Assessing the Recovery of Spinal Cord on Traumatic Spinal Cord Injury using Diffusion Tensor Imaging
Poster No:
2366
Submission Type:
Abstract Submission
Authors:
Bing Yao1, Gail Forrest1, Steven Kirshblum1
Institutions:
1Kessler Foundation, West Orange, NJ
First Author:
Co-Author(s):
Introduction:
The challenges of spinal cord injury (SCI) extend far beyond physical damage; patients face severe disability, difficulty functioning, and expensive treatments. The questionnaires and exams used to measure recovery [1,2] have several shortcomings, including variability across examiners and not being able to evaluate the spinal cord function below the neurological level [3]. The conventional MRI, however, cannot fully reveal complexities of the change during recovery, providing very little information about the damage that occurs on a microstructural level. In this study, we investigated using the diffusion tensor imaging (DTI) to detect nerve fiber structural changes above and below the injury level in SC.
Methods:
Participants: Thirteen acute SCI patients (age=41±17 y/o, F/M=3/10, AIS grade=B to D) and Twelve gender and age matched healthy controls (HCs) (age=43±17 y/o, F/M=3/9) have participated the study. All the participants went through five visits over the course of the first-year post injury (baseline, 2 weeks, 1, 3, and 6 months after the commencement of rehabilitative treatment). The outcome measurements including American Spinal Injury Association Impairment Scale (ASIA), Modified Ashworth Scale (MAS) and Spinal Cord Independence Measure III (SCIM III) were performed at each visit for the patient group.
Image Acquisition: All MRIs were acquired at a 3T Siemens scanner. The axial DTI covering the entire cervical and thoracic sections of the cord was acquired with the following parameters: TE=97ms, TR=3600ms, Flip angle=90°; in-plane resolution=1.6x1.6mm, thickness = 3mm, 30 directions with b=1000s/mm. A high-resolution anatomical scan using T2*-weighted Multi-Echo Data Image Combination (MEDIC) sequence matching the DTI slice location was also acquired.
Data Analysis: The raw DTI data were corrected for eddy current distortion and motion using FSL then further processed using Diffusion Toolkit. DTI indices including FA, MD, AD, and RD were computed for each voxel. Virtual nerve fibers were reconstructed using the fiber assignment through line propagation approach based on 2nd order Runge Kutta algorithm.
Image Acquisition: All MRIs were acquired at a 3T Siemens scanner. The axial DTI covering the entire cervical and thoracic sections of the cord was acquired with the following parameters: TE=97ms, TR=3600ms, Flip angle=90°; in-plane resolution=1.6x1.6mm, thickness = 3mm, 30 directions with b=1000s/mm. A high-resolution anatomical scan using T2*-weighted Multi-Echo Data Image Combination (MEDIC) sequence matching the DTI slice location was also acquired.
Data Analysis: The raw DTI data were corrected for eddy current distortion and motion using FSL then further processed using Diffusion Toolkit. DTI indices including FA, MD, AD, and RD were computed for each voxel. Virtual nerve fibers were reconstructed using the fiber assignment through line propagation approach based on 2nd order Runge Kutta algorithm.
Results:
Shorter and thinner fibers were seen on the SCI patients comparing to those on the HCs, suggesting the damaged white matter fibers. The outcome measures by SCIM showed a significant change over the 5 visits(f(4,28) = 13.7, p<.001), suggesting a recovery over the six months post injury. The ASIA result showed the same recovery trend over time but not significantly (figure not shown). Fig. 1 shows the overall AD and FA in the SCI group were significantly lower than those in the HC group and the differences varies at spine locations. Higher values of AD, MD and RD were observed from T3 to T10 Level, indicating a possible structural variation in spine locations. Fig. 2 shows significant differences in AD (Above, below and LOI) and FA (Above and LOI) (p<0.05, Mixed Model Analysis) between the SCI and HC groups; All diffusivity measures demonstrated obvious significant changes over time at Below injury level (p<0.05, independent t-test). No significant changes over time were found at LOI.
Conclusions:
Our data shows FA and AD had significantly lower values in the SCI group. A significant FA reductions above the injury in each visit after baseline, and at the injury level in visits 2, 3, and 5 was observed, which is consistent with the findings of reduced FA particularly at the injury level in previous reports on both acute and chronic patients [4]. It is also noteworthy that FA differed from controls above and at the injury but not below injury regions, suggesting that different impacts to the spine structure due to the injury. This is consistent with previous reports in acute and chronic patients, after injury [5]. Our study demonstrates that DTI may serve as a tool to assess the changes at different regions of the spine, of which information is usually hard to be obtained by traditional evaluation methods.
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis 2
Novel Imaging Acquisition Methods:
Diffusion MRI 1
Keywords:
Data analysis
MRI
Spinal Cord
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2) Marino, R.J. and D.E. Graves (2004), “Metric properties of the ASIA motor score: subscales improve correlation with functional activities”, Arch Phys Med Rehabil, 85(11): p. 1804-10.
3) Mulachey, M. J., et al. (2013), “Neuromuscular scoliosis in children with spinal cord injury”, Top Spinal Cord Inj Rehabil, 19(2): p. 96-103.
4) Chang, Y., et al., (2010), “Diffusion tensor imaging and fiber tractography of patients with cervical spinal cord injury”, Journal of Neurotrauma, 27(11), 2033-40.
5) Koskinen, et al., (2013), “The current role of decompressive craniectomy in the management of neurological emergencies”, Journal of Neurotrauma, 30(18), 1587-95.