ArticleEuropean journal of neurology2022
Lesion features on magnetic resonance imaging discriminate multiple sclerosis patients.
Article in European journal of neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Biomarkers of Progression Independent of Relapse Activity-Can We Actually Measure It Yet?International journal of molecular sciences · 2025Review
- Harnessing myelin water fraction as an imaging biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination: A review.Journal of neurochemistry · 2024Review
- Disentangling the heterogeneity of multiple sclerosis through identification of independent neuropathological dimensions.Acta neuropathologica · 2024Article
- Personalized estimates of morphometric similarity in multiple sclerosis and neuromyelitis optica spectrum disorders.NeuroImage. Clinical · 2023Article
- Distinct characteristics and severity of brain magnetic resonance imaging lesions in women and men with multiple sclerosis assessed using verified texture analysis measures.Frontiers in neurology · 2023Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundMagnetic resonance imaging (MRI) provides insight into various pathological processes in multiple sclerosis (MS) and may provide insight into patterns of damage among patients.
objectiveWe sought to determine if MRI features have clinical discriminative power among a cohort of MS patients.
methodsNinety-six relapsing remitting and seven progressive MS patients underwent myelin water fraction (MWF) imaging and conventional MRI for cortical thickness and thalamic volume. Patients were clustered based on lesion level MRI features using an agglomerative hierarchical clustering algorithm based on principal component analysis (PCA).
resultsOne hundred and three patients with 1689 MS lesions were analyzed. PCA on MRI features demonstrated that lesion MWF and volume distributions (characterized by 25th, 50th, and 75th percentiles) accounted for 87% of the total variability based on four principal components. The best hierarchical cluster confirmed two distinct patient clusters. The clustering features in order of importance were lesion median MWF, MWF 25th, MWF 75th, volume 75th percentiles, median individual lesion volume, total lesion volume, cortical thickness, and thalamic volume (all p values <0.01368). The clusters were associated with patient Expanded Disability Status Scale (EDSS) (n = 103, p = 0.0338) at baseline and at 5 years (n = 72, p = 0.0337).
conclusionsThese results demonstrate that individual MRI features can identify two patient clusters driven by lesion-based values, and our unique approach is an analysis blinded to clinical variables. The two distinct clusters exhibit MWF differences, most likely representing individual remyelination capabilities among different patient groups. These findings support the concept of patient-specific pathophysiological processes and may guide future therapeutic approaches.
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