Diffusion kurtosis imaging‐based habitat analysis identifies high‐risk molecular subtypes and heterogeneity matching in diffuse gliomas

Abstract Objective High‐risk types of diffuse gliomas in adults include isocitrate dehydrogenase (IDH) wild‐type glioblastomas and grade 4 astrocytomas. Achieving noninvasive prediction of high‐risk molecular subtypes of gliomas is important for personalized and precise diagnosis and treatment. Methods We retrospectively collected data from 116 patients diagnosed with adult diffuse gliomas. Multiple high‐risk molecular markers were tested, and various habitat models and whole‐tumor models were constructed based on preoperative routine and diffusion kurtosis imaging (DKI) sequences to predict high‐risk molecular subtypes of gliomas. Feature selection and model construction utilized Least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM). Finally, the Wilcoxon rank‐sum test was employed to explore the correlation between habitat quantitative features (intra‐tumor heterogeneity score，ITH score) and heterogeneity, as well as high‐risk molecular subtypes. Results The results showed that the habitat analysis model based on DKI performed remarkably well (with AUC values reaching 0.977 and 0.902 in the training and test sets, respectively). The model's performance was further enhanced when combined with clinical variables. (The AUC values were 0.994 and 0.920, respectively.) Additionally, we found a close correlation between ITH score and heterogeneity, with statistically significant differences observed between high‐risk and non‐high‐risk molecular subtypes. Interpretation The habitat model based on DKI is an ideal means for preoperatively predicting high‐risk molecular subtypes of gliomas, holding significant value for noninvasively alerting malignant gliomas and those with malignant transformation potential.