Multimodal Deep Learning for Postoperative Liver Cancer Risk Stratification and Intervention

This study is for patients with early-stage liver cancer who are planning to have surgery. The goal of this research is to see if a personalized treatment plan, guided by a computer model (an artificial intelligence tool), can help prevent the cancer from coming back after surgery. First, the computer model will analyze each patient's medical images and health data to predict their personal risk of the cancer returning. Patients whom the model predicts have a high risk of the cancer coming back will be offered a special treatment plan. This plan involves receiving medication (neoadjuvant therapy) before surgery and additional medication (adjuvant therapy) after surgery. The effectiveness of this plan will be compared to the standard approach of surgery alone. The main goal is to see if this new, personalized plan can better prevent the cancer from returning within 2 years after surgery. The study will also closely monitor the safety of the medications used. All patients in the study will be followed closely for 2 years with regular scans and check-ups to monitor their health.

NCT Number	NCT07282184
Lead Sponsor	Tongji Hospital
Conditions	Hepotacellular Carcinoma
Enrollment	144 participants
Start Date	2025-10-26
Primary Completion	2027-06-30 (estimated)
Study Completion	2028-06-30 (estimated)
Updated on ClinicalTrials.gov	2025-12-18