Differentiation of IDH-mutant Glioma Subtypes Using Unsupervised Dimensionality Reduction of MRI Biomarkers

Motivation: Radiomic features can potentially help distinguish subtypes of IDH-mutant gliomas that appear similar on MRI. Goal(s): The aim of this study was to evaluate whether imaging-based clustering of radiomic biomarkers of IDH-mutant gliomas may identify patterns or subgroups based on the 2021 CNS WHO classification. Approach: Dimensionality reduction techniques were applied to radiomic features of 179 patients of different sequence combinations to analyze the high dimensional feature space. Results: FLAIR and T1 post-contrast imaging revealed unique clusters, and survival analysis suggested potential differences amongst clusters. However, further research with a larger dataset is needed to determine whether the observed differences are significant. Impact: This study analyzed quantitative imaging biomarkers to differentiate IDH-mutant gliomas according to the 2021 WHO classification. The findings suggest that radiomic features may hold insights into potential survival differences among subtypes. Larger-scale research is required to further investigate these findings.