Consistency of the "central vein sign" in chronic multiple sclerosis lesions.


Journal

Multiple sclerosis and related disorders
ISSN: 2211-0356
Titre abrégé: Mult Scler Relat Disord
Pays: Netherlands
ID NLM: 101580247

Informations de publication

Date de publication:
Feb 2022
Historique:
received: 21 12 2021
revised: 05 01 2022
accepted: 14 01 2022
pubmed: 24 1 2022
medline: 3 3 2022
entrez: 23 1 2022
Statut: ppublish

Résumé

In recent years, there has been an increasing interest in the central vein sign (CVS) as a new imaging marker and previous cross-sectional studies demonstrated that the CVS has the potential to discriminate multiple sclerosis (MS) lesions from non-MS lesions. The aim of this study was to investigate the consistency of the CVS in a longitudinal magnetic resonance imaging (MRI) data set. 3T MRI datasets from seventy-one people with MS acquired at baseline and after 12 months-follow-up were analyzed. Chronic lesions were identified on fluid-attenuated inversion recovery (FLAIR) images. Co-registered susceptibility-weighted/FLAIR images were analyzed for the presence of a CVS at baseline and follow-up. A total of 183 chronic lesions were included in the final analysis. At baseline MRI, a CVS was detectable in 141/183 (77%) lesions. Overall, the CVS was consistent in 114/141 (81%) lesions (Cohen's kappa = 0.46, standard error = 0.07). The CVS is a rather stable feature in chronic MS lesions and therefore represents a robust imaging marker that could increase the specificity of MRI in MS.

Sections du résumé

BACKGROUND BACKGROUND
In recent years, there has been an increasing interest in the central vein sign (CVS) as a new imaging marker and previous cross-sectional studies demonstrated that the CVS has the potential to discriminate multiple sclerosis (MS) lesions from non-MS lesions. The aim of this study was to investigate the consistency of the CVS in a longitudinal magnetic resonance imaging (MRI) data set.
METHODS METHODS
3T MRI datasets from seventy-one people with MS acquired at baseline and after 12 months-follow-up were analyzed. Chronic lesions were identified on fluid-attenuated inversion recovery (FLAIR) images. Co-registered susceptibility-weighted/FLAIR images were analyzed for the presence of a CVS at baseline and follow-up.
RESULTS RESULTS
A total of 183 chronic lesions were included in the final analysis. At baseline MRI, a CVS was detectable in 141/183 (77%) lesions. Overall, the CVS was consistent in 114/141 (81%) lesions (Cohen's kappa = 0.46, standard error = 0.07).
CONCLUSION CONCLUSIONS
The CVS is a rather stable feature in chronic MS lesions and therefore represents a robust imaging marker that could increase the specificity of MRI in MS.

Identifiants

pubmed: 35066270
pii: S2211-0348(22)00045-1
doi: 10.1016/j.msard.2022.103530
pii:
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

103530

Informations de copyright

Copyright © 2022 Elsevier B.V. All rights reserved.

Auteurs

Matthias Reichl (M)

Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany.

Matthias Wittayer (M)

Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany.

Claudia E Weber (CE)

Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany.

Michael Platten (M)

Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany.

Achim Gass (A)

Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany.

Philipp Eisele (P)

Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany. Electronic address: philipp.eisele@medma.uni-heidelberg.de.

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Classifications MeSH