An Accessible Toolbox for MR Spectroscopy Data Extraction and Analysis with Optimization for Diabetes Patients

Motivation: Offline MR spectroscopy (MRS) analyses are limited by proprietary software on the console. Goal(s): This study proposes a novel MATLAB-based toolbox to process the scanner-derived MRS raw data offline. Approach: Functions in the proposed toolbox were programmed to efficiently perform MRS data extraction, peak detection in the spectral data, and Lorentzian curve fitting to provide a noiseless spectrum. Results: With the toolbox, raw MRS data can be utilized offline; clinically relevant metabolites whose peaks were originally obscured in console-derived spectra can now be clearly resolved. Impact: The development of a MATLAB toolbox for MRS data processing streamlines access to valuable MRS information and enhances peak detection, thus potentially increasing the utility and accessibility of MRS clinically and providing medical practitioners with more diagnostic information.