Ligneul, ClemenceNajac, ChloeDoring, AndreBeaulieu, ChristianBranzoli, FrancescaClarke, William T.Cudalbu, CristinaGenovese, GuglielmoJbabdi, SaadJelescu, IleanaKarampinos, DimitriosKreis, RolandLundell, HenrikMarjanska, MalgorzataMoeller, Harald E.Mosso, JessieMougel, EloisePosse, StefanRuschke, StefanSimsek, KadirSzczepankiewicz, FilipTal, AssafTax, ChantalOeltzschner, GeorgPalombo, MarcoRonen, ItamarValette, Julien2024-02-192024-02-192024-02-192023-11-0910.1002/mrm.29877https://infoscience.epfl.ch/handle/20.500.14299/204294WOS:001103032500001Brain cell structure and function reflect neurodevelopment, plasticity, and aging; and changes can help flag pathological processes such as neurodegeneration and neuroinflammation. Accurate and quantitative methods to noninvasively disentangle cellular structural features are needed and are a substantial focus of brain research. Diffusion-weighted MRS (dMRS) gives access to diffusion properties of endogenous intracellular brain metabolites that are preferentially located inside specific brain cell populations. Despite its great potential, dMRS remains a challenging technique on all levels: from the data acquisition to the analysis, quantification, modeling, and interpretation of results. These challenges were the motivation behind the organization of the Lorentz Center workshop on "Best Practices & Tools for Diffusion MR Spectroscopy" held in Leiden, the Netherlands, in September 2021. During the workshop, the dMRS community established a set of recommendations to execute robust dMRS studies. This paper provides a description of the steps needed for acquiring, processing, fitting, and modeling dMRS data, and provides links to useful resources.Life Sciences & BiomedicineAcquisitionDmrsFittingModellingProcessingtext::journal::journal article::research article