Reduced Field of View Diffusion Tensor Imaging and Fiber Tractography of the Pediatric Cervical and Thoracic Spinal Cord Injury.

Abstract

The aim of this study is to assess the utility and effectiveness of diffusion tensor imaging (DTI) and diffusion tensor tractography (DTT) of the entire pediatric cervical and thoracic spinal cord toward discrimination of typically developing (TD) controls and subjects with spinal cord injury (SCI). A total of 43 pediatric subjects, including 23 TD subjects ranging in age from 6 to 16 years old and 20 subjects with SCI ranging in age from 7 to 16 years, were recruited and scanned using a 3.0 Tesla magnetic resonance scanner. Reduced field of view diffusion tensor images were acquired axially to cover the entire spinal cord across two slabs. For DTI analysis, motion correction was performed by coregistration of the diffusion-weighted images to the reference image (b0). Streamline deterministic tractography results were generated from the preprocessed data. DTI and DTT parameters of the whole cord, including fractional anisotropy (FA), mean diffusivity (MD), tract length, and tract density, were calculated, averaged across the whole spinal cord, and compared between the TD and SCI groups. Statistically significant decreases have been shown in FA (TD = 0.46 ± 0.11; SCI = 0.37 ± 0.09; p < 0.0001) and tract density (TD = 405.93 ± 243.84; SCI = 268.90 ± 270.34; p < 0.0001). However, the mean length of tracts and MD did not show significant differences. When investigating differences in DTI and DTT parameters above and below the injury site, it was shown that the FA and tract density in patients with cervical SCI decreased significantly in the thoracic region. An identical trend was observed in the cervical region for patients with thoracic SCI as well. When comparing TD and SCI subjects, FA and tract density were the most sensitive parameters in detecting functional changes of the spinal cord in chronic pediatric SCI. The results show that both DTI and DTT have the potential to be imaging biomarkers in the diagnosis of SCI.