ArticleHuman brain mapping2021
Classification of multiple sclerosis based on patterns of CNS regional atrophy covariance.
Article in Human brain mapping, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Combined magnetic resonance imaging and serum analysis reveals distinct multiple sclerosis types.Brain : a journal of neurology · 2025Article
- Exploring the Link Between IL-6 rs1800795 G > C SNP and the Severity of Epstein-Barr Virus-Associated Multiple Sclerosis: Potential Impact on Cognitive Impairment.Molecular neurobiology · 2025Article
- Spatiotemporal subtypes of brain and spinal cord atrophy in neuromyelitis optica spectrum disorders and multiple sclerosis.BMC medicine · 2025Article
- Spatial structural abnormality maps associated with cognitive and physical performance in relapsing-remitting multiple sclerosis.European radiology · 2025Article
- On how SAM might help improving personalized treatments in relapsing-remitting multiple sclerosis.European radiology · 2025Article
- Spinal cord and brain atrophy patterns in neuromyelitis optica spectrum disorder and multiple sclerosis.Journal of neurology · 2024Article
- Comparison of ocular changes in multiple sclerosis and neuromyelitis optica spectrum disorder patients.Frontiers in neurology · 2024Article
- Emerging Perspectives on MRI Application in Multiple Sclerosis: Moving from Pathophysiology to Clinical Practice.Radiology · 2023Review
- Multiple sclerosis as a model to investigate SARS-CoV-2 effect on brain atrophy.CNS neuroscience & therapeutics · 2023Article
- Multiple sclerosis progression: time for a new mechanism-driven framework.The Lancet. Neurology · 2023Review
- Brainstem lesions are associated with diffuse spinal cord involvement in early multiple sclerosis.BMC neurology · 2022Article
- The role of cerebellar damage in explaining disability and cognition in multiple sclerosis phenotypes: a multiparametric MRI study.Journal of neurology · 2022Article
- Serum neurofilament as a predictor of 10-year grey matter atrophy and clinical disability in multiple sclerosis: a longitudinal study.Journal of neurology, neurosurgery, and psychiatry · 2022Article
- Longitudinal changes of deep gray matter shape in multiple sclerosis.NeuroImage. Clinical · 2022Article
- Classification of multiple sclerosis based on patterns of CNS regional atrophy covariance.Human brain mapping · 2021Article
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
There is evidence that multiple sclerosis (MS) pathology leads to distinct patterns of volume loss over time (VLOT) in different central nervous system (CNS) structures. We aimed to use such patterns to identify patient subgroups. MS patients of all classical disease phenotypes underwent annual clinical, blood, and MRI examinations over 6 years. Spinal, striatal, pallidal, thalamic, cortical, white matter, and T2-weighted lesion volumes as well as serum neurofilament light chain (sNfL) were quantified. CNS VLOT patterns were identified using principal component analysis and patients were classified using hierarchical cluster analysis. 225 MS patients were classified into four distinct Groups A, B, C, and D including 14, 59, 141, and 11 patients, respectively). These groups did not differ in baseline demographics, disease duration, disease phenotype distribution, and lesion-load expansion. Interestingly, Group A showed pronounced spinothalamic VLOT, Group B marked pallidal VLOT, Group C small between-structure VLOT differences, and Group D myelocortical volume increase and pronounced white matter VLOT. Neurologic deficits were more severe and progressed faster in Group A that also had higher mean sNfL levels than all other groups. Group B experienced more frequent relapses than Group C. In conclusion, there are distinct patterns of VLOT across the CNS in MS patients, which do not overlap with clinical MS subtypes and are independent of disease duration and lesion-load but are partially associated to sNfL levels, relapse rates, and clinical worsening. Our findings support the need for a more biologic classification of MS subtypes including volumetric and body-fluid markers.
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