Original articleDiffusion tensor MR imaging in spinal cord injury
Review articleOpen access
2017/04/01 Full-length article DOI: 10.1016/j.injury.2017.02.016
AbstractBackgroundThe 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 methods20 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.ResultsIn 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.ConclusionQuantitative 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.
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