4.4 Article

Diffusion tensor MR imaging in spinal cord injury

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Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.injury.2017.02.016

Keywords

Diffusion tensor imaging; Spinal cord injury; Neurological outcome

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Background: The ability of diffusion tensor imaging (DTI) to complement conventional MR imaging by diagnosing subtle injuries to the spinal cord is a subject of intense research. We attempted to study change in the DTI indices, namely fractional anisotropy (FA) and mean diffusivity (MD) after traumatic cervical spinal cord injury and compared these with corresponding data from a control group of individuals with no injury. The correlation of these quantitative indices to the neurological profile of the patients was assessed. Material and methods: 20 cases of acute cervical trauma and 30 age and sex matched healthy controls were enrolled. Scoring of extent of clinical severity was done based on the Frankel grading system. MRI was performed on a 3T system. Following the qualitative tractographic evaluation of white matter tracts, quantitative datametrics were calculated. Results: In patients, the Mean FA value at the level of injury (0.43+/-0.08) was less than in controls (0.62+/-0.06), which was statistically significant (p value < 0.001). Further, the Mean MD value at the level of injury (1.30+/-0.24) in cases was higher than in controls (1.07+/-0.12, p value < 0.001). Statistically significant positive correlation was found between clinical grading (Frankel grade) and FA values at the level of injury (r value = 0.86). Negative correlation was found between clinical grade and Mean MD at the level of injury (r value = -0.38) which was however statistically not significant. Conclusion: Quantitative DTI indices are a useful parameter for detection of spinal cord injury. FA value was significantly decreased while MD value was significantly increased at the level of injury in cases as compared to controls. Further, FA showed significant correlation with clinical grade. DTI could thus serve as a reliable objective imaging tool for assessment of white matter integrity and prognostication of functional outcome. (C) 2017 Elsevier Ltd. All rights reserved.

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