Diagnostic performance of central vein sign for multiple sclerosis with a simplified three-lesion algorithm
Andrew J Solomon1, Richard Watts2, Daniel Ontaneda3
1Department of Neurological Sciences, Larner College of Medicine, The University of Vermont, Burlington, VT, USA.
Multiple Sclerosis (Houndmills, Basingstoke, England)
|August 19, 2017
Summary
Simplified algorithms for the central vein sign (CVS) on FLAIR* MRI show promise for diagnosing multiple sclerosis (MS). These methods offer good specificity and sensitivity, potentially aiding clinical application in MS detection.
Area of Science:
- Neurology
- Radiology
- Medical Imaging
Background:
- The central vein sign (CVS) detected on FLAIR* MRI is a highly specific and sensitive biomarker for multiple sclerosis (MS).
- Evaluating simplified algorithms for CVS detection is crucial for improving diagnostic accuracy and clinical utility in MS.
Purpose of the Study:
- To assess the specificity and sensitivity of simplified central vein sign (CVS) algorithms for diagnosing multiple sclerosis (MS).
- To determine the inter-rater reliability of these simplified CVS detection methods.
Main Methods:
- Retrospective analysis of 3T MRI FLAIR* images from 40 participants across four groups: MS, MS with comorbidities, migraine with white matter abnormalities, and prior misdiagnosis of MS.
- Two simplified CVS algorithms were evaluated by three blinded MS physician reviewers: 'select3' (evaluating pre-selected FLAIR lesions on FLAIR*) and 'select3*' (evaluating up to three lesions with CVS on FLAIR*).
Main Results:
- The 'select3' algorithm achieved an average specificity of 0.98 and sensitivity of 0.52 for MS diagnosis, with a kappa of 0.29.
- The 'select3*' algorithm demonstrated a specificity of 0.81 and sensitivity of 0.83, with a kappa of 0.31, indicating fair inter-rater reliability.
Conclusions:
- Simplified determination of the central vein sign (CVS) in three white matter lesions on 3T FLAIR* MRI exhibits good specificity and sensitivity for MS diagnosis.
- These simplified CVS algorithms show potential for clinical application in MS diagnosis, warranting further investigation.
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