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Multimodal Deep Learning for Postoperative Liver Cancer Risk Stratification and Intervention

NCT07282184 · Status: RECRUITING · Phase: PHASE1/PHASE2 · Type: INTERVENTIONAL · Enrollment: 144

Last updated 2025-12-18

No results posted yet for this study

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

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.

Sponsors & Collaborators

  • Tongji Hospital

    lead OTHER

Study Design

Allocation
NON_RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Max Age
75 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-10-26
Primary Completion
2027-06-30
Completion
2028-06-30

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07282184 on ClinicalTrials.gov