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

Abstract 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 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.