitation spin physics directly informs the construction of the compressed transmit coil array. This talk will describe how pulses can be designed for acpTx and how it can be implemented in hardware. We will also talk about its potential embodiments and impact on ultra-high field MRI, including how it might be used to improve transmit coil design.

Special Seminar: May 26th at noon

Ernest Feleppa, PhD, Research Director
Jeffrey Ketterling, PhD, Associate Research Director
Jonathan Mamou, PhD, Research Manager
Daniel Rohrbach, PhD, Member of the Research Staff

Biomedical Engineering at Riverside Research

Abstract: Riverside Research has been engaged in biomedical research since it was the Electronics Research Laboratory of Columbia University in the 1950s. Over the past several decades, the Biomedical Engineering Laboratory at Riverside Research has become internationally recognized as a leader in advanced biomedical ultrasound. The history, capabilities, and interests of the Laboratory will be summarized.

High-frequency ultrasound annular-array probes operating at frequencies higher than 15 MHz provide resolution superior to linear arrays operating at the same frequencies. We have developed custom imaging systems based on five-ring, 20-MHz and 40-MHz annular arrays, and have shown that the devices permit a significant improvement in image quality over current technology for small-animal- and ophthalmic-ultrasound imaging. An overview of the systems and examples of in vivo human and in utero mouse-embryo scans will be shown. Extensions of the work to photoacoustic imaging of mouse embryos as well as applications such as characterization of the human vitreous and analysis of brain development in mouse embryos will be discussed.

Quantitative ultrasound (QUS) methods permit characterizing tissue microstructure at a sub-resolution level. Our group is considered to be a pioneer in using these methods for tissue characterization. As an example, a high-frequency ultrasound study focusing on 3D imaging and characterization of lymph nodes freshly-excised from cancer patients will be presented. QUS images were formed and used to detect metastases using a transducer that has a 26-MHz center frequency. Classification results suggest that these QUS methods may provide a clinically-important means of identifying small metastatic foci that might not be detected using standard pathology procedures.

Scanning acoustic microscopy (SAM) is a well-established method for fine-resolution material characterization in particular for non-destructive testing. However, accurate estimation of the mechanical properties for soft-tissue applications is still challenging. We developed a novel quantitative acoustic microscope (QAM) operating at 250-MHz and 500-MHz center frequencies that allows characterizing soft-tissue material properties (i.e. mass density and bulk modulus) at resolutions down to four micrometers. The presentation will provide an overview of the device and its working principle. We will present current research results obtained for ophthalmologic tissues and human lymph nodes, and will discuss the potential applications for the measured material properties.

May 3rd at noon.

Frederic Noo, PhD

Professor of Radiology and Imaging Sciences
The University of Utah
Salt Lake City, Utah
Early assessment of image quality in X-ray computed tomography using model-based iterative reconstruction

Abstract: Radiation dose associated with CT scans has become an important concern in medical imaging. Fortunately, there are many pathways to reducing dose, one of which amounts to using a model-based iterative reconstruction method. A major strength of this approach is its flexibility: there are many ways to design such a reconstruction, allowing adaptation to both anatomy and diseases. This strength however comes with major challenges in terms of gain assessment. Early assessment of image quality, before clinical deployment, is critical to identify and refine solutions. Moreover, given the non-linear nature of model-based iterative reconstruction methods, task-based assessment must be embraced, which further complicates the problem. Currently, there are few publications reporting on early, task-based assessment of image quality achieved with iterative reconstruction methods. This talk will present results in this direction using LROC analysis with computer-simulated data read by human observers. At the same time, it will be demonstrated that the grayscale used for image display is a critical factor in such image quality comparison studies.

About the speaker: Frederic Noo is a Professor of Radiology and Imaging Sciences at The University of Utah. His education took place in Belgium, where he completed a Ph.D. degree in Engineering Sciences in 1998, with emphasis on image reconstruction problems in cone-beam tomography. The National Science Foundation in Belgium supported his research from 1993 until 2001, first as a Ph.D. student, then as a post-doctoral research. In 2001, he decided to move to The University of Utah, where he had built strong collaboration ties. Since then, he has expanded his range of expertise to encompass all aspects of X-ray computed tomography, including image reconstruction algorithms, scanner design, simulation models and Monte-Carlo transport of photons, noise and dose evaluations, and task-based assessment of image quality using both model and human observers. His publications include 65 peer-reviewed articles, 112 conference proceedings, and 9 patents. His CT expertise is recognized in the industry as well as in the academia. He launched a highly successful biennial stand-alone conference in 2010, called "The International Conference on Image Formation in X-ray Computed Tomography". This effort was offered as a community service to address a growing need for CT scientists. His work has been continuously supported by the NIH and by corporate funds since 2001. He has supervised a number of Ph.D. students and post-doctoral researchers, who have become prolific scientists with Siemens, GE, Philips, and the FDA. A number of his image reconstruction methods are or have been used by vendors; and the FDA supports his methods for image quality assessment.

April 26th at noon.

Nicole Wake

Graduate Student
Biomedical Imaging Program
Sackler Institute, Radiology Department
NYU School of Medicine
3D Printing: Applications in Urologic Oncology

Abstract: Three-dimensional (3D) printing in radiology represents the fabrication of physical objects from imaging data, with the intent of impacting patient care. 3D printing of anatomical data allows radiologists, surgeons, and other physicians to physically hold in their hands patient-specific models and use visuo-haptic inputs to better understand both complex anatomy and the condition being treated. In this talk, I will describe the steps required to derive anatomically accurate, patient-specific models in the context of urological oncology. In particular, the application of 3D printing in the pre-operative evaluation of prostate and kidney cancer will be demonstrated.

About the speaker: Nicole Wake received her Bachelors in Biology and History from the University of Pennsylvania and her Masters in Science from the Mount Sinai School of Medicine. She has extensive experience working as a research assistant in a cardiovascular CT and MR imaging lab at Brigham and Women's Hospital, Boston, MA. Nicole is currently a PhD Candidate at NYU School of Medicine, where she works under the direction of Hersh Chandarana and Daniel K. Sodickson on applications of 3D printing in urologic oncology.

April 19th at noon.

Dan Wu, PhD

Research Associate
Department of Radiology
Johns Hopkins University School of Medicine
Road onto Microstructural Imaging: Diffusion MRI at high-resolution and varying time scales

Abstract: Diffusion MRI is a powerful tool for noninvasive mapping of the microstructural organization in the brain. One part of my work focuses on developing high-resolution in vivo imaging techniques to resolve structures and connections in the live mouse brain. With a localized high-resolution imaging technique, we achieved in-utero diffusion MRI of the embryonic mouse brain. I also worked on probing brain microstructural features using oscillating gradient diffusion MRI (OGSE). In a neonatal mouse model of hypoxia-ischemia, OGSE diffusion MRI showed drastic change of contrast in the edema tissue and enhanced sensitivity in mild edema region compared to conventional pulsed gradient diffusion MRI. We have explored the diffusion-time dependence of kurtosis property of water diffusion and the time dependence of intra-voxel incoherent motion at varying oscillating frequencies. These work may lead to better understanding of the relation between diffusion MRI signals and the underlying tissue microstructural properties.

About the speaker: Dr. Wu obtained Masters and PhD degrees from Johns Hopkins University, Department of Biomedical Engineering, where she conducted the thesis study mainly on diffusion MRI. Currently, she is a Research Associate in the Department of Radiology at Hopkins, starting her independent research in the technical development and biomedical applications of advanced diffusion MRI techniques.

Special Seminar: April 8th at 2:00 p.m.

Choong Heon Lee, PhD

Postdoctoral Researcher
Rush University
Chicago, IL
Magnetic Resonance Microscopy from Tissues to Potential Clinical Applications

Abstract: MR microscopy has developed over the last 25 years as a complementary microimaging technique. Although it offers the potential to study tissues in vivo, the inherently low sensitivity of NMR has limited MR microscopy to the study of relatively large cells, i.e. frog ova (~1mm in diameter) and Aplysia neurons (~ 300-350 μm in diameter). Recently, using new surface microcoils and high field magnets to improve sensitivity, we performed the first MR microscopy of neurons in mammalian tissue, and potential identification of mammalian nuclei in the tissue. These findings have the potential to change the way we interpret clinical MR images by revealing unique signal and contrast characteristics of the microstructural elements that comprise tissues: perikarya, nuclei, neurites, vasculature etc. Developing a better understanding of subcellular elements and how their MR characteristics change under the influences of pathology will lead to advances in tissue modeling and provide diagnostic criteria for earlier and more accurate disease detection. Such improvements are critically needed in the case of neuropathologies which often present with abnormalities at the cellular level many years prior to the development of symptoms which spur patients to seek treatment. In this work, we offer an overview of the progress made in MR microscopy of neural tissues and non-neural tissue applications, and potentials of offering a better references to clinical treatment.

April 5th at noon

Assaf A. Gilad, PhD

Associate Professor
Russell H. Morgan Department of Radiology and Radiological Science
Division of MR Research and the Institute for Cell Engineering
Johns Hopkins University
Developing MRI reporter genes for optimal drug, virotherapy, and stem cell delivery

Abstract: The tremendous developments in the field of (bio) medical imaging that have revolutionized modern medicine have opened a new niche for technologies that enable the collection of information above and beyond anatomical, metabolic, and functional information. Our lab has been focusing on the development of one such technology, which is based on genetically encoded systems that can generate MRI contrast from specific cellular and molecular events. These are genes–synthetic, semi–synthetic, and adopted from other organisms that we introduced into the cell's genome. These genes, once expressed, can be used for numerous applications. Here, we will demonstrate how such genes can be used to monitor:

  • Cell-specific expression
  • Drug delivery
  • Oncolytic viral therapy in cancer
  • Cancer immunotherapy
  • Tracking transplanted stem cells in the heart.
While most of the studies were performed in live rodents, we have recently demonstrated the feasibility of these technologies in pigs, using clinical MRI scanners. Our research is a part of an on-going effort to expand the toolkit of MRI technologies for more comprehensive diagnostics.

Special Seminar: March 30th at noon

Wyger Brink

Department of Radiology
Leiden University Medical Center
The Netherlands
Dielectric Shimming – Exploiting Dielectric Interactions in High Field MR

Abstract: One of the main challenges in MR operation at high fields is to acquire images when the dimensions of the body section being imaged are comparable to the RF wavelength. The resulting RF interferences within the body can severely reduce diagnostic image quality. However, the underlying electromagnetic interactions also raise the question of whether these mechanisms may be exploited to improve performance. This approach, termed "Dielectric Shimming," is a very simple method which allows for adjusting the radiofrequency (RF) fields in high field MR. Previous work has shown that this can improve MR operation in various body applications at 3T as well as neuro applications at 7T. Currently, numerical methods are being developed to harness and exploit this approach.

Special Seminar: March 25th at noon

Luis J. Garay

Associate Professor
Universidad Complutense de Madrid
Pieces of time

Abstract: In this overview presentation I will describe from a personal—and necessarily biased—point of view a few aspects of TIME which I have dealt with during my research and teaching on gravity and quantum theory. They encompass various contexts: from Newtonian mechanics and general relativity to quantum gravity and the microscopic structure of spacetime.

About the speaker: Luis J Gray is a Associate Professor at the Universidad Complutense de Madrid. His area of research is classical and quantum gravity. In particular he has worked on black holes, quantum fields in curved backgrounds, Hawking radiation, Analog models of gravity, emergent gravity, acoustic black holes in Bose-Einstein condensates, Quantum gravity and cosmology, Relativistic Quantum Information.

Special Seminar: March 23rd at 2:00 p.m.

Marcelo Victor Wüst Zibetti, Dr. Eng.

Associate Professor
Graduate Program in Electrical and Computer Engineering
Federal University of Technology - Paraná (UTFPR), Brazil
Visiting Scholar
Computer Science
Graduate Center, City University of New York (CUNY)
Improving compressed sensing in MRI with separate magnitude and phase priors

Abstract: Compressive sampling/compressed sensing (CS) has shown that it is possible to perfectly reconstruct non-bandlimited signals sampled well below the Nyquist rate. Magnetic Resonance Imaging (MRI) is one of the applications that has benefited from this theory. Sparsifying operators that are effective for real-valued images, such as finite difference and wavelet transform, also work well for complex-valued MRI when phase variations are small. As phase variations increase, even if the phase is smooth, the sparsifying ability of these operators for complex-valued images is reduced. If the phase is known, it is possible to remove it from the complex-valued image before applying the sparsifying operator. Another alternative is to use the sparsifying operator on the magnitude of the image, and use a different operator for the phase, i.e., one related to a smoothness enforcing prior. The proposed method separates the priors for the magnitude and for the phase, in order to improve the applicability of CS to MRI. An improved version of previous approaches, by ourselves and other authors, is proposed to reduce computational cost and enhance the quality of the reconstructed complex-valued MR images with smooth phase. The proposed method utilizes L1 penalty for the transformed magnitude, and a modified L2 penalty for phase, together with a non-linear conjugated gradient optimization. Also, this paper provides an extensive set of experiments to understand the behavior of previous methods and the new approach.

March 22nd at noon

Gang Chen

Graduate Student
Biomedical Imaging Program
Sackler Institute, Radiology Department
NYU School of Medicine
Approaching the Ultimate Intrinsic SNR with dense arrays of electric dipole antennas

Abstract: Radiofrequency(RF) Coil designs motivated by the ideal current patterns corresponding to the Ultimate Intrinsic SNR (UISNR) have been used to boost central SNR at 3T and 7T for MR imaging. For a cylindrical phantom and a current distribution defined on a concentric cylindrical surface, the ideal current pattern for optimal central SNR includes both divergence-free and curl-free components. At low field, divergence-free current patterns saturate the UISNR and arrays with an increasing number of loops can approach the UISNR. While loops are exclusively divergence-free, recent work has shown that electric dipole antennas include both divergence-free and curl-free current components. To shorten a dipole compared to its self-resonant l/2 length it is necessary to incorporate inductors, which are lossy. In this talk I will present that arrays with an increasing number of electric dipole antennas can approach UISNR for all currents in the center of a head-sized phantom at 7T despite these losses.

Special Seminar: March 16th at 2:00 p.m.

Pep Pàmies, PhD

Chief Editor
Nature Biomedical Engineering
Help shape Nature Biomedical Engineering

Abstract: Launching in January 2017, Nature Biomedical Engineering will publish original research, reviews and commentary of high significance to the biomedical engineering community, including bench scientists interested in devising materials, methods, technologies or therapies to understand or combat disease; engineers designing or optimizing medical devices and procedures; and clinicians leveraging research outputs in biomedical engineering to assess patient health or deliver therapy across a variety of clinical settings and healthcare contexts. In this discussion, the Chief Editor will welcome suggestions about what the journal could do for your field and for the broader biomedical engineering community.

About the speaker: Pep is leading the editorial team of Nature Biomedical Engineering. He has been an editor for Nature Materials for more than 5 years, where he championed the biomaterials content, handling manuscripts and commissioning articles in a wide variety of subjects, including tissue engineering, medical imaging, regenerative medicine, cancer therapy and diagnostics. Previously, Pep conducted research in computational soft matter and biophysics at Columbia University's Chemistry Department in New York City, at the Max Planck Institute of Colloids and Interfaces in Potsdam, and at the Atomic and Molecular Physics Institute in Amsterdam. Pep obtained a PhD in Chemical Engineering in December 2003 from Rovira i Virgili University in Catalonia, Spain.

March 15th at noon

Alberto Pepe

Research Associate
Harvard University
Data-driven, Interactive Scientific Articles in a Collaborative Environment with Authorea

Abstract: Most tools that scientists use for the preparation of scholarly manuscripts, such as Microsoft Word and LaTeX, function offline and do not account for the born-digital nature of research objects. Also, most authoring tools in use today are not designed for collaboration and as scientific collaborations grow in size, research transparency and the attribution of scholarly credit are at stake. In this talk, I will show how Authorea allows scientists to collaboratively write rich data-driven manuscripts on the web–articles that would natively offer readers a dynamic, interactive experience with an article’s full text, images, data, and code–paving the road to increased data sharing, data reuse, research reproducibility, and Open Science.

About the speaker: Alberto Pepe is the co-founder of Authorea. He recently finished a Postdoctorate in Astrophysics at Harvard University. During his postdoctorate, Alberto was also a fellow of the Berkman Center for Internet and Society and the Institute for Quantitative Social Science. Alberto is the author of 30 publications in the fields of Information Science, Data Science, Computational Social Science, and Astrophysics. He obtained his Ph.D. in Information Science from the University of California, Los Angeles with a dissertation on scientific collaboration networks which was awarded with the Best Dissertation Award by the American Society for Information Science and Technology (ASIS&T). Prior to starting his Ph.D., Alberto worked in the Information Technology Department of CERN, in Geneva, Switzerland, where he worked on data repository software and also promoted Open Access among particle physicists. Alberto holds a M.Sc. in Computer Science and a B.Sc. In Astrophysics, both from University College London, U.K. Alberto was born and raised in the wine-making town of Manduria, in Puglia, Southern Italy.

February 23th at noon

Gillian Haemer

Graduate Student
Biomedical Imaging Program
Sackler Institute, Radiology Department
NYU School of Medicine
Incorporation of high permittivity materials into RF transmit coil design

Abstract: High permittivity, low conductivity materials (HPMs) placed between RF coils and a subject can be used to passively vary the spatial distribution of electric and magnetic fields, independent of or in combination with RF shimming or parallel transmission. This field redistribution has the potential to improve both receive sensitivity and transmit efficiency, and therefore HPMs have the potential to greatly benefit transmit-receive coil array design. In this talk I will present a method for determining the optimal relative permittivity and placement of HPMs close to a transmit array, and the practical restrictions that come along with placing materials with very high permittivities close to resonant loops.

About the speaker: Gillian Haemer received here Bachelors in Biomedical (Electrical) Engineering from the University of Southern California. During her time in Los Angeles she discovered medical imaging research working as a research assistant on CTA/SPECT data registration at Cedars Sinai Medical Center. She then completed her Masters at the joint program in Biomedical Engineering and Medical Imaging at the University of Tennessee and the University of Memphis, with the design and development of a prototype variable-resolution x-ray breast CT scanner. She is currently a PhD student at the NYU School of Medicine, where she works under the direction of Daniel K Sodickson and Graham C Wiggins on MRI hardware engineering challenges at ultra high field strengths.

Special Seminar: February 19th at noon

Marios Georgiadis, PhD

Postdoctoral Fellow
ETH Zurich
X-ray scattering for microstructural anisotropy of tissues—the examples of bone and brain

Abstract: Small-angle X–ray scattering (SAXS) occurs when part of the X–ray beam that probes a sample is scattered at small angles, due to differences in electron density distributions within the sample. Moreover, it gives a particularly strong signal in the presence of ordered and periodic systems, that act like slits. Recently, we developed two techniques based on SAXS that can reconstruct the 3D organization of tissue microstructure. In the first technique, called 3D scanning SAXS, local 3D tissue anisotropy is derived by scanning thin sections at different rotation angles. In the second technique, called small–angle scattering tensor tomography, a non–destructive method to reconstruct local anisotropy is introduced by the use of a second sample rotation axis and an iterative reconstruction algorithm based on spherical harmonics. Small-angle scattering tensor tomography extends the concept of traditional tomography: it reconstructs not only scalar values, but multiple parameters per voxel, providing a 3D representation of local material anisotropy. These methods were demonstrated for reconstructing the orientation of the mineralized collagen fibrils in bone trabeculae. Similar experiments can also be performed in other tissues and materials which exhibit structural anisotropy, such as the human brain.

About the speaker: Marios Georgiadis received his Mechanical Engineering diploma from the National Technical University of Athens, Greece. He did his Masters studies in Biomedical Engineering at ETH Zurich, Switzerland, where his thesis “Microfluidic probe for tissue staining in advanced pathology” was awarded the ETH medal. In his PhD at the Institute for Biomechanics of ETH Zurich he developed methods for investigating local tissue anisotropy using X-ray scattering, and applied that to investigate local tissue anisotropy of human trabecular bone. He was runner-up for the Student Award of the European Society of Biomechanics in 2015. He is currently at the Institute for Biomedical Engineering of ETH Zurich and the University of Zurich, where he will be looking at the microstructural anisotropy of brain tissue using X-ray scattering and diffusion MRI.

February 9th at noon

Gregory Lemberskiy

Graduate Student
Biomedical Imaging (BIO) Program
Sackler Institute, Radiology Department
NYU School of Medicine
Time-Dependent Diffusion in the Body

Abstract: Diffusion of water molecules is directly influenced by the biological tissue architecture at the micrometer length scale. Capturing this effect using Diffusion MRI has led to the development of numerous applications including early detection of stroke and cancer. However, despite the overwhelming tissue complexity, important non-Gaussian nuances of the diffusion signal are ignored. I have been focused on using time-dependent diffusion as a probe for non-Gaussian behavior within the muscle and prostate. This presents a unique challenge, as acquisition techniques such as STEAM, PGSE, and OGSE, must be tailored to the tissue of interest. In this talk, I will discuss the clinical motivation for pursuing time-dependent diffusion as well as advances in diffusion modeling and acquisition.

About the speaker: Greg immigrated from the city of Tomsk, Russia to Brooklyn, NY in 1994, where he grew up and attended school in Sheepshead Bay. He attended NYU as an undergrad, where he majored in Physics and followed the premed track. However, after numerous experiences working with and shadowing both scientists and clinicians he concluded that a PhD in MRI physics was a suitable middle ground between the two disciplines. He has since been working closely with Dmitry S. Novikov and Els Fieremans on development of Time-Dependent diffusion applications in the body.

Special Seminar: February 5th at 1:00 p.m.

Kyunghyun Cho, PhD

Assistant Professor
Department of Computer Science
New York University
Deep Learning: what it is and what it is becoming

Abstract: Deep learning has become one of the hottest topic in machine learning research in recent years. It began with the 2012 breakthrough in computer vision, the breakthrough that essentially transformed the whole field of computer vision. This breakthrough was followed by those in automatic speech recognition, natural language processing and machine translation. Beyond these recent success stories, deep learning promises much more especially in the areas of multimodal, multitask learning and sequential decision making. In this talk, I will start with a high-level overview on deep learning and discuss these future promises and challenges.

Special Seminar: February 3rd at noon

Baiyu Chen, PhD

Research Fellow
Department of Radiology
Mayo Clinic
Development and optimization of CT reconstruction algorithms – Challenges and my solutions

Abstract: The rising public concerns on CT radiation dose have greatly motivated the development of dose-reducing reconstruction algorithms. However, the development of a reconstruction algorithm is challenged by several aspects. First, collecting CT projection data (i.e., raw materials for CT reconstruction) is challenging: The CT projection data acquired on commercial CT scanners are proprietary and vendor-specific, and therefore not accessible to researchers who do not have research agreements with the vendor. Second, optimizing the algorithm is challenging: Any optimization needs to use diagnostic accuracy as the end goal, but the assessment of diagnostic accuracy via reader studies is time-consuming. Last but not least, validating the algorithm via clinical trials is challenging: The process can be very expensive and labor-intensive. In this talk, I will discuss solutions to these three challenges using examples from my current research: A library of patient projection data in an open and standardized format; a mathematical model that predicts the detection performance of human observers based on the image quality, the viewing condition, and the lesion characteristic; and a computer program that creates positive cases for clinical trials by inserting lesion of known characteristics into images of healthy patients. The same framework not only facilities the development of CT reconstruction algorithms, but can also be adapted by clinical practices (such as the optimization of clinical protocols) to improve diagnostic performance.

January 26th at noon

Matthew Gounis, PhD

Associate Professor
University of Massachusetts Medical School
Worcester, MA
From Bench to Brain: Toward Quantitative Assays of Brain Aneurysm Vulnerability

Abstract: The last two-decades have seen an explosion of technology to improve upon the safety and efficacy of brain aneurysm treatment. Despite remarkable improvements in treatment modalities, risk of severe neurological morbidity varies between 5 and 15% of patients with treated unruptured aneurysms. In parallel, increased access to noninvasive neuroimaging has led to a historically unprecedented detection rate of unruptured brain aneurysms. Although the risk of aneurysm rupture is often quite low, the consequences of aneurysmal subarachnoid hemorrhage are devastating with approximately half of the patients not surviving the rupture. Therefore, an approach enabling appropriate selection of patients who would benefit from treatment is urgently needed. Currently, best evidence indicates that size, ethnicity (Finnish, Japanese, or other), location, prior history of subarachnoid hemorrhage, and hypertension should all be considered. Other potential factors elevating rupture risk are family history of subarachnoid hemorrhage, cigarette smoking, and aneurysm morphology. However, given the uncertainty of aneurysm pathophysiology in the progression toward rupture, the precise model to accurately predict aneurysm rupture risk remains elusive. Over the last decade, a plethora of data from human brain aneurysm specimens as well as animal models of intracranial aneurysms has highlighted the role of aneurysm wall inflammation in mural destabilization. Our leading hypothesis is that stable aneurysms can become active, and hence undergo a process of remodeling that involves the invasion of immune cells. This invasion and pursuant inflammation precedes the breakdown of the structural components of the aneurysm wall. Capitalizing on models of vulnerable plaque, we have focused our efforts on in vivo imaging to detect active myeloperoxidase (MPO) in brain aneurysms as a precursor to structural destabilization. We have identified that human brain aneurysms that contain MPO have a statistically higher estimated 5-year rupture risk. Logistic regression modeling of 5-year aneurysm rupture risk and irregular aneurysm morphology when coupled are strong predictors of histologically confirmed MPO presence. Taken together, these data on human brain aneurysm specimens indicate the potential role of MPO as a biomarker for aneurysm instability. In parallel, MR probes have been tested in both animal models of inflamed aneurysms as well as using a unique micro-MRI approach to imaging human brain aneurysm specimens to quantify MPO presence. In summary, MPO detection by MRI may provide clinicians critical information on aneurysm wall biology to make informed decisions regarding treatment.

Special Seminar: January 14th at noon

Mootaz Eldib

Doctoral Candidate
Senior Associate Researcher
Mount Sinai Mecical Center
Optimization of PET Imaging on Simultaneous PET/MR Scanners

Abstract: With the recent introduction of simultaneous PET/MR imaging, various opportunities exist to utilize the co-acquired MRI data to improve the quantitative accuracy of the PET component of the scanner. In this presentation, I will introduce several MR-guided methods for PET attenuation and motion correction focusing on cardiovascular and liver imaging applications.

Special Seminar: January 13th at noon

Koen Michielsen

Department of Radiology
University Hospitals Leuven
Maximum Likelihood Reconstruction for Breast Tomosynthesis and Model Observer Evaluation

Abstract: Digital breast tomosynthesis is a recent imaging modality gaining acceptance as valuable diagnostic tool. Clinical evaluations have shown that when combined with digital mammography it improves diagnostic accuracy and reduces recall rate. When looking closer at the different lesion types, evidence points to improved visualization of masses and distortions, but potentially worse visualization of microcalcification clusters. Therefore, we improved the visualization of these microcalcification by expanding the forward model of the maximum likelihood for transmission tomography reconstruction to include an exposure specific resolution model and modified the update sequence to obtain faster convergence. Concurrently, we developed a channelized Hotelling observer that can predict human observer performance when evaluating detectability of microcalcification targets in a structured phantom background.

About the speaker: Koen Michielsen obtained the degree of Bachelor of Science at the University of Hasselt in 2003, and continued his education at KU Leuven where he graduated cum laude in 2005 with the degree of Master of Science in Physics, with a thesis on "Determining the time delays of lensed quasar J1155+635 from a series of CCD images". After receiving a second Master degree in 2007, this time in the field of Medical Radiation Physics and with a thesis titled "Automated data collection strategies and results for patient dosimetry in mammography", he started working as a certified medical physics expert at the department of radiology of the University Hospitals in Leuven. He worked there until December 2010, when he started his PhD project at the department of Imaging and Pathology at KU Leuven on the topic "Maximum a Posteriori Reconstruction of Limited Angle Tomography".

January 12th at noon

Antonios Papaioannou

Doctoral Candidate
Research Assistant
City University of New York
Probing structural disorder and permeability of porous media with diffusion NMR

Abstract: Characterizing the most relevant geometric structure of complex systems with a single transport measurement is central in many fields. Such characterization of the underlying structural complexity may contribute to early detection of cerebral ischemia, optimization of oil production from rock formations or characterization of complex biological networks such as protein–interaction networks. The increased structural complexity of such systems—or disorder—makes the establishment of relations between dynamic parameters, such as the diffusion coefficient, and the underlying geometric structure a challenging problem. Disorder may be categorized in a "handful" of universality classes which lead to distinct long time power law behaviors of the diffusion coefficient, characterized by the dynamical exponent θ. In this seminar, an introduction of the theory of classical transport in disordered media will be discussed. A direct experimental validation of the universal scaling of the diffusion coefficient of H2O diffusing through a homemade phantom of polycarbonate permeable films in a well defined geometry will be presented. In addition, structural parameters such as the diffusive permeability and structural disorder class of the phantom are experimentally determined. Other topics of the seminar include Pulsed Field Gradient NMR techniques and NMR probe development techniques for spin diffusion measurements.

About the speaker: Antonios received his Bs in Physics from University of Ioannina, Greece and is currently a Ph.D. candidate at the physics department of the City University of New York, The Graduate Center under the supervision of Gregory Boutis. His Ph.D. thesis focuses on classical transport in disordered systems. During his Ph.D he also had collaboration with Ravinath Kausik and Yi-Qiao Song (Schlumberger Doll Research-Boston) working on methane gas adsorption in disordered media. He is also interested in the statistical mechanics of complex networks (collaboration with Hernan Makse-CUNY).

January 8th at noon

Christopher Kroenke, PhD

Associate Professor
Oregon Health & Science University
MRI methods to assess fetal brain development and placental function: Application to fetal alcohol exposure

Abstract: The efficacy of therapeutic interventions for neurodevelopmental disorders improves when the disorder is detected early central nervous system development. We have developed MRI strategies for characterizing neural maturation in the fetal cerebral cortex, and for monitoring placental function, throughout the second half of the gestational period. To assess the sensitivity of these fetal MRI methods, we have developed a nonhuman primate model of fetal alcohol spectrum disorders. In this context we demonstrate the utility of MRI for precise characterization of perturbations to normal fetal development.

About the speaker: Dr. Kroenke's research group focuses on developing MRI strategies for characterizing the biological bases of neurodevelopmental disorders. Dr. Kroenke received his PhD in molecular biophysics and biochemistry at Columbia University. He then completed postdoctoral studies in the Washington University Department of Radiology. Dr. Kroenke is currently Associate Professor of Behavioral Neuroscience, and Associate Scientist in the Oregon Health & Science University Advanced Imaging Research Center and Oregon National Primate Research Center.

Special Seminar: December 17th at noon

Garry Gold, MD

Professor of Radiology
Stanford University
Vice President, ISMRM
December 15th at noon

Arvind P. Pathak, PhD

Division of Cancer Imaging Research
Russell H. Morgan Department of Radiology and Radiological Science
The Sidney Kimmel Comprehensive Cancer Center
The Johns Hopkins University School of Medicine
Imaging the Tumor ‘Vasculome’

Abstract: Angiogenesis or new blood vessel formation is one of the ‘hallmarks’ of cancer and necessary for tumor progression and metastasis. However, tumor blood vessels are structurally and functionally abnormal compared to vessels in healthy tissue. These abnormalities profoundly affect tumor hemodynamics, metastatic potential, and drug delivery. A recent explosion in imaging technologies has revolutionized our understanding of the role of the tumor vasculature and these phenomena. This lecture will highlight new 3D imaging techniques for visualizing the tumor vasculature; strategies for imaging the vascular phenotype at different spatial scales; and describe how 3D imaging data that quantify tissue morphology and molecular factors can be used in computational models of cancer and image contrast. The integration of preclinical cancer imaging data lays the ground work for systems biologists to map the ‘vasculome’ of a wide array of diseases. Mapping the tumor vasculature using multiscale imaging and modeling also enhances our understanding of the tumor microenvironment. Collectively, these advances enable us to relate the genotype to the vascular phenotype, identify novel drug targets and develop reliable clinical biomarkers of cancer.

About the speaker: Arvind P. Pathak received the BS in Electronics Engineering from the University of Poona, India. He received his PhD from the joint program in Functional Imaging between the Biophysics Department at the Medical College of Wisconsin and the department of Biomedical Engineering at Marquette University, Milwaukee, Wisconsin. During his PhD he was a Whitaker Foundation Fellow. He completed his postdoctoral fellowship at the Johns Hopkins University School of Medicine in the Molecular Imaging Program. He then joined the faculty of the Departments of Radiology and Oncology at Johns Hopkins. His cancer imaging research has been recognized by numerous journal covers and awards including the Bill Negendank Award from the International Society for Magnetic Resonance in Medicine (ISMRM) given to “outstanding young investigators in cancer MRI” and the Career Catalyst Award from the Susan Komen Foundation.

Special Seminar: December 14th at noon

Michael Garwood, PhD

Malcolm B. Hanson Professor of Radiology
Center for Magnetic Resonance Research and Department of Radiology
University of Minnesota
Performing MRI outside the usual technical boundaries
December 4th at noon

Todd Constable, PhD

Professor of Radiology and Biomedical Imaging and of Neurosurgery
Director of MRI Research
Yale University
Functional Connectome Fingerprinting: Connectivity Profiles Are Both Unique and Meaningful

Abstract: This presentation will discuss the uniqueness of individual functional connectivity profiles and how these signatures reflect behavior. The connectivity measures reflect underlying intrinsic connections that are modified only slightly with different task or resting-state conditions. A method for relating connectivity profiles to behavior, building a model, and then testing the predictive capabilities of the model will be shown. It will be shown that the areas that most characterize individual identification include frontal and parietal circuits. It will also be shown that specific connectivity patterns reflect measures of fluid intelligence and attention.

Special Seminar: November 25th at noon

Karen Holst

Doctoral Candidate
Karolinska Institutet
Challenges in free-breathing 3D cardiac magnetic resonance cine imaging

Abstract: Cardiac cine imaging is an important part of the clinical cardiac exam today, used for assessment of wall function and ventricular volume measurements. However, this is still mostly done with a stack of 2D images, each acquired during a breath-hold to avoid motion artifacts from the respiration. This method is both time consuming, inflexible and gives rise to many artifacts from poor or inconsistent breath holding. The desirable solution is a 3D free breathing technique which minimizes patient cooperation and gives high flexibility after acquisition for extracting arbitrary slice positions from the whole heart. This talk will focus on fast 3D k-space acquisition and reconstruction and the specific requirements trajectories need in order to cope with the constant motion of the beating heart and respiration. Furthermore, examples of different respiratory self-gating techniques will be shown and discussed. Finally, some preliminary results from our suggestion of combing a 3D acquisition technique and self-gating method will be given.

About the speaker: Karen Holst is a PhD student at Karolinska Institutet, Stockholm. She received her MSc in biomedical engineering at Technical University of Denmark where she specialized in medical imaging and radiation physics. Her thesis work is focused on free-breathing ventricular volumetric imaging resolved over both the cardiac and the respiratory cycles with magnetic resonance imaging.

Special Seminar: November 24th at noon

David Rigie

Doctoral Candidate
Medical Physics
University of Chicago
Acceleration Methods for Magnetic Resonance Imaging: Algorithms and Modelling

Abstract: Recent advances in x-ray computed tomography (CT) have led to a new imaging paradigm, called “spectral CT,” whereby a plurality of unique energy measurements are acquired, nearly simultaneously, in a single scan. It has been shown that this extra spectral information can be used to determine the entire energy dependence of the x-ray attenuation coefficient. This leads to the elimination of common image artifacts (e.g. beam hardening), a reduction in radiation dose, and improved quantification of contrast materials. In this talk, I will give a brief overview of spectral CT theory and clinical applications. Then, I will discuss how task based, mathematical observer models and image reconstruction algorithms can be generalized to accommodate this extra “spectral” dimension. The primary goal of my research is to improve the accuracy and robustness of spectral CT imaging by (1) developing objective metrics for optimizing imaging parameters and hardware design and (2) combining optimization based reconstruction methods with sparsity exploiting image priors, tailored to multispectral data. I will discuss some applications of these techniques to novel geometries with challenging data conditions.

About the speaker: David Rigie is a Ph.D. candidate in Medical Physics at the University of Chicago. Prior to arriving in Chicago, he studied Applied Physics at Cornell, with a concentration in molecular biophysics. His research interests include model-based image reconstruction, physical modelling, and spectral x-ray CT. He is currently involved in a collaboration with Toshiba Medical Research Institute, USA investigating the use of energy-resolving, photon-counting detectors for diagnostic CT.

October 27th at noon

Helen Benveniste, MD, PhD

Professor and Vice Chair for Research
Department of Anesthesiology
Stony Brook School of Medicine
Anesthesia-induced neurotoxicity investigated by MRI
October 20th at noon

Gwenn Smith, PhD

Richman Family Professor of Alzheimer’s and Related Diseases
Department of Psychiatry and Behavioral Sciences
Johns Hopkins University School of Medicine
Molecular Imaging of the Depression-Dementia Continuum

Abstract: Neuropsychiatric symptoms in late life are a major predictor of cognitive decline and the dementia transition. The pathophysiology underlying these symptoms is poorly understood. Over the past decade, advances in positron emission tomography (PET) instrumentation and radiotracer chemistry have provided an unprecedented opportunity to test mechanistic hypotheses generated from human post-mortem data and transgenic Alzheimer mouse models. Studies have been performed to identify the neural circuitry of affective and cognitive symptoms in late life depression and the role of the serotonin system. Building upon this work, multi-radiotracer PET imaging studies have been performed in late-life depression and mile cognitive impairment. These studies have tested the observation based on transgenic amyloid mouse models; of vulnerability of cortical monoamine projections (serotonin, to a greater extent) may precede beta-amyloid deposition. Understanding of the pathophysiology of late life depression and neuropsychiatric symptoms and targeting these symptoms may represent a strategy for earlier intervention and prevention.

Special Seminar: October 19th at noon

Matthew Muckley

Doctoral Candidate
Biomedical Engineering Department
University of Michigan
Acceleration Methods for Magnetic Resonance Imaging: Algorithms and Modelling

Abstract: In recent years there has been a growing interest in accelerating MRI scans, both from the viewpoint of reducing the computation time necessary to produce images as well as reducing the amount of time the patient spends in the scanner. This presentation will discuss both of these aspects of MRI acceleration. The first will be the development of a fast algorithm for the setting when parallel receive coils are used in conjunction with compressed sensing assumptions to reduce the scan time. This requires solving a complicated optimization problem, which can take more time than the scan itself. I will discuss an algorithm, BARISTA, that significantly reduces this computation time relative to state-of-the-art methods by carefully considering the structure of the sensitivity maps from the parallel receive coils. For the second aspect of MRI acceleration, I will discuss recent advances for the estimation of functional MRI time series of images using low rank modelling. The low rank modelling approach is demonstrated to be effective in simulation results relative to standard acquisition methods, and preliminary results using prospectively undersampled data will also be shown.

About the speaker: Matthew Muckley is a Ph.D. candidate in the biomedical engineering department at the University of Michigan. Matthew started his academic career by earning his B.S. at Purdue University, where he graduated With Distinction. Matthew's research at Michigan focuses on the application of signal processing methods to various imaging modalities, including MRI, X-Ray CT, optical imaging, and atomic force microscopy. For his research Matthew has been awarded first place in a KLA-Tencor Image Processing contest, a Rollin M. Gerstacker Foundation Fellowship, a GAANN Fellowship, and a Rackham Predoctoral Fellowship. and Aside from his research endeavors, Matthew also actively participates in the Biomedical Engineering Graduate Student Council at Michigan, for which he has served as President for the last year.

October 13th at noon

Joseph Ricker, PhD

Professor of Rehabilitation Medicine and Psychiatry
Director of Psychology, Rusk Rehabilitation
NYU Langone Medical Center
Acceleration Methods for Magnetic Resonance Imaging: Algorithms and Modelling

Abstract: Advances in neuroimaging have clearly changed the way that brain function, dysfunction, and rehabilitation may be conceptualized and studied. In addition to complementing existing behavioral and psychometric data, neuroimaging technologies such as fMRI and DTI novel inferences that cannot necessarily be made through other approach to studying brain-behavior relationships. This talk will provide an overview of contemporary functional neuroimaging techniques that have been specifically applied to traumatic brain injury in humans. The evidence-base (and often the lack thereof) of some technologies will be discussed in relation to the clinical appropriateness of these technologies. Finally, future research issues will be addressed through discussion of methodological and technical concerns rehabilitation, as well as how the integration of functional neuroimaging and clinical neuropsychology may inform the assessment and rehabilitation process.

About the speaker: Dr. Ricker is a board certified neuropsychologist and rehabilitation psychologist who came to NYU in 2013 as Professor of Rehabilitation Medicine and Director of Psychology for Rusk Rehabilitation at NYU Langone Medical Center. Prior to coming to NYU, he was a tenured Associate Professor and Vice Chair for Neuropsychology & Rehabilitation Psychology in the Department of Physical Medicine & Rehabilitation at the University of Pittsburgh School of Medicine. Dr. Ricker’s research career has been devoted to the study of cognitive impairment, recovery, and rehabilitation following human traumatic brain injury (TBI). He was among the very first investigators in the late 1990s to apply functional neuroimaging to investigate cognition after TBI. His work was honored in 2001 by two separate early career awards from the American Psychological Association, one in clinical neuropsychology and the other in rehabilitation psychology. Dr. Ricker’s current research focuses on the application of anatomic, functional, connectomic, and molecular brain imaging technologies in the investigation of neuropsychological impairment after brain injury. His NIH-funded research has included the use of technologies such as functional MRI, positron emission tomography, diffusion tensor imaging after TBI. He is a member of the editorial boards of four research journals (Journal of Clinical & Experimental Neuropsychology; Journal of Head Trauma Rehabilitation; Clinical Neuropsychologist; and, Rehabilitation Psychology), and serves as a grant reviewer for several U.S. and Canadian agencies, including the National Institutes of Health, the Centers for Disease Control and Injury Prevention, the Department of Veterans Affairs, and the Ontario Neurotrauma Foundation.

September 29th at noon

Thomas Benkert, PhD

Postdoctoral Researcher
Bernard & Irene Schwartz Center for Biomedical Imaging
NYU Langone Medical Center
Novel Steady-State Techniques for Magnetic Resonance Imaging

Abstract: Steady-state sequences are a class of rapid imaging techniques based on gradient-echo acquisitions with short repetition times. This class includes the balanced Steady-State Free Precession (bSSFP, TrueFISP) sequence, which provides the highest signal-to-noise ratio per unit time among all known imaging sequences. However, aside from a few applications such as cardiac imaging, this method is hardly established in the clinical routine. The main reasons are banding artifacts, which are signal voids due to magnetic field inhomogeneities, and the obtained T2/T1-weighted mixed contrast. In this talk, two novel techniques will be presented, which overcome these limitations and could allow for a more widespread use of bSSFP for MR diagnostics.

About the speaker: Dr. Benkert is a postdoctoral researcher at CBI working under the supervision of Dr. Block. During his undergraduate studies he studied to become a teacher for Physics and Mathematics in Wuerzburg, Germany and then focused on MRI, writing his thesis on “Quantification of Relaxation Times in MRI with Steady-State sequences”. During his PhD in Wuerzburg, he continued his MRI work under the supervision of Dr. Felix Breuer. The title of his dissertation was “Novel Steady-State Techniques for Magnetic Resonance Imaging”. His PhD work represents the topic of his Research Forum talk. His current research focuses on further developments for GRASP using fat-water separation.

Special Seminar: September 23rd at noon

Jill Slade, PhD

Department of Radiology
Michigan State University
The influence of age and physical activity on microvascular function

Abstract: The microvasculature is critical for the control of blood flow and tissue perfusion. Compromised microvascular function occurs during aging as well as several disease states and may contribute to compromised muscle performance within these populations. Muscle fMRI using blood-oxygen level-dependent imaging (BOLD) allow noninvasive assessment of peripheral microvascular function. Our findings show age related reductions in lower extremity BOLD and enhancement of muscle BOLD with exercise training in older adults.

September 18th at noon

Georg Schramm, PhD

Postdoctoral Fellow
KU Leuven
Initial results from simulations of joint PET/MRI reconstructions

Abstract: Regularized iterative image reconstruction is used in Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI). In combined PET/MRI acquisitions, PET and MR images both suffer from artifacts due to acquisition time constraints. Since these artifacts are fundamentally different, we would like to investigate whether joint iterative reconstruction using joint prior information could improve the image quality in both modalities. In this presentation, Georg Schramm will give a short overview of initial results from simulations with different joint priors.

September 15th at noon

Khegai Oleksandr, PhD

Postdoctoral Fellow
Bernard & Irene Schwartz Center for Biomedical Imaging
NYU Langone Medical Center
Quantification methods for time-resolved metabolic magnetic resonance imaging using hyperpolarized [1-13C]pyruvate

Abstract:Dissolution dynamic nuclear polarization enables real-time non-invasive measurement of metabolic fluxes using magnetic resonance spectroscopy. Quantitative kinetic information of in vivo metabolism is of great interest for medicine as a key characteristic of some diseases, i.e. tumors. In this talk, the developed comprehensive methods for the data acquisition, quantification, interpretation and visualization of dynamic 13C metabolite signals in vitro and in vivo will be presented on the example of hyperpolarized [1-13C]pyruvate.

August 25th at noon

Marta Moreno, PhD

Postdoctoral Research Fellow
Department of Psychiatry
Columbia University
Studying depression with 7T MRI

Abstract:Functional magnetic resonance imaging/spectroscopy (fMRI/MRS) have been used to visualize abnormalities in unipolar depression (MDD) with mixed results. Patients with medication refractory depression (TRD) represent almost one-third of all patients with MDD. There are relatively few treatment options for these patients. Prefrontal repetitive transcranial magnetic stimulation (rTMS) is a non-invasive, well-tolerated alternative technique to pharmacological treatment for MDD. TMS induces stronger electric currents in superficial regions than in deeper structures. However, TMS can modify ongoing neuronal activity within complex neuronal circuits. Effects of TMS can propagate beyond the site of stimulation, impacting a distributed network of brain regions. These observations suggest that TMS may relieve depression by modulating synaptic strength both locally and at distant sites modulating functional connectivity in cortical networks. Some evidence for TMS as an antidepressant points toward cortical excitability increases to normalize abnormal level of activity and distributed modulation of brain activity resulting in network-specific release of neurotransmitters and activity modulation. However, it remains unclear how TMS targeted to Dorsolateral Prefrontal Cortex (DLPFC) exerts its antidepressant effect. The future of TMS relies on identifying its mechanisms of action across the brain. The combination of TMS and BOLD fMRI or MR spectroscopy at lower field strength have shown to be promising. However, the resolution of fMRI and MRSI at lower fields are too low for depiction of node size and temporal resolution. These shortcomings of low field MRI prevents detection of default mode networks (DMN) function with appropriate representation of the strength of FC between the nodes. We have used 7T functional connectivity and MRSI at 0.5cc resolution to demonstrate correlation between glutamate concentration and DMN function. We will discuss how 7T is crucial in visualizing DMN in various brain regions implicated in MDD. A discussion will be presented of technical challenges in realizing 7T advantages in order to use the combined fMRI/MRSI in search for faulty networks. Eliminating 7T RF coil and B0 inhomogeneity in skull base will allow comparing fMRI/MRSI of normal subjects and patients with MDD which, in turn, could make diagnosis and treatment of these patients a quantitative practice. Such tools will reveal further understanding into the impact of TMS on brain function.

Special Seminar: August 4th at noon

Chantal Tax

PhD Candidate
University Medical Center Utrecht
From acquisition to tractography: Some recent advances in diffusion MRI data processing

Abstract:Diffusion MRI (dMRI) has offered exciting new avenues for investigating microstructural and architectural characteristics of tissue in vivo. The growing interest for integrating dMRI in many clinical and scientific studies has triggered the development of different strategies to process dMRI data. These developments include, amongst others, modeling and reconstruction of the dMRI signal beyond diffusion tensor imaging (DTI), and new ways to extract information on the (local) geometry of fiber tractography streamlines. This presentation will focus on our recent work in this area, including robust fitting in diffusion kurtosis imaging (DKI), calibrating the response function for spherical deconvolution (SD), the acquisition of a reference dataset to test processing pipelines, and quantifying whether streamlines locally form a grid-like pattern.

Special Seminar: August 4th at 3pm

Maxime Chamberland

PhD Candidate
Universite de Sherbrooke
Navigating through brain connectivity in real-time: A neurosurgical perspective

Abstract:In the past decade, the fusion between diffusion magnetic resonance imaging (dMRI) and functional magnetic resonance imaging (fMRI) has opened the way for exploring structure-function relationships in-vivo. As it stands, the common approach usually consists of analysing fMRI and dMRI datasets separately or using one to inform the other, such as using fMRI activation sites to reconstruct dMRI streamlines that interconnect them. Also, given the large inter-individual variability of the healthy human brain, it is possible that valuable information is lost when a fixed set of dMRI/fMRI analysis parameters such as threshold values are assumed constant across subjects. By allowing one to modify such parameters while viewing the results in real-time, one can begin to fully explore the sensitivity of structure-function relations and how they differ across brain areas and individuals. This is especially important when interpreting how structure-function relationships are altered in patients with neurological disorders, such as the presence of a tumor. In this study, we present and validate a novel approach to achieve such visualization: First, we present an interactive method to generate and visualize tractography-driven resting-state functional connectivity. Next, we demonstrate how our proposed approach can be used in a neurosurgical planning context. We believe this approach will promote the exploration of structure-function relationships in a subject-specific aspect and will open new opportunities for connectomics.

July 28th at noon

Jakob Asslander, PhD

Research Assistant
Department of Radiology
University Medical Center Freiburg
Spin Echoes in the Regime of Weak Dephasing: From SE-FLASH to MR-Fingerprinting

Abstract: In this talk I will demonstrate the possibility to form spin echoes after a single excitation pulse, where the time between the end of the pulse and the echo is longer than the length of the pulse itself. This stands in contrast to Hahn's theory spin echoes, where the length of a composite pulse is at least equal to the time between the end of the pulse and the echo. A representative spin echo pulse is implemented in an inversion recovery SNAPSHOT-FLASH sequence in order to retrieve quantitative T1- and proton density maps of the lung with increased signal intensity. Last but not least the theoretical concept in translated to a pseudo steady state free precession sequence for MR-fingerprinting.

About the Speaker: Jakob Asslander studied physics in Würzburg (Germany), where he began conducting MRI research. Thereafter, he obtained a PhD under Jürgen Henning in Freiburg (Germany). During doctoral study, Dr. Asslander focused on fast fMRI acquisition techniques with reduced susceptibility to artifacts. More recently, he has pursued research in RF-pulse design and optimal control algorithms.

July 27th at 3:00pm

Sung-Hong Park, PhD

Assistant Professor
Department of Bio and Brain Engineering
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
Development of New Anatomical, Physiological, and Functional Magnetic Resonance Imaging Techniques

Abstract: Magnetic resonance imaging (MRI) provides anatomical, physiological, and functional information of our body noninvasively. In this seminar, some new approaches to these imaging modalities will be introduced. The new approaches include techniques for (i) acquisition of time-of-flight MR angiogram and blood oxygenation level dependent (BOLD) MR venogram (often called susceptibility-weighted Imaging, SWI) simultaneously with minimal impacts on the image quality to each other, (ii) imaging blood perfusion and magnetization transfer (MT) asymmetry simultaneously with interslice blood flow and MT effects in 2D sequential multi-slice imaging, and (iii) better understanding of signal sources of high-resolution balanced steady-state free precession functional MRI at high field. Applications of compressed sensing algorithms to these imaging methods will be introduced. Images from humans and animals at various field strengths (3T - 9.4T) will be demonstrated and potential applications of these imaging methods for clinical diagnosis will be discussed.

About the Speaker: Sung-Hong Park received a PhD in bioengineering from the University of Pittsburgh in 2009

July 24, 2015 at noon

Pamela Woodard, PhD

Professor of Radiology and Biomedical Engineering
Washington University
Targeted Molecular Imaging of Atherosclerosis or "Tales in Translation"

Abstract: The talk focuses on PET-MR imaging of atherosclerosis using novel radiopharmaceuticals targeted to specific components suggestive of plaque vulnerability including Natriuretic Peptide Receptor-C and hypoxic macrophages. The speaker will go describe the steps of taking one of these radiotracers from preclinical development and toxicity testing to FDA IND application, approval and clinical trial.

About the Speaker: Pamela Woodard is a Professor of Radiology and Biomedical Engineering at Washington University where she is Radiology Vice Chair of Clinical and Translational Research, Director of the Center for Clinical Imaging Research (CCIR) and Head of Advanced Cardiac Imaging. She is past chair of the Cardiovascular Radiology and Intervention (CVRI) Council and of the American Heart Association and is currently a member of the AHA Operations Committee and past president of the North American Society for Cardiovascular Imaging. She has over 140 peer-reviewed publications and has been PI, on the steering committee or co-investigator on multiple NIH-funded grants and clinical trials.

July 21, 2015 at noon

Tuomo Valkonen, PhD

Research Associate
University of Cambridge
Approaches for dealing with the non-linearity of the Stejskal-Tanner equation

Abstract: The Stejskal-Tanner equation for diffusion tensor imaging (DTI) produces a non-linear correspondence between the DWI measurements and the tensor field. For correct noise modelling, we should in principle include this non-linearity in our DTI reconstruction models. This results in a difficult non-convex optimisation problem. In this talk, I will discuss a primal-dual optimisation method that can effectively handle the Stejskal-Tanner equation—at least when no other complications enter the reconstruction model. In practise, however, our knowledge of the measurement errors and noise is only partial, and accurate noise modelling is not feasible. I will therefore look at the efficacy of foregoing accurate noise modelling, and reducing our knowledge of measurement and model errors and noise to simple bounds, effectively obliterating the Stejskal-Tanner equation from the model (joint work with Yury Korolev and Artur Gorokh).

About the Speaker: Tuomo Valkonen received his Ph.D in scientific computing from the University of Jyväskylä (Finland) in 2008. He has since then worked in well-known research groups in Graz, Cambridge and Quito. Currently in Cambridge, his research concentrates on the mathematical analysis of image processing models, towards studying their reliability, and the development of fast optimisation algorithms for the solution of these models.

April 21, 2015 at noon

Elias Kellner, PhD

Medical Physics
Department of Radiology
University Medical Center Freiburg
Quantitative Cerebral Blood Flow Measurements using Dynamic-Susceptibility-Contrast-MRI: Development of a Measurement Sequence and Comparison with PET

Abstract: Dynamic Susceptibility-Contrast MRI can be used to measure the cerebral blood flow in the brain. The method has successfully been applied in clinical routine for over a decade, particularly in Stroke, but it is currently not exploting its full potential due to several problems concerning the correct quantification. The major problem is related to the measurement of the arterial input function (AIF). The key weakness of the existing, conventional technique is an insufficient consideration of the different physical effects of paramagnetic contrast agent in large blood vessels, and in tissue. In this work, these effects are thoroughly analysed to design an extended measurement sequence with an additional module dedicated to the correct measurement of the blood signal. With this, the AIF can accurately and quantitatively be determined. In a comparison study in the porcine model, the proposed technique is validated against the current gold standard, positron-emission-tomography (PET). This quantitative comparison can for the first time be performed without additional normalisation factors. The results demonstrate a good agreement of both methods. The comparison further reveals that the reasonable interpretation of calulcated maps for both, MRI and PET is not straightforward, and requires consideration of the corresponding kinetic models as well as the physics of the tracers used in the different methods.

About the Speaker: Dr. Kellner's profile at Universtats Klinikum Freiburg.

March 31st, 2015 at noon

Rama Jayasundar, PhD

Department of NMR
All India Institute of Medical Sciences
New Delhi, India
Applications of NMR in the Indian traditional medicine of ayurveda

Abstract: The growing interest in systems perspective is not only revolutionising cell biology but also providing the impetus for clinical medicine to shift from a reductionistic to a holistic approach for efficient disease management. This inevitably brings into focus one of the longest unbroken healthcare system in the world, i.e. ayurveda, indigenous to Indian subcontinent. The unique ability of NMR to study whole systems (in vitro and in vivo) and generate a wide range of information non-invasively makes it ideally suited to study holistic medicine like ayurveda. It offers a powerful non-invasive means to not only validate ayurveda but also to gain understanding of its concepts and translate them for use in modern healthcare. Different areas ranging from ayurveda’s therapeutic use of medicinal plants to diagnosis, treatment efficacy and concepts of preventive healthcare can be studied and validated effectively through NMR, opening new vistas for expanding the role of NMR in healthcare. This presentation, while outlining the various potential applications of MR in ayurveda will also elaborate on the systems approach of ayurveda.

About the Speaker: Dr. Rama Jayasundar, after her initial training in Physics, obtained her PhD in NMR from Cambridge University, UK. In addition to her main training as a physicist, she is also a qualified doctor trained in both ayurveda (the indigenous Indian medical system) and modern medicine. She holds a Bachelor’s degree in Ayurvedic Medicine (BAMS - Bachelor of Ayurvedic Medicine and Surgery). She is currently a faculty in the Department of NMR, All India Institute of Medical Sciences (AIIMS), New Delhi, India. Her area of specialization is Biomedical MR - RF coil designing and building, RF pulse sequence programming, clinical imaging and spectroscopy. She developed indigenously a low cost MR coil for clinical use, for which she received the Young Scientist Award. During her stint as a visiting Professor at the Max Planck Institute of Biophysical Chemistry, Gottingen, Germany (1997-1998), she worked on the development of functional MR spectroscopy techniques. She has authored a number of research publications in peer reviewed journals and has also won many awards and honors. Using her dual qualification as an NMR scientist and a professionally qualified ayurvedic doctor, she is currently involved in scientific research in Ayurveda. Her research interests range from applications of NMR, MRI and other analytical techniques in basic and clinical ayurvedic research.

March 30th, 2015 at noon

Dr. Elmar Merkle

Professor and Chairman
Department of Radiology
University Hospital Basel
A hard look at MR: is it simple and fast enough to fill the gap?

Abstract:This talk was initially presented as a plenary during the annual ISMRM meeting in Montreal in 2011. It focuses on the lack of speed and simplicity as well as the lack of robustness of MR imaging in comparison to other cross sectional imaging modalities. Now, almost 4 years later, this talk will be repeated in its original form to challenge NYU’s research group to answer the simple question – what has changed since?

About the Speaker: Dr. Merkle's profile at Universitatsspital Basel.

March 24th, 2014 at 11:00am

Dmitri “Mitya” Chklovskii, PhD

Group Leader for Neuroscience
Simons Center for Data Analysis
Simons Foundation, New York City
How do animals see motion? Insights from fly connectomics.

Abstract: Animal behaviour arises from computations in neuronal circuits, but our understanding of these computations has been frustrated by the lack of detailed synaptic connection maps, or connectomes. For example, despite intensive investigations over half a century, the neuronal implementation of local motion detection in the visual system remains elusive. By developing a semi-automated pipeline using electron microscopy we were able to reconstruct the biggest connectome to-date within the Drosophila visual system and identify neurons and synapses comprising the motion detection circuit motif. Electrophysiological recordings from the identified neurons have confirmed our predictions. More recently, a similar motif has been identified in the vertebrate retina suggesting that the principles of neural computation are shared across species.  

About the Speaker: Before coming to the Simons Foundation in 2014, Mitya Chklovskii was a group leader at the Howard Hughes Medical Institute’s (HHMI) Janelia Farm Research Campus in Ashburn, Virginia. Chklovskii also initiated and led a collaborative project at HHMI that assembled the largest-ever connectome, a comprehensive map of neural connections in the brain. Before that, he worked at Cold Spring Harbor Laboratory in New York, where he founded the first theoretical neuroscience group, having worked there as a first assistant, and later an associate professor. As group leader for neuroscience, Chklovskii leads an effort to understand how the brain analyzes complex datasets streamed by sensory organs, in an attempt to create artificial neural systems. He holds a Ph.D. in physics from the Massachusetts Institute of Technology.

August 26th, 2014 at 12:00pm

Lior Weizman, PhD

Postdoctoral Fellow
Department of Electrical Engineering
Technion – Israel Institute of Technology, Haifa
The application of compressed sensing for longitudinal MRI

Abstract: Magnetic Resonance Imaging (MRI) is the method of choice for diagnosis, evaluation and follow-up of brain pathologies. In the common treatment scheme, patients are repeatedly scanned every few weeks or months to assess disease progression and treatment response. Although the important information for clinical evaluation lies in the change between the follow-up MRI and the former one, every follow-up scan is acquired anew. This makes most of the data in the later scan redundant. In MRI, data is acquired in a spatial frequency domain, called "k-space". In my talk I'll discuss the application of compressed sensing (CS) for MRI and the mutual similarity of follow-up scans in longitudinal MRI studies. I'll present a sampling and reconstruction framework that exploits the redundancy of the acquired data in longitudinal studies. This would rely on two extensions of compressed sensing, adaptive-CS and weighted-CS. In adaptive CS, k-space sampling locations are optimized such that the acquired data is focused on the change between the follow-up MRI and the former one. Weighted CS uses the locations of the nonzero coefficients in the sparse domains as a prior in the recovery process.Results are presented on MRI scans of patients with brain tumors, and demonstrate improved spatial resolution and accelerated acquisition for 2D and 3D brain imaging at 10-fold k-space undersampling.

About the Speaker: Lior Weizman received the B.Sc. and M.Sc. degrees in Electrical Engineering from Ben-Gurion University of the Negev, Beer-Sheva, Israel, in 2002 and 2004, respectively, and the Ph.D. degree in computer science in 2013 from the Hebrew University of Jerusalem, Israel. From 2005 through 2008 he was with RAFAEL, Advanced Defense Systems LTD. During 2011 he was a visiting student at Stanford University, CA. He is currently a post-doctoral fellow at the Department of Electrical Engineering, Technion - Israel Institute of Technology, Haifa. His research interests are in the general areas of sampling theory, statistical signal processing and their applications to medical image processing and medical imaging.

August 25th, 2014 at 12:00pm

Afonso Silva, PhD

Chief, Cerebral Microcirculation Unit
Laboratory of Functional and Molecular Imaging
National Institute of Neurological Disorders and Stroke
National Institutes of Health
Anatomical and Functional MRI of Conscious, Awake Marmosets
August 20th, 2014 at 12:00pm

James M. Balter PhD

Department of Radiation Oncology and Biomedical Engineering
University of Michigan Medical School
Integration of MRI in the Radiation therapy environment

Yue Cao, PhD

Department of Radiation Oncology, Radiology and Biomedical Engineering
University of Michigan Medical School

MRI-based perfusion measurements for assessment and individualization of patients undergoing radiation therapy for intrahepatic cancer
August 19th, 2014 at 12:00pm

Eric T. Ahrens, PhD

Professor and Director of Stem Cell Molecular Imaging
Department of Radiology
University of California, San Diego
MRI-based approaches to quantitatively study cell trafficking and function in vivo

Abstract:An unmet challenge to successful clinical development of stem cell therapies is the development of non-invasive methods to image the behavior and movement of cells following transplant into patients. Moreover, imaging is needed to improve safety surveillance of cell therapies to help overcome regulatory hurdles. MRI is experiencing a rapid expansion in its ability to visualize specific cell populations in vivo. These capabilities are facilitated by the development of new imaging probes that tag cells prior to transfer or alter a cell’s proteome to facilitate MRI detection. This talk will first cover a new approach for cell tracking developed in our lab called ‘in vivo cytometry.’ In this approach, cell populations of interest, such as stem cells, are tracked and quantified in vivo. We formulate novel perfluorocarbon (PFC) emulsions to label cells ex vivo. The labeled cells are then introduced into the subject and their migration can be monitored using fluorine-19 (19F) MRI. The 19F images are extremely selective for the labeled cells, with no background signal from the host’s tissues. Moreover, the absolute number of labeled cells in regions of interest can be estimated directly from the in vivo 19F images. Additionally, the PFC emulsion reagents have bio-sensing properties that report on the absolute level of intracellular oxygen and can potentially be used to monitor cell differentiation or apoptosis in vivo. Looking ahead, MRI will be able to harvest the power of molecular biological tools to impart exogenous image contrast to living tissue in a cell-specific or event-related manner. This will be accomplished using transgenic and vector technologies to express reporter genes coding for paramagnetic metalloproteins. Towards this goal, I will describe efforts to develop and characterize new generations of nucleic-acid based MRI reporters that render cells paramagnetic and detectable in vivo. For example, MRI reporters can be used for labeling stem cells for long-term tracking in vivo.

About the Speaker:Eric T. Ahrens, Ph.D., is a Professor and Director of Stem Cell Molecular Imaging in the Department of Radiology at the University of California, San Diego. Formally, he was a Professor of Biological Sciences at Carnegie Mellon University and the Director of the Pittsburgh NMR Center for Biomedical Research. Prior to this, he served as a Senior Research Fellow in the Department of Biology at the California Institute of Technology. He holds a Ph.D. in physics from the University of California at Los Angeles and was a graduate fellow at Los Alamos National Laboratory. Ahrens’ research investigates in vivo biological processes using unique molecular, cellular and anatomical MRI and NMR methods.

August 12th, 2014 at 12:00pm

Charles Watson, PhD

Siemens Healthcare Molecular Imaging
A Sparse Transmission Method for PET Attenuation Correction in the Head

Abstract: In positron emission tomography (PET), attenuation of the annihilation radiation in the body is the largest physical effect confounding the quantitative interpretation of the emission data. Traditional g-ray transmission (TX) measurements for attenuation correction in clinical PET were largely abandoned 12 years ago with the advent of PET/CT. Recently, however, several technological developments have converged to significantly enhance the power of TX measurements, sparking renewed interest. These include new joint reconstruction algorithms for simultaneously acquired emission and transmission data; time-of-flight (TOF) measurement capability for discriminating attenuation effects in emission data; and the positron beam technique for injecting transmission sources into the field of view of integrated PET/MR systems. In this talk we will describe a novel solution for PET attenuation correction in the head based on the joint reconstruction of simultaneously acquired emission and sparse transmission (sTX) data corresponding to 20 fixed line sources placed in a ring around the head. Simulations of an 18FDG study show that the sTX data effectively constrain cross-talk. Bone, soft tissue and voids are approximately represented in the estimated attenuation image. The results are compared to a standard MLEM reconstruction of emission-only data, and to joint reconstruction of simultaneous emission-transmission data using a full-ring source. We find that 10 to 20% underestimation of activity in the peripheral regions of the brain in the latter two images is reduced to < 5% on average in the sTX case. We thus demonstrate that an sTX array can provide better cross-talk reduction than a conventional full-ring transmission source, and will offer a qualitative explanation of why this occurs. We will also examine the impact of TOF information on the joint reconstruction in the noise-free case. We estimate that such an sTX technique would increase patient radiation dose in a typical 18FDG clinical study by < 4%.

About the Speaker:Dr Watson earned a PhD in physics from Yale University in 1980. Following post-doctoral study at the California Institute of Technology in planetary science, he joined the corporate research staff of Schlumberger in Ridgefield, Connecticut in 1982, where he developed Monte Carlo simulations of g-ray and neutron transport for the design and interpretation of nuclear well-logging instruments. In 1993, he joined CTI PET Systems in Knoxville, Tennessee, which subsequently merged into Siemens Healthcare. At CTI/Siemens Dr Watson has been involved in nearly all aspects of the physics of PET, PET/CT and PET/MR scanners. He is the author of a widely used 3D scatter simulation algorithm for the correction of positron emission data. From 1999 to 2002 he was the project leader for the development of the first commercial PET/CT scanner. He served as the chief PET physicist for the development of the first integrated whole-body PET/MR, Siemens’ mMR. His current research interests include applications of positron beams in PET/MR systems, and the development of next-generation transmission systems for the attenuation correction of PET data. He is the author of numerous scientific publications and patents in the field of PET instrumentation, and serves on the editorial board of EJNMMI-Physics.

August 11th, 2014 at 10:00am

Chunlei Liu, PhD

Assistant Professor of Radiology
Durham, NC
Quantitative Susceptibility Mapping and Susceptibility Tensor Imaging

When the brain is situated in a magnetic field, it creates a small field of its own in response to the presence of the external field. This interaction, though extremely weak, becomes measurable under the strong field provided by MRI scanners. With MRI, this small perturbation field can also be spatially localized and quantified. The strength and direction of the perturbation is influenced by a number of physiologically important factors including molecular composition, cellular organization and neuronal connectivity. By imaging this field perturbation, one may then be able to infer a wealth of information about brain microstructure. Such information include, for example, iron deposit in aging and Parkinson’s disease, myelination in brain development, demyelination in multiple sclerosis, and neuronal connectivity. Besides brain, this magnetic interaction is also significant in many other organs including kidney and heart. I will present some recent methodological developments and discuss potential applications.

August 4th, 2014 at 9:30am

Colin Studholme, PhD

Professor Pediatrics and Bioengineering
Adjunct Professor of Radiology
Department of Pediatrics, University of Washington, Seattle, WA
MR Imaging the Moving, Growing Human Fetal Brain

Recent work that combines computer vision with fast MR imaging techniques is beginning to allow the collection of full 3D MRI scans of the human fetal brain in-utero without sedation. The basic ideas behind the engineering approaches to these techniques will be reviewed with examples on typical clinical structural and diffusion imaging studies. Results of the application of these imaging techniques to study human fetal brain development by constructing spatio-temporal growth models will then be covered.

About the speaker: Dr. Studholme is a Professor of Pediatrics and Bioengineering, and Adjunct Professor of Radiology at University of Washington, Seattle. He completed his Ph.D. in medical physics and biophysics from the University of London and a postdoctoral fellowship in diagnostic radiology at Yale University. Dr. Studholme’s research focuses on the development of new mathematical and computational algorithms to manipulate and analyze biomedical image data. His work is currently motivated by the study of brain anatomy and the patterns of its change over time in two broad clinical areas: fetal and pre-term infant brain development, and neurodegenerative processes in adults.

July 29th, 2014 at 12:00pm

Joseph Alukal, M.D..

Assistant Professor; Dir Reproductive Health & Benign Disorders of Prostate
Departments of Obstetrics and Gynecology (Obs/Gyn) and Urology (Urology)
NYU Urology Associates
Management of non-obstructive azoospermia: is there a role for imaging?

For information on Timothy Duong's current research, please click here.

July 25th, 2014 at 12:00pm

Timothy Q. Duong, Ph.D.

SI Glickman MD Endowed Chair, Professor
MRI Division Chief, RII
Assistant Director for Research, RII
University of Texas Health Science Center
San Antonio, TX
MRI of experimental stroke and TBI

For information on Timothy Duong's current research, please click here.

July 22nd, 2014 at 12:00pm

Paul Vaska, PhD

Department of Biomedical Engineering
Stony Brook University
Novel PET and multimodal imaging technologies, from neuroscience to oncology

Our research encompasses the development of new detector materials and concepts, low-noise microelectronic signal processing, high-throughput data acquisition methods, Monte Carlo simulation, and new data processing techniques to optimize the extraction of quantitative information from the PET data. This talk will present an overview of our unique imaging technologies - RatCAP, small-animal PET-MRI, human breast PET-MRI, wrist scanner for input function, and future human brain imagers.

July 16th, 2014 at 2:00pm

Theresa Bachschmidt

PhD Candidate
Siemens MR Erlangen, MSK Team
Metal artifact correction using pTX
July 15th, 2014 at 12:00pm

Ricardo Otazo, PhD

Assistant Professor Radiology
New York University School of Medicine
Stretching the limits of compressed sensing dynamic MRI: Low-rank plus sparse reconstruction and self discovery of motion

Abstract: Extensive spatiotemporal correlations in dynamic MRI enable the application of compressed sensing techniques to accelerate data acquisition. Low-rank plus sparse (L+S) matrix decomposition or robust principal component analysis (RPCA) can be employed to represent dynamic images as a superposition of a background component (L) and a dynamic component (S). The dynamic component can include for example organ motion or contrast-enhancement information. The L+S model increases the compressibility of dynamic images with respect to L- or S-only models and performs automatic background suppression in the S component. This talk will describe how the L+S model can be employed to reconstruct undersampled dynamic MRI data with automatic separation of background and dynamic components. An extension of the L+S approach that incorporates a motion model to improve the performance in the presence of organ motion will be also discussed. Reconstruction of highly-accelerated dynamic MRI data corresponding to cardiac perfusion, cardiac cine, time-resolved peripheral angiography, and abdominal perfusion using Cartesian and golden-angle radial sampling will be presented to show feasibility and general applicability of the L+S method.

Bio: Ricardo Otazo is an Assistant Professor of Radiology at New York University School of Medicine. He received his B.Sc. in Electronics Engineering from Universidad Catolica de Asuncion, Paraguay in 2001, and his M.Sc. and Ph.D. in Electrical Engineering from the University of New Mexico in 2005 and 2007 respectively. His research interests include the development of rapid MRI and low-dose CT techniques using compressed sensing, image reconstruction algorithms, application of MRI techniques to clinical studies and signal processing methods in general.

June 25th, 2014 at 2:00pm

Rafael O’ Halloran, PhD

Assistant Professor Radiology
Mount Sinai Hospital
Diffusion-Weighted MRI in the (Not-So-) Steady State

Abstract: Diffusion-weighted (DW) MRI is mostly done with single-shot EPI because multi-shot DW MRI is sensitive to motion-induced phase. Solving the multi-shot problem would open up DW MRI to other pulse sequences, allowing gains in resolution and geometric fidelity. In this talk we’ll look at some solutions to this problem in the context of a 3D (massively multi-shot) DW steady-state free precession sequence.

Bio: Rafael O’Halloran started his career in MRI at the University of Wisconsin in Madison where he worked in Sean Fain’s group on hyper-polarized Helium-3 MRI of the lung, fast radial imaging, and diffusion. After graduation, he moved to sunny Stanford, California to work with Roland Bammer on DW MRI of the brain with steady state free precession sequences. In January of this year Rafael joined Mount Sinai as Assistant Professor of Radiology and continues to work on diffusion and other interesting contrasts in the brain. He lives with his wife and 22-month-old son on the upper East side and is slowly adjusting to life in New York.

June 24th, 2014 at 12:00pm

Jiangyang Zhang, PhD

Associate Professor
Johns Hopkins University
Imaging Brain Structures and Injuries with Oscillating Gradient Diffusion MRI

Diffusion MRI utilizes water molecule diffusion to probe brain microstructures and is an important tool to visualize a wide spectrum of pathologies. In recent years, a special diffusion MRI technique, the oscillating gradient diffusion MRI, has shown promise in providing additional information on tissue microstructures. Our research focus on using oscillating gradient diffusion MRI to bring novel imaging contrasts to visualize structures and pathology in the brain. We have demonstrated that the technique can reveal densely packed neuronal layers in the mouse hippocampus and cerebellum. In a mouse model of neonatal hypoxia ischemia, our results suggest that the technique can detect swelling of glial cells and their processes at 24 hours after insult.

June 20th, 2014 at 12:00pm

Jack Poulson, PhD

Assistant Professor
Department of Computational Science and Engineering
Georgia Institute of Technology
High-performance Low-rank Plus Sparse Matrix Decompositions for Undersampled Dynamic MRI

Low-rank plus Sparse matrix decompositions were recently proposed (by Otazo et al.) as a means of separating the background and dynamic components of undersampled dynamic MRI. For typical model sizes, a sequential plane-by-plane 4D reconstruction using an Alternating Direction Method of Multipliers (ADMM) requires a few hours of computation, most of which is spent within 2D non-uniform Fourier transforms (NUFTs) and the proximal map for the nuclear norm, so-called singular-value soft-thresholding (SVT).Due to the structure of the acquisition operator, within each plane, the NUFTs are embarrassingly parallel over both the channels and timesteps, whereas the SVT primarily consists of a QR decomposition of a tall-skinny matrix and is best decomposed within the image domain. It is shown that, with a careful redistribution of the data at each iteration, both the NUFTs and SVTs can be effectively parallelized on thousands of cores and reconstruction times have been observed to reduce from several hours to roughly one minute. Furthermore, the preliminary implementation is made available as part of an open source package, currently named Real Time Low-Rank Plus Sparse MRI (RT-LPS-MRI).

Jack Poulson is an Assistant Professor in the Department of Computational Science and Engineering at the Georgia Institute of Technology. Jack completed his PhD in Computational and Applied Mathematics at UT Austin at the end of 2012 and spent a brief postdoc in Stanford's Department of Mathematics before moving to Georgia Tech in November of 2013.

June 11th, 2014 at 12:00pm

Shalom Michaeli, PhD

Center for Magnetic Resonance Research
Department of Radiology
University of Minnesota
"Probing biological systems using frequency swept pulses: relaxation in high rank rotating frames, n ≥ 2."

NMR offers a plethora of tools for investigating tissue properties in vivo. The present presentation aims to describe novel MRI and MRS approaches that have been recently developed in our laboratory, based on the implementation of frequency swept (FS) pulses operating in adiabatic and non-adiabatic regimes. The tissue contrasts generated by such techniques will be explained within the context of rotating frame relaxation mechanisms, magnetization transfer effects [6], relaxation along a fictitious field (RAFF) in the rotating frames of rank n ≥2 (RAFFn), and MRI with RAFFn preparations using no echo time SWIFT readout. Frequency swept pulses offer unique capabilities to investigate biological systems for both in vivo and high-resolution NMR. Applications to glioma gene therapy, Parkinson diseases and multiple sclerosis, and to quantification of protein dynamics will be presented.

June 10th, 2014 at 1:00pm

Silvia Mangia, PhD

Assistant Professor
Department of Radiology
University of Minnesota
"Functional 1H MRS at ultra-high field"

Proton magnetic resonance spectroscopy (1H MRS) allows the non-invasive measurement of metabolite concentrations, and is a powerful tool to investigate brain biochemistry and metabolism in health and disease. Similar to MRI, 1H MRS benefits from the gain in signal-to-noise ratio which originates in the increased polarization at higher magnetic field. High magnetic fields also increase chemical shift dispersion, thus emphasizing the characteristic spectral patterns of metabolites and decreasing spectral overlaps. Greater spectral dispersion additionally improves water suppression and spectral editing. The improved sensitivity achieved at high magnetic fields ultimately results in gains in spatial resolution, temporal resolution and/or reliability of quantification of an increased number of metabolites. Magnetic fields higher than 4 T are widely employed in 1H MRS studies of animal models. Recent progresses in magnet technology, gradient system performance, RF coil and pulse sequence design enabled localized in vivo 1H MRS also in humans at ultra-high magnetic fields up to 7 T. Exciting applications of 1H MRS in humans involve the functional studies of the metabolic events occurring during various stimuli. Our group (Mangia et al, 2007a; 2007b) and others (Lin et al, 2012; Schaller et al, 2013) have measured the concentrations of multiple metabolites with unprecedented sensitivity and temporal resolution at 7 T in the human primary visual cortex during paradigms of visual stimulation. These studies provided critical insights into the metabolic events of increased neuronal activity, and shed light into the neurometabolic coupling of astrocytes and neurons.

May 6th, 2014 at 12:00pm

Steven Baete, Ph.D.

Post-doctoral fellow
New York University School Of Medicine
Langone Medical Center
"Improved Diffusion Spectrum Imaging by Radial q-space sampling using a multi-echo stimulated echo diffusion sequence"

Diffusion Spectrum Imaging (DSI) is a powerful means for robustly and non-invasively imaging long-range neuronal architecture in the human brain. This robustness is rooted in DSIs model-independent determination of the Orientation Distribution Function (ODF) through the sampling of the ODFs Fourier transform in q-space. The large number of q-space samples needed for accurate measurements of the ODF lead to long acquisition times, hindering practical implementation. These long acquisition times can be partially mitigated by multi-slice or multiband techniques where several slices are encoded at the same time. A second hindrance is that practically feasible b-values (e.g. 4000 s/mm2) limit the achievable angular resolution as the angular resolution is proportional to the inverse of the largest distance sampled in q-space when sampling q-space on a Cartesian grid.
In this talk we will show that these limitations to the practical implementation of DSI can be overcome by radially sampling q-space (RDSI) using a multi-echo stimulated echo diffusion sequence. When sampling q-space along radial lines, each radial line in q-space is directly connected by the Fourier slice theorem to the value of the radial ODF at the same angular location. This has the advantage that the angular resolution depends on the number of radial lines sampled rather than on the maximum b-value. Hence, Radial q-space sampling for DSI results in an improved angular resolution at lower b-values compared to Cartesian q-space sampling for a similar number of samples. In addition, the radial sampling lends itself to using a multiple echo stimulated echo diffusion sequence, accelerating the acquisition almost fourfold. The higher diffusion times of the stimulated echoes are also expected to lead to increased anisotropy and better fiber tracking. The findings which will be presented in this talk suggest that radial acquisition of q-space can be favorable for the practical implementation of DSI.

April 29th, 2014 at 12:00pm

Florian Knoll
Postdoctoral Researcher
NYU Langone Medical Center

"Joint Reconstruction of MR-PET data with multi-sensor compressed sensing"

Integrated MR-PET systems like the Siemens Biograph mMR allow simultaneous acquisition of PET and MR data. However, image reconstruction is performed separately and results are only combined at the visualization stage. PET images are reconstructed using a variant of Expectation Maximization while MR data are reconstructed with an inverse Fourier transform or iterative algorithms for parallel imaging or compressed sensing. We propose an integrated joint reconstruction framework based on multi-sensor compressed sensing. This approach uses MR and PET data simultaneously during image reconstruction and exploits anatomical correlations between the two modalities. Results will be shown for numerical simulations and in-vivo imaging that demonstrate improvements in image quality of both MR and PET images. We expect that joint reconstruction can provide additional enhancements to the information content of multimodality studies in the future.

April 25th, 2014 at 3:00pm

Beatriz Luna, PhD
Staunton Professor of Psychiatry and Pediatrics
University of Pittsburgh

"Functional Specificity and Integration of Brain Processes underlying Cognitive Development"

The adolescent period incurs vulnerabilities that undermine survival (risk-taking behaviors) and importantly increase the risk for the emergence of psychopathology. These vulnerabilities have been associated with a protracted maturation of prefrontal executive and striatal motivational systems. The contribution of each of these systems and importantly systems-level processing to cognitive development are not well understood. I will present a set of fMRI and DTI studies that identify developmental changes in functional specificity including prefrontal systems underlying inhibitory control and striatal neurophysiology and function in reward processing. In addition, studies characterizing changes in functional and structural connectivity through adolescence will be discussed. Together, these findings indicate that adolescents have access to executive systems supporting decision-making but in the context of a reactive motivational system underlied by an established though specializing network connectivity.

April 22nd, 2014 at 12:00pm

Yiğitcan Eryaman, PhD
Associate Prof. Neurobiology
Post-Doctoral Fellow at Research Laboratory of Electronics,MIT
Martinos Center for Biomedical Imaging, MGH

"Improving RF Safety in High Field MRI"

Magnetic Resonance Imaging (MRI) is a safe imaging technology that provides various clinical benefits. Basically, MRI is performed by exciting magnetic spins with radiofrequency (RF) pulses and receiving the response generated by these spins as they relax into their original state. This response is spatially encoded by using the gradient fields and converted to an actual image. Although it is not desirable, the body is exposed to an electric field during the RF excitation of the spins. The electric field distribution may cause heat dissipation in the conductive medium of body tissues. Safety problems related to such local heating arise when patients with medical implants are to be imaged using MRI. Currently, there are more than 1.5 million patients in US who have active implants (e.g., pacemakers and deep brain stimulators (DBS) ) in their bodies. 50 to 75 percent of these patients will need an MRI scan during the lifetime of their devices. Every 5 minutes, a patient is denied an MRI scan because of the safety issues related to an active implanted medical device. A solution towards improving the safety of patients with implants under MRI is crucial.

April 9th, 2014 at 12:00pm

Alayar Kangarlu, PhD
Associate Prof. Neurobiology
Department of Psychiatry, Radiology and Biomedical Engineering
Columbia University
Head of MRI Physics and Engineering
MRI Research Center
New York State Psychiatric Institute

"Magnetic Resonance in Psychiatry"

Magnetic resonance (MR) imaging has recently shown unique capabilities in characterization of psychiatric disorders. MR technologies such as voxel based morphometry (VBM), functional MRI (fMRI), magnetic resonance spectroscopy (MRS), and diffusion imaging (DTI) have shown to be capable of visualizing structural and functional manifestation of neural abnormalities and potential for characterizing their expression. MRI provides tools for in vivo examination of neuroanatomy with potential to differentiate among psychiatric and healthy subject groups. Finding the neural substrates of some psychiatric disorders is now within the reach of structural MRI. In addition, structural MRI is more potent when combined with functional and MRS studies. For example, two metabolites, GABA and glutamate have been found to be most prevalent in schizophrenia. Contrary to the early use of MRS, today’s scanners are capable of resolving glutamate-glutamine levels which sheds light on glutametergic biosynthetic pathway in schizophrenia. The great potential of fMRI lies in its ability to detect the BOLD signal in specific brain regions to identify differences of activity between brains of clinical, subclinical and healthy subjects. Arterial spin labeling has shown promise in revealing subtle brain perfusion changes occurring in psychiatric illnesses. DTI has visualized abnormalities in structural connectivity of the brain regions which in their comparison with functional connectivity maps offer a great tool for assessment of the etiology of psychiatric disorders. This talk will offer a brief discussion about MRI applications and their associated perils and payoffs in psychiatry research. In this context, the challenges in the development of the biomarkers for such use of MRI will be discussed. Potentials of MRI in providing new insight into the etiology and pathophysiology of psychiatric disorders will also be discussed.

March 27th, 2014 at 9:00am

Thomas O’Donnell, PhD
Senior Staff Scientist
CT Collaborations R&D
Siemens Healthcare

"Modelling the physics in the iterative reconstruction for transmission computed tomography,” by Johan Nuyts et al.

There is an increasing interest in iterative reconstruction (IR) as a key tool to improve quality and increase applicability of x-ray CT imaging. IR has the ability to significantly reduce patient dose; it provides the flexibility to reconstruct images from arbitrary x-ray system geometries and allows one to include detailed models of photon transport and detection physics to accurately correct for a wide variety of image degrading effects. This paper reviews discretization issues and modelling of finite spatial resolution, Compton scatter in the scanned object, data noise and the energy spectrum. The widespread implementation of IR with a highly accurate model-based correction, however, still requires significant effort. In addition, new hardware will provide new opportunities and challenges to improve CT with new modeling.

March 26th, 2014 at 12:00pm

Leo Tam, Ph.D.
Postdoctoral Associate
Magnetic Resonance Research Center
Department of Diagnostic Radiology
Yale University School of Medicine

"Nonlinear Gradient Encoding: Design and Implementation on a 3T Human Scanner"

Imaging with several detectors concurrently, known as parallel imaging, is a method to accelerate scans. However, parallel imaging encounters diminishing returns when increasing the number of detectors. Nonlinear gradient encoding allows encoding fields to complement the receiver coil detection to reconstruct equivalent images from less data. Nonlinear gradient encoding expands the encoding functions available to efficiently encode MR images. From the literature, nonlinear encoding has been shown to increase resolution in regions of the image, reduce peripheral nerve stimulation, and localize the field of view during radiofrequency excitation. Nonlinear gradient encoding and its optimization for faster images with equivalent image quality are examined. O-space imaging using the Z2 field has previously reported dispersed artifacts during accelerated scans. The inherent incoherence (distributed artifacts) of O-space imaging is explored and optimized within a compressed sensing framework. Null Space Imaging is a generalization of O-space imaging and uses an algebraic method of determining encoding fields from coil receiver profiles. Gradient hardware to perform nonlinear encoding is featured, including a 12 cm ID Z2 gradient wrist imaging insert, a 38 cm ID Z2 neuroimaging insert, and a 10 channel 20 cm ID gradient insert. The resulting body of work suggests nonlinear gradient imaging is a flexible and advantageous improvement on traditional parallel MR imaging.

March 25th, 2014 at 12:00pm

Riccardo Lattanzi, PhD
Assistant Professor of Radiology
New York University School of Medicine

"Novel tools for rational design and absolute performance assessment of MR coils"

At high and ultra-high magnetic field strengths, understanding interactions between tissues and the electromagnetic fields generated by radiofrequency coils becomes crucial for safe and effective coil design as well as for insight into limits of performance. In this work, we present a rigorous electrodynamic modeling framework, using dyadic Green’s functions, to derive the electromagnetic field in homogeneous spherical and cylindrical samples resulting from arbitrary surface currents. We show how to calculate ideal current patterns that result in the highest possible signal-to-noise ratio (ultimate intrinsic signal-to-noise ratio) compatible with electrodynamic principles. We identify familiar coil designs within optimal current patterns at low to moderate field strength, thereby establishing and explaining graphically the near-optimality of traditional surface and volume quadrature designs. We also document the emergence of less familiar patterns, e.g., involving substantial electric- as well as magnetic-dipole contributions, at high field strength. Performance comparisons with particular coil array configurations demonstrate that optimal performance may be approached with finite arrays if ideal current patterns are used as a guide for coil design.

March 18th, 2014 at 12:00pm

Alexander Leemans, Ph.D.
Associate Professor
Image Sciences Institute
University Medical Center Utrecht
The Netherlands

"The do’s and don’ts of processing and analyzing diffusion MRI data"

Abstract: "With its unique way of characterizing tissue organization, diffusion MRI (dMRI) has been used in a wide range of clinical and biomedical applications. In addition to a brief introduction to the basic concepts of dMRI, I will cover practical guidelines on quality and processing of dMRI data for subsequent analysis. Several considerations regarding dMRI limitations and data interpretation will also be presented. For relevant background information, see for instance and"

Bio: "Alexander Leemans is a physicist who received his PhD in 2006 at the University of Antwerp, Belgium. From 2007 to 2009, he worked as a postdoctoral researcher at the Cardiff University Brain Research Imaging Center (CUBRIC), Cardiff University, Wales, United Kingdom. In 2009, he joined the Image Sciences Institute (ISI), University Medical Center Utrecht, the Netherlands, where he currently holds a tenured faculty position as Associate Professor. He heads the PROVIDI Lab and is the developer of ExploreDTI, which is a graphical toolbox for investigating diffusion MRI data."

February 28th, 2014 at 12:00pm

Jan Paška, PhD student
Institute for Biomedical Engineering
University and ETH Zurich

"Modeling, Design, and Safety, of RF-Transmitters for High Field MRI"
February 25th, 2014 at 3:00pm

J. Thomas Vaughan, Ph.D.
Departments of Radiology, Electrical Engineering and Biomedical Engineering
University of Minnesota


UHF MRI requires new RF technology and methods to realize the full high field benefit to biomedical science and clinical diagnositcs. New multi-channel transmitters, receivers, and safety monitoring methods for 3T, 7T, and 10.5T are included. New approaches to these UHF challenges are being developed in Minnesota, at NYU, and at other luminary labs around the world. This talk will present some of Minnesota's work, will invite sharing from NYU's experience, and will provide a forum for mutual discussion of approaches taken by other labs. The results of this presentation and following discussions will lead to formulation of future collaborations between NYU and the UMN.

February 25th, 2014 at 12:00pm

Jeffrey Berman, Ph.D.
Assistant Professor of Radiology
The Children's Hospital of Philadelphia (CHOP) and the University of Pennsylvania, Perelman School of Medicine

"DTI and HARDI Tractography for Presurgical White Matter Mapping"

Abstract: A goal of neurosurgery is to preserve both functionally important cortices and the underlying white matter tracts. Diffusion MR tractography is a non-invasive method of visualizing the 3D course of white matter tracts. Traditional DTI fiber tracking is widely used for surgical planning, but fails to accurately represent the microstructure of crossing white matter tracts. The insufficiencies of DTI have motivated the application of high angular resolution diffusion imaging (HARDI) tractography to neurosurgical planning. This talk will describe the development, validation, and clinical utility of diffusion MR tractography for surgical planning, with an emphasis on recent HARDI techniques.

Bio: Jeffrey Berman is an Assistant Professor of Radiology at the Children's Hospital of Philadelphia (CHOP) and the University of Pennsylvania, Perelman School of Medicine. He received his PhD from the joint UC Berkeley - UC San Francisco bioengineering graduate program where he developed and validated diffusion MR techniques for surgical planning. During a postdoc at UC San Francisco, he used diffusion MR to study the developing brain of premature and term infants. At CHOP since 2010, his research interests include combining diffusion MR with MEG to study neuropsychiatric disorders such as autism and developing advanced diffusion MR tools for surgical planning.

February 12th, 2014 at 12:00pm

Mehmet Akcakaya, PhD
Instructor of Medicine, Harvard Medical School
Senior Research Scientist, Beth Israel Deaconess Medical Center

"Acceleration Methods for High-Resolution Cardiac MRI Using Compressed Sensing"

Abstract: One of the major challenges of cardiac MRI is its lengthy acquisition, which limits the achievable spatial and temporal resolutions, and volumetric coverage. In this talk, we will discuss novel compressed sensing (CS) based image reconstruction techniques used for accelerating data acquisition in cardiac MRI. We will introduce techniques that utilize patient and anatomy-specific information to improve reconstruction quality with respect to standard CS methods, as well as to state-of-the-art parallel imaging techniques. We will validate these techniques in accelerated high-resolution coronary artery and late gadolinium enhancement imaging. We will also extend these acceleration techniques to accelerated perfusion cardiac MRI with free-breathing applicability. We will conclude with a brief overview of ongoing research, as well as future research directions.

February 11th, 2014 at 12:00pm

Hersh Chandarana, MD
Assistant Professor
Department of Radiology
New York University School of Medicine

"Advanced Imaging of the Renal Cancer and Renal Function"

Renal cancers are being increasingly diagnosed incidentally. Some of these tumors are aggressive whereas others have relatively indolent course. Current morphologic imaging is limited in assessment of tumor aggressiveness. Promising MR techniques such as intravoxel incoherent diffusion weighted imaging (IVIM) and dynamic contrast enhanced (DCE) imaging will be discussed. Unsolved problems and clinical need will be highlighted. There is also need to develop and validate better techniques to assess renal function. MR techniques such as DCE, DTI, and BOLD have shown considerable early promise.

Short Bio: Dr. Chandarana is an abdominal radiologist and clinical scientist in the Department of Radiology, New York University School of Medicine, with interest in advanced oncologic and functional imaging.

February 4th, 2014 at 12:00pm

Lauren Burcaw, Ph.D.
Postdoctoral Fellow
Department of Radiology
New York University School of Medicine

"Time Dependent Diffusion in White Matter"

The sensitivity of time-dependent diffusion to the overall structure of its environment makes it appealing tool in the study of white matter fibers. Previous studies have mainly focused on increasing the q value as much as possible under a clinical system. In contrast, we vary the diffusion time, t, which allows us to probe the structure by increasing the diffusion length.
We observe via DTI measurements on a fiber phantom that the long time diffusion exhibits a unique (log t)/t dependence transverse to fibers as a result of disordered packing. This has implications in a variety of diffusion experiments such as oscillating gradients and axon diameter estimation.
This leads to the question of whether or not time-dependent diffusion is even observable on a clinical scanner. So far, the literature is inconclusive. We scan five healthy volunteers using a DTI protocol with diffusion times ranging from 26 to 400 ms and find that we indeed do see time dependence parallel and perpendicular to the axons. The effect is strongest along the axonal direction possibly indicative of heterogeneities within axonal fibers.

January 28, 2014 at 12:00pm

Dr. N. Jon Shah
Director of the Institute of Neurosciences and Medicine
Forschungszentrum Julich in Germany

"Simultaneous Multimodal Imaging: MR-PET-EEG at 3T and 9.4T"
January 21, 2014 at 12:00pm

Olivier Reynaud, Ph.D.
Postdoctoral Fellow
Department of Radiology
New York University School of Medicine

"Characterization of microvascular flow dynamics using flow-enhanced MRI"

In clinical neuroimaging, perfusion MRI is of spectacular importance to study cerebrovascular diseases and cancer. However, at the moment, there is no perfusion MRI sequence that allows for a complete, non-invasive and precise quantification of microvascular flow dynamics. This work focuses on the use of the recently introduced Flow Enhanced Signal Intensity method (FENSI) to characterize and quantify vasculature at capillary level, at high magnetic field (7T). For that purpose, the possible quantification of blood flux with FENSI is explored in vivo. The combination of flux quantification and flow-enhanced signal (compared to Arterial Spin Labeling) can make of FENSI an ideal method to characterize in a complete non-invasive way the brain microvasculature. After removal of magnetization transfer (MT) effects, the blood flow dynamics are studied with FENSI in a very aggressive and propagative rat brain tumor model: the 9L gliosarcoma. The objective is to assess whether FENSI is suitable for a longitudinal non-invasive characterization of microvascular changes associated with tumor growth. The results obtained with FENSI are compared with literature on 9L perfusion and immuno-histochemistry. functional MRI might also benefit from the development of flow enhanced MRI. With the implementation of a new MT-free FENSI technique, the possibility to map the brain cerebral functioning based on a quantitative physiological parameter (CBFlux) more directly related to neuronal activity than the usual BOLD signal is within reach. Preliminary results on rats and human brain are presented.

January 14, 2014 at 12:00pm

Jean-Christophe Brisset, PhD
Postdoctoral Fellow
Department of Radiology
Center for Biomedical Imaging
New York University Langone Medical Center

"Susceptibility Blooming Effects on High Field MR"

In recent years, there is increasing recognition of cerebral microbleeds (MCBs) in patients with cerebrovascular diseases and dementia with MRI, in particular at high-field-strength. The detection of CMBs or lesions small iron component (i.e. amyloid plaques) depends on several MRI characteristics including field strength, pulse sequence, imaging parameters, spatial resolution, iron concentration, and image post-processing. We hypothesized that using optimal imaging sequence/parameters, there is a significantly enhanced blooming effect (ie. larger area than the actual object size) at high field MR, which has potential to detect much smaller iron containing lesions or structures. In this study, we used 3D gradient-echo imaging to quantify the susceptibility blooming factor (i.e. detected size/real size of object) based on a tube phantom with different iron concentrations and post-mortem brain slices. Ultra-high-field MR (e.g. 7T) provides superb susceptibility contrast (i.e. marked blooming effects) to enhance the capability of the detection of small lesions that contain iron component. We have characterized and demonstrated the actual degree, enhanced visibility and imaging optimization of the blooming effects based on the results of phantom, simulation, and clinical images on 7T as compared to standard 3T and 1.5T MR. We investigate the use of available iron contrast agent to found the optimal parameters in a clinical perspective at high field (7T). Our results suggest that a 3D gradient echo with optimal TE and voxel size help to detect even small quantity of iron. We establish each blooming factor (measured size/actual size) for specific TE, iron concentration, or spatial resolution on 7T as compared to 3T and 1.5T. The blooming factor may provide a tool to approximate the actual size of structure even with a size even smaller than a voxel.

December 19th, 2013 2:00pm

Miriam Bredella, M.D
Associate Professor of Radiology
Musculoskeletal Imaging and Intervention Division Department of Radiology Massachusetts General Hospital
Harvard Medical School

"The Bone-Fat Connection"

Dr. Bredella's research is at the interface of radiology and endocrinology. In this talk, she will describe her work investigating the effects of different kinds of fat depots on bone density, structure, strength, and marrow fat in obesity and anorexia nervosa. She is also investigating the role of growth hormone in improving bone health and decreasing cardiovascular risk in obesity. Dr. Bredella attended medical school at the University of Hamburg in Germany. She subsequently worked for 2 years at the Osteopororsis and Arthritis Research Group at UCSF under Harry Genant. She completed her residency at UCSF followed by a musculolskeletal radiology fellowship at MGH, where she has been on staff since 2005. She is currently an Associate Professor of Radiology at Harvard Medical School. She was previously awarded an NIH K23 grant and most recently received an R01 grant focusing on skeletal dysregulation in obesity. She is also a co-investigator on an R24 grant examining the role of marrow fat.

December 13th, 2013 11:00am

BJ Casey, PhD.
Director of Sackler Institute for Developmental Psychobiology
Professor of Developmental Psychobiology
Weill Medical College of Cornell University

"Combining human imaging with mouse genetics to understand fear regulation and development"

About the speaker: BJ Casey is the Sackler Professor and Director of the Sackler Institute at Weill Medical College of Cornell University. She is a pioneer in novel uses of neuroimaging methodologies to examine behavioral and brain development. Her program of research focuses on attention and affect regulation, particularly their development, disruption and neurobiological basis. She has been examining the normal development of brain circuitry involved in attention and behavioral regulation and how disruptions in these brain systems (prefrontal cortex, basal ganglia and cerebellum) can give rise to a number of developmental disorders. Using a mechanistic approach she has dissociated attentional deficits observed across the disorders of Attention Deficit Hyperactivity Disorder, Obsessive Compulsive Disorder, Tourette Syndrome and Childhood Onset Schizophrenia.

December 10th, 2013 12:00pm

Thomas Koesters, Ph.D.
Research Scientist
Department of Radiology
Center for Biomedical Imaging
NYU School of Medicine

"Advanced PET Image Reconstruction for the Siemens Biograph mMR "

Abstract: The Siemens Biograph mMR installed in the CBI (first floor of 660 First Ave) allows simultaneous acquisition of MR and PET data. Although spatially and temporally aligned raw data is available, both modalities are often treated separately and corresponding images are only fused after independent reconstruction. This talk gives an overview of current research projects in the CBI where MR information is used to improve the PET image reconstruction. These projects include motion detection, motion correction and finally joint reconstruction of PET and MR data.

2012 - 2013: Development Engineer at GEA
2010 - 2012: PostDoc at European Institute for Molecular Imaging (Muenster, Germany)
2006 - 2010: PhD in Mathematics at WWU (Muenster, Germany)
2001 - 2006: Mathematics at WWU (Muenster, Germany)

December 3rd, 2013 12:00pm

Ileana Jelescu, Ph.D.
Postdoctoral Fellow
Department of Radiology
NYU School of Medicine

" Magnetic resonance microscopy of Aplysia neurons: studying neurotransmitter-modulated transport and response to stress"

Recent progress in MRI has opened the way for micron-scale resolution, and thus for imaging biological cells. The goal of my thesis work was to perform magnetic resonance microscopy (MRM) on the nervous system of Aplysia californica, a model particularly suited due to its simplicity and to its very large neuronal cell bodies, in the aim of studying cellular-scale processes with various MR contrasts. Experiments were performed on a 17.2 T horizontal magnet, at resolutions down to 25 µm isotropic. Initial work consisted in conceiving and building radiofrequency microcoils adapted to the size of single neurons and ganglia. The first major part of the project consisted in using the manganese ion (Mn2+) as neural tract tracer in the nervous system of Aplysia. We performed the mapping of axonal projections from motor neurons into the peripheral nerves of the buccal ganglia. We also confirmed the existence of active Mn2+ transport inside the neural network upon activation with the neurotransmitter dopamine. In the second major part of the project, studied the changes in water ADC at different scales in the nervous system, triggered by cellular challenges. A 3D Diffusion-Prepared FISP sequence was first implemented, which met criteria for high resolution in a short acquisition time, with minimal artifacts. Using this sequence, ADC measurements were performed on single isolated neuronal bodies and on ganglia tissue, before and after two types of challenge (hypotonic shock and ouabain). Both types of stress produced an ADC increase inside the cell and an ADC decrease at tissue level. The results favor the hypothesis that the increase in membrane surface area associated with cell swelling is responsible for the decrease of water ADC in tissue, typically measured in ischemia or other conditions associated with cell swelling.

November 26th, 2013 12:00pm

Andrew Maudsley, Ph.D.
Professor of Radiology
Miller School of Medicine
University of Miami

"Whole Brain Metabolite Imaging"

MR spectroscopic measurements of human brain are commonly limited to small regions to minimize difficulties associated with magnetic field inhomogeneities and lipid contamination; however, several clinical applications could greatly benefit from obtaining MRS measurements over larger brain volumes, including for example, measurement of diffuse tissue injury with traumatic brain injury, characterization of tumor volumes for therapy planning, and localization of neocortical epilepsy. This presentation will review some of the experimental approaches that can be used to extend the measurement volume for MR spectroscopic imaging, and show examples of clinical applications of these methods.

November 19th, 2013 12:00pm

Valentin Riedl, MD, PhD
Department of Neuroradiology and Nuclear Medicine
TUM-Neuroimaging Center
Klinikum Rechts der Isar der Technischen Universität München (TUM), Germany

"How does multimodal brain imaging advance our understanding of large-scale brain networks?"

Recent functional magnetic resonance imaging (fMRI) revealed organized activity in the brain at rest which gained enormous relevance for systems and clinical neuroscience. Particularly, this organized activity is defined by synchronous, low frequency (<0.1Hz) fluctuations of the blood-oxygenation-level-dependent (BOLD) fMRI signal between remote brain areas, termed resting-state functional connectivity (rs-FC). However, the neurophysiological and metabolic underpinnings of rs-FC are still incompletely understood. In this talk I will summarize recent findings of rs-fMRI and present first data of simultaneous PET/MR imaging in humans indicating a neuronal basis of resting state FC.

November 5th, 2013 12:00pm

Ryan Brown
Assistant Professor
Department of Radiology
Center for Biomedical Imaging
New York University Langone Medical Center

"Adventures in 3D Printing"

CBI's RF lab (second floor of 660 First Ave) houses a 3D printer that provides the capability to build a wide range of MRI compatible fixtures. This talk is aimed at educating potential users on the printer's general capabilities for rapid prototyping. Specifications on CAD software, build-size, resolution, and print speed will be reviewed in the context of objects designed at CBI during the past year. While many of the examples are hardware-related fixtures such as anatomically-correct and aesthetically-pleasing RF coil formers, it is anticipated that the lecture will spark interest in a more expansive range of applications.


October 30, 2013 12:00pm

Rainer Schneider
Institute of Biomedical Engineering and Informatics
Ilmenau University of Technology
Ilimenau, Germany

"Multi-slice pTX pulse design for local signal recovery"

For compensating the signal loss in GRE-based sequences induced by through-plane susceptibility, two state-of-the-art techniques using the parallel transmit technology (pTX) were analyzed. Both approaches, the tailored 3-dimensional RF pulses (3DTRF) and time-shifted spokes excitation, were implemented on the 3T Skyra system with two integrated whole-body transmit channels. The methods were extended and evaluated with human in-vivo experiments.


September 24, 2013 12:00pm

Jelle Veraart
Vision Lab, University of Antwerp
Antwerp, Belgium

"Accurate estimation of diffusion MRI parameters"

Diffusion magnetic resonance imaging (dMRI) is currently the method of choice for the in vivo and non-invasive quantification of water self-diffusion in biological tissue. Several diffusion models have been proposed to obtain quantitative diffusion parameters. Those parameters might provide novel information on the structural and organizational features of biological tissue, the brain white matter in particular. However, an accurate and precise estimation of those diffusion parameters remains challenging because of the non-Gaussian MR data distributions. Indeed, widely used estimator – e.g. the class of least squares estimators – will show systematic errors in the estimation of diffusion measures because the actual data statistics are not taken into account. The squashing of the ADC peanut or the overestimation of the kurtosis metrics are typical examples of such, so called, noise artifacts. During the seminar, an overview of the commonly used parameter estimators will be given. Their strengths and limitations will be discussed. In addition, a comprehensive framework for accurate diffusion MRI parameter estimation will be introduced.


September 17, 2013 12:00pm

Lisa Mosconi, PhD
New York University School of Medicine
New York, New York

"Preclinical Detection of Alzheimer’s Disease Using Brain Positron Emission Tomography Imaging"

The development of biomarkers for the preclinical detection of Alzheimer’s disease (AD) is a vital step in developing prevention therapies. For many years, we and others have been using biological markers of AD pathology and its effects on brain structure and function to characterize early changes in presymptomatic individuals at risk for AD. Such markers include in vivo brain Magnetic Resonance Imaging (MRI); Positron Emission Tomography (PET) imaging using 2-[18F]fluoro-2-Deoxy-D-glucose (FDG) and N-methyl[ 11C]2-(4'-methylaminophenyl)-6-hydroxy-benzothiazole (PiB) as the tracers to measure glucose metabolism and fibrillar amyloid-beta (Aß) deposition, respectively; cerebrospinal fluid levels of Aß1-40 and 1-42, tau pathology (total tau and hyperphosphorylated tau231) and inflammation (F2-isoprostanes); and recently plasma measures of oxidative stress (activity of mitochondria cytochrome oxidase, electron transport chain complex IV, COX).
This lecture will give an overview of biomarker findings in individuals at risk for AD, with the main focus on presymptomatic individuals carrying genetic mutations responsible for early-onset familial AD and cognitively normal (NL) people with a first degree family history of LOAD. Overall, these studies have shown that it is possible to identify and track biomarker changes prior to cognitive impairments arise and along with AD progression. All told there is considerable promise for an early and specific diagnosis of AD by assessing biomarkers in NL individuals at risk for AD.


August 20, 2013 12:00pm

Dikoma C. Shungu, PhD
Professor of Physics in Radiology
Weill Medical College of Cornell University
New York, New York, USA

"In Vivo Proton MRS Measurement of Cortical GABA, Glutamate and Glutathione: Methods and Selected Clinical Research Applications"

The most widely investigated neurochemical hypotheses of major psychiatric disorders now posit neurodevelopmental deficits that involve, among others, dysregulations of the inhibitory and excitatory amino neurotransmitter systems of gamma-Aminobutyric acid (GABA) and glutamate (Glu), respectively. Glutathione (GSH) is a major intracellular antioxidant and redox regulator, whose dysregulations and in vivo deficits have been implicated in various neurological, neuropsychiatric and neurodegenerative disorders. Currently, proton magnetic resonance spectroscopy (1H MRS) is the only noninvasive neuroimaging technology that offers the possibility to investigate abnormalities in GABA, Glu and GSH in the living human brain. In this presentation, our decade-long experience in developing and optimizing the relevant MRS technology will first be described, and then the full power and growing importance of the technology in biomedical and neuroscience research will be illustrated with selected clinical applications in neuropsychiatry and neurology.


July 30, 2013 12:00pm

Chao-Gan Yan, PhD
Nathan Kline Institute for Psychiatric Research,
Child Mind Institute, and
New York University Child Study Center

"Resting-state fMRI: Algorithms, Applications to Brain Disorders and Data Processing"

Resting-state functional magnetic resonance imaging (R-fMRI) has emerged as a mainstream imaging modality with myriad applications in basic, translational and clinical neuroscience. Beyond impressive demonstrations of accuracy, reliability and reproducibility for measures of intrinsic brain function, this approach has gained popularity due to its sensitivity to developmental, aging and pathological processes, ease of data collection in otherwise challenging populations, and amenability to aggregation across studies and sites. In this talk, I would like to introduce the principles, computational algorithms and methodological issues of R-fMRI as well as its clinical application to brain disorders (e.g., Alzheimer's disease). Finally, I would like to demonstrate the data processing of R-fMRI with our convenient pipeline toolbox DPARSF.


July 29, 2013 12:00pm

Kristian Bredies, PhD
Institute for Mathematics and Scientific Computing
University of Graz

"Variational modelling with total generalized variation"

We discuss the recently introduced total generalized variation (TGV) which is a well-suited regularizer for variational imaging problems. In addition to the well-known total variation (TV), it does not only model free discontinuities but is also aware of higher-order smoothness. It can be interpreted as a regularizer which adaptively selects the appropriate smoothness level.
After studying basic properties of the TGV functional, we show how abstract methods for finding convex-concave saddle point problems can be applied to solve variational imaging problems with TGV-regularization. Several applications are presented, ranging from basic imaging problems like denoising and deconvolution to applications in MRI, CT and compressed sensing.
Finally, we show the potential of general measure-based regularization beyond TV and TGV. In particular, convex regularization functionals are discussed which are able to count vertices and edges. Furthermore, their application to the reconstruction of elongated structures is presented.


July 17, 2013 12:00pm

Prof. Haim Azhari
Associate Professor
Department of Biomedical Engineering
Technion-Israel Institute of Technology

"Improving PET Imaging"

PET is a powerful modality in medical imaging. However, its spatial resolution is very poor compared to other major modalities (CT, MRI and Ultrasound). The challenge is to improve PET image quality without inserting any physical changes in the scanner hardware. In this lecture two approaches will be introduced. The first approach is to implement super-resolution strategy. With super-resolution several low resolution images are acquired, where each image is shifted by a sub pixel distance relative to the other. An algorithm is then implemented to combine the information and produce a high resolution image. The second approach is implemented on data acquired by a hybrid PET-CT scanner. The images obtained from the CT are fused with the images obtained from the PET using an algorithm called "Hybrid Computerized Tomography (HCT)". The obtained images depict sharp border PET distribution.


June 19, 2013 9:00am

Nicole Seiberlich, PhD
Assistant Professor
Biomedical Engineering
Case Western Reserve University and Biomedical Engineering

Vikas Gulani, MD, PhD
Assistant Professor
Director of MRI
Departments of Radiology, Urology
Case Western Reserve University

"Pushing the Limits: Novel Acquisition and Reconstruction Strategies for Rapid Quantitative MRI"


June 13, 2013 9:00am

Gregory Metzger, PhD
Associate Professor
Department of Radiology
University of Minnesota

"Developing MRI biomarkers of prostate cancer aggressiveness and UHF body imaging"


May 28, 2013 12:00pm

Assaf Tal, PhD
NYU Langone Medical Center

"Short echo time spectroscopy in the human brain via Hadamard Encoding at 3T"

Abstract: "Magnetic resonance spectroscopy is used routinely to measure metabolite concentrations in the human brain. Due to fast relaxation times and complex J-coupling patterns, many of the most important metabolites observable with spectroscopy - such as GABA and Glutamine/Glutamate - are difficult to discern using standard spectroscopic techniques. In this talk, I will argue why short echo times (<10 ms) offer significant benefits when trying to image such metabolites, why in-vivo spectroscopy has only fairly recently begun exploring these possibilities, and present our own approach for doing so using radiofrequency Hadamard pulses.
I will also briefly discuss two other projects which may be of interest to other researchers at the CBI: our approach to dealing with B0 field drifts, as well as our approach to analyzing global white/grey matter metabolite concentrations."

Short bio: "Assaf Tal obtained his BSc in physics from the Hebrew University in Israel, and his PhD from the Weizmann Institute of Science in Israel with Prof. Lucio Frydman in the field of liquid state NMR, where he has done work on single-scan methods in 2D NMR as well as fast imaging methods based on quadratic spin phase. His current post-doctoral research in the lab of Oded Gonen focuses on developing new sequences and processing methodologies for in-vivo human brain spectroscopic imaging."


May 15, 2013 12:00pm

Sanjeev Chawla, PhD
Research Associate
Department of Radiology, University of Pennsylvania

"MR Imaging and Spectroscopy in Brain Infections, Brain Tumors and Head and Neck Cancers"

Abstract: Non-invasive differentiation of brain abscesses such as pyogenic and tuberculous, anaerobic and aerobic or sterile is essential for facilitating prompt and appropriate treatment of patients. MR spectroscopy and magnetization transfer MR imaging may be used to characterize intracranial cystic lesions with similar features on conventional MR imaging. Precise MR imaging correlation of different stages of neurocysticercosis with histopathology is essential for better understanding of the disease that is usually hampered by complexities in performing such studies on humans. Therefore, detailed correlative MR imaging and histopathological studies on pigs infected with neurocysticercosis are warranted.

Given the heterogeneous nature of neoplastic lesions and inherently different physiological information provided by different MR pulse sequences, multi-parametric data analysis may be a better approach in differential diagnosis, predicting prognosis, monitoring treatment response in brain tumors and head and neck cancers with greater accuracy. Combined use of MR spectroscopy and perfusion weighted imaging may be used to distinguish histological grades, histological subtypes and genetic profiles of the gliomas.


May 10, 2013 12:00pm

Evren Ozarslan, PhD
Lecturer on Radiology
Department of Radiology, Brigham and Women’s Hospital, Boston, MA

"Recent advances in diffusion-weighted MRI: From multi-pulse experiments to new analysis schemes."

Conventional magnetic resonance (MR) imaging scans suffer from limited resolution that prohibits the visualization of individual cells thus providing information at coarse length scales. To obtain information at smaller length scales, the MR signal can be sensitized to self-diffusion of water molecules whose motional history is influenced by the local microstructure. I will present several new developments in the field of diffusion-weighted MRI. Emphasis will be given to the multiple pulsed field gradient techniques, which could be used to characterize the local microstructural features of the medium without the need to employ strong magnetic field gradients. In the second part of the talk, I will describe the recently introduced mean apparent propagator (MAP) MRI technique, which is a comprehensive computational framework that could be employed to address a number of challenges encountered in the analysis of diffusion-weighted MRI data.

About the speaker: Evren Özarslan is a research associate at Brigham and Women's Hospital and holds a concurrent academic appointment at Harvard Medical School (HMS). Before joining HMS, Dr. Özarslan performed research at the Section on Tissue Biophysics and Biomimetics (STBB), NICHD, National Institutes of Health (NIH) first as a postdoctoral fellow, then as a scientist with the Center for Neuroscience and Regenerative Medicine (CNRM) and the Henry M. Jackson Foundation. He graduated with a Bachelor of Science in Physics from the University of Illinois at Urbana-Champaign, and obtained his M.S. degree in Biomedical Engineering and Ph.D. in Physics, both from the University of Florida. His current research is on modeling diffusion in biological tissue and other porous media with the specific aim of characterizing the microstructure of the specimen using noninvasive magnetic resonance techniques.


April 30, 2013 12:00pm

José P. Marques
Department of Radiology, University of Lausanne
Switzerland Functional and Metabolic Imaging Laboratory, EPFL, Switzerland

"Imaging with inhomogeneous RF fields: avoiding, fighting and making the most of them"



April 16, 2013 12:00pm

Christopher M. Collins, PhD
Professor of Radiology
NYU Langone Medical Center

Use of high-permittivity materials to enhance coil performance in MRI

In a growing number of studies and applications, strategic selection and placement of passive high-permittivity materials are shown to improve SNR and/or reduce required transmit power in imaging a select region of interest. We will discuss some basic mechanisms by which high-permittivity materials can improve RF efficiency in MRI and review a variety of cases where they have been demonstrated to do so.


April 5, 2013 12:00pm

Daniel S. Weller, Ph.D.
University of Michigan

Sparse Modeling for Magnetic Resonance Imaging

In this talk, I discuss my research concerning sparse modeling for magnetic resonance imaging. First, I elaborate on three methods for using sparsity to improve upon GRAPPA, an autocalibrating reconstruction method for accelerated parallel imaging. These three methods (1) denoise the reconstructed k-space, (2) regularize the calibration of the GRAPPA kernels, and (3) jointly estimate the full k-space and GRAPPA kernels using prior and likelihood models.

All these methods make use of fixed parameters that control the regularization. While hand-tuning these methods may be possible, we desire an automatic parameter selection method that would work for data-preserving reconstructions. To this end, I introduce Stein's Unbiased Risk Estimate and describe how I extend it to data-preserving regularized parallel imaging reconstructions.

I follow this discussion by outlining my current research exploiting sparsity to prospectively correct for head motion in functional MRI. I demonstrate that this usage of sparsity allows for high-quality time-series correlation analysis in the presence of head motion.


April 2, 2013 12:00pm

Susumu Mori, Ph.D.
Professor, Department of Radiology
Johns Hopkins University School of Medicine, Baltimore, MD

Multi-Modal Image Analysis Based on Atlas-Based Spatial Filtering and Cloud-Based Analysis System

One of the most challenging aspects of image analysis is the overwhelming amount of spatial information. For example, typical T1-weighted image with 1mm resolution contains more than 1 million voxels, each of which carry noisy information. Cross-contrast (e.g. T1 and DTI) and cross-modality (e.g. MRI, MRS, fMRI, PET) data integration have been postulated as potentially a powerful approach to delineate anatomical and functional phenotype of patient populations, which would lead to further increase in spatial information with different coordinate frames and, thus, a systematic reduction of the spatial dimension seems an essential and inevitable requirement. This presentation will introduce our current effort to establish a modern MRI atlas system and associated software tools to perform atlas-based image analysis, in which the entire spatial information is reduced to approximately 200 pre-defined structures. For demonstration, integrative analyses of anatomical MRI, DTI, MRS, and rs-fMRI data and clinical applications will be shown. The automated pipeline for the atlas-based analysis is currently being deployed using a cloud-based architecture for dissemination and future direction of the service model will also be discussed.


March 26, 2013 12:00pm

Pablo Velasco, Ph.D.
Senior Research Scientist/Chief MR Physicist
New York University
Center for Brain Imaging

Real-Time Data-Quality Monitoring of fMRI Data

Functional MRI data quality can be compromised by a series of factors --especially motion and spikes-- which are hard to assess until you start processing your data, well after the scanning session is over. By that time, your subject is gone and you might find you are left with too little data to be able to include that subject in your analysis. I will present the implementation of a real-time data-quality monitoring tool that reconstructs the images, estimates motion parameters and some other statistics on them and displays them on the screen as they are being acquired, so that users can repeat those runs with excessive motion or with spikes, and give feedback to the subject on how well he or she is avoiding motion in the scanner.


March 5, 2013

Dr. Gisele Caseiras, M.D., Ph.D.
PhD in Neuroradiology at University College London-UCL, London England

The use of Conventional and Advanced Magnetic Resonance Technique in the Assessment of Primary Brain Tumours

Low-grade gliomas in adults are diffusively infiltrating tumours that may undergo malignant transformation into high-grade gliomas. This malignant transformation is highly variable and difficult to predict in an individual patient. The purpose of this study was to investigate the value of conventional and advanced magnetic resonance imaging in patients with histology-proven low-grade gliomas and the potential role of these methods as markers of malignant transformation.


February 26, 2013

Leeor Alon
Doctoral Candidate
The Sackler Institute of Graduate Biomedical Sciences
New York University School of Medicine, NY

A New Application for MR - Safety Testing of RF Emitting Devices

By the end of 2012, the number of mobile-connected devices will exceed the number of people on Earth, and by 2016 there will be 1.4 mobile devices per capita." -Cisco VNI Mobile 2012.

Radio frequency (RF) emitting wireless devices such as mobile phones are required to undergo standardized safety testing prior to entering the consumer market. Strict regulations are imposed on the amount of RF energy these devices are allowed to emit to prevent excessive deposition of RF energy into the body. In this presentation, a novel safety evaluation test for wireless devices using magnetic resonance (MR) thermometry is proposed.


February 5, 2013

Uri Nevo, PhD
Senior Lecturer and Director
Laboratory of Cellular Biophysics and Imaging
Tel-Aviv University, Israel

Studying the cellular origins of Diffusion Weighted NMR

Diffusion Weighted NMR (DW-NMR) of tissues characterizes two linked cellular properties: microstructure and viability. DW-NMR in cells is affected by structures that restrict and hinder diffusion. Following brain insults, such as ischemia, water displacement is attenuated and is commonly linked to microstructural changes affecting diffusion. Water displacement is linked not only to microstructure but also to cellular viability and function, as in the case of neuronal activity that is suggested to be correlated with restricted diffusion.

We attempt to quantify the different components of water displacement in cells, in order to obtain an accurate characterization of cells' microstructure and function. In the coming lecture I will first describe our method for quantifying pore size distribution, towards the characterization of cells' sizes. This is done by the use of a double pulsed field gradient experiment, in which gradient pairs are varied by amplitude and direction.

A central hypothesis in our research is that diffusion is not the only component of displacement in cells: we suggest that a significant component of water displacement in neurons is that of actively induced micro-streaming. I will describe our theoretical and experimental work aiming to quantify the relation of function and micro-streaming inside neurons. This is done by using biophysical models and by DW-NMR of isolated and viable neural tissues. I will end by speculating the possible implications of our work on brain function study.


January 29, 2013

Manushka Vaidya
Doctoral Candidate
The Sackler Institute of Graduate Biomedical Sciences
New York University School of Medicine

Understanding and manipulating B1 field distribution inside a dielectric object

The first part of the talk will cover the dependence of the B1 spatial distribution on the electrical properties of the sample and the magnetic field strength. Unanticipated B1 field patterns may be encountered during simulation and experiments, particularly at high operating frequencies. While a distinctive curling of the B1 field is observed at high field strengths, elaborate checkerboard-like patterns may be obtained for certain dielectric samples. In this work, we use full-wave electrodynamic simulations based on dyadic Green's functions to study the effect of the electrical properties of the sample and main magnetic field strength on the B1 field pattern inside a uniform cylindrical object. We show examples of the curling of the field and interference patterns near resonance, providing a conceptual explanation for each case.

In the second half, manipulation of the B1 field distribution inside a sample by placing dielectric pads at a distance from a surface transmit coil will be discussed. The use of dielectric pads between the radiofrequency (RF) coil and sample has been proposed to "focus" the B1 field into the sample to improve transmit efficiency. In this study, we investigated how dielectric pads placed at a distance from the RF coil affect the B1+ spatial distribution inside the sample. We performed numerical simulations of the B1+ distribution inside a uniform cylinder at 7T for various positions of the dielectric pad with and without a surrounding shield. Manipulating B1 spatial distribution with dielectric pads can be advantageous for various MR applications, including improving RF homogeneity at ultra-high fields


January 15, 2013

Dmitry Novikov, PhD
Assistant Professor of Radiology
The Bernard and Irene Schwartz Center for Biomedical Imaging
New York University Langone Medical Center, NY

Characterizing microstructure of living tissues with time-dependent diffusion

A major challenge of in vivo MR is to characterize tissue microstructure at the cellular level, orders of magnitude below the imaging resolution. I will show how a diffusion measurement, taken at a range of diffusion times, can distinguish between different classes of microgeometry. Based on the specific values of the dynamical exponent of a velocity autocorrelator measured with diffusion MRI, we identify the relevant tissue microanatomy in muscles and in brain, quantify cell membrane permeability in muscles, and reveal the microstructural changes driving the diffusivity drop in ischemic stroke. Our framework presents a systematic way to identify the most relevant part of structural complexity with diffusion.

January 10, 2012

Giselle A. Suero-­‐Abreu, MD, MS
Doctoral Candidate
The Slacker Institute of Graduate Biomedical Sciences
New York University School of Medicine, NY


Significant progress has been made in our understanding of the pathogenesis of brain tumors partly due to the development of genetically engineered mouse models that recapitulate the human disease. In this regard, in vivo micro-­‐MRI protocols are powerful tools for the non-­‐invasive, three-­‐dimensional (3D) characterization of these preclinical cancer models and are gradually being recognized as an integral part of basic and translational brain tumor research. In our study, we optimized an in vivo high resolution Manganese-­‐Enhanced MRI protocol (MEMRI) for the characterization of tumor progression in a novel mouse model of Medulloblastoma (MB), the most common malignant pediatric brain tumor originating in the cerebellum (Cb).

In this talk, I will present the characteristics of our tumor model and show that our imaging approach successfully allowed the detection of early tumoral lesions and the longitudinal assessment of their progression into advanced-­‐stage tumors. Furthermore, I will discuss recent results which indicate that these tumors display at least two distinct molecular and imaging features. Ultimately, we are interested in correlating these findings with the clinical and imaging characteristics of human MBs and we expect to draw insights that inform the design of studies to test current and novel drug therapies using this unique pre-­‐clinical model.


February 9, 2012

Tracy Butler, MD
Assistant Professor of Psychiatry and Neurology
Epilespsy Center
New York University Langone Medical Center, NY

Neuroreceptor PET and PET/fMRI: proposed and ongoing projects in epilepsy and neuropsychiatry

In addition to her proposed research, she will also present her ideas as to why simultaneous imaging of PET and MRI is so exciting..


February 13, 2012

Sharmila Majumdar, PhD
Professor of Radiology and Biomedical Imaging
School of Medicine
University of California, San Francisco, CA


Osteoarthritis (OA) is a degenerative disease that is characterized by cartilage thinning and compositional changes, and it is estimated that 20 million individuals in the United States are living with the disease with an annual cost of over 15 billion dollars.

The disease preferentially affects older (> 65 years) individuals, but with traumatic injury such as anterior cruciate ligament injury being a risk-­‐factor, 1 in 20 working age (18-­‐64 years old) adults report activities being limited by arthritis. Despite the recognition that 3D imaging is likely to provide important information regarding joint health, OA, and that biomechanics plays a role in OA and its' progression, the translation and cross-­‐correlation of these metrics have been limited.

The overall objective of this talk is to integrate cutting edge quantitative imaging technologies, link the image derived metrics to joint kinematics, kinetics, patient function, and translate the linkages found to the musculoskeletal clinic, thus affecting patient management and outcome


February 28, 2012

Gadi Goelman, PhD
Associate Professor of Medical Biophysics
The Hebrew University of Jerusalem, Israel

Coherent low frequency fluctuations of the BOLD signal in resting state (rest-fcMRI) were shown to contain functional neuronal network information. Resting-state networks (RSN) exhibit positive correlations between the regions that constitute the network, suggesting a functional link between them. However, several RSNs were shown to have an inverse correlation between each other. The underlying physiological mechanisms and the relevance of negative correlations to neurobiology are not clear and are the subject of this study.

We compared human and rat rest-fcMRI data, making use of both the similarities (e.g., similar organization: cortical vs. non-cortical structures, inter-hemispheric symmetry etc.) and differences (e.g., different hemodynamic characteristics such as cardiac rates and spatial distances) between them. In addition, the fact that the rats' cortex is relatively unfolded, enables to minimize confounding effects of CSF and large blood vessels on the rest-fcMRI correlations.

We show that: (i) Negative correlations observed in rest-fcMRI reflect true physiological traits and are not the mere result of mathematical biases introduced by data analysis. (ii) At least two distinct mechanisms may underlay the appearance of negative correlations, reflecting the actual synchronization between regional neural activities on the one hand and their manifested BOLD signal responses on the other hand. (iii) The variant involvement of CBV in the hemodynamic responses of two different regions may introduce such negative correlations.


March 13, 2012

Tobias Block, PhD
Assistant Professor of Radiology
Center for Advanced Imaging Innovation and Research
New York University Langone Medical Center, NY

Iterative Reconstruction Concepts for Magnetic Resonance Imaging

Iterative reconstruction techniques are currently getting popular in the MRI community because they enable to reconstruct images from highly incomplete data, which can be exploited to skip acquisition steps and, thus, to reduce the scan time. This talk will first give a step-by-step introduction to the reconstruction technique and demonstrate how the technique can be applied for MRI data. The second part will discuss four application examples to illustrate the advantages over conventional methods. These advantages arise from two main components that inherently compensate for incompletely sampled data: First, the ability to incorporate prior knowledge about the object and, second, the ability to extend the signal modelling for advanced pulse sequences and acquisition techniques.

In the first example, it is shown that the higher sampling requirement for radial k-space sampling can be ameliorated with a constraint on the solution's total variation (TV), based on the assumption that many objects are piece-wise constant to some degree. Further, by extending the signal model to account for varying sensitivities of the receive coils, all channels can be processed simultaneously in a parallel imaging manner. In example 2, the concept is extended for radial fast spin-echo imaging where spokes with increasing T2 weighting are acquired along the echo train. When adding a spatial relaxation component to the signal calculation, the iterative approach is able to model these contrast inconsistencies and renders a proton-density map and a relaxation map directly from k-space, which can be used for fast T2 quantification.

In example 3, the signal model is extended to calculate the coil sensitivities jointly with the image content during the reconstruction, which offers improved parallel-imaging quality. Because in this way all sampled data is included for estimation of the coil profiles instead of only few reference lines, the method yields artifact-free images in conditions where conventional parallel-imaging reconstructions already show spurious aliasing artifacts. Finally, the last example combines the above ideas with a temporal constraint on sequentially acquired time frames. For measurements with an optimized radial real-time sequence, the technique achieves temporal resolutions of up to 20 ms and yields cinematic insight into the human body.


March 20, 2012

Jason P. Lerch, PhD
Assistant Professor of Medical Biophysics
Hospital for Sick Children
University of Toronto, Canada

Why do our brains differ so much? Using mouse imaging to understand variations in neuroanatomy in normal development and autism

A striking feature of any imaging study is just how much variability there is in brain shapes and sizes. This is especially the case in autism spectrum disorders, where the heterogeneity of the disease has resulted in a plethora of conflicting findings. In this talk I will use brain imaging in the mouse, where we have much tighter control over genetics and the environment, to illustrate both how different genetic mutations related to autism can lead to similar behavioural outcomes yet divergent neuroanatomical alterations as well as how the environment, learning, and memory can themselves change local brain shape.


March 27, 2012

Els Fieremans, PhD

Assistant Professor of Radiology
The Bernard and Irene Schwartz Center for Biomedical Imaging
New York University Langone Medical Center, NY


Assessment of white matter microstructural integrity with non Gaussian diffusion MRI

Diffusion MRI is a powerful tool to characterize brain white matter microstructural and architectural tissue organization. Diffusional kurtosis imaging (DKI) is a clinical feasible diffusion MRI method that quantifies the non-Gaussian diffusion properties in biological tissue through estimation of the diffusional kurtosis. In this talk, I will present a specific white matter model that allows for a direct physical interpretation of the non-Gaussian signal in terms of specific white matter microstructural integrity metrics, such as the axonal water fraction and intra- and extra-axonal compartmental diffusivities.

Next, I will discuss how these white matter integrity markers may serve as specific and sensitive biomarkers useful to study both healthy development and a variety of pathological conditions. In particular, our initial findings in human ischemic stroke and Alzheimer's disease illustrate how investigating changes in these white matter metrics reveal new insights in the underlying pathophysiology.


April 23, 2012

Hanzhang Lu, PhD
Associate Professor
Advanced Imaging Center
University of Texas Southwestern Medical Center, TX

A turn-key solution for the measurement of brain oxygen metabolism

We propose a procedure to measure global CMRO2 by combining several non-invasive measures obtained from MRI and pulse oximetry. A key technique of this procedure is a T2-Relaxation-Under-Spin-Tagging (TRUST) technique for the determination of global venous oxygenation. The TRUST MRI technique applies the spin labeling principle on the venous side and acquires control and labeled images, the subtraction of which yields pure venous blood signal. T2 value of the pure venous blood was then determined using non-selective T2-preparation pulses, minimizing the effect of flow on T2 estimation. Further technical considerations were made by using composite RF pulses and RF phase cycling in the T2-preparation.

We have measured Yv in both superior sagittal sinus (SSS) and internal jugular vein (IJV). Both measures yielded results consistent with expected venous values (50-75%) and, furthermore, a strong correlation was observed between them (P=0.0015), which is in agreement with the drainage path of venous blood. CMRO2 was estimated using TRUST and phase-contrast. Studies of intra-session and inter-session reproducibility of the CMRO2 measurement were conducted in seven subjects (26.4±4.0 years, 3 males and 4 females) and each subject underwent 5 sessions on different days. Intra-session and inter-session Coefficient of Variation (CoV) was 2.8±1.3% and 5.9±1.6%, respectively, suggesting a high reproducibility of this technique.

The dependence of CMRO2 on age was evaluated in our recent study. Average CMRO2 of typical 20-year-old subjects is approximately 164.1 µmol/100g/min and it increases with age at a rate of 2.6µmol/100g/min per decade, suggesting a reduced brain energy efficiency with age. We have also studied CMRO2 in an early stage of Alzheimer's Disease (AD) called Mild Cognitive Impairment (MCI) (Clinical Dementia Rating, CDR=0.5). In collaboration with the UTSW Alzheimer's Disease Center, we recruited 18 MCI patients (age 67±7 years) and 19 elderly controls (68±7 years). It was found that CMRO2 in MCI patients was 151.3±26.4 µmol/100g/min (mean±SD), which was significantly lower (P=0.04) than that of the control group (171.2±29.6 µmol/100g/min), suggesting that CMRO2 may be a sensitive marker for Alzheimer's Disease


June 19, 2012

Dung Minh Hoang
Doctoral Candidate
University of Lyon-1, France

The Filling Factor Redefined: Determining the Dominant Sensitivity Driver of a Flat Histology Slide RF Coil

This work investigates the relative gain in sensitivity of a set of five histology coils designed in-house compared to a circularly polarized (CP) mouse head birdcage coil (L=29-mm x ID=28-mm). The dimensions of these coils were tailored to fit tissue sections ranging from 5-µm to 100-µm when mounted on either standard glass slides and/or coverslips. Our simulations and experimental measurements demonstrate that the sensitivity of this flat structure underperforms by a factor of two relative to the CP birdcage coil based on the expected gain in their filling factor ratios. Despite the inevitable dielectric losses attributed to this capacitor-like shape resonator, our results demonstrate that the overall net increase in filling factor overcomes the current leaks inherent to this structure.

Surprisingly, this leads to an enhancement in sensitivity of up to seven-fold for the smallest structure constructed (W=12-mm x L=24-mm x H=0.45-mm). Alternatively, the largest histology coil design (W=52-mm x L=48-mm x H=1.35-mm) enables two times wider radiofrequency flat coverage at equal sensitivity to the CP birdcage. Examples of tissue sections from both mouse organs and human specimens acquired during overnight experiments illustrate the level of detail observed and the near-perfect co-registration with optical microscopy.


September 11, 2012

Steven Baete, PhD
Post-Doctoral Fellow
The Bernard and Irene Schwartz Center for Biomedical Imaging
New York University Langone Medical Center, NY

(Dynamic) Multiple Echo Diffusion Tensor Acquisition Technique (MEDITATE) in a 3T clinical scanner

Diffusion tensor imaging (DTI) provides biomarkers of tissue anisotropy and microstructure (principal diffusivities, mean diffusivity (MD) and fractional anisotropy (FA)), which have many applications in oriented biological tissue (e.g. neural fibers, renal tubules, muscle fibers). One route of acceleration of the multidirectional sampling required for DTI is multiple echoes. This presentation will describe progress in our use of this strategy to construct a dynamic DTI acquisition mode.

The first part of this talk will cover the feasibility of a two-scan Multiple Echo Diffusion Tensor Acquisition Technique (MEDITATE) on a clinical system for muscle DTI. In the MEDITATE-sequence, a pattern of diffusion gradients between the multiple RF-pulses encodes a train of echoes with each a different diffusion weighting and direction sufficient to estimate the 3D diffusion tensor. The work presented in this talk extends the original MEDITATE-approach, previously employed in preclinical settings, by exploiting longitudinal magnetization storage to reduce T2-weighting and optimizing a two-shot full tensor encoding within the clinical scanner hardware regime. Spin-warp phase encoding is used for image encoding. MEDITATE was tested on isotropic (agar gel) and anisotropic diffusion phantoms (asparagus), and in vivo skeletal muscle in healthy volunteers with cardiac-gating. Good quantitative agreement was found between diffusion eigenvalues, mean diffusivity, and fractional anisotropy derived from standard twice-refocused spin echo (TRSE) EPI-DTI and from several varieties of the MEDITATE sequence.

When combined with appropriate k-space trajectories or single voxel acquisition strategies, the accelerated encoding approach of MEDITATE may be used in clinical applications requiring time-sensitive acquisition of DTI parameters such as dynamical DTI in muscle. In that spirit, the second part of this talk will address the measurement of the exercise response of DTI biomarkers in skeletal muscle using dynamic MEDITATE, currently implemented using a line-scan image encoding approach. Finally, future plans and applications of the MEDITATE technique will be discussed.


September 17, 2012

J. Thomas Vaughan, PhD
Professor of Radiology, Electrical and Biomedical Engineering
Center for Magnetic Resonance Research
University of Minnesota

RF Safety (SAR and RF Heating) in MRI

The Radiofrequency (RF) transmit signal which stimulates the MR image signal, also deposits RF energy in the body resulting in heating. Because this RF heating can potentially result in pain, thermogenic tissue damage, and/or thermal stress to the human body, it must be better understood, predicted and monitored. Current MR safety practices however largely ignore tissue temperature as a safety metric in favor of the specific absorption rate (SAR) of RF energy deposition predicted from simple "standard" models of the human anatomy.

The problems with this "SAR" approach to RF safety are: 1. SAR by itself is not the cause of safety concerns, temperature is. 2.) SAR alone indicates neither the location nor the magnitude of thermal hot spots or overall body temperature. SAR based safety models consider only the electrodynamics, but not the thermodynamics or the physiology of humans being scanned. SAR is but one of six or more parameters in bioheat equations needed to predict temperature.

Modeling SAR only is therefore insufficient for predicting RF safety. By basing our safety metric on temperature rather than SAR however, we can not only be more safe, but in many cases we can safely use more RF power in our MRI scan protocols. This presentation will explore and explain SAR, RF Heating, and means to predict, monitor, and control them for MRI.


September 25, 2012

Leslie R. Yan
Doctoral Candidate
The Sackler Institute of Graduate Biomedical Sciences
New York University School of Medicine, NY

Imaging characteristics of posttraumatic stress disorder

Posttraumatic stress disorder is a prevalent psychiatric disorder in civil population and especially among combat veterans. The present study is about imaging characteristics of posttraumatic stress disorder in combat veterans. The neural characteristics of combat veterans who passed the diagnostic criteria of posttraumatic stress disorder were compared with those of combat veterans who did not met the diagnostic criteria. The neural substrates are characterized by MRI in terms of amplitudes of spontaneous activity, temporal synchronization of spontaneous activity, properties and architecture of the neural networks. Results have suggested valuable characteristics such as spontaneous activity in the insula and precuneus, temporal synchronization between the amygdala and prefrontal cortex, disorganization of neural networks etc.


October 23, 2012

Walter Schneider, PhD
Professor of Psychology and Neurosurgery
The Bernard and Irene Schwartz Center for Biomedical Imaging
University of Pittsburgh, PA

Quantifying TBI White Matter Damage in Individual Patients with High Definition Fiber Tracking (HDFT)

High Definition Fiber Tracking (HDFT) enables noninvasive MRI diffusion tracking of millimeter tracts over long distances accurately following from source to destination through tract crossings to detail axon projection fields of white matter tracts. Connection disorders are a major medical problem impacting tens of millions of patients with trauma (TBI), neuro-oncology, neurodegeneration (Alzheimer's) and developmental (autism) pathologies. HDFT involves mapping a million microtracts on a single individual with 3T MRI 257d DSI imaging with novel computation methods calculating directional axonal volume (dAV), tractography, and tract segmentation..

It creates a circuit diagram of the patient quantifying and visualizing the integrity of twenty brain white matter tracts. In a group TBI study the method produced high discriminant validity diagnosis of the anatomical basis of TBI showing nearly all TBI cases have visually and statistically clear damage to multiple tracts in mild TBI that was generally not detectable by previous methods. This provides the potential of definitive anatomically diagnosis of mild TBI and a foundation for a new ecology of personalized care and rehabilitation management.


November 13, 2012

Elfar Adalsteinsson, PhD
Associate Professor of Health Sciences and Technology
Athinoula A. Martinos Center for Biomedical Imaging
New York University Langone Medical Center, NY

Simulation studies of parallel transmit arrays under local and global SAR constraints

Despite intense research in pTx hardware development there has been relatively little theoretical evaluation or optimization of pTx coil arrays, for example determining the benefit of increasing number of transmit channels. We quantify the performance of three pTx body arrays with 4, 8 and 16 channels by incorporating simultaneous constraints on global and local SAR as well as average and maximum forward input power. We analyze RF shimming and 2 spokes excitations in the torso at 3T and compare the tradeoff between excitation fidelity, pulse power metrics and local and global SAR.


November 27, 2012

William Wu
Doctoral Candidate
The Sackler Institute of Graduate Biomedical Sciences
New York University School of Medicine, NY

Quantitative 3D Multivoxel Proton-MR Spectroscopy of In Vivo Cerebral Metabolism in a Rhesus Macaque Model of HIV-Associated Neurocognitive Disorders

Growth in rare and expensive animal models of human disease has increased interest in non-destructive evaluation of tissue injury and/or response to therapy. Proton magnetic resonance spectroscopy (1H-MRS) is a valuable tool because of its unique ability to probe cellular metabolism and bioenergetics noninvasively and nondestructively. However, 1H resonances from metabolites of interest (other than water) typically occur in vivo at 104–105 orders of magnitude lower concentrations than water, leading to much lower sensitivity. To overcome this limitation, we utilize a three dimensional (3D) multivoxel 1H MRS technique, which localizes multiple tissue regions simultaneously, and collect spectra from hundreds of ‹‹1 cm3 voxels. Compared with single-voxel techniques, 3D 1H MRS benefits from improved (~15×) signal-to-noise ratio and higher spectral resolution. Acquiring 3D 1H MRS together with high resolution MRI may provide a quantitative, long-term solution to costly, invasive and destructive histology studies, and improve diagnostic sensitivity and specificity.

Over 50% of the million Americans infected with HIV will suffer milder, long-term HIV associated neurocognitive disorders (HAND). 1H MRS has proven valuable in detecting brain abnormalities in HAND patients, and in simian immunodeficiency virus (SIV) infected rhesus macaques, an excellent model system. Prior histology has demonstrated neuronal dysfunction in (sub)cortical gray and white matter, as well as glial activation. Based on these observations, we test the hypothesis that decreased N acetylaspartate, the MRS-observed marker for neuronal integrity, and increased glial markers: myo-inositol, choline and creatine, can be detected with 3D 1H-MRS both globally and regionally—in subcortical structures—using SIV-infected rhesus macaques.


Latest Updates

04/05/2021 - 09:00
03/24/2021 - 17:06

Philanthropic Support

We gratefully acknowledge generous support for radiology research at NYU Langone Health from:
• The Big George Foundation
• Bernard and Irene Schwartz

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