Microstructural characterization of multiple sclerosis lesion phenotypes using multiparametric longitudinal analysis.

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Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_E7BF3FB2AF82
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Microstructural characterization of multiple sclerosis lesion phenotypes using multiparametric longitudinal analysis.
Journal
Journal of neurology
Author(s)
Ravano V., Andelova M., Piredda G.F., Sommer S., Caneschi S., Roccaro L., Krasensky J., Kudrna M., Uher T., Corredor-Jerez R.A., Disselhorst J.A., Maréchal B., Hilbert T., Thiran J.P., Richiardi J., Horakova D., Vaneckova M., Kober T.
ISSN
1432-1459 (Electronic)
ISSN-L
0340-5354
Publication state
Published
Issued date
09/2024
Peer-reviewed
Oui
Volume
271
Number
9
Pages
5944-5957
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Abstract
In multiple sclerosis (MS), slowly expanding lesions were shown to be associated with worse disability and prognosis. Their timely detection from cross-sectional data at early disease stages could be clinically relevant to inform treatment planning. Here, we propose to use multiparametric, quantitative MRI to allow a better cross-sectional characterization of lesions with different longitudinal phenotypes.
We analysed T1 and T2 relaxometry maps from a longitudinal cohort of MS patients. Lesions were classified as enlarging, shrinking, new or stable based on their longitudinal volumetric change using a newly developed automated technique. Voxelwise deviations were computed as z-scores by comparing individual patient data to T1, T2 and T2/T1 normative values from healthy subjects. We studied the distribution of microstructural properties inside lesions and within perilesional tissue.
Stable lesions exhibited the highest T1 and T2 z-scores in lesion tissue, while the lowest values were observed for new lesions. Shrinking lesions presented the highest T1 z-scores in the first perilesional ring while enlarging lesions showed the highest T2 z-scores in the same region. Finally, a classification model was trained to predict the longitudinal lesion type based on microstructural metrics and feature importance was assessed. Z-scores estimated in lesion and perilesional tissue from T1, T2 and T2/T1 quantitative maps carry discriminative and complementary information to classify longitudinal lesion phenotypes, hence suggesting that multiparametric MRI approaches are essential for a better understanding of the pathophysiological mechanisms underlying disease activity in MS lesions.
Keywords
Humans, Male, Female, Adult, Longitudinal Studies, Multiple Sclerosis/diagnostic imaging, Multiple Sclerosis/pathology, Phenotype, Middle Aged, Brain/diagnostic imaging, Brain/pathology, Multiparametric Magnetic Resonance Imaging, Disease Progression, Cross-Sectional Studies, Magnetic Resonance Imaging, Enlarging lesions, Lesion subtyping, Multiple sclerosis, Quantitative MRI, Relaxometry
Pubmed
Web of science
Open Access
Yes
Create date
19/07/2024 14:10
Last modification date
21/01/2025 8:29
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