The central vein sign in multiple sclerosis patients with vascular comorbidities.

Central vein sign cerebral small vessel disease magnetic resonance imaging multiple sclerosis vascular risk factors

Journal

Multiple sclerosis (Houndmills, Basingstoke, England)
ISSN: 1477-0970
Titre abrégé: Mult Scler
Pays: England
ID NLM: 9509185

Informations de publication

Date de publication:
06 2021
Historique:
pubmed: 5 8 2020
medline: 25 9 2021
entrez: 5 8 2020
Statut: ppublish

Résumé

The central vein sign (CVS) is an imaging biomarker able to differentiate multiple sclerosis (MS) from other conditions causing similar appearance lesions on magnetic resonance imaging (MRI), including cerebral small vessel disease (CSVD). However, the impact of vascular risk factors (VRFs) for CSVD on the percentage of CVS positive (CVS To investigate the association between different VRFs and the percentage of CVS In 50 MS patients, 3T brain MRIs (including high-resolution 3-dimensional T2*-weighted images) were analyzed for the presence of the CVS and MRI markers of CSVD. A backward stepwise regression model was used to predict the combined predictive effect of VRF (i.e. age, hypertension, diabetes, obesity, ever-smoking, and hypercholesterolemia) and MRI markers of CSVD on the CVS. The median frequency of CVS The proportion of CVS

Sections du résumé

BACKGROUND
The central vein sign (CVS) is an imaging biomarker able to differentiate multiple sclerosis (MS) from other conditions causing similar appearance lesions on magnetic resonance imaging (MRI), including cerebral small vessel disease (CSVD). However, the impact of vascular risk factors (VRFs) for CSVD on the percentage of CVS positive (CVS
OBJECTIVE
To investigate the association between different VRFs and the percentage of CVS
METHODS
In 50 MS patients, 3T brain MRIs (including high-resolution 3-dimensional T2*-weighted images) were analyzed for the presence of the CVS and MRI markers of CSVD. A backward stepwise regression model was used to predict the combined predictive effect of VRF (i.e. age, hypertension, diabetes, obesity, ever-smoking, and hypercholesterolemia) and MRI markers of CSVD on the CVS.
RESULTS
The median frequency of CVS
CONCLUSION
The proportion of CVS

Identifiants

pubmed: 32749948
doi: 10.1177/1352458520943785
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1057-1065

Auteurs

François Guisset (F)

Department of Neurology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium/Department of Neurology, Hôpital Brugmann, Université Libre de Bruxelles, Brussels, Belgium.

Valentina Lolli (V)

Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium.

Céline Bugli (C)

Plateforme technologique de Support en Méthodologie et Calcul Statistique, Université Catholique de Louvain, Brussels, Belgium.

Gaetano Perrotta (G)

Department of Neurology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium.

Julie Absil (J)

Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium.

Bernard Dachy (B)

Department of Neurology, Hôpital Brugmann, Université Libre de Bruxelles, Brussels, Belgium.

Caroline Pot (C)

Department of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.

Marie Théaudin (M)

Department of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.

Marco Pasi (M)

University of Lille, Inserm, CHU Lille, U1172-LilNCog-Lille Neuroscience & Cognition, Lille, France.

Vincent van Pesch (V)

Department of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.

Pietro Maggi (P)

Department of Neurology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium/Department of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland/Department of Neurology, Cliniques universitaires Saint Luc, Université Catholique de Louvain, Brussels, Belgium.

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Classifications MeSH