Marwa Kaisey1, Andrew J Solomon2, Brooke L Guerrero3, Brian Renner4, Zhaoyang Fan5, Natalie Ayala6, Michael Luu7, Marcio A Diniz8, Pascal Sati9, Nancy L Sicotte10. 1. Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA. Electronic address: marwa.kaisey@csmc.edu. 2. Larner College of Medicine at the University of Vermont, Department of Neurological Sciences, 1 South Prospect Street, Arnold, Level 2, Burlington, Vermont 05401, USA. Electronic address: andrew.solomon@uvmhealth.org. 3. Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA. Electronic address: brooke.guerrero@cshs.org. 4. Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA. Electronic address: brian.renner@cshs.org. 5. Cedars-Sinai Biomedical Imaging Research Institute, 116 N Robertson Blvd, Los Angeles, CA 90048, USA. Electronic address: zhaoyang.fan@cshs.org. 6. Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA. Electronic address: natalie.ayala@cshs.org. 7. Cedars-Sinai Biostatistics and Bioinformatics Research Center, 8700 Beverly Blvd North Tower, Los Angeles, CA 90048, USA. Electronic address: michael.luu@cshs.org. 8. Cedars-Sinai Biostatistics and Bioinformatics Research Center, 8700 Beverly Blvd North Tower, Los Angeles, CA 90048, USA. Electronic address: marcio.diniz@cshs.org. 9. Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA. Electronic address: pascal.sati@cshs.org. 10. Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, Suite A6600, Los Angeles, CA 90048, USA. Electronic address: nancy.sicotte@cshs.org.
Abstract
BACKGROUND: Misdiagnosis of multiple sclerosis (MS) is common and often occurs due to misattribution of non-MS magnetic resonance imaging (MRI) lesions to MS demyelination. A recently developed MRI biomarker, the central vein sign (CVS), has demonstrated high specificity for MS lesions and may thus help prevent misdiagnosis. OBJECTIVE: This study explores the potential "real world" diagnostic value of CVS by comparing CVS in patients with MS and patients previously misdiagnosed with MS. METHODS: Fifteen patients with MS and 15 misdiagnosed with MS were prospectively recruited to undergo 3T brain MRI. T2-weighted fluid-attenuated inversion recovery (FLAIR) and T2*-weighted segmented echo-planar-imaging (T2*-EPI) were acquired. The generated FLAIR* images were analyzed by two independent raters. The percentage of lesions with CVS was calculated for each patient. RESULTS: A CVS lesion threshold of 29% or higher resulted in high sensitivity (0.79) and specificity (0.88) for MS and correctly identified 87% of patients previously misdiagnosed with MS. Interrater reliability for CVS was high with a Cohen's kappa coefficient of 0.86. CONCLUSION: This study demonstrates the ability of CVS to differentiate between patients with MS and patients with an MS misdiagnosis resulting from standard MRI and clinical evaluation. Clinical application of CVS may reduce MS misdiagnosis.
BACKGROUND: Misdiagnosis of multiple sclerosis (MS) is common and often occurs due to misattribution of non-MS magnetic resonance imaging (MRI) lesions to MS demyelination. A recently developed MRI biomarker, the central vein sign (CVS), has demonstrated high specificity for MS lesions and may thus help prevent misdiagnosis. OBJECTIVE: This study explores the potential "real world" diagnostic value of CVS by comparing CVS in patients with MS and patients previously misdiagnosed with MS. METHODS: Fifteen patients with MS and 15 misdiagnosed with MS were prospectively recruited to undergo 3T brain MRI. T2-weighted fluid-attenuated inversion recovery (FLAIR) and T2*-weighted segmented echo-planar-imaging (T2*-EPI) were acquired. The generated FLAIR* images were analyzed by two independent raters. The percentage of lesions with CVS was calculated for each patient. RESULTS: A CVS lesion threshold of 29% or higher resulted in high sensitivity (0.79) and specificity (0.88) for MS and correctly identified 87% of patients previously misdiagnosed with MS. Interrater reliability for CVS was high with a Cohen's kappa coefficient of 0.86. CONCLUSION: This study demonstrates the ability of CVS to differentiate between patients with MS and patients with an MS misdiagnosis resulting from standard MRI and clinical evaluation. Clinical application of CVS may reduce MS misdiagnosis.
Authors: Omar Al-Louzi; Sargis Manukyan; Maxime Donadieu; Martina Absinta; Vijay Letchuman; Brent Calabresi; Parth Desai; Erin S Beck; Snehashis Roy; Joan Ohayon; Dzung L Pham; Anish Thomas; Steven Jacobson; Irene Cortese; Pavan K Auluck; Govind Nair; Pascal Sati; Daniel S Reich Journal: Mult Scler Date: 2022-06-08 Impact factor: 5.855