Myelin water and tensor‐valued diffusion imaging: (How) are they related?
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| Title: | Myelin water and tensor‐valued diffusion imaging: (How) are they related? |
|---|---|
| Authors: | Balaji, Sharada1 (AUTHOR) sbalaji@phas.ubc.ca, Dvorak, Adam V.1 (AUTHOR), Wiley, Neale1 (AUTHOR), MacMillan, Erin L.2,3 (AUTHOR), Traboulsee, Anthony4 (AUTHOR), Vavasour, Irene M.1,3,5 (AUTHOR), Gilbert, Guillaume2 (AUTHOR), Moore, G. R. Wayne4,5,6 (AUTHOR), Li, David K. B.3 (AUTHOR), Laule, Cornelia1,3,5,6 (AUTHOR), MacKay, Alex L.1,3 (AUTHOR), Kolind, Shannon1,3,4,5 (AUTHOR) |
| Source: | Magnetic Resonance in Medicine. Nov2025, Vol. 94 Issue 5, p2038-2056. 19p. |
| Subjects: | Myelin, Anisotropy, Microstructure, Multiple sclerosis, Diffusion tensor imaging, Magnetic resonance imaging |
| Abstract: | Purpose: Conventional MRI offers limited insight into specific characteristics of central nervous system tissue, whereas quantitative MRI measures can provide more detailed information about different aspects of microstructure. A multi‐metric approach involving multiple quantitative measures may improve our understanding of healthy tissue and pathology. Previous work shows myelin water fraction (MWF) is related to fractional anisotropy (FA), but this relationship is complicated by confounding factors that may be resolved using tensor‐valued diffusion imaging, which yields measurements of microscopic FA (μFA) and tissue heterogeneity (CMD). Our aims were to better understand how measures from myelin water and tensor‐valued diffusion imaging relate to one another, and to demonstrate how these measures can be used to characterize microstructure in both healthy white matter and pathological changes. Methods: We assessed the relationship between MWF, FA, μFA, and CMD from 25 healthy individuals through atlas comparison, correlation analysis, and tract profiling. We also applied z‐score analysis and tract profiling in five people with multiple sclerosis (MS) to evaluate the multi‐metric utility of these measures in assessing pathology. Results: Although correlation analysis showed moderate, but potentially misleading relationships between metrics, tract profiling showed consistent tract‐specific pattern differences between metrics in healthy tissue. In MS, MWF, μFA, and CMD were the most sensitive to pathological changes, showing regions of abnormality even in normal‐appearing white matter and along lesional tracts, and highlighting different types of damage. Conclusion: Using MWF, μFA, and CMD to separately assess myelination, anisotropy, and tissue heterogeneity enhances our ability to investigate development, aging, disease, and injury. [ABSTRACT FROM AUTHOR] |
| Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 187617631 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Myelin water and tensor‐valued diffusion imaging: (How) are they related? – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Balaji%2C+Sharada%22">Balaji, Sharada</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> sbalaji@phas.ubc.ca</i><br /><searchLink fieldCode="AR" term="%22Dvorak%2C+Adam+V%2E%22">Dvorak, Adam V.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wiley%2C+Neale%22">Wiley, Neale</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22MacMillan%2C+Erin+L%2E%22">MacMillan, Erin L.</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Traboulsee%2C+Anthony%22">Traboulsee, Anthony</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Vavasour%2C+Irene+M%2E%22">Vavasour, Irene M.</searchLink><relatesTo>1,3,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gilbert%2C+Guillaume%22">Gilbert, Guillaume</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Moore%2C+G%2E+R%2E+Wayne%22">Moore, G. R. Wayne</searchLink><relatesTo>4,5,6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+David+K%2E+B%2E%22">Li, David K. B.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Laule%2C+Cornelia%22">Laule, Cornelia</searchLink><relatesTo>1,3,5,6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22MacKay%2C+Alex+L%2E%22">MacKay, Alex L.</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kolind%2C+Shannon%22">Kolind, Shannon</searchLink><relatesTo>1,3,4,5</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Magnetic+Resonance+in+Medicine%22">Magnetic Resonance in Medicine</searchLink>. Nov2025, Vol. 94 Issue 5, p2038-2056. 19p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Myelin%22">Myelin</searchLink><br /><searchLink fieldCode="DE" term="%22Anisotropy%22">Anisotropy</searchLink><br /><searchLink fieldCode="DE" term="%22Microstructure%22">Microstructure</searchLink><br /><searchLink fieldCode="DE" term="%22Multiple+sclerosis%22">Multiple sclerosis</searchLink><br /><searchLink fieldCode="DE" term="%22Diffusion+tensor+imaging%22">Diffusion tensor imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetic+resonance+imaging%22">Magnetic resonance imaging</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Purpose: Conventional MRI offers limited insight into specific characteristics of central nervous system tissue, whereas quantitative MRI measures can provide more detailed information about different aspects of microstructure. A multi‐metric approach involving multiple quantitative measures may improve our understanding of healthy tissue and pathology. Previous work shows myelin water fraction (MWF) is related to fractional anisotropy (FA), but this relationship is complicated by confounding factors that may be resolved using tensor‐valued diffusion imaging, which yields measurements of microscopic FA (μFA) and tissue heterogeneity (CMD). Our aims were to better understand how measures from myelin water and tensor‐valued diffusion imaging relate to one another, and to demonstrate how these measures can be used to characterize microstructure in both healthy white matter and pathological changes. Methods: We assessed the relationship between MWF, FA, μFA, and CMD from 25 healthy individuals through atlas comparison, correlation analysis, and tract profiling. We also applied z‐score analysis and tract profiling in five people with multiple sclerosis (MS) to evaluate the multi‐metric utility of these measures in assessing pathology. Results: Although correlation analysis showed moderate, but potentially misleading relationships between metrics, tract profiling showed consistent tract‐specific pattern differences between metrics in healthy tissue. In MS, MWF, μFA, and CMD were the most sensitive to pathological changes, showing regions of abnormality even in normal‐appearing white matter and along lesional tracts, and highlighting different types of damage. Conclusion: Using MWF, μFA, and CMD to separately assess myelination, anisotropy, and tissue heterogeneity enhances our ability to investigate development, aging, disease, and injury. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/mrm.30620 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 2038 Subjects: – SubjectFull: Myelin Type: general – SubjectFull: Anisotropy Type: general – SubjectFull: Microstructure Type: general – SubjectFull: Multiple sclerosis Type: general – SubjectFull: Diffusion tensor imaging Type: general – SubjectFull: Magnetic resonance imaging Type: general Titles: – TitleFull: Myelin water and tensor‐valued diffusion imaging: (How) are they related? Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Balaji, Sharada – PersonEntity: Name: NameFull: Dvorak, Adam V. – PersonEntity: Name: NameFull: Wiley, Neale – PersonEntity: Name: NameFull: MacMillan, Erin L. – PersonEntity: Name: NameFull: Traboulsee, Anthony – PersonEntity: Name: NameFull: Vavasour, Irene M. – PersonEntity: Name: NameFull: Gilbert, Guillaume – PersonEntity: Name: NameFull: Moore, G. R. Wayne – PersonEntity: Name: NameFull: Li, David K. B. – PersonEntity: Name: NameFull: Laule, Cornelia – PersonEntity: Name: NameFull: MacKay, Alex L. – PersonEntity: Name: NameFull: Kolind, Shannon IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 07403194 Numbering: – Type: volume Value: 94 – Type: issue Value: 5 Titles: – TitleFull: Magnetic Resonance in Medicine Type: main |
| ResultId | 1 |