Value of the central vein sign at 3T to differentiate MS from seropositive NMOSD

Cortese, Rosa; Magnollay, Lise; Tur, Carmen; Abdel-Aziz, Khaled; Jacob, Anu; Angelis, Floriana De; Yiannakas, Marios C.; Prados, Ferrán; Ourselin, Sébastien; Yousry, Tarek; Barkhof, Frederik; Ciccarelli, Olga

doi:10.1212/wnl.0000000000005256

Cited by 82 publications

(71 citation statements)

References 31 publications

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“…Most existing studies focusing on the clinical value of the CVS for the differential diagnosis of MS included patients with an already known clinical diagnosis. 6,[8][9][10][11][12] One prior study investigated the diagnostic predictive value of the CVS in patients with possible MS, showing promising results. 28 However, this pilot study was done on a research 7T MRI scanner, and not all included patients experienced a neurological syndrome suggestive of MS.…”

Section: Discussionmentioning

confidence: 99%

“…2,5 The presence of a vein at the center of brain white matter (WM) lesions, the "central vein sign" (CVS), is a specific feature of MS and can now be depicted at clinical MRI field strength using specialized gradient-echo MRI sequences. [5][6][7] Several studies have shown how this promising imaging biomarker can differentiate MS from other disorders, including migraine, 8,9 cerebral The "central vein sign" in patients with diagnostic "red flags" for multiple sclerosis: A prospective multicenter 3T study small vessel disease, 10 neuromyelitis optica, 11 Susac syndrome, 12 and primary or secondary vasculitis of the CNS, showing similar WM lesions on MRI. 6 However, most prior studies are retrospective.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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Background: The central vein sign (CVS) has been shown to help in the differential diagnosis of multiple sclerosis (MS), but most prior studies are retrospective. Objectives: To prospectively assess the diagnostic predictive value of the CVS in diagnostically difficult cases. Methods: In this prospective multicenter study, 51 patients with suspected MS who had clinical, imaging, or laboratory “red flags” (i.e. features atypical for MS) underwent 3T fluid-attenuated inversion recovery (FLAIR*) magnetic resonance imaging (MRI) for CVS assessment. After the diagnostic work-up, expert clinicians blinded to the results of the CVS assessment came to a clinical diagnosis. The value of the CVS to prospectively predict an MS diagnosis was assessed. Results: Of the 39 patients who received a clinical diagnosis by the end of the study, 27 had MS and 12 received a non-MS diagnosis that included systemic lupus erythematosus, sarcoidosis, migraine, Sjögren disease, SPG4-spastic-paraparesis, neuromyelitis optica, and Susac syndrome. The percentage of perivenular lesions was higher in MS (median = 86%) compared to non-MS (median = 21%; p < 0.0001) patients. A 40% perivenular lesion cutoff was associated with 97% accuracy and a 96% positive/100% negative predictive value. Conclusion: The CVS detected on 3T FLAIR* images can accurately predict an MS diagnosis in patients suspected to have MS, but with atypical clinical, laboratory, and imaging features.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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“…This represents the imaging equivalent of inflammatory activity surrounding a vein on histology. 11 , 12 Studies in RRMS have shown its potential to differentiate RRMS from neuromyelitis optica 13 – 15 and SVD at 3 and 7T. 10 , 16 , 17 Studies at 7T showed PPMS had similar proportions of WMLs with central veins compared to RRMS.…”

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confidence: 99%

The MRI central vein marker; differentiating PPMS from RRMS and ischemic SVD

Samaraweera

Falah²,

Dineen

et al. 2018

Neurol Neuroimmunol Neuroinflamm

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ObjectiveTo determine whether the assessment of brain white matter lesion (WML) central veins differentiate patients with primary progressive MS (PPMS) from relapsing-remitting MS (RRMS) and ischemic small vessel disease (SVD) using 3T MRI.MethodsIn this cross-sectional study, 71 patients with PPMS, RRMS, and SVD were imaged using a T2*-weighted sequence. Two blinded raters identified the total number of WMLs, proportion of WMLs in periventricular, deep white matter (DWM) and juxtacortical regions, and proportion of WMLs with central veins in all patient groups. The proportions were compared between disease groups, including effect sizes. MS or SVD was categorized using a threshold of ≥40% WMLs with central veins as indicative of MS. Interrater and intrarater reproducibility was calculated.ResultsThe mean proportion of WMLs with central veins was 68.4% in PPMS, 74.3% in RRMS, and 4.7% in SVD. The difference in proportions between PPMS and SVD groups was significant (p < 0.0005; effect size: 3.8) but not significant between MS subtypes (p = 0.3; effect size: 0.29). Distribution of WMLs was similar across both MS groups, but despite SVD patients having more DWM lesions than PPMS patients, proportions of WMLs with central veins remained low (2.75% in SVD; 62.5% in PPMS). Interrater and intrarater reproducibility comparing proportions of WMLs with central veins across all patients was 0.86 and 0.90, respectively. Level of agreement between the proportion of WML central veins and established diagnosis was 0.84 and 0.82 for each rater.ConclusionsWML central veins could be used to differentiate PPMS from SVD but not between MS subtypes.

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“…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%

“…Indeed, pathology studies as early as the 19th century described the presence of a vein at the center of inflammatory lesions as a hallmark of the MS plaque . Today, the vein at the center of WM lesions can be imaged in vivo using optimized susceptibility‐based MRI sequences, and several studies have shown that the CVS can accurately distinguish MS from other disorders showing similar T2 hyperintensities on MRI . 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 .…”

Section: Introductionmentioning

confidence: 99%

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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Value of the central vein sign at 3T to differentiate MS from seropositive NMOSD

Abstract: This study provides Class III evidence that the CVS on 3T MRI accurately distinguishes patients with MS from those with seropositive NMOSD.

Cited by 82 publications

References 31 publications

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

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

The MRI central vein marker; differentiating PPMS from RRMS and ischemic SVD

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

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