So You Want to Image Myelin Using MRI: An Overview and Practical Guide for Myelin Water Imaging
Abstract
Myelin water imaging (MWI) is an MRI imaging biomarker for myelin. This method can generate an in vivo whole-brain myelin water fraction map in approximately 10 minutes. It has been applied in various applications including neurodegenerative disease, neurodevelopmental, and neuroplasticity studies. In this review we start with a brief introduction of myelin biology and discuss the contributions of myelin in conventional MRI contrasts. Then the MRI properties of myelin water and four different MWI methods, which are categorized as T 2 -, T 2 *-, T 1 -, and steady-state-based MWI, are summarized. After that, we cover more practical issues such as availability, interpretation, and validation of these methods. To illustrate the utility of MWI as a clinical research tool, MWI studies for two diseases, multiple sclerosis and neuromyelitis optica, are introduced. Additional topics about imaging myelin in gray matter and non-MWI methods for myelin imaging are also included. Although technical and physiological limitations exist, MWI is a potent surrogate biomarker of myelin that carries valuable and useful information of myelin. Evidence Level: 5 Technical Efficacy: 1 J. MAGN. RESON. IMAGING 2021;53:360-373.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Other approaches for tractography quantification leverage information from imaging modalities other than dMRI, such as T1-weighted imaging, myelin sensitive maps, and g-ratio.
“Other approaches for tractography quantification leverage information from imaging modalities other than dMRI, such as T1-weighted (T1w) imaging (Boshkovski et al., 2020a; Yeatman et al., 2014a), myelin sensitive maps (Lee et al., 2020; Mancini et al., 2020; Piredda et al., 2021) and g-ratio (Campbell et al., 2018).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Lee et al., 2020
Cites
The basis of anisotropic water diffusion in the nervous system—A technical review.
Beaulieu, C. (2002) · NMR in Biomedicine · doi:10.1002/nbm.782 · Cited by 4,653 · see citing works
Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water
Song, S.-K., Sun, S.-W., Ramsbottom, M. J., Chang, C., Russell, J., & Cross, A. H. (2002) · NeuroImage · doi:10.1006/nimg.2002.1267 · Cited by 2,582 · see citing works
Motor skill learning requires active central myelination
McKenzie, I. A., Ohayon, D., Li, H., Paes de Faria, J., Emery, B., Tohyama, K., & Richardson, W. D. (2014) · Science · doi:10.1126/science.1254960 · Cited by 1,177 · see citing works
Deoni, S. C. L., Dean, D. C., O'Muircheartaigh, J., Dirks, H., & Jerskey, B. A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.07.037 · Cited by 390 · see citing works
Using high-resolution quantitative mapping of R1 as an index of cortical myelination
Lutti, A., Dick, F., Sereno, M. I., & Weiskopf, N. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.06.005 · Cited by 346 · see citing works
Magnetic Resonance Imaging of Myelin
Laule, C., Vavasour, I. M., Kolind, S. H., Li, D. K. B., Traboulsee, T. L., Moore, G. R. W., & MacKay, A. L. (2007) · Neurotherapeutics · doi:10.1016/j.nurt.2007.05.004 · Cited by 334 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Zhang, F., Daducci, A., He, Y., Schiavi, S., Seguin, C., Smith, R. E., Yeh, C.-H., Zhao, T., & O’Donnell, L. J. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2021.118870 · Cited by 302 · see citing works
“, 2014a), myelin sensitive maps (Lee et al., 2020; Mancini et al., 2020; Piredda et al., 2021) and g-ratio (Campbell et al.”
BackgroundYang, J. Y.-M., Yeh, C.-H., Poupon, C., & Calamante, F. (2021) · Physics in Medicine & Biology · doi:10.1088/1361-6560/ac0d90 · Cited by 80 · see citing works
Oertel, F. C., Krämer, J., Motamedi, S., Keihani, A., Zimmermann, H. G., Dimitriou, N. G., Condor-Montes, S., Bereuter, C., Cordano, C., Abdelhak, A., et al. (2023) · Neurology Neuroimmunology & Neuroinflammation · doi:10.1212/nxi.0000000000200092 · Cited by 33 · see citing works
Kölle, M., Mackert, S., Heckel, K., Philipsen, A., Ulrich, M., & Grön, G. (2022) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.210135 · Cited by 11 · see citing works
- Authors
- Lee, J., Hyun, J., Lee, J., Choi, E., Shin, H., Min, K., Nam, Y., Kim, H. J., & Oh, S.
- Affiliations
- Seoul National University (KR)
- National Cancer Center (KR)
- The Catholic University of Korea Seoul St. Mary's Hospital (KR)
- Cleveland Clinic (US)
- Corresponding author
- Kim, Ho Jin
- Oh, Se‐Hong
- ORCID
- Venue
- Journal of Magnetic Resonance Imaging
- Publisher
- Wiley
- Published
- 2020-02-03
- Volume
- 53
- Issue
- 2
- Pages
- 360-373
- ISSN
- 1053-1807 (ISSN-L)
- 1522-2586
- OpenAlex
- W3003348160
- Cited by
- 134
- References
- 6
- Citations by year
- 2026: 16 · 2025: 28 · 2024: 29 · 2023: 23 · 2022: 16 · 2021: 17 · 2020: 5
- FWCI
- 2.25
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Magnetic Resonance Imaging (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Research Foundation of Korea (NRF‐2017M3C7A1047864, NRF‐2018R1A4A1025891,NRF‐2017R1C1B1008345, NRF‐2017R1C1B1008345)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
- Keywords
- myelin water imaging, myelin, myelin water fraction, MRI biomarkers, multiple sclerosis, neuromyelitis optica, neurodegenerative diseases, neuroplasticity
- MeSH terms
- Brain, Humans, Magnetic Resonance Imaging, Multiple Sclerosis, Myelin Sheath, Water, Neurodegenerative Diseases
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
