Objectives
Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive technique for probing metabolism. MRSI enables spatial mapping of metabolite distributions, offering insights into regional metabolic heterogeneity that single-voxel spectroscopy (SVS) cannot capture. However, MRSI produces large multidimensional datasets and requires complex processing pipelines, limiting reproducibility and accessibility. While human studies benefit from advanced processing tools, similar developments in preclinical research remain scarce, highlighting a demand for practical tools accessible to non-experts. Furthermore, recent advances in deuterium-based MRSI have opened metabolic pathway studies, introducing additional dimensions for kinetic information and specific positional labeling, thus substantially increasing dataset complexity and analysis demands.
Methods
To address these needs, we introduce the MRS4Brain Toolbox, a freely available MATLAB-based platform for preclinical MRSI supporting proton, deuterium, and other nuclei, with extended functionalities for SVS and diffusion-weighted spectroscopy.
Results
The toolbox integrates reconstruction, preprocessing, quantification, quality control, brain segmentation automatically overlaid on metabolite maps, modeling, and statistical analysis into unified workflows accessible via a graphical interface.
Conclusion
By streamlining data processing and reducing technical barriers, MRS4Brain Toolbox promotes reproducibility, harmonization, and broader adoption of basic and advanced spectroscopic techniques in preclinical studies, ultimately facilitating translational metabolic research
