Value of conventional MRI and diffusion tensor imaging parameters in predicting surgical outcome in patients with...

In addition to conventional magnetic resonance imaging (cMRI), diffusion tensor imaging (DTI) has been investigated as a potential diagnostic and prognostic tool for patients with degenerative cervical myelopathy (DCM).

To assess the efficacy of cMRI and DTI parameters in prediction of surgical outcome in DCM patients.

One hundred and forty-two patients with DCM who underwent presurgical cMRI and DTI of the cervical spine were included. Quantitative parameters obtained by cMRI included compression ratio (CR), transverse area (TA), and signal intensity ratio (SIR). DTI was evaluated for apparent diffusion coefficient (ADC) and fractional anisotropy (FA). The Japanese Orthopaedic Association (JOA) score and recovery rate were used to evaluate clinical outcomes. A JOA recovery rate < 50% was defined as a poor surgical outcome. The relationship of surgical outcome with various imaging parameters was examined. Receiver operating characteristic (ROC) curves were used to measure the predictive ability and determine the best cut-off values of the quantitative parameters.

By ROC curve analyses of imaging parameters, the largest area under the ROC curve (AUC) was for FA (0.750), followed by ADC (0.719), TA (0.716), SIR (0.673), and CR (0.591). The cut-off values with the best compromise between sensitivity and specificity were set at 0.390 for FA, 1.344 × 10-3 mm2/s for ADC, 46.02 mm2 for TA, 1.556 for SIR, and 26.56% for CR. Multivariate logistic regression model revealed that JOA score ⩽ 8 points, TA ⩽ 46.02 mm2, and FA ⩽ 0.390 were independently associated with poor surgical outcome. The AUC value for the three-predictor model was 0.871, indicating strong predictive discrimination, and was significantly higher than the AUC value for the model containing only the JOA score (0.763; P= 0.003).

JOA score is a reasonable predictor of surgical outcome in DCM. However, a model inclusive of TA and FA provides superior predictive ability. Thus, quantitative analysis of cMRI and DTI is useful for predicting surgical outcome in DCM.