Evidence map›Paper›PMID 39622133›Full record

ArticleMultiple sclerosis and related disorders2025

Incorporation of the central vein sign into the McDonald criteria.

Moein Amin, Kunio Nakamura, Lynn Daboul, Carly O'Donnell, Quy Cao, Paulo Rodrigues, John Derbyshire, Christina Azevedo, Amit Bar-Or, Eduardo Caverzasi and 20 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Multiple sclerosis and related disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

30 authors.

Moein AminMellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, United States.
Kunio NakamuraDepartment of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, United States.
Lynn DaboulTranslational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States; Cleveland Clinic Lerner College of Medicine, Cleveland, United States.
Carly O'DonnellPenn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.
Quy CaoPenn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.
Paulo RodriguesQMENTA Inc., Boston, United States.
John DerbyshireFunctional MRI Facility, NIMH, National Institutes of Health, Bethesda, United States.
Christina AzevedoDepartment of Neurology, University of Southern California, Los Angeles, United States.
Amit Bar-OrDepartment of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.
Eduardo CaverzasiDepartment of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy; UCSF Weill Institute for Neurosciences, Department of Neurology, University of California at San Francisco, San Francisco, United States.
Peter A CalabresiDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, United States.
Bruce A C CreeUCSF Weill Institute for Neurosciences, Department of Neurology, University of California at San Francisco, San Francisco, United States.
Leorah FreemanDepartment of Neurology, Dell Medical School, The University of Texas, Austin, United States.
Roland HenryUCSF Weill Institute for Neurosciences, Department of Neurology, University of California at San Francisco, San Francisco, United States.
Erin E LongbrakeDepartment of Neurology, Yale University, New Haven, United States.
Jiwon OhDivision of Neurology, St. Michael's Hospital, University of Toronto, Toronto, Canada.
Nico PapinuttoUCSF Weill Institute for Neurosciences, Department of Neurology, University of California at San Francisco, San Francisco, United States.
Daniel PelletierDepartment of Neurology, University of Southern California, Los Angeles, United States.
Vesna PrčkovskaQMENTA Inc., Boston, United States.
Praneeta C RazaCleveland Clinic Lerner College of Medicine, Cleveland, United States; Duke Clinical Research Institute, Durham, United States.
Marc RamosQMENTA Inc., Boston, United States.
Rohini SamudralwarDepartment of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States; Department of Neurology, University of Texas Health Science Center, Houston, United States.
Matthew SchindlerDepartment of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.
Elias S SotirchosDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, United States.
Nancy SicotteDepartment of Neurology, Cedars-Sinai Medical Center, Los Angeles, United States.
Andrew J SolomonDepartment of Neurological Sciences, Larner College of Medicine, The University of Vermont, Burlington, United States.
Russell ShinoharaPenn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States.
Daniel S ReichTranslational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States.
Pascal SatiTranslational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, United States.
Daniel OntanedaMellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, United States. Electronic address: ontaned@ccf.org.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Multimodal MRI in Multiple SclerosisZIANS003119 · NINDS · NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE · PI REICH, DANIEL · 2010 to 2025
$53.4M
The Role of B cells in the Origin and Progression of Multiple SclerosisR35NS111644 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI STEPHEN L HAUSER · 2019 to 2026
$9.1M
Central Vein Sign: A Diagnostic Biomarker in Multiple SclerosisU01NS116776 · NINDS · CLEVELAND CLINIC LERNER COM-CWRU · PI ONTANEDA, DANIEL, SATI, PASCAL · 2020 to 2024
$7.1M
Inter-modal Coupling Image AnalyticsR01MH112847 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Theodore Satterthwaite, Russell Takeshi Shinohara · 2017 to 2026
$5.9M
Harmonization of Multi-Site Neuroimaging Data from Complex Study DesignsR01MH123550 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI SHINOHARA, RUSSELL TAKESHI · 2020 to 2025
$4.0M
Advanced Statistical Analytics of MRI in MSR01NS112274 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI SHINOHARA, RUSSELL TAKESHI · 2020 to 2024
$2.8M
Interactions between Gut Microbiome and B-Cell Depletion in Multiple SclerosisK23NS107624 · NINDS · YALE UNIVERSITY · PI LONGBRAKE, ERIN · 2019 to 2023
$980k
Intramural NIH HHS ZIA NS003119NCATS NIH HHS UL1 TR001863NIMH NIH HHS R01 MH112847NIMH NIH HHS R01 MH123550NINDS NIH HHS K23 NS107624NINDS NIH HHS R01 NS112274NINDS NIH HHS R35 NS111644NINDS NIH HHS U01 NS116776
6 · The paper itself

Abstract

backgroundDiagnosis of multiple sclerosis (MS) frequently relies on MRI dissemination in time (DIT) and space (DIS), as codified in 2017 McDonald criteria (McD 2017). The central vein sign (CVS) is a proposed MS diagnostic biomarker, but its optimal incorporation into McD 2017 has not been extensively studied.

objectiveEvaluate the diagnostic performance of several methods incorporating CVS into McD 2017 radiological DIS criteria.

methodsData were obtained from the CAVS-MS Pilot, a cross-sectional, international multi-center study conducted by the North American Imaging in MS Cooperative (NAIMS) that recruited adults referred for suspicion/diagnosis of demyelinating disease. Diagnostic performance of methods incorporating CVS into McD 2017 radiological DIS were evaluated by comparing sensitivity, specificity, and accuracy.

results78 participants (37 MS, 41 others) were included. For MS diagnosis, sensitivity, specificity, and accuracy of DIS based on brain imaging (DIS-B) alone was 92 %, 69 %, and 78 %. Requiring at least one lesion with CVS in any brain location in addition to DIS-B increased specificity (sensitivity 92 %, specificity 81 %, accuracy 86 %). Presence of 2 deep white matter lesions with CVS as an additional topography for DIS-B had higher sensitivity (sensitivity 97 %, specificity 59 %, accuracy 77 %).

conclusionsIncorporation of CVS in McD 2017 DIS criteria can be used to improve diagnostic accuracy. Validation in additional prospective studies is needed.

Indexed as

Cerebral VeinsMagnetic Resonance ImagingMultiple SclerosisNeuroimagingAdultBrainCross-Sectional StudiesFemaleHumansMaleMiddle AgedPilot ProjectsSensitivity and SpecificityBiomarkerCentral vein signDiagnostic accuracyMisdiagnosisMRIMultiple sclerosis

Identifiers

PMID39622133
PMCPMC11779579

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