Voxel-based cervical spinal cord mapping of diffusion abnormalities in MS-related myelitis.

Toosy, AT; Kou, N; Altmann, D; Wheeler-Kingshott, CA; Thompson, AJ; Ciccarelli, O; (2014) Voxel-based cervical spinal cord mapping of diffusion abnormalities in MS-related myelitis. Neurology. ISSN 0028-3878 DOI: https://doi.org/10.1212/WNL.0000000000000857

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OBJECTIVE To apply a novel postprocessing voxel-based analysis for diffusion tensor imaging of the cervical spinal cord in multiple sclerosis (MS) in a prospective cross-sectional study. METHODS Fourteen patients with MS who were within 4 weeks of the onset of cervical myelitis (lesion C1-3) and 11 healthy controls underwent cervical spinal cord diffusion tensor imaging. Cervical spinal cord maps of fractional anisotropy (FA), mean diffusivity, radial diffusivity (RD), and axial diffusivity were registered and compared between patients and controls. Mean FA and RD values from significant thresholded clusters were regressed with clinical scores, after adjusting for cord area and age, to determine associations with physical disability. RESULTS Cord registrations for subjects were qualitatively assessed (scored out of 5) and those with low scores (1 or 2) were excluded from further analysis. Cord registration was considered good in 11 patients (6 females; mean age = 35.5 years) and 10 controls (6 females; mean age 44 years). Voxel-based comparisons showed patients with MS had lower FA and higher RD at C2-3 levels (left >right mainly in gray matter; p < 0.01, uncorrected). Extracted values of both FA and RD from thresholded clusters were significantly associated with greater disability measured using the Expanded Disability Status Scale and Timed 25-Foot Walk Test in patients with MS. CONCLUSIONS Mapping diffusion abnormalities within the cervical spinal cord using a novel voxel-based approach can localize clinically relevant pathology.

Item Type: Article
Faculty and Department: Faculty of Epidemiology and Population Health > Dept of Medical Statistics
PubMed ID: 25186861
Web of Science ID: 345337300008
URI: http://researchonline.lshtm.ac.uk/id/eprint/1917929


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