3T T2* MRI DISTINGUISHES MS FROM MICROANGIOPATHIC LESIONS. Issue 10 (9th September 2014)

• Record Type: Journal Article
• Authors: Mistry, Niraj; Abdel-Fahim, Rasha; Samaraweera, Amal; Mougin, Olivier; Tallantyre, Emma; Tench, Christopher; Jaspan, Tim; Morgan, Paul; Evangelou, Nikos
• Is Part Of: Journal of neurology, neurosurgery and psychiatry. Volume 85:Issue 10(2014)
• Page Start: e4
• Page End: e4
• Publication Date: 2014-09-09
• Subjects: EPILEPSY; Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Psychiatry -- Periodicals; 616.8
• DOI: 10.1136/jnnp-2014-309236.9
• Languages: English
• ISSNs: 0022-3050

Abstract

Abstract : Background: White matter lesions are frequently detected using brain MRI performed for various indications. Most are microangiopathic but demyelination, including multiple sclerosis, is an important cause and conventional MRI cannot always distinguish between these pathologies. The proportion of lesions with a central vein on 7T T2*-weighted MRI prospectively distinguishes demyelination from microangiopathic white matter lesions. Objective: To test whether 3T T2*-weighted MRI can differentiate multiple sclerosis patients from patients with microangiopathic brain lesions. Methods: Forty patients were studied. Initially a test cohort of 10 patients with multiple sclerosis and 10 patients with microangiopathic white matter lesions underwent brain 3T MRI. Anonymised scans were analysed blind to clinical data, and simple diagnostic rules were devised, which were applied to a validation cohort of 20 patients (13 with multiple sclerosis and 7 with microangiopathic lesions). Results: Within the test cohort, all patients with multiple sclerosis had central veins visible in >45% of lesions, while the others all had central veins visible in <45% of lesions. By applying diagnostic rules to the validation cohort, all 20 patients were correctly categorised. Conclusion: T2*-weighted 3T MRI distinguishes multiple sclerosis from microangiopathic brain white matter lesions. Clinical application of this technique could supplement existing diagnostic algorithms.