Actively Recruiting

Phase 1
Phase 2
Age: 18Years - 75Years
All Genders
NCT07282184

Multimodal Deep Learning for Postoperative Liver Cancer Risk Stratification and Intervention

Led by Tongji Hospital · Updated on 2025-12-18

144

Participants Needed

1

Research Sites

139 weeks

Total Duration

On this page

AI-Summary

What this Trial Is About

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

Official Title

Multimodal Deep Learning for Postoperative Liver Cancer Risk Stratification and Intervention

Who Can Participate

Age: 18Years - 75Years
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • Patients aged 18 to 75 years who can understand and voluntarily sign informed consent
  • Clinical diagnosis of BCLC stage 0-A hepatocellular carcinoma confirmed by histopathology or imaging
  • Scheduled for curative-intent liver resection surgery
  • Predicted high risk of aggressive cancer recurrence by the pre-operative deep learning model (PRE score 2 0.5)
  • Child-Pugh liver function class A (score 2 7)
  • ECOG Performance Status of 0 or 1
  • Availability of a standard pre-operative MRI scan within 1 month before enrollment with acceptable quality
  • Willing and able to comply with study procedures and follow-up for at least 2 years
Not Eligible

You will not qualify if you...

  • Postoperative pathology confirming non-hepatocellular carcinoma malignancy
  • History of other active cancers in the past 5 years except certain low-risk treated cancers
  • Death or loss to follow-up within 90 days after surgery
  • Known allergy to any part of the neoadjuvant therapy drugs (oxaliplatin, fluorouracil, PD-1 inhibitors, lenvatinib)
  • Severe uncontrolled medical conditions such as NYHA Class III/IV heart failure, severe kidney problems, or uncontrolled high blood pressure
  • Any condition that would prevent participation or affect study evaluation, as judged by the investigator

AI-Screening

AI-Powered Screening

Complete this quick 3-step screening to check your eligibility

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Trial Site Locations

Total: 1 location

1

Tongji Hospital

Wuhan, Hubei, China, 438700

Actively Recruiting

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Research Team

Y

Yang Wu, M.D.

CONTACT

How is the study designed?

Study Type

INTERVENTIONAL

Masking

NONE

Allocation

NON_RANDOMIZED

Model

PARALLEL

Primary Purpose

TREATMENT

Number of Arms

2

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Multimodal Deep Learning for Postoperative Liver Cancer Risk Stratification and Intervention | DecenTrialz