Hepatocellular Carcinoma (HCC)NCT07030842
Precision Recurrence Risk Assessment in Early-stage Hepatocellular Carcinoma
An observational study of Hepatocellular Carcinoma (HCC), run by Tongji Hospital at 1 site in China.
Trial summary
This retrospective observational study aims to evaluate whether artificial intelligence (AI) models can predict aggressive recurrence in patients who underwent liver resection for early-stage hepatocellular carcinoma (HCC). Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Hepatocellular Carcinoma (HCC)
- What is being tested?
- liver resection
- Type of treatment
- Surgery or procedure
- How many people
- 579 participants
- Where
- 1 siteChina
- Study dates
- 25 Aug 2023to 30 Jul 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
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 Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: This retrospective multicenter study analyzed 579 patients with early-stage hepatocellular carcinoma (HCC) who underwent curative liver resection at two tertiary academic medical centers in China. The study population consisted of: Primary Cohort (Training/Validation): 462 patients from Tongji Hospital (2018-2021) External Test Cohort: 117 patients from Sun Yat-sen Memorial Hospital (2021-2022) All patients met strict inclusion criteria: curative (R0) resection, preoperative MRI within 1 month before surgery, available postoperative pathology slides, and complete follow-up. The population represents typical early-stage HCC patients eligible for surgical resection in endemic areas.
Who may be able to join
- Patients who underwent curative liver resection (R0) for pathologically confirmed primary HCC
- BCLC stage 0-A at diagnosis
- Availability of preoperative contrast-enhanced MRI performed within 1 month before surgery
- Availability of postoperative H\&E-stained whole slide images (WSIs) with adequate tumor representation
- Complete clinical follow-up data (minimum 2 years if no recurrence)
Who cannot join
- R1/R2 resection (micro/macroscopically positive margins)
- Missing or poor-quality preoperative MRI (motion artifacts/insufficient contrast enhancement)
- Received neoadjuvant or adjuvant therapy (to avoid treatment confounding)
- Incomplete follow-up (loss to follow-up or missing recurrence status)
- Non-curative procedures (e.g., palliative resection)
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Multimodal Deep Learning Models for Predicting Recurrence Pattern in Hepatocellular Carcinoma: A Multicenter Retrospective Development and Validation Study
This retrospective observational study aims to evaluate whether artificial intelligence (AI) models can predict aggressive recurrence in patients who underwent liver resection for early-stage hepatocellular carcinoma (HCC). The main question it seeks to answer is:
Can deep learning models combining preoperative MRI, postoperative pathology slides, and clinical data accurately identify HCC patients at high risk of aggressive recurrence after surgery?
Read more
To answer this, the investigators will analyze existing medical data (preoperative MRIs, postoperative whole-slide images, and clinical records) from 579 patients across two medical centers. All data will be anonymized before analysis, and no additional interventions are required from participants.
This study may help clinicians stratify high-risk patients who could benefit from closer surveillance or adjuvant therapies
- Conditions
- Hepatocellular Carcinoma (HCC)
- Being tested
- liver resection
- Keywords
- artificial intelligence, recurrence pattern, multimodal, deep learning
- Medical subject headings
- Carcinoma, Hepatocellular
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
liver resectionProcedure or surgery
This is a retrospective observational study analyzing existing clinical data; no experimental interventions were administered. The study evaluates the predictive performance of two deep learning models (preoperative and postoperative) using standard-of-care medical data collected during routine clinical practice, including:
Preoperative contrast-enhanced MRI scans Postoperative hematoxylin and eosin (H\&E)-stained whole slide images Clinical variables (laboratory results, pathology reports, and demographic data)
All data were collected as part of standard diagnostic and treatment protocols for hepatocellular carcinoma (HCC) patients undergoing liver resection. No additional interventions or modifications to clinical care were implemented for study purposes. The artificial intelligence models were applied to previously acquired, de-identified data to predict aggressive recurrence patterns
| Study group | Role | What they receive |
|---|---|---|
| TJ Cohort (Training/Validation) | Internal cohort from Tongji Hospital (2018-2021) used for model training and validation. Includes 462 patients with early-stage HCC who underwent curative resection. Data: preoperative MRI, clinical variables, and postoperative pathology slides. No interventions beyond standard care. Receives: Procedure: liver resection | |
| SYSMH Cohort (External Test) | Independent external test cohort from Sun Yat-sen Memorial Hospital (2021-2022). Includes 117 patients with early-stage HCC meeting identical inclusion criteria. Used to validate generalizability of multimodal DL models. Data anonymized; no additional interventions. Receives: Procedure: liver resection |
What is being measured
The primary outcome is the main question the study is designed to answer.
Aggressive Recurrence Pattern
Defined as first recurrence exceeding Milan criteria within 2 years after liver resection.
Measured: 2 years after surgery
Secondary outcomes (2)
Recurrence-Free Survival (RFS)
Time from surgery date to radiologically confirmed recurrence or last follow-up (until July 30, 2024).
Measured: From surgery until first recurrence or July 30, 2024
Overall Survival (OS)
Time from surgery date to death from any cause or last follow-up.
Measured: From surgery until death or July 30, 2024
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Jun 2025
- Study start25 Aug 2023
- Primary completion30 Jul 2024
- Study completion30 Jul 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Hepatocellular Carcinoma (HCC)Studies of the same condition, open and under way.
- More trials run by Tongji HospitalThe sponsor's other registered studies.
- 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
- Retrospective
- Enrolment
- 579 participants (actual)
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
- NCT07030842
- Sponsor's protocol ID
- TJ-IRB20230863
- Status last verified
- Jun 2025
- First submitted
- 12 Jun 2025
- Last updated
- 29 Jun 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 29 Jun 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Multimodal Deep Learning Models for Predicting Recurrence Pattern in Hepatocellular Carcinoma: A Multicenter Retrospective Development and Validation Study
- ClinicalTrials.gov ID
- NCT07030842
- Acronym / sponsor ID
- TJ-IRB20230863
- Conditions
- Hepatocellular Carcinoma (HCC)
- Keywords
- artificial intelligence, recurrence pattern, multimodal, deep learning
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 579 participants (actual)
- Lead sponsor
- Tongji HospitalUniversity, hospital or other
- Collaborators
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
- Study start
- 25 Aug 2023 (actual)
- Primary completion
- 30 Jul 2024 (actual)
- Study completion
- 30 Jul 2024 (actual)
- First posted
- 22 Jun 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 retrospective observational study aims to evaluate whether artificial intelligence (AI) models can predict aggressive recurrence in patients who underwent liver resection for early-stage hepatocellular carcinoma (HCC). The main question it seeks to answer is:
Can deep learning models combining preoperative MRI, postoperative pathology slides, and clinical data accurately identify HCC patients at high risk of aggressive recurrence after surgery?
To answer this, the investigators will analyze existing medical data (preoperative MRIs, postoperative whole-slide images, and clinical records) from 579 patients across two medical centers. All data will be anonymized before analysis, and no additional interventions are required from participants.
This study may help clinicians stratify high-risk patients who could benefit from closer surveillance or adjuvant therapies
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| TJ Cohort (Training/Validation) | – | Procedure: liver resectionInternal cohort from Tongji Hospital (2018-2021) used for model training and validation. Includes 462 patients with early-stage HCC who underwent curative resection. Data: preoperative MRI, clinical variables, and postoperative pathology slides. No interventions beyond standard care. |
| SYSMH Cohort (External Test) | – | Procedure: liver resectionIndependent external test cohort from Sun Yat-sen Memorial Hospital (2021-2022). Includes 117 patients with early-stage HCC meeting identical inclusion criteria. Used to validate generalizability of multimodal DL models. Data anonymized; no additional interventions. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- This retrospective multicenter study analyzed 579 patients with early-stage hepatocellular carcinoma (HCC) who underwent curative liver resection at two tertiary academic medical centers in China. The study population consisted of: Primary Cohort (Training/Validation): 462 patients from Tongji Hospital (2018-2021) External Test Cohort: 117 patients from Sun Yat-sen Memorial Hospital (2021-2022) All patients met strict inclusion criteria: curative (R0) resection, preoperative MRI within 1 month before surgery, available postoperative pathology slides, and complete follow-up. The population represents typical early-stage HCC patients eligible for surgical resection in endemic areas.
Key inclusion criteria (5 listed)
- Patients who underwent curative liver resection (R0) for pathologically confirmed primary HCC
- BCLC stage 0-A at diagnosis
- Availability of preoperative contrast-enhanced MRI performed within 1 month before surgery
- Availability of postoperative H\&E-stained whole slide images (WSIs) with adequate tumor representation
- Complete clinical follow-up data (minimum 2 years if no recurrence)
Key exclusion criteria (5 listed)
- R1/R2 resection (micro/macroscopically positive margins)
- Missing or poor-quality preoperative MRI (motion artifacts/insufficient contrast enhancement)
- Received neoadjuvant or adjuvant therapy (to avoid treatment confounding)
- Incomplete follow-up (loss to follow-up or missing recurrence status)
- Non-curative procedures (e.g., palliative resection)
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 |
|---|---|---|
| liver resectionThis is a retrospective observational study analyzing existing clinical data; no experimental interventions were administered. The study evaluates the predictive performance of two deep learning models (preoperative and postoperative) using standard-of-care medical data collected during routine clinical practice, including: Preoperative contrast-enhanced MRI scans Postoperative hematoxylin and eosin (H\&E)-stained whole slide images Clinical variables (laboratory results, pathology reports, and demographic data) All data were collected as part of standard diagnostic and treatment protocols for hepatocellular carcinoma (HCC) patients undergoing liver resection. No additional interventions or modifications to clinical care were implemented for study purposes. The artificial intelligence models were applied to previously acquired, de-identified data to predict aggressive recurrence patterns | Procedure or surgery | SYSMH Cohort (External Test), TJ Cohort (Training/Validation) |
Primary outcome
Aggressive Recurrence Pattern
Time frame: 2 years after surgery
Defined as first recurrence exceeding Milan criteria within 2 years after liver resection.
2 secondary outcomes
Recurrence-Free Survival (RFS)
Time frame: From surgery until first recurrence or July 30, 2024
Overall Survival (OS)
Time frame: From surgery until death or July 30, 2024
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Jun 2025.
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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. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
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 Hepatocellular Carcinoma (HCC), 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 5 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: finished, as of the sponsor's last update on 29 Jun 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Aggressive Recurrence Pattern (time frame: 2 years after 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 29 Jun 2025; AzTrials last refreshed its copy on 6 Nov 2026.