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Updated: Jun 11, 2025
Diffusion Tensor Magnetic Resonance Imaging in Chronic Spinal Cord Compression
Published on: May 7, 2019
Predictive value of dynamic diffusion tensor imaging for surgical outcomes in patients with cervical spondylotic
Xiaoyun Wang1, Xiaonan Tian2, Yujin Zhang1
1Department of Radiology and Nuclear Medicine, The First Hospital of Hebei Medical University, No. 89 Donggang Road, Shijiazhuang, Hebei, 050000, People's Republic of China.
Background:
Cervical spondylotic myelopathy (CSM) is the most common chronic spinal cord injury with poor surgical and neurologic recovery in the advanced stages of the disease. DTI parameters can serve as important biomarkers for CSM prognosis. The study aimed to investigate the predictive value of dynamic diffusion tensor imaging (DTI) for the postoperative outcomes of CSM.
Methods:
One hundred and five patients with CSM who underwent surgery were included in this study. Patients were assessed using the Modified Japanese Orthopedic Association Score (mJOA) before and one year after surgery and then divided into groups with good (≥ 50%) and poor (< 50%) prognoses according to the rate of recovery. All patients underwent preoperative dynamic magnetic resonance imaging of the cervical spine, including T2WI and DTI in natural(N), extension (E), and flexion (F) positions. ROM, Cross-sectional area, fractional anisotropy (FA), and apparent diffusion coefficient (ADC) were measured at the narrowest level in three neck positions. Univariate and multivariate logistic regression were used to identify risk factors for poor postoperative recovery based on clinical characteristics, dynamic T2WI, and DTI parameters. Predictive models were developed for three different neck positions.
Results:
Forty-four (41.9%) patients had a good postoperative prognosis, and 61 (58.1%) had a poor prognosis. Univariate analysis showed statistically significant differences in diabetes, number of compression segments, preoperative mJOA score, cross-sectional area ((Area-N), (Area-E), (Area-F)), ADC((ADC-N), (ADC-E), (ADC-F)) and FA (((FA-N), (FA-E), (FA-F)) (p < 0.05). Multivariable logistic regression showed that natural neck position: Area-N ([OR] 0.226; [CI] 0.069-0.732, p = 0.013),FA-N([OR]3.028;[CI]1.12-8.19,p = 0.029); extension ne-ck position: Area-E([OR]0.248;[CI]0.076-0.814,p = 0.021), FA-E([OR]4.793;[CI]1.737-13.228,p = 0.002);And flextion neck postion: Area-F([OR] 0.288; [CI] 0.095-0.87, p = 0.027),FA-F ([OR] 2.964; [CI] 1.126-7.801, p = 0.028) were independent risk factors for poor prognosis.The area under the curve (AUC) of the prediction models in the natural neck position, extension neck position, and flexion neck positions models were 0.708[(95% CI:0.608∼0.808), P < 0.001]; 0.738 [(95% CI:0.641∼0.835), P < 0.001]; 0.703 [(95% CI:0.602∼0.803), P < 0.001], respectively.
Conclusion:
Dynamic DTI can predict postoperative outcomes in CSM. Reduced FA in the extension position is a valid predictor of poor postoperative neurological recovery in patients with CSM.
