Diagnostic performance of central vein sign for multiple sclerosis with a simplified three-lesion algorithm

采用简化的三病灶算法评估中心静脉征在多发性硬化症诊断中的性能

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Abstract

BACKGROUND: Detection of a "central vein sign" (CVS) on FLAIR* magnetic resonance imaging (MRI) is highly specific and sensitive for multiple sclerosis (MS). We evaluated the specificity and sensitivity of simplified CVS algorithms for MS diagnosis. METHODS: MRIs from 10 participants with MS without additional comorbidities for MRI white matter abnormalities; 10 with MS and additional comorbidities for white matter abnormalities; 10 with migraine, white matter abnormalities, and no additional comorbidities; and 10 who had previously been erroneously diagnosed with MS were evaluated. 3T MRI T2-FLAIR and T2*-weighted sequences were acquired to create FLAIR* images. Three MS physician reviewers, blinded to diagnosis, evaluated two different algorithms: (1) three lesions pre-selected on FLAIR were subsequently evaluated for CVS on FLAIR*( select3). (2) FLAIR* was evaluated for up to three lesions with CVS ( select3*). RESULTS: For select3, average specificity across reviewers for MS was 0.98 and sensitivity 0.52 and a correct prediction of diagnosis demonstrated kappa = 0.29. For select3*, specificity was 0.81, sensitivity was 0.83, and kappa was 0.31. CONCLUSION: A simplified determination of CVS in three white matter lesions on 3T FLAIR* MRI demonstrated good specificity and sensitivity and fair inter-rater reliability for a diagnosis of MS and with further study, may be a candidate for clinical application.

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