Building a standalone automated High-Throughput LCModel prototype application for 1H-MRS data processing: HT-LCModel

Motivation: LCModel is the gold standard for processing clinical and preclinical 1H-MRS data, but batch processing large datasets in non-Linux environments remains challenging, limiting its broader implementation. Goal(s): We propose a standalone MATLAB application that simplifies batch processing in LCModel. Approach: We developed High-Throughput LCModel (HT-LCModel), a user-friendly MATLAB application for high-throughput MRS processing using LCModel. We validated it by processing 1H-MRS data from clinical (Siemens) and preclinical (Bruker) settings using both HT-LCModel and manual methods. Results: Pearson correlation coefficients were 1.0 for all measured metabolites and ratios, indicating perfect agreement between manual and HT-LCModel-derived values. Impact: HT-LCModel provides an intuitive, user-friendly, high-throughput pipeline for MRS processing for processing 1H-MRS data with LCModel, the most widely used MRS-processing application. By offering a built-in viewer accessible on any computer, HT-LCModel enhances research consistency and accessibility in MRS studies.