Diffusion-weighted MR spectroscopy: Consensus, recommendations, and resources from acquisition to modeling
Publication date
2024-03
Authors
Ligneul, Clémence
Najac, Chloé
Döring, André
Beaulieu, Christian
Branzoli, Francesca
Clarke, William T
Cudalbu, Cristina
Genovese, Guglielmo
Jbabdi, Saad
Jelescu, Ileana
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Advisors
Supervisors
Document Type
Article
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cc_by_nc_nd
Abstract
Brain 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.
Keywords
acquisition, dMRS, fitting, modelling, processing, Radiology Nuclear Medicine and imaging
Citation
Ligneul, C, Najac, C, Döring, A, Beaulieu, C, Branzoli, F, Clarke, W T, Cudalbu, C, Genovese, G, Jbabdi, S, Jelescu, I, Karampinos, D, Kreis, R, Lundell, H, Marjańska, M, Möller, H E, Mosso, J, Mougel, E, Posse, S, Ruschke, S, Simsek, K, Szczepankiewicz, F, Tal, A, Tax, C, Oeltzschner, G, Palombo, M, Ronen, I & Valette, J 2024, 'Diffusion-weighted MR spectroscopy : Consensus, recommendations, and resources from acquisition to modeling', Magnetic Resonance in Medicine, vol. 91, no. 3, pp. 860-885. https://doi.org/10.1002/mrm.29877