Hepatecellular CarcinomaNCT07062380
AI-Based Prediction of HCC Recurrence Patterns After Resection (APAR)
An observational study of Hepatecellular Carcinoma and Hepatectomy, run by Tongji Hospital at 1 site in China.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 18 to 75 years
- Conditions the study is for
- Hepatecellular Carcinoma, Hepatectomy
- What is being tested?
- Curative liver resection and Real-world multimodal therapy
- Type of treatment
- Surgery or procedure
- How many people
- 353 participants
- Where
- 1 siteChina
- Study dates
- 10 Jun 2025to 10 Jun 2028
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 75 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: This study will enroll patients with early-stage hepatocellular carcinoma (BCLC 0-A) scheduled for curative liver resection at tertiary academic medical centers in China. Participants will be consecutively recruited from hepatobiliary surgery clinics, with preoperative MRI and postoperative pathology confirmation of HCC. The population reflects real-world clinical practice, including both surgery-only patients and those receiving neoadjuvant/adjuvant therapies per physician discretion.
Who may be able to join
- 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.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
Tongji Hospital
Wuhan, Hubei, 430030
Wanguang Zhang, 13636076910, wgzhang@tjh.tjmu.edu.cn
About this study
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
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.
- Conditions
- Hepatecellular Carcinoma, Hepatectomy
- Being tested
- Curative liver resection, Real-world multimodal therapy
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Curative liver resectionProcedure or surgery
Standard radical hepatectomy performed according to 2024 HCC guidelines. No neoadjuvant or adjuvant therapies administered. Follows institutional surgical protocols for BCLC 0-A HCC.
Real-world multimodal therapyProcedure or surgery
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.
| Study group | Role | What they receive |
|---|---|---|
| Surgery-Only Validation Cohort | Patients with early-stage HCC (BCLC 0-A) receiving curative liver resection without neoadjuvant/adjuvant therapy . Preoperative MRI, clinical data and pathological data will be used for AI model prediction of recurrence risk. Standard follow-up imaging for 2 years will validate model accuracy. Receives: Procedure: Curative liver resection | |
| Exploratory Treatment Cohort | Patients with early-stage HCC receiving real-world neoadjuvant/adjuvant therapies (per physician discretion) alongside surgery. Treatment regimens and outcomes (RFS/OS) will be analyzed to assess therapy efficacy in model-stratified high/low-risk subgroups. Receives: Procedure: Real-world multimodal therapy |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of AI Model in Predicting Aggressive HCC Recurrence (AUC)
The area under the receiver operating characteristic curve (AUC) of the multimodal deep learning model (PRE/POST) for predicting postoperative recurrence beyond Milan criteria within 2 years after resection, validated against actual imaging/histopathology-confirmed recurrence patterns.
Unit : Dimensionless (0-1)
Measured: 2 years post-surgery
Secondary outcomes (2)
Recurrence-Free Survival (RFS)
Time from surgery to first radiologically confirmed recurrence (any pattern) or death from any cause, analyzed by Kaplan-Meier method and compared between model-predicted high/low-risk groups.
Unit : Months
Measured: Up to 3 years
Overall Survival (OS)
Time from surgery to death from any cause, compared between patients stratified by AI model predictions (high-risk vs. low-risk) and treatment cohorts (surgery-only vs. real-world therapy).
Unit : Months
Measured: Up to 5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 Jul 2025
- Study start10 Jun 2025
- Primary completion10 Jun 2026 (estimated)
- Study completion10 Jun 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Hepatecellular CarcinomaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 353 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Tongji Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Wan-Guang Zhang, Tongji Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07062380
- Sponsor's protocol ID
- TJ-IRB202505060
- Status last verified
- Jun 2025
- First submitted
- 2 Jul 2025
- Last updated
- 3 Sep 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 3 Sep 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- 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
- ClinicalTrials.gov ID
- NCT07062380
- Acronym / sponsor ID
- TJ-IRB202505060
- Conditions
- Hepatecellular Carcinoma, Hepatectomy
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 353 participants (estimated)
- Lead sponsor
- Tongji HospitalUniversity, hospital or other
- Study start
- 10 Jun 2025 (actual)
- Primary completion
- 10 Jun 2026 (estimated)
- Study completion
- 10 Jun 2028 (estimated)
- First posted
- 14 Jul 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Surgery-Only Validation Cohort | – | Procedure: Curative liver resectionPatients with early-stage HCC (BCLC 0-A) receiving curative liver resection without neoadjuvant/adjuvant therapy . Preoperative MRI, clinical data and pathological data will be used for AI model prediction of recurrence risk. Standard follow-up imaging for 2 years will validate model accuracy. |
| Exploratory Treatment Cohort | – | Procedure: Real-world multimodal therapyPatients with early-stage HCC receiving real-world neoadjuvant/adjuvant therapies (per physician discretion) alongside surgery. Treatment regimens and outcomes (RFS/OS) will be analyzed to assess therapy efficacy in model-stratified high/low-risk subgroups. |
Who may qualify
- Ages
- 18 to 75 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- This study will enroll patients with early-stage hepatocellular carcinoma (BCLC 0-A) scheduled for curative liver resection at tertiary academic medical centers in China. Participants will be consecutively recruited from hepatobiliary surgery clinics, with preoperative MRI and postoperative pathology confirmation of HCC. The population reflects real-world clinical practice, including both surgery-only patients and those receiving neoadjuvant/adjuvant therapies per physician discretion.
Key inclusion criteria (7 listed)
- 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.
Key exclusion criteria (5 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Curative liver resectionStandard radical hepatectomy performed according to 2024 HCC guidelines. No neoadjuvant or adjuvant therapies administered. Follows institutional surgical protocols for BCLC 0-A HCC. | Procedure or surgery | Surgery-Only Validation Cohort |
| Real-world multimodal therapyCurative resection combined with clinically indicated therapies (e.g., TACE, targeted drugs, immunotherapy) as per treating physician's decision. Treatments recorded but not protocol-mandated. | Procedure or surgery | Exploratory Treatment Cohort |
Primary outcome
Accuracy of AI Model in Predicting Aggressive HCC Recurrence (AUC)
Time frame: 2 years post-surgery
The area under the receiver operating characteristic curve (AUC) of the multimodal deep learning model (PRE/POST) for predicting postoperative recurrence beyond Milan criteria within 2 years after resection, validated against actual imaging/histopathology-confirmed recurrence patterns. Unit : Dimensionless (0-1)
2 secondary outcomes
Recurrence-Free Survival (RFS)
Time frame: Up to 3 years
Overall Survival (OS)
Time frame: Up to 5 years
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 3 Sep 2025.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Hepatecellular Carcinoma and Hepatectomy, run by Tongji Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 7 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 3 Sep 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Yang Wu, M.D. (+8613636076910, 255001907@qq.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of AI Model in Predicting Aggressive HCC Recurrence (AUC) (time frame: 2 years post-surgery). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 3 Sep 2025.