Multicenter Automated Central Vein Sign Detection Performs as Well as Manual Assessment for the Diagnosis of Multiple Sclerosis

Automated CVS assessment was comparable to manual CVS scoring for differentiating patients with MS from those with other diagnoses. Large, prospective, multicenter studies utilizing automated methods and enrolling the breadth of disorders referred for suspicion of MS are needed to determine optimal approaches for clinical implementation of an automated CVS detection method.

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Institutions

Publication Details

Journal
American Journal of Neuroradiology
Published
2024-09-27
DOI
https://doi.org/10.3174/ajnr.a8510
Citations
7
Primary Topic
Multiple Sclerosis Research Studies
Type
article
Field-Weighted Citation Impact
2.97

Funders

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article

Multicenter Automated Central Vein Sign Detection Performs as Well as Manual Assessment for the Diagnosis of Multiple Sclerosis

Daniel Pelletier, Vijay Letchuman, Eduardo Caverzasi, Timothy Robert‐Fitzgerald et al.
7 citations
American Journal of Neuroradiology
Multiple Sclerosis Research Studies
2.97
article

Multicenter Automated Central Vein Sign Detection Performs as Well as Manual Assessment for the Diagnosis of Multiple Sclerosis

Daniel Pelletier, Vijay Letchuman, Eduardo Caverzasi, Timothy Robert‐Fitzgerald, Jiwon Oh, Léorah Freeman, Andrew J Solomon, Michel Bilello, Daniel Ontaneda, María Jesús Ramos, Bruce Cree, J. Andrew Derbyshire, Omar Al‐Louzi, Praneeta Raza, Brian Renner, Erin E. Longbrake, Melissa L. Martin, Russell Taki Shinohara, Lynn Daboul, Christina Azevedo, Matthew K. Schindler, Carly M. O’Donnell, Abigail R. Manning, Quy Cao, Elias S. Sotirchos, Peter A. Calabresi, Roland G. Henry, Jae W. Song, Nancy L. Sicotte, Nico Papinutto, Amit Bar‐Or, Suradech Suthiphosuwan, Pascal Sati, Rohini Samudralwar, Paulo Rodrigues, D S Reich, Elaina Gombos
article en
7 citations

Abstract

Automated CVS assessment was comparable to manual CVS scoring for differentiating patients with MS from those with other diagnoses. Large, prospective, multicenter studies utilizing automated methods and enrolling the breadth of disorders referred for suspicion of MS are needed to determine optimal approaches for clinical implementation of an automated CVS detection method.

American Journal of NeuroradiologyVol. 46(3)
University of Vermont (US), University of Southern California (US), Cedars-Sinai Medical Center (US), St. Michael's Hospital (CA), Cleveland Clinic (US), Johns Hopkins University (US), University of California, San Francisco (US), Universidad Nacional Experimental Simón Rodríguez (VE), University of Pavia (IT), Johns Hopkins Medicine (US), Foundation Center (US), Yale University (US), Cleveland Clinic Lerner College of Medicine (US), Fondazione Istituto Neurologico Nazionale Casimiro Mondino (IT), National Institute of Neurological Disorders and Stroke (US), National Institute of Mental Health (US), University of Pennsylvania (US), The University of Texas at Austin (US)
Foundation for the National Institutes of Health, National Institute of Neurological Disorders and Stroke
Openalex Percentile: Top 9%
Multiple Sclerosis Research Studies
2.97
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