Diffusion‐weighted <scp>MR</scp> spectroscopy: Consensus, recommendations, and resources from acquisition to modeling-Reference-Cited by-同舟云学术

Diffusion‐weighted MR spectroscopy: Consensus, recommendations, and resources from acquisition to modeling

Published:2023-11-09 Issue:3 Volume:91 Page:860-885
ISSN:0740-3194
Container-title:Magnetic Resonance in Medicine
language:en
Short-container-title:Magnetic Resonance in Med

Author:

Ligneul Clémence¹^ORCID,Najac Chloé²^ORCID,Döring André³⁴^ORCID,Beaulieu Christian⁵^ORCID,Branzoli Francesca⁶^ORCID,Clarke William T.¹^ORCID,Cudalbu Cristina⁴⁷^ORCID,Genovese Guglielmo⁸^ORCID,Jbabdi Saad¹^ORCID,Jelescu Ileana⁹¹⁰^ORCID,Karampinos Dimitrios¹¹^ORCID,Kreis Roland¹²¹³^ORCID,Lundell Henrik¹⁴¹⁵^ORCID,Marjańska Małgorzata⁸^ORCID,Möller Harald E.¹⁶^ORCID,Mosso Jessie⁴⁷¹⁷^ORCID,Mougel Eloïse¹⁸,Posse Stefan¹⁹²⁰^ORCID,Ruschke Stefan¹¹^ORCID,Simsek Kadir³²¹^ORCID,Szczepankiewicz Filip²²^ORCID,Tal Assaf²³^ORCID,Tax Chantal²⁴²⁵^ORCID,Oeltzschner Georg²⁶²⁷^ORCID,Palombo Marco³²¹^ORCID,Ronen Itamar²⁸^ORCID,Valette Julien¹⁸^ORCID

Affiliation:

1. Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences University of Oxford Oxford UK

2. C.J. Gorter MRI Center, Department of Radiology Leiden University Medical Center Leiden The Netherlands

3. Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology Cardiff University Cardiff UK

4. CIBM Center for Biomedical Imaging Lausanne Switzerland

5. Departments of Biomedical Engineering and Radiology University of Alberta Alberta Edmonton Canada

6. Paris Brain Institute–ICM, Sorbonne University, UMR S 1127, Inserm U 1127, CNRS UMR 7225 Paris France

7. Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland

8. Center for Magnetic Resonance Research, Department of Radiology University of Minnesota Minnesota Minneapolis USA

9. Department of Radiology Lausanne University Hospital Lausanne Switzerland

10. Faculty of Biology and Medicine University of Lausanne Lausanne Switzerland

11. Department of Diagnostic and Interventional Radiology Technical University of Munich Munich Germany

12. MR Methodology, Department for Diagnostic and Interventional Neuroradiology University of Bern Bern Switzerland

13. Translational Imaging Center (TIC) Swiss Institute for Translational and Entrepreneurial Medicine Bern Switzerland

14. Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research Copenhagen University Hospital–Amager anf Hvidovre Hvidovre Denmark

15. Department of Health Technology Technical University of Denmark Lyngby Denmark

16. NMR Methods & Development Group Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany

17. LIFMET, EPFL Lausanne Switzerland

18. Université Paris‐Saclay, CEA, CNRS, MIRCen, Laboratoires des Maladies Neurodégénératives Fontenay‐aux‐Roses France

19. Department of Neurology University of New Mexico School of Medicine New Mexico Albuquerque USA

20. Department of Physics and Astronomy University of New Mexico School of Medicine New Mexico Albuquerque USA

21. School of Computer Science and Informatics Cardiff University Cardiff UK

22. Medical Radiation Physics, Clinical Sciences Lund Lund University Lund Sweden

23. Department of Chemical and Biological Physics The Weizmann Institute of Science Rehovot Israel

24. University Medical Center Utrecht Utrecht The Netherlands

25. Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy Cardiff University Cardiff United Kingdom

26. Russell H. Morgan Department of Radiology and Radiological Science The Johns Hopkins University School of Medicine Maryland Baltimore USA

27. F. M. Kirby Center for Functional Brain Imaging Kennedy Krieger Institute Maryland Baltimore USA

28. Clinical Imaging Sciences Centre Brighton and Sussex Medical School Brighton UK

Abstract

AbstractBrain 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.

Funder

Lorentz Center

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.29877

Reference125 articles.

1. Clinical Applications of Diffusion MR Imaging for Acute Ischemic Stroke

2. Microstructural Characterization of Normal and Malignant Human Prostate Tissue With Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumours Magnetic Resonance Imaging

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