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Normalizing spinal cord compression measures in degenerative cervical myelopathy.
Sandrine Bédard1, Jan Valošek2, Maryam Seif3
1NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, 2500 Chem. de Polytechnique, Montréal, H3T 1J4, Québec, Canada.
Summary
This study introduces an automated MRI analysis for measuring spinal cord compression in degenerative cervical myelopathy (DCM), improving treatment decisions. The new method offers a more accurate and efficient assessment than traditional techniques.
Area of Science:
- Medical imaging analysis
- Spinal cord imaging
- Degenerative cervical myelopathy research
Background:
- Accurate MRI measurements are crucial for assessing spinal cord compression severity in degenerative cervical myelopathy (DCM).
- Traditional maximum spinal cord compression (MSCC) index has limitations including sensitivity to compression level, individual anatomy variations, and reliance on manual, time-consuming expert-rater analysis.
- Existing methods are prone to variability and do not fully account for anatomical differences.
Purpose of the Study:
- To develop and validate a fully automatic pipeline for computing normalized maximum spinal cord compression (MSCC) measures.
- To improve the accuracy and efficiency of spinal cord compression assessment in DCM patients.
Main Methods:
- Developed a novel normalization strategy for traditional MSCC using a healthy adult database (n=203) to account for individual anatomy.
- Evaluated additional morphometrics: transverse diameter, area, eccentricity, and solidity.
- Validated the automatic method in a mild DCM patient cohort (n=120) against manual measurements.
- Utilized stepwise binary logistic regression to predict therapeutic decisions (operative/conservative).
Main Results:
- The automatic and normalized MSCC measures showed significant correlation with clinical scores.
- The automated method predicted therapeutic decisions more accurately than manual MSCC.
- Key predictors identified included upper extremity sensory dysfunction, T2w hyperintensity, and the novel MRI-based measures.
- Receiver operating characteristic analysis yielded an area under the curve (AUC) of 0.80.
Conclusions:
- An automated method for computing normalized spinal cord compression measures from MRIs has been successfully introduced.
- This approach has the potential to enhance therapeutic decision-making for DCM patients.
- The open-source method is integrated into Spinal Cord Toolbox v6.0 and above.