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EMC-Based Quantitative T2 Mapping Package

Software for quantification of T2 relaxation time and proton density from multi-echo spin-echo MRI data.

We are sharing a software package for post-processing multi-echo spin-echo (MESE) MRI datasets into quantitative T2 relaxation and proton density (PD) maps.

Genuine quantification of T2 relaxation times in vivo is highly challenging because of long scan times required for full spin-echo acquisitions. In MESE protocols the simulated and indirect echoes, non-rectangular, slice profiles, and inhomogeneous B1+ field profiles contaminate the echo train and bias the T2 values. The EMC-based quantitative T2 mapping package relies on computer simulations of Bloch equations to enable generation of accurate T2 maps at clinically feasible scan times.

The package is based on a T2 mapping technique called the echo modulation curve (EMC) algorithm, which relies on accurate Bloch simulations that mimic the exact signal evolution in MESE pulse sequences. The algorithm employs a range of parameters, including RF pulse shapes, gradient pulses, and the exact timing diagram of the protocol as run on the scanner. Simulations are repeated for a range of B1+ inhomogeneity values, e.g., from 70 to 130 percent, and T2 values ranging from 1 to 1,000 milliseconds. These simulations produce dictionaries of signal curves, each associated with a unique [B1+,T2] value pair. The desired T2 parametric maps are generated by matching experimentally acquired MESE data to the EMC dictionary via l2-norm minimization of the difference between experimental EMC and pre-calculated EMC curves. Proton density maps are then calculated by back-projecting the first echo image to time t=0 using the calculated T2 map.

The package is written in MATLAB and C++ and is accessible via MATLAB scripts or a graphical user interface (GUI).

Related Publications

Ben-Eliezer N, Sodickson DK, and Block KT.
Rapid and accurate T2 mapping from multi-spin-echo data using Bloch-simulation-based reconstruction.
Magn Reson Med. 2015 Feb;73(2):809-17. doi: 10.1002/mrm.25156

Ben-Eliezer N, Block KT, inventors. New York University, assignee.
Method and device for accurate quantification of T2 relaxation times based on fast multi spin-echo NMR sequences.
US patent 10,281,544 B2. May 7, 2019.

Radunsky D, Stern N, Nassar J, Tsarfaty G, Blumenfeld-Katzir T, Ben-Eliezer N.
Quantitative platform for accurate and reproducible assessment of transverse (T2 ) relaxation time.
NMR Biomed. 2021 Aug;34(8):e4537. doi: 10.1002/nbm.4537

Please cite these publications if you are using the EMC-based quantitative T2 mapping package in your research.

Get the Code

The software available on this page is provided free of charge and comes without any warranty. CAI²R and NYU Grossman 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 authors (Noam Ben-Eliezer, Tobias Block) and NYU Grossman School of Medicine. If you use the software for academic work, please give credit to the author in publications and cite the related publications. For information regarding commercial use of the package or the underlying algorithm, get in touch with Noam Ben-Eliezer.

Please spell out your affiliation (e.g. “New York University” rather than “NYU”).

Installation and Use

The resource download contains documentation files, including:

  • manual for the T2-mapping platform
    EMC_T2_FIT - User manual - T2 & PD Fitting.pdf
  • manual for generating EMC dictionaries
    EMC_T2_FIT - User manual - Generate new EMC dictionary.pdf

Version History

VersionNotes
5.0
(2026)
Improved B1+ fitting algorithm.
Added support for generating synthetic FLAIR images.
Added preprocessing of MP-PCA denoising of MESE data.
4.0
(2024)
Added ability to generate synthetic T2 weighted imaged at arbitrary echo-times (TEs). 
Fixed bug in mono-exponential fit of very low-SNR data.
3.0
(2022)
Added multi-slice support.
Fixed miscellaneous bugs.
2.0
(2019)
Improved T2 mapping GUI.
Added EMC database code generator.
Added iterative model-based reconstruction package.
1.0
(2013)
First release.

Contact

Questions about this resource may be directed to Noam Ben-Eliezer, PhD at noambe@tauex.tau.ac.il.


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