Diffusion kurtosis imaging as an imaging biomarker for predicting prognosis of the patients with high-grade gliomas.

PURPOSE

To retrospectively explore the utilization of MR diffusion kurtosis imaging (DKI) in predicting prognosis of the patients with high-grade gliomas.

MATERIALS AND METHODS

Thirty-three consecutive patients with cerebral gliomas underwent pretreatment DKI and diffusion-weighted imaging examination on a 3.0-T MR scanner. Diffusion parameters, including conventional tensor parameters, kurtosis metrics (mean kurtosis [MK], radial kurtosis [AK], and axial kurtosis [RK]), and minimum apparent diffusion coefficient (minADC), were obtained and normalized to the contralateral normal-appearing white matter. Correlations among each diffusion parameter and overall survival were analyzed by a Spearman method. The diagnostic efficiency of each parameter in predicting survival for patients with high-grade gliomas was assessed by a receiver operating characteristic curve. The favorable prognostic imaging biomarkers were further analyzed by using a Kaplan-Meier method with log-rank test.

RESULTS

In 33 patients, 17 patients reached overall survival >15 months (long survival group), whereas 16 showed overall survival <15 months (short survival group). Negative correlations between kurtosis metrics (MK, AK, and RK) and overall survival were obtained by using Spearman analysis (r = -0.63, -0.57, and -0.61, respectively, all P < 0.01), whereas minADC was positively correlated with overall survival (r = 0.56, P < 0.01). The kurtosis parameters of the long survival group were significantly lower than that of the short survival group (P < 0.001), while the minADC of the long survival group was significantly higher than that of the short survival group (P = 0.002). Among these diffusion parameters, the optimal cut-off value of MK (0.688) provided the best combination of sensitivity (93.75%) and specificity (76.47%) for differentiation of patients with long survival from those with short survival. High kurtosis metrics and low minADC were significant predictors of poor outcome. (P < 0.05).

CONCLUSION

Both kurtosis metrics and minADC have the potential to predict survival for the patients with high-grade gliomas. The preoperative kurtosis parameters, especially MK, can be taken as a preoperative prognostic biomarker to predict prognosis in patients with high-grade gliomas.