Liver Metastases of Colorectal CancerNCT07088393
Artificial Intelligence Diagnosis of Different Histopathological Growth Patterns of Colorectal Cancer Liver Metastasis
An observational study of Liver Metastases of Colorectal Cancer, run by Sun Yat-sen University at 1 site in China.
Trial summary
This study selected cases of colorectal cancer liver metastasis patients who underwent liver metastasis tumor resection, retrieved the pathological HE sections of the metastatic lesions, and constructed a predictive model. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Liver Metastases of Colorectal Cancer
- How many people
- 437 participants
- Where
- 1 siteChina
- Study dates
- 9 Jul 2025to 31 Dec 2025
- 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 Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: Patients must meet all inclusion and exclusion criteria. In addition, the patient should be thoroughly informed about the study, including the study visit schedule and required evaluations and all regulatory requirements for informed consent. The written informed consent should be obtained from the patient prior toenrollment. The following criteria apply to all patients enrolled onto the study unless otherwise specified.
Who may be able to join
- Patients with colorectal cancer liver metastases who underwent resection of liver metastases;
- Confirmed by a pathologist as having liver metastases from colorectal cancer;
Who cannot join
- Cases of colorectal cancer liver metastasis that cannot be classified by histopathology.
Trial locations and contacts
1 site in 1 country.
China1 site
Sixth Affiliated Hospital, Sun Yat-sen University
Guangzhou, Guangdong, 510655
About this study
This study selected cases of colorectal cancer liver metastasis patients who underwent liver metastasis tumor resection, retrieved the pathological HE sections of the metastatic lesions, and constructed a predictive model. AI software was applied to delineate different types of regions, achieving full automation of HGP prediction and constructing a predictive model. Statistical analysis was conducted on the classification of histopathological growth patterns (HGP) of liver metastasis and the survival prognosis of patients, and the differences in prognosis among different HGP classification methods were compared. This provides a new method for judging prognosis and treatment for clinical treatment of colorectal cancer liver metastasis patients.
- Conditions
- Liver Metastases of Colorectal Cancer
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Colorectal cancer liver metastasis cohort | A total of 437 cases of colorectal cancer liver metastasis patients who underwent liver metastasis tumor resection were selected, with a total of 1205 tumor lesions. Pathological HE sections were retrieved and a predictive model was constructed. Among them, 301 cases were in the training set and 106 cases were in the validation set. After constructing the model, it was used to prospectively interpret 30 lesions. The interpretation result of a senior pathologist with a high professional title was taken as the standard to evaluate the accuracy and interpretation time of the model. |
What is being measured
The primary outcome is the main question the study is designed to answer.
The accuracy rate of the predictive model for HGP classification
We will build an AI prediction model for HGP prediction and verify the accuracy of the AI-assisted prediction model in classifying HGP.
Measured: Half a year
Secondary outcomes (2)
The time for the predictive model to perform HGP classification
We will measure the time it takes for the AI-assisted predictive model to classify HGP and compare the difference in interpretation time between the model and pathologists.
Measured: Half a year
Progression-free survival of patients with different HGP classifications
The time from surgery to tumor progression in patients with colorectal cancer liver metastasis of different HGP types
Measured: Through study completion, an average of 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Jul 2025
- Study start9 Jul 2025
- Primary completion31 Dec 2025 (estimated)
- Study completion31 Dec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Liver Metastases of Colorectal CancerStudies of the same condition, open and under way.
- More trials run by Sun Yat-sen UniversityThe 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
- Case only
- Time perspective
- Prospective
- Enrolment
- 437 participants (actual)
Sponsor and investigators
- Lead sponsor
- Sun Yat-sen University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yanhong Deng, Sun Yat-sen University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07088393
- Sponsor's protocol ID
- 2023ZSLYEC-256
- Status last verified
- Jul 2025
- First submitted
- 10 Jul 2025
- Last updated
- 28 Jul 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 28 Jul 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence Diagnosis of Different Histopathological Growth Patterns of Colorectal Cancer Liver Metastasis
- ClinicalTrials.gov ID
- NCT07088393
- Acronym / sponsor ID
- 2023ZSLYEC-256
- Conditions
- Liver Metastases of Colorectal Cancer
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 437 participants (actual)
- Lead sponsor
- Sun Yat-sen UniversityUniversity, hospital or other
- Study start
- 9 Jul 2025 (actual)
- Primary completion
- 31 Dec 2025 (estimated)
- Study completion
- 31 Dec 2025 (estimated)
- First posted
- 28 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 study selected cases of colorectal cancer liver metastasis patients who underwent liver metastasis tumor resection, retrieved the pathological HE sections of the metastatic lesions, and constructed a predictive model. AI software was applied to delineate different types of regions, achieving full automation of HGP prediction and constructing a predictive model. Statistical analysis was conducted on the classification of histopathological growth patterns (HGP) of liver metastasis and the survival prognosis of patients, and the differences in prognosis among different HGP classification methods were compared. This provides a new method for judging prognosis and treatment for clinical treatment of colorectal cancer liver metastasis patients.
Study design
- Observational model
- Case only
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Colorectal cancer liver metastasis cohort | – | –A total of 437 cases of colorectal cancer liver metastasis patients who underwent liver metastasis tumor resection were selected, with a total of 1205 tumor lesions. Pathological HE sections were retrieved and a predictive model was constructed. Among them, 301 cases were in the training set and 106 cases were in the validation set. After constructing the model, it was used to prospectively interpret 30 lesions. The interpretation result of a senior pathologist with a high professional title was taken as the standard to evaluate the accuracy and interpretation time of the model. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Patients must meet all inclusion and exclusion criteria. In addition, the patient should be thoroughly informed about the study, including the study visit schedule and required evaluations and all regulatory requirements for informed consent. The written informed consent should be obtained from the patient prior toenrollment. The following criteria apply to all patients enrolled onto the study unless otherwise specified.
Key inclusion criteria (2 listed)
- Patients with colorectal cancer liver metastases who underwent resection of liver metastases;
- Confirmed by a pathologist as having liver metastases from colorectal cancer;
Key exclusion criteria (1 listed)
- Cases of colorectal cancer liver metastasis that cannot be classified by histopathology.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
The accuracy rate of the predictive model for HGP classification
Time frame: Half a year
We will build an AI prediction model for HGP prediction and verify the accuracy of the AI-assisted prediction model in classifying HGP.
2 secondary outcomes
The time for the predictive model to perform HGP classification
Time frame: Half a year
Progression-free survival of patients with different HGP classifications
Time frame: Through study completion, an average of 1 year
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 28 Jul 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. 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 Liver Metastases of Colorectal Cancer, run by Sun Yat-sen University 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 2 inclusion and 1 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: under way, not looking for participants, as of the sponsor's last update on 28 Jul 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?
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?
The accuracy rate of the predictive model for HGP classification (time frame: Half a year). 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 28 Jul 2025.