RecruitingPhase 1Phase 2NCT07282184

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


Sponsor

Tongji Hospital

Enrollment

144 participants

Start Date

Oct 26, 2025

Study Type

INTERVENTIONAL

Conditions

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.


Eligibility

Min Age: 18 YearsMax Age: 75 Years

Plain Language Summary

Simplified for easier understanding

This study is using artificial intelligence and medical imaging to predict which liver cancer patients are at high risk of their cancer coming back after surgery, and then testing whether targeted treatment can prevent that recurrence. **You may be eligible if...** - You are between 18 and 75 years old - You have been diagnosed with early-stage liver cancer (BCLC stage 0 or A) confirmed by imaging or biopsy - You are scheduled for a surgery to remove the tumor with the goal of a cure - An AI model has predicted you are high-risk for recurrence (a pre-op score of 0.5 or higher) - Your liver function is rated Child-Pugh class A - Your performance status (ECOG) is 0 or 1 - A pre-operative MRI was done within the past month **You may NOT be eligible if...** - Your liver cancer is at a more advanced stage - Your liver function is impaired (Child-Pugh B or C) - You are not a surgical candidate - You do not meet imaging or lab requirements Talk to your doctor to see if this trial is right for you.

This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.

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Interventions

COMBINATION_PRODUCTNeoadjuvant 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.

PROCEDURECurative 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

OTHERMultimodal 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.


Locations(1)

Tongji Hospital

Wuhan, Hubei, China

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NCT07282184


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