AI-Based Prediction of HCC Recurrence Patterns After Resection (APAR)

Recruiting now

Conditions studied: Hepatecellular Carcinoma, Hepatectomy

In brief

This observational study aims to validate a deep learning model for predicting aggressive recurrence patterns in patients with early-stage liver cancer (HCC) after surgery. The main question it aims to answer is: Can the AI model accurately identify patients at high risk of cancer recurrence within 2 years after surgery? Participants will provide clinical data and undergo standard surgery, followed by 2-year imaging surveillance. Their data will be used for both AI prediction and validation of recurrence patterns.

Key facts

Study ID

NCT07062380

Run by

Tongji Hospital

People needed

353

Starts

2025-06-10

Expected to finish

2028-06-10

Last updated by the study team

2025-09-03

Who can join

Age: 18 and older, up to 75. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Aged 18-75 years, regardless of gender.
• BCLC stage 0-A, scheduled for curative liver resection.
• Preoperative clinical diagnosis of hepatocellular carcinoma (HCC).
• Availability of dynamic contrast-enhanced MRI within 1 month before surgery, with acceptable image quality.
• Child-Pugh liver function score ≤7.
• ECOG Performance Status (PS) 0-1.
• No severe organic diseases of the heart, lungs, brain, or other vital organs.

You may not qualify if…

• Concurrent other malignancies (except cured non-melanoma skin cancer or cervical carcinoma in situ).
• Postoperative pathology confirms non-HCC diagnosis.
• Pregnant or lactating women.
• History of organ transplantation.
• Inability to comply with the study protocol or follow-up schedule.

Where it is running

• Tongji Hospital — Wuhan, Hubei, China (enrolling)

Full record on ClinicalTrials.gov

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