Artificial Intelligence-assisted HER2 Expression Assessment in Urothelial Carcinoma Based on Imaging-pathology Omics

This study aims to build upon previous research by using artificial intelligence methods to fuse multimodal data from imaging and pathology to construct a predictive model for HER2 expression in urothelial carcinoma. The model's performance will be validated and optimized using a multicenter cohort study, ultimately achieving accurate and rapid prediction of HER2 expression. This will guide precise decision-making for further HER2-targeted therapy and improve patient prognosis. Big data analysis and deep learning will also assist physicians in more accurately diagnosing the disease and developing personalized treatment plans. The research findings will promote the integration and development of artificial intelligence technology with the healthcare industry in the application of multimodal data from clinical, imaging, and pathology perspectives.

NCT Number	NCT07454941
Lead Sponsor	Cancer Institute and Hospital, Chinese Academy of Medical Sciences Collaborators: Shanxi Province Cancer Hospital, Cancer Hospital Chinese Academy of Medical Science, Shenzhen Center, RenJi Hospital, First Hospital of China Medical University, Huadong Hospital, Huaxi Hospital, The First Affiliated Hospital of Anhui Medical University, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
Conditions	Urothelial Carcinoma (UC), HER2, Diagnostic
Enrollment	4,000 participants
Start Date	2026-03-02
Primary Completion	2028-06-03 (estimated)
Study Completion	2030-06-03 (estimated)
Updated on ClinicalTrials.gov	2026-03-06