The “central vein sign” in patients with diagnostic “red flags” for multiple sclerosis: A prospective multicenter 3T study

Maggi, Pietro; Absinta, Martina; Sati, Pascal; Perrotta, Gaetano; Massacesi, Luca; Dachy, Bernard; Pot, Caroline; Meuli, Reto; Reich, Daniel S.; Filippi, Massimo; Pasquier, Renaud Du; Théaudin, Marie

doi:10.1177/1352458519876031

Cited by 47 publications

(62 citation statements)

References 32 publications

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“…a Cases were dichotomized as overall CVS-positive versus CVS-negative based on the previously described "40% rule" 4,6,19 . high specificity (96%, 95% CI = 89-99%), sensitivity (99%, 95% CI = 93-100%), and accuracy (area under ROC curve = 0.99, 95% CI = 0.98-1).…”

Section: Resultsmentioning

confidence: 99%

“…Inter-rater reliability was assessed based on the previously described "40% rule." 4,6,19 Statistical Analysis Demographic, clinical, and MRI differences were assessed with ANOVA and Tukey's post-hoc multiple-comparison test, with Fisher's exact or chi-square test, when appropriate. The inter-rater reliability for PRL and CVS assessment was computed using Cohen's κ.…”

Section: Methodsmentioning

confidence: 99%

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Paramagnetic Rim Lesions are Specific to Multiple Sclerosis: An International Multicenter 3T MRI Study

Maggi

Sati

Nair

et al. 2020

Annals of Neurology

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In multiple sclerosis (MS), a subset of chronic active white matter lesions are identifiable on magnetic resonance imaging by their paramagnetic rims, and increasing evidence supports their association with severity of clinical disease. We studied their potential role in differential diagnosis, screening an international multicenter clinical research-based sample of 438 individuals affected by different neurological conditions (MS, other inflammatory, infectious, and non-inflammatory conditions). Paramagnetic rim lesions, rare in other neurological conditions (52% of MS vs 7% of non-MS cases), yielded high specificity (93%) in differentiating MS from non-MS. Future prospective multicenter studies should validate their role as a diagnostic biomarker.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Paramagnetic Rim Lesions are Specific to Multiple Sclerosis: An International Multicenter 3T MRI Study

Maggi

Sati

Nair

et al. 2020

Annals of Neurology

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“…We propose a deep learning‐based automated detection of the CVS differentiating MS from its mimics with high diagnostic sensitivity, specificity and accuracy. CVSnet performed nearly as well as the previously obtained proportion of CVS+/CVS‐ lesions based on manual rating, often achieving perfect discrimination between MS and its mimics, and is much faster compared with manual rating. Importantly, this method showed high performance across different scanner types and hospitals, strengthening its potential for clinical applicability.…”

Section: Discussionmentioning

confidence: 57%

“…Our findings are particularly relevant considering that recent studies using manual CVS classification at clinical field strengths have shown potential for application of the CVS imaging biomarker in clinical practice . Importantly, the most recent international panel for MS diagnosis called for further research on this topic before considering inclusion of the CVS in future MS diagnostic criteria .…”

Section: Discussionmentioning

confidence: 81%

“…Results from a recent multicenter study suggest that the diagnostic performance of this CVS biomarker at clinical field strengths is highly dependent on the type of susceptibility‐based MRI sequence used . In this context, recent data from our group using an optimized three‐dimensional (3D) T2*‐weighted segmented echo‐planar imaging (T2*‐EPI) sequence at clinical field strengths have shown that the CVS can efficiently discriminate between MS and inflammatory vasculopathies of the CNS and that this imaging biomarker can accurately predict an MS diagnosis in patients harboring atypical features for the disease …”

Section: Introductionmentioning

confidence: 99%

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CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis

et al. 2020

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The central vein sign (CVS) is an efficient imaging biomarker for multiple sclerosis (MS) diagnosis, but its application in clinical routine is limited by inter-rater variability and the expenditure of time associated with manual assessment. We describe a deep learning-based prototype for automated assessment of the CVS in white matter MS lesions using data from three different imaging centers. We retrospectively analyzed data from 3 T magnetic resonance images acquired on four scanners from two different vendors, including adults with MS (n = 42), MS mimics (n = 33, encompassing 12 distinct neurological diseases mimicking MS) and uncertain diagnosis (n = 5). Brain white matter lesions were manually segmented on FLAIR* images. Perivenular assessment was performed according to consensus guidelines and used as ground truth, yielding 539 CVS-positive (CVS + ) and 448 CVS-negative (CVS − ) lesions. A 3D convolutional neural network ("CVSnet") was designed and trained on 47 datasets, keeping 33 for testing. FLAIR* lesion patches of CVS + /CVS − lesions were used for training and validation (n = 375/298) and for testing (n = 164/150). Performance was evaluated lesion-wise and subject-wise and compared with a state-of-the-art vesselness filtering approach through McNemar's test. The proposed CVSnet approached human performance, with lesion-wise median balanced accuracy of 81%, and subject-wise balanced accuracy of 89% on the validation set, and 91% on the test set. The process of CVS assessment, in previously manually segmented lesions, was~600-fold faster using the proposed CVSnet compared with human visual assessment (test set: 4 seconds vs. 40 minutes). On the validation and test sets, the lesion-wise performance outperformed the vesselness filter method (P < 0.001). The proposed deep learning prototype shows promising performance in differentiating MS from its mimics. Our approach was evaluated using data from different hospitals, enabling larger multicenter trials to evaluate the benefit of introducing the CVS marker into MS diagnostic criteria.Abbreviations used: AUC, area under the curve; CVS, central vein sign; FLAIR, 3D T2-weighted fluid-attenuated inversion recovery; GPU, graphics processing unit; MRI, magnetic resonance imaging; MS, multiple sclerosis; NIR, no information rate; ReLU, rectified linear unit; ROC, receiver operating characteristic; T2*-EPI, T2*-weighted segmented echo-planar imaging; 3D, threedimensional; WM, white matter.Pietro Maggi and Mário João Fartaria contributed equally to this work.

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The diagnostic value of the central vein sign in radiologically isolated syndrome

Landes‐Chateau,

Levraut,

Okuda

et al. 2024

Ann Clin Transl Neurol

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ObjectiveThe radiologically isolated syndrome (RIS) represents the earliest detectable preclinical phase of multiple sclerosis (MS). Increasing evidence suggests that the central vein sign (CVS) enhances lesion specificity, allowing for greater MS diagnostic accuracy. This study evaluated the diagnostic performance of the CVS in RIS.MethodsPatients were prospectively recruited in a single tertiary center for MS care. Participants with RIS were included and compared to a control group of sex and age‐matched subjects. All participants underwent 3 Tesla magnetic resonance imaging, including postcontrast susceptibility‐based sequences, and the presence of CVS was analyzed. Sensitivity and specificity were assessed for different CVS lesion criteria, defined by proportions of lesions positive for CVS (CVS+) or by the absolute number of CVS+ lesions.Results180 participants (45 RIS, 45 MS, 90 non‐MS) were included, representing 5285 white matter lesions. Among them, 4608 were eligible for the CVS assessment (970 in RIS, 1378 in MS, and 2260 in non‐MS). According to independent ROC comparisons, the proportion of CVS+ lesions performed similarly in diagnosing RIS from non‐MS than MS from non‐MS (p = 0.837). When a 6‐lesion CVS+ threshold was applied, RIS lesions could be diagnosed with an accuracy of 87%. MS could be diagnosed with a sensitivity of 98% and a specificity of 83%. Adding OCBs or Kappa index to CVS biomarker increased the specificity to 100% for RIS diagnosis.InterpretationThis study shows evidence that CVS is an effective imaging biomarker in differentiating RIS from non‐MS, with similar performances to those in MS.

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The “central vein sign” in patients with diagnostic “red flags” for multiple sclerosis: A prospective multicenter 3T study

Cited by 47 publications

References 32 publications

Paramagnetic Rim Lesions are Specific to Multiple Sclerosis: An International Multicenter 3T MRI Study

Paramagnetic Rim Lesions are Specific to Multiple Sclerosis: An International Multicenter 3T MRI Study

CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis

The diagnostic value of the central vein sign in radiologically isolated syndrome

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