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. 2005 Jul 1;26(3):822-8.
doi: 10.1016/j.neuroimage.2005.02.033. Epub 2005 Mar 31.

Mean diffusivity and fractional anisotropy histogram analysis of the cervical cord in MS patients

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Mean diffusivity and fractional anisotropy histogram analysis of the cervical cord in MS patients

Paola Valsasina et al. Neuroimage. .

Abstract

The spinal cord is frequently involved in multiple sclerosis (MS), and cord damage may be an important contributor to disability. Diffusion tensor magnetic resonance imaging (DT-MRI) provides quantitative information about the structural and orientational features of the central nervous system. In order to assess whether diffusion tensor-derived measures of cord tissue damage are related to clinical disability, mean diffusivity (MD) and fractional anisotropy (FA) histograms from the cervical cord were acquired from a large cohort of MS patients. Diffusion-weighted sensitivity-encoded (SENSE) echo planar images of the cervical cord, and brain dual-echo and diffusion-weighted scans were acquired from 44 patients with MS and 17 healthy controls. Cord and brain MD and FA histograms were produced. An analysis of variance model, adjusting for cord volume and patient age, was used to compare cord DT-MRI parameters from controls and patients. A multivariate linear regression model was used to identify DT-MRI variables independently associated with disability. Average cervical cord FA was significantly lower in MS patients compared to controls. Cord cross-sectional area, average FA and average MD were all significantly correlated with the degree of disability (r values ranging from 0.36 to 0.51). The multivariate linear regression model retained average cord FA and average brain MD as variables independently associated with disability, with a correlation coefficient of 0.73 (P < 0.001). DT-MRI reveals a loss of cervical cord tissue structure in MS patients. The strong correlation found between a composite DT-MRI score and disability suggests that a full and accurate assessment of cervical cord damage in MS provides information that usefully contributes to an explanation of the clinical manifestations of the disease.

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