Preoperative Adult-Type Diffuse Glioma Subtype Prediction with Dynamic Contrast-Enhanced MR Imaging and Diffusion...

Background/Objectives: The non-invasive identification of glioma subtypes is useful for initial diagnosis, treatment planning, and follow-up. The aim of this study was to evaluate the performance of diffusion kurtosis imaging (DKI) and dynamic contrast-enhanced (DCE)-MRI in differentiating subtypes of adult-type diffuse gliomas. Methods: In a prospective multicenter study, standardized MRI was analyzed in 59 patients with adult-type diffuse glioma. DKI and DCE-MRI parameter values were quantitatively evaluated in ROIs of contrast-enhancing/solid tumor and four concentric shells of peritumoral tissue. The parameter means of glioblastomas, IDH wildtype; astrocytomas, IDH mutant; and oligodendrogliomas, IDH mutant were compared. Binary logistic regression analyses were performed to differentiate between IDH mutant and IDH wildtype gliomas and between IDH mutant astrocytomas and oligodendrogliomas. ROC curves were analyzed for each parameter and for combined regression. Results: Significant differences between the three aforementioned subtypes were found for the DKI and DCE-MRI parameters, depending on the distance to the tumor core. A combination of the parameters' apparent diffusion coefficient (ADC) and fractional volume of extravascular extracellular space (ve) revealed the best prediction of IDH mutant vs. wildtype gliomas (AUC = 0.976 (0.943-1.000)) and astrocytomas vs. oligodendrogliomas (AUC = 0.840 (0.645-1.000)) with the lowest Akaike information criterion. Conclusions: The combined evaluation of DKI and DCE-MRI at different distances to the contrast-enhancing/solid tumor seems to be helpful in predicting glioma subtypes according to the WHO 2021 classification.