Integration of radiomics, habitat imaging, and deep learning for MRI-based prediction of parametrial invasion in cervical cancer: A dual-center study

The multimodal integrated model, combining radiomics, habitat imaging, 2.5D deep learning, and clinical features, demonstrated superior predictive performance for parametrial invasion in cervical cancer compared with individual models. This approach may enhance preoperative assessment, guide clinical decision-making, and optimize treatment strategies.