Radiomics and deep learning in upper tract urothelial carcinoma: advancing preoperative risk stratification and clinical decision-making

Background Upper tract urothelial carcinoma (UTUC) is a relatively rare but aggressive malignancy. Accurate preoperative assessment of tumor grade, invasiveness, and prognosis remains challenging using conventional imaging, cytology, and ureteroscopic biopsy alone. Radiomics and deep learning may provide noninvasive tools for improving risk stratification and clinical decision-making. Methods This narrative review summarizes current evidence on radiomics, machine learning, and deep learning in U