To evaluate the effectiveness of histogram features from conventional diffusion weighted imaging (DWI), diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) parameters in predicting the status of glioma IDH mutation and 1p/19q codeletion based on the 2021 WHO classification of central nervous system tumors. A total of 422 participants who had DWI, DKI, and IVIM were enrolled between January 2020 and March 2024. The histogram characteristics of ADC, diffusional kurtosis(K), diffusion coefficient (Dk), pseudo-diffusion coefficient(D*), pure diffusion coefficient(D), perfusion fraction(f) in the solid component of tumors were calculated. Groups were compared by IDH genotype and 1p/19q codeletion status, utilizing logistic regression analysis and receiver operating characteristic curve to evaluate the differential diagnostic performance in predicting IDH and 1p/19q genotypes. Significant differences were observed in thirty-nine histogram-based features of diffusion parameters between IDH mutant gliomas and IDH wildtype glioblastoma. In IDH mutant gliomas, significant differences were found in thirty-six histogram-based features of DWI, DKI and IVIM parameters between those with and without 1p/19q codeletion. The IVIM model and the combined model showed superior diagnostic performance compared to the DWI model in terms of AUCs for predicting IDH mutations (0.903, 0.913 and 0.807, respectively p < 0.05), and 1p/19q codeletion in IDH mutant gliomas (0.825, 0.855, and 0.769, respectively; p < 0.05). Correlations between Ki-67 and the mean values of ADC, Dk, K, D, D*, and f were significant, with correlation coefficients from − 0.17 to 0.36 (all p < 0.05). The prediction of IDH mutation status in adult diffuse glioma and the 1p/19q codeletion status in IDH mutant glioma could be improved through histogram features of IVIM-derived parameters and the combined model.
Yang et al. (Wed,) studied this question.