ABSTRACT
OBJECTIVE: A major shortcoming in optimizing care for patients with cervical spondylotic myelopathy (CSM) is the lack of robust quantitative imaging tools offered by conventional MRI. Advanced MRI modalities, such as diffusion MRI (dMRI), including diffusion tensor imaging (DTI) and diffusion basis spectrum imaging (DBSI), may help address this limitation by providing granular evaluations of spinal cord microstructure. METHODS: Forty-seven patients with CSM underwent comprehensive clinical assessments and dMRI, followed by DTI and DBSI modeling. Conventional MRI metrics included 10 total qualitative and quantitative assessments of spinal cord compression in both the sagittal and axial planes. The dMRI metrics included 12 unique measures including anisotropic tensors, reflecting axonal diffusion, and isotropic tensors, describing extraaxonal diffusion. The primary outcome was the modified Japanese Orthopaedic Association (mJOA) score measured at 2 years postoperatively. Extreme gradient boosting-supervised classification algorithms were used to classify patients into disease groups and to prognosticate surgical outcomes at 2-year follow-up. RESULTS: Forty-seven patients with CSM, including 24 (51%) with a mild mJOA score, 12 (26%) with a moderate mJOA score, and 11 (23%) with a severe mJOA score, as well as 21 control subjects were included. In the classification task, the traditional MRI metrics correctly assigned patients to healthy control versus mild CSM versus moderate/severe CSM cohorts, with an accuracy of 0.647 (95% CI 0.64-0.65). In comparison, the DTI model performed with an accuracy of 0.52 (95% CI 0.51-0.52) and the DBSI model's accuracy was 0.81 (95% CI 0.808-0.814). In the prognostication task, the traditional MRI metrics correctly predicted patients with CSM who improved at 2-year follow-up on the basis of change in mJOA, with an accuracy of 0.58 (95% CI 0.57-0.58). In comparison, the DTI model performed with an accuracy of 0.62 (95% CI 0.61-0.62) and the DBSI model had an accuracy of 0.72 (95% CI 0.718-0.73). CONCLUSIONS: Conventional MRI is a powerful tool to assess structural abnormality in CSM but is inherently limited in its ability to characterize spinal cord tissue injury. The results of this study demonstrate that advanced imaging techniques, namely DBSI-derived metrics from dMRI, provide granular assessments of spinal cord microstructure that can offer better diagnostic and prognostic utility.
ABSTRACT
BACKGROUND AND OBJECTIVES: Advanced diffusion-weighted MRI (DWI) modeling, such as diffusion tensor imaging (DTI) and diffusion basis spectrum imaging (DBSI), may help guide rehabilitation strategies after surgical decompression for cervical spondylotic myelopathy (CSM). Currently, however, postoperative DWI is difficult to interpret, owing to signal distortions from spinal instrumentation. Therefore, we examined the relationship between postoperative DTI/DBSI-extracted from the rostral C3 spinal level-and clinical outcome measures at 2-year follow-up after decompressive surgery for CSM. METHODS: Fifty patients with CSM underwent complete clinical and DWI evaluation-followed by DTI/DBSI analysis-at baseline and 2-year follow-up. Clinical outcomes included the modified Japanese Orthopedic Association score and comprehensive patient-reported outcomes. DTI metrics included apparent diffusion coefficient, fractional anisotropy, axial diffusivity, and radial diffusivity. DBSI metrics evaluated white matter tracts through fractional anisotropy, fiber fraction, axial diffusivity, and radial diffusivity as well as extra-axonal pathology through restricted and nonrestricted fraction. Cross-sectional Spearman's correlations were used to compare postoperative DTI/DBSI metrics with clinical outcomes. RESULTS: Twenty-seven patients with CSM, including 15, 7, and 5 with mild, moderate, and severe disease, respectively, possessed complete baseline and postoperative DWI scans. At 2-year follow-up, there were 10 significant correlations among postoperative DBSI metrics and postoperative clinical outcomes compared with 3 among postoperative DTI metrics. Of the 13 significant correlations, 7 involved the neck disability index (NDI). The strongest relationships were between DBSI axial diffusivity and NDI (r = 0.60, P < .001), DBSI fiber fraction and NDI (rs = -0.58, P < .001), and DBSI restricted fraction and NDI (rs = 0.56, P < .001). The weakest correlation was between DTI apparent diffusion coefficient and NDI (r = 0.35, P = .02). CONCLUSION: Quantitative measures of spinal cord microstructure after surgery correlate with postoperative neurofunctional status, quality of life, and pain/disability at 2 years after decompressive surgery for CSM. In particular, DBSI metrics may serve as meaningful biomarkers for postoperative disease severity for patients with CSM.
