Abstract

Background: The central vein sign (CVS) is a radiological feature proposed as a multiple sclerosis (MS) imaging biomarker able to accurately differentiate MS from other white matter diseases of the central nervous system. In this work, we evaluated the pooled proportion of the CVS in brain MS lesions and to estimate the diagnostic performance of CVS to perform a diagnosis of MS and propose an optimal cut-off value. Methods: A systematic search was performed on publicly available databases (PUBMED/MEDLINE and Web of Science) up to 24 August 2020. Analysis of the proportion of white matter MS lesions with a central vein was performed using bivariate random-effect models. A meta-regression analysis was performed and the impact of using particular sequences (such as 3D echo-planar imaging) and post-processing techniques (such as FLAIR*) was investigated. Pooled sensibility and specificity were estimated using bivariate models and meta-regression was performed to address heterogeneity. Inclusion and publication bias were assessed using asymmetry tests and a funnel plot. A hierarchical summary receiver operating curve (HSROC) was used to estimate the summary accuracy in diagnostic performance. The Youden index was employed to estimate the optimal cut-off value using individual patient data. Results: The pooled proportion of lesions showing a CVS in the MS population was 73%. The use of the CVS showed a remarkable diagnostic performance in MS cases, providing a pooled specificity of 92% and a sensitivity of 95%. The optimal cut-off value obtained from the individual patient data pooled together was 40% with excellent accuracy calculated by the area under the ROC (0.946). The 3D-EPI sequences showed both a higher pooled proportion compared to other sequences and explained heterogeneity in the meta-regression analysis of diagnostic performances. The 1.5 Tesla (T) scanners showed a lower (58%) proportion of MS lesions with a CVS compared to both 3T (74%) and 7T (82%). Conclusions: The meta-analysis we have performed shows that the use of the CVS in differentiating MS from other mimicking diseases is encouraged; moreover, the use of dedicated sequences such as 3D-EPI and the high MRI field is beneficial.

Highlights

  • Multiple sclerosis (MS) is one of the most common autoimmune disorders of the central nervous system (CNS), characterized by diffuse inflammatory/demyelinating and neurodegenerative alterations [1]

  • Evaluating the role of more specific magnetic resonance imaging (MRI) features of multiple sclerosis (MS) lesions, such as the central vein sign (CVS), is considered a high-priority area for research according to The International Panel on Diagnosis of MS, which produced the 2017 revised diagnostic criteria [60]

  • The systematic review and meta-analysis we performed aimed to assess the prevalence of the CVS in white matter (WM) MS brain lesions with respect to other WM diseases, as well as to investigate the use of the CVS in the differential diagnosis of MS by suggesting an optimal cut-off to differentiate MS from other conditions with Magnetic resonance imaging (MRI) T2 hyperintensities and analyze the diagnostic performance measured with pooled sensitivity and specificity

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Summary

Introduction

Multiple sclerosis (MS) is one of the most common autoimmune disorders of the central nervous system (CNS), characterized by diffuse inflammatory/demyelinating and neurodegenerative alterations [1]. The diagnostic criteria, implementing MRI in the diagnostic process, have increased their sensitivity, allowing an even earlier MS diagnosis, after a first/isolated event suggestive of acute CNS demyelination [2]. Their specificity remains limited, especially in the presence of atypical history, and this could result in misdiagnosis and initiation/delay of inappropriate/approved disease-modifying treatment [3]. The 3D-EPI sequences showed both a higher pooled proportion compared to other sequences and explained heterogeneity in the meta-regression analysis of diagnostic performances. Conclusions: The meta-analysis we have performed shows that the use of the CVS in differentiating MS from other mimicking diseases is encouraged; the use of dedicated sequences such as 3D-EPI and the high MRI field is beneficial

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