• Jiao-Long Cui, Chun-Yi Wen, Yong Hu, Kin-Cheung Mak, Ka-Hung Henry Mak, and Keith Dip-Kei Luk.
• Department of Orthopaedics and Traumatology, Li Ka Shing Faculty of Medicine, the University of Hong Kong, Hong Kong.
• Neuroimage. 2011 Oct 15;58(4):1028-33.

AbstractThe majority of nerve fibers in the spinal cord run longitudinally, playing an important role in connecting the brain to the peripheral nerves. There is a growing interest in applying diffusion tensor imaging (DTI) to the evaluation of spinal cord microarchitecture. The current study sought to compare the organization of longitudinal nerve fibers between healthy and myelopathic spinal cords using entropy-based analysis of principal eigenvector mapping. A total of 22 subjects were recruited, including 14 healthy subjects, seven cervical myelopathy (CM) patients with single-level compression, and one patient suffering from multi-level compression. Diffusion tensor magnetic resonance (MR) images of the cervical spinal cord were obtained using a pulsed gradient, spin-echo echo-planar imaging (SE-EPI) sequence with a 3T MR system. Regions of interest (ROIs) were drawn manually to cover the spinal cord, and Shannon entropy was calculated in principal eigenvector maps. The results revealed no significant differences in orientation entropy values along the whole length of cervical spinal cord in healthy subjects (C2-3: 0.73±0.05; C3-4: 0.71±0.07; C4-5: 0.72±0.048; C5-6: 0.71±0.07; C6-7: 0.72±0.07). In contrast, orientation entropy values in myelopathic cord were significantly higher at the compression site (0.91±0.03), and the adjacent levels (above: 0.85±0.03; below: 0.83±0.05). This study provides a novel approach to analyze the orientation information in diffusion MR images of healthy and diseased spinal cord. These results indicate that orientation entropy can be applied to determine the contribution of each compression level to the overall disorganization of principal nerve tracts of myelopathic spinal cord in cases with multi-level compression.Copyright © 2011 Elsevier Inc. All rights reserved.

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