Keywords: Radiomics, Radiomics, Habitats, Multiparametric MRI, Endometrial Carcinoma, Tumor Heterogeneity
Motivation: Endometrial carcinoma (EC) risk stratification and prognosis is essential for treatment planning, yet conventional radiomics often lacks biological interpretability.
Goal(s): To assess if MRI-based habitat analysis can be a promising non-invasive tool for risk stratification and prognosis prediction in EC.
Approach: We developed structural and functional habitat models using T2WI, ADC, and CE-T1WI MRI sequences and used pathological examination results as the gold standard to evaluate habitat models' performance in predicting EC risk.
Results: Habitat models, particularly GMM- and K-means-based models, achieved comparable or improved predictive performance relative to the clinical model, furthermore offered non-invasive cellularity and vascularity information, enhancing EC risk assessment.
Impact: MRI-based habitat analysis and imaging provides a non-invasive method for predicting EC risk levels and prognosis at the celluar level, aiding treatment decision-making.
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