AI-Based Prediction of HCC Recurrence Patterns After Resection (APAR)
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Curative liver resection, Real-world multimodal therapy.
- Who it may be relevant to
- Registry conditions: Hepatecellular Carcinoma, Hepatectomy. Basic parameters: 18 years — 75 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Prospective Validation of Multimodal Deep Learning Models for Predicting Recurrence Patterns in Early-Stage Hepatocellular Carcinoma After Resection: A Natural Treatment Cohort Stratification Study
Overview
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.
Interventions
- Procedure Curative liver resection
Standard radical hepatectomy performed according to 2024 HCC guidelines. No neoadjuvant or adjuvant therapies administered. Follows institutional surgical protocols for BCLC 0-A HCC. - Procedure Real-world multimodal therapy
Curative resection combined with clinically indicated therapies (e.g., TACE, targeted drugs, immunotherapy) as per treating physician's decision. Treatments recorded but not protocol-mandated.
Primary outcome measures
- Accuracy of AI Model in Predicting Aggressive HCC Recurrence (AUC) [Time frame: 2 years post-surgery]
Secondary outcome measures (2)
- Recurrence-Free Survival (RFS) [Time frame: Up to 3 years]
- Overall Survival (OS) [Time frame: Up to 5 years]
Eligibility criteria
Inclusion criteria
- 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.
Exclusion criteria
- 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.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
China · 1 center
- Tongji Hospital — Wuhan
Identifiers
NCT: NCT07062380 · TJ-IRB202505060