Role of magnetic resonance imaging in predicting surgical outcome in patients with cervical spondylotic myelopathy.

Abstract

Ambispective, retrospective cohort study from prospectively collected data. Cervical spondylotic myelopathy is the commonest cause of spinal cord impairment in the elderly population worldwide. Although magnetic resonance imaging (MRI) is the primary imaging modality for confirming the diagnosis, its role in predicting surgical outcome remains unclear. Two hundred seventy-eight patients with 1 or more clinical signs of myelopathy were enrolled; and they underwent decompression surgery. Complete baseline clinical and MRI data were available for 102 patients. MRI parameters measured included presence/absence of signal change on T1 and T2, T2 signal quantitative factors, and anatomical measurements. A dichotomized postoperative modified Japanese Orthopedic Association (mJOA) score at 6 months was used to characterize patients with mild myelopathy (≥16) and those with substantial residual neurological impairment (<16). Univariate analysis assessed the relationship between baseline parameters and outcome. Multivariate logistic regression was conducted after a conceptual division of variables into 3 groups: T1 signal analysis, T2 signal analysis, and anatomical measurements. Baseline mJOA (P<0.001; odds ratio [OR]=1.644, 95% confidence interval [95% CI]: 1.326-2.037), maximum canal compromise (MCC) (P=0.0322; OR=0.965, 95% CI: 0.934-0.997), T2 hyperintensity region of interest area (P=0.0422; OR=0.67; 95% CI: 0.456-0.986), and sagittal extent (P=0.026; OR=0.673; 95% CI: 0.475-0.954) were significantly associated with outcome univariately. The final model was comprised of T1 hypointensity (P=0.029; OR=0.242; CI: 0.068-0.866), MCC (P=0.005; OR=0.940; CI: 0.90-0.982) and baseline mJOA (P<0.001; OR=1.743; CI: 1.353-2.245), yielding an area under the receiver operating characteristic curve (AUC) of 0.845. Baseline mJOA is a strong predictor of postsurgical outcome in cervical spondylotic myelopathy at 6 months. However, a model inclusive of MCC and T1 hypointensity assessment provides superior predictive capacity. This suggests that MRI analysis has a significant role in predicting surgical outcome. 3.