NCT07282184

Multimodal Deep Learning for Postoperative Liver Cancer Risk Stratification and Intervention

A Multimodal Deep Learning-Driven Study for Perioperative Risk Stratification and Precision Intervention in Hepatocellular Carcinoma Recurrence

• Status: Recruiting
• Phase: Phase 1 / Phase 2
• Study type: Interventional
• Enrollment: 144 (estimated)
• Sponsor: Tongji Hospital · Academic / Other
• Sex: All
• Age: 18 Years – 75 Years
• Healthy volunteers: Not accepted

Summary

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.

Conditions

• Hepotacellular Carcinoma

Interventions

Type	Name	Description
COMBINATION_PRODUCT	Neoadjuvant HAIC + Lenvatinib + PD-1 Inhibitor	A combination drug regimen used as neoadjuvant therapy. Includes Hepatic Arterial Infusion Chemotherapy (HAIC) with mFOLFOX6 (Oxaliplatin, Leucovorin, Fluorouracil), oral Lenvatinib, and an intravenous PD-1 inhibitor.
PROCEDURE	Curative Liver Resection	Standard anatomic or non-anatomic liver resection with the intention of achieving complete tumor removal with negative margins. This is the standard surgical procedure for resectable hepatocellular carcinoma
OTHER	Multimodal AI Risk Stratification	The use of a pre-established deep learning model (PRE/POST model) to analyze preoperative imaging and clinical data to stratify patients' risk of aggressive recurrence. This stratification is used to determine treatment arm assignment.

Timeline

• Start date: 2025-10-26
• Primary completion: 2027-06-30
• Completion: 2028-06-30
• First posted: 2025-12-15
• Last updated: 2025-12-18

Locations

1 site across 1 country: China