MRSIPrep: A Robust Preprocessing Pipeline for Whole-Brain MRSI Data

About

MRSIPrep is a preprocessing and derivative-generation pipeline for already quantified whole-brain MRSI maps, run as a BIDS App via Docker. Its default mni-norm mode normalizes MRSI maps to a specified template for voxel-based analysis. parc-con mode adds SynthSeg+FAST tissue maps, PETPVC, and Chimera/MNI-atlas regional profile extraction for metabolic connectivity computation. MRSIPrep creates a quality-control report for each run.

Full documentation, installation, and usage instructions are on Read the Docs.

Design Principles

MRSIPrep was designed according to four main principles:

• Reproducibility — distributed as open-source software, executed in containerized environments to minimize differences across computing platforms.
• Modularity — each processing stage is an independent module, so users can enable, disable, or replace specific steps according to their acquisition protocol and scientific question.
• Transparency — automated quality-control reports summarize spatial registration, metabolite coverage, voxel-level quality metrics, tissue composition, and atlas projection.
• Analysis agnosticism — MRSIPrep does not impose a specific downstream analysis; it generates standardized derivatives usable for voxelwise analyses, regional analyses, metabolic connectomics, gradient mapping, or machine-learning workflows.

See Read the Docs for the full workflow architecture and quality-control framework.

Test Dataset

A small, public, synthetic MRSI dataset — SynthMRSI-Project — is available for anyone to download and run through MRSIPrep themselves, without needing access to real MRSI acquisitions. It pairs real T1w anatomical images (subsetted from two CC0 OpenNeuro datasets) with model-synthesized MRSI signal and empirical CRLB/SNR/FWHM quality maps, following MRSIPrep's own raw-MRSI-input convention.

• Published on Zenodo: 10.5281/zenodo.21477047 (CC0)
• Full download and usage instructions: PUBLIC_DATASET.md
• Used as the fixture for this repo's automated end-to-end pipeline test (see the "tested on SynthMRSI-Project" badge above)

Use Cases

Code derived from this pipeline has been used in the following peer-reviewed publications:

• Lucchetti, F., Céléreau, E., Steullet, P., Alemán-Gómez, Y., Hagmann, P., Klauser, A., & Klauser, P. (2025). Constructing the human brain metabolic connectome with MR spectroscopic imaging reveals cerebral biochemical organization. Nature Communications, 16. doi:10.1038/s41467-025-66124-w
• Céléreau, E., Lucchetti, F., Alemán-Gómez, Y., Dwir, D., Cleusix, M., Ledoux, J.-B., Jenni, R., Conchon, C., Bach Cuadra, M., Schilliger, Z., Solida, A., Armando, M., Plessen, K. J., Hagmann, P., Conus, P., Klauser, A., & Klauser, P. (2026). High-resolution whole-brain magnetic resonance spectroscopic imaging in youth at risk for psychosis. Imaging Neuroscience, 4. doi:10.1162/imag.a.1276
• Céléreau, E., Lucchetti, F., Steullet, P., Schilliger, Z., Alemán-Gómez, Y., Jenni, R., Petrova, T., Forrer, S., Delavari, F., Ledoux, J.-B., et al. (2026). Sex differences in brain metabolism assessed with whole-brain magnetic resonance spectroscopic imaging. bioRxiv, 2026-06. doi:10.64898/2026.06.30.735476

License

MRSIPrep is distributed under the CHUV academic non-commercial research license; see LICENSE for the full text.

Attribution

Substantial implementation logic is cropped and refactored by Federico Lucchetti and Edgar Céléreau. The original license is included in LICENSE.

Acknowledgments

MRSIPrep builds on the work of the ANTs, FreeSurfer, FSL, PETPVC, Chimera, and TemplateFlow projects.