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Spinal cord morphology in degenerative cervical myelopathy patients ; assessing key morphological characteristics using Mmchine vision tools

Kalum Ost, W. Bradley Jacobs, Nathan Evaniew, Julien Cohen-Adad, David Anderson and David W. Cadotte

Article (2021)

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Despite Degenerative Cervical Myelopathy (DCM) being the most common form of spinal cord injury, effective methods to evaluate patients for its presence and severity are only starting to appear. Evaluation of patient images, while fast, is often unreliable; the pathology of DCM is complex, and clinicians often have difficulty predicting patient prognosis. Automated tools, such as the Spinal Cord Toolbox (SCT), show promise, but remain in the early stages of development. To evaluate the current state of an SCT automated process, we applied it to MR imaging records from 328 DCM patients, using the modified Japanese Orthopedic Associate scale as a measure of DCM severity. We found that the metrics extracted from these automated methods are insufficient to reliably predict disease severity. Such automated processes showed potential, however, by highlighting trends and barriers which future analyses could, with time, overcome. This, paired with findings from other studies with similar processes, suggests that additional non-imaging metrics could be added to achieve diagnostically relevant predictions. Although modeling techniques such as these are still in their infancy, future models of DCM severity could greatly improve automated clinical diagnosis, communications with patients, and patient outcomes.

Uncontrolled Keywords

degenerative cervical myelopathy; personalized medicine; machine learning; spinal cord

Subjects: 1900 Biomedical engineering > 1900 Biomedical engineering
1900 Biomedical engineering > 1901 Biomedical technology
Department: Department of Electrical Engineering
Institut de génie biomédical
Research Center: NeuroPoly - Laboratoire de Recherche en Neuroimagerie
Funders: Alberta Spine Foundation, Hotchkiss Brain Institute - Cumming School of Medicine - Department of Clinical Neurosciences
PolyPublie URL: https://publications.polymtl.ca/9395/
Journal Title: Journal of Clinical Medicine (vol. 10, no. 4)
Publisher: MDPI
DOI: 10.3390/jcm10040892
Official URL: https://doi.org/10.3390/jcm10040892
Date Deposited: 07 Sep 2023 10:08
Last Modified: 08 Apr 2024 12:18
Cite in APA 7: Ost, K., Jacobs, W. B., Evaniew, N., Cohen-Adad, J., Anderson, D., & Cadotte, D. W. (2021). Spinal cord morphology in degenerative cervical myelopathy patients ; assessing key morphological characteristics using Mmchine vision tools. Journal of Clinical Medicine, 10(4), 18 pages. https://doi.org/10.3390/jcm10040892


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