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1000
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Abstract/Summary
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Objectives!#!In multiple sclerosis (MS), iron rim lesions (IRLs) are indicators of chronic low-grade inflammation and ongoing tissue destruction. The aim of this study was to assess the relationship of IRLs with clinical measures and magnetic resonance imaging (MRI) markers, in particular brain and cervical cord volume.!##!Methods!#!Clinical and MRI parameters from 102 relapsing MS patients (no relapses for at least 6 months, no contrast-enhancing lesions) were included; follow-up data obtained after 12 months was available in 49 patients. IRLs were identified on susceptibility-weighted images (SWIs). In addition to standard brain and spinal cord MRI parameters, normalised cross-sectional area (nCSA) of the upper cervical cord was calculated.!##!Results!#!Thirty-eight patients had at least one IRL on SWI MRI. At baseline, patients with IRLs had higher EDSS scores, higher lesion loads (brain and spinal cord), and lower cortical grey matter volumes and a lower nCSA. At follow-up, brain atrophy rates were higher in patients with IRLs. IRLs correlated spatially with T1-hypointense lesions.!##!Conclusions!#!Relapsing MS patients with IRLs showed more aggressive MRI disease characteristics in both the cross-sectional and longitudinal analyses.!##!Key points!#!• Multiple sclerosis patients with iron rim lesions had higher EDSS scores, higher brain and spinal cord lesion loads, lower cortical grey matter volumes, and a lower normalised cross-sectional area of the upper cervical spinal cord. • Iron rim lesions are a new lesion descriptor obtained from susceptibility-weighted MRI. Our data suggests that further exploration of this lesion characteristic in regard to a poorer prognosis in multiple sclerosis patients is warranted.
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1000
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Hinweis
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DeepGreen-ID: a26f15f6a6b64cdb82692eedb02e1568 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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