Multi-Omics Integration of MRI Habitat, Pathology, and Clinical Parameters for Predicting Platinum Resistance of HGSOC

Motivation: Platinum resistance of high-grade serous ovarian carcinoma (HGSOC) is related to tumor heterogeneity. Multi-omics integration can complement tumor heterogeneity at multiple scales and enhance the predictive power of single models. Goal(s): We aimed to explore a range of diverse multi-omics models to predict platinum resistance of HGSOC. Approach: Multi-omics models were developed and validated using MRI-based habitat radiomics, pathomics based on haematoxylin and eosin (H&E)-stained whole slide images (WSIs), and clinical parameters. Results: Among the array of single and composite models, the Clinic_Habitat model exhibited the most promising predictive performance, with the Clinic_Habitat_Pathology model ranking as the second-best performer. Impact: This study carries the potential to equip clinicians with treatment strategies aimed at enhancing the efficacy of individualized therapy.