Role of Diffusion Kurtosis Imaging in Grading of Brain Gliomas

Abstract Background: Since the 2016 WHO classification, the mutation status of the encoding gene of Isocitrate-dehydrogenase enzyme (IDH) is an important element in the integrated diagnosis of gliomas. Diffusion Kurtosis imaging (DKI) has been used to assess the microstructure of brain tissue as well as gliomas by quantifying the water molecules' non-Gaussian distribution. Aim of Study: This study aimed in this study to try to elucidate the diagnostic performance of DKI in the character-isation of brain gliomas and its role in the identification of IDH mutation status among different glioma subtypes. Patients and Methods: 48 patients with histopathological-proven gliomas were included in this prospective study. Diffusion images were obtained on a 3T system with 10/ 30/ 60 diffusion gradient directions with b-value of 300-2500 sec/mm2. Kurtosis analysis was performed using the Diffu-sional Kurtosis Estimator software, and segmentation was manually drawn on the co-registered FLAIR-DTI images. The mean value of the “mean kurtosis (MK)” and “mean diffusivity (MD)” were extracted from the solid tumour component and from the contralateral normal-appearing white matter. We then correlated MK and MD with the 2016 CNS WHO tumor grades using statistical software STATA, V15. Results: Most of the DKI parameters were able to stratify CNS gliomas both according to the 2007 and 2016 WHO classification. MK and MD significantly differed between IDH-mutant and IDH-wt gliomas. In those patients with a lack of 1p/19q codeletion all MKn, MK, MDn, MD signifi-cantly differed (p<0.007). Conclusion: DKI enables the differentiation of gliomas according to the WHO 2016 integrated diagnosis. This would be confirmed after soaring up and standardization of the technique in further research studies.