EMC Based T2-Mapping Package
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Home / EMC Based T2-Mapping PackageEMC Based T2-Mapping Package
Introduction Installation and Usage Copyright
1. Introduction
Genuine quantification of T2 relaxation in vivo is highly challenging due to the very long scan times associated with full spin-echo (SE) acquisitions (10’s of min), or, in the case of multi-SE (MSE) protocols, due to an inherent bias of the T2 values resulting from contamination of the echo-train by stimulated and indirect echoes, non rectangular slice profiles, and inhomogeneous B1+ field profiles.
This software package allows post-processing MSE datasets to produce proton density (PD), and T2 maps. The package is written in MATLAB and C++ and used through execution of MATLAB scripts and a graphical user interface (GUI).
Thw package is based on a T2 mapping technique – the Echo Modulation Curve (EMC) algorithm – which relies on accurate Bloch simulations to model the exact signal evolution in MSE pulse-sequences by employing the exact RF pulse shapes and other experimental parameters. Simulations are repeated for a range of T2 and B1+ inhomogeneity values (T2=1…1000ms, B1+ = 50…130 %), producing a database of EMCs, each associated with a unique [B1+,T2] value pair. The desired T2 parametric map is generated by matching experimentally acquired MSE data to the EMC database via l2-norm minimization of the difference between experimental and pre-calculated EMCs. PD maps are then calculated by back-projecting the first echo image to time t=0 using the calculated T2 map.
References
[1] Ben-Eliezer N, Sodickon DK, and Block KT. Rapid and accurate T2 mapping from multi-spin-echo data using Bloch-simulation-based reconstruction. Magn Reson Med 2014. doi: 10.1002/mrm.25156.
[2] Ben-Eliezer N, Feng L, Block KT, Sodickson DK, Otazo R. Accelerated in vivo mapping of T2 relaxation from radially undersampled datasets using compressed sensing and model-based reconstruction. Proc Int Soc Magn Reson Med, v.22 pp. 1597, Milan, Italy.
[3] Ben-Eliezer N, Sodickson DK, Shepherd T, Wiggins G, Block KT. Accelerated and motion-robust in vivo T2 mapping from radially undersampled data using Bloch-simulation-based iterative reconstruction. Magn Reson Med, in press.
2. Installation and Usage
The package is implemented in MATLAB using standard script code, embedded with dedicated C++ API. Using the package requires:
- Standard MATLAB installation.
- Software development kit (SDK) - for executing the C++ code from within MATLAB
The downloaded zip file contains three different sub-packages:
pkg_I. EMC Database Generator: MATLAB (and C++) script code allowing to generate new EMC databses based on input parameter values.
pkg_II. T2 Map Reconstruction GUI: MATLAB based graphical user interface for postprocessing experimental multi-SE set of DICOMs to produce T2 parametric maps (requires a previously generated EMC database). DICOMs can be arbitrarily reconstructed, hence allowing any sampling trajectories or reconstruction techniques.
Once the installation requirements have been met, the package code should be simply copied to any folder on the post-processing computer and operated from within MATLAB by typing in the GUI name in the command line:
>> EMC_T2_FIT.fig
pkg_III. Iterative model-based reconstruction code
C++ code package for post processing radially sampled multi SE data. In its basis this package will generate T2 & PD maps through the use of an iterative non-linear conjugate-gradient algorithm implementing a three-parameter [B1+,T2,PD] optimization. True estimation of the T2 parametric maps is enabled in this case by integrating the EMC database into the signal model used by the algorithm. See reference [2] for further details.
! Note:
T2 map reconstruction (pkg_II) requires an EMC database to which experimental data is matched. This can be generated using pkg_I. Alternatively, if no database is found please send an email to:
with the experimental DICOM parameters (or the set of DICOMs that needs to be matched), and a database will be generated for your data. DICOM parameters appear on the bottom part of the GUI.
See the EMC DB GUI User Manual for more details.
3. Copyright
The code and algorithm provided in this package is protected by an international patent. Use of the package is free for research and scientific purposes. Please contact Noam.Ben-Eliezer@nyumc.org for information regarding commercial use of the package or the underlying algorithm.
▪ Ben-Eliezer N, Block KT, “Method and device for accurate quantification of T2 relaxation times based on fast spin-echo NMR sequences”, 2013 (provisional patent application number 61/767,663).
4. Version History
Version 1.0 First release.
Version 2.0 T2 mapping GUI enhancement; Addition of EMC DB code generator; Addition of Iterative model-based reconstruction package.
Version 3.0 Multi-Slice support; bug fixes.
Version 4.0 Added ability to generate synthetic T2 weighted imaged at arbitry echo-times (TEs); fixed bug in monoexponential fit of very low SNR data.

PLEASE NOTE: The software available on this page is provided free of charge and comes without any warranty. CAI²R and the NYU School of Medicine do not take any liability for problems or damage of any kind resulting from the use of the files provided. Operation of the software is solely at the user's own risk. The software developments provided are not medical products and must not be used for making diagnostic decisions.

The software is provided for non-commercial, academic use only. Usage or distribution of the software for commercial purpose is prohibited. All rights belong to the author (Noam Ben-Eliezer) and the NYU School of Medicine. If you use the software for academic work, please give credit to the author in publications and cite the related publications.
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Philanthropic Support
We gratefully acknowledge generous support for radiology research at NYU Langone Health from:
• The Big George Foundation
• Bernard and Irene Schwartz
© 2021 Center for Advanced Imaging Innovation and Research. All rights reserved. This content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Additional disclaimers.