Colorectal Cancer Liver MetastasisNCT07392567
Prospective Validation of an AI Model for Predicting Liver Metastasis in Colorectal Cancer
An observational study of Colorectal Cancer Liver Metastasis, run by Tongji Hospital at 1 site in China.
Trial summary
This is a prospective, multicenter, observational study designed to validate the predictive accuracy of a pre-developed multimodal deep learning model. The model integrates preoperative contrast-enhanced CT scans, digitized postoperative pathology images, and standard clinical data to estimate the risk of liver… Read more about this study
- Who is it for?
- Ages 18 to 75 years
- Conditions the study is for
- Colorectal Cancer Liver Metastasis
- What is being tested?
- Multimodal Deep Learning Prediction Model
- How many people
- 160 participants
- Where
- 1 siteChina
- Study dates
- 30 Jan 2026to 30 Jan 2029
- 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 population consists of adult patients (aged 18-75) with newly diagnosed, stage I-III primary colorectal cancer who are scheduled to undergo curative resection at one of the participating clinical centers. This prospective cohort will be used for the independent validation of a pre-developed multimodal deep learning model designed to predict the risk of metachronous liver metastasis. All participants will provide informed consent prior to enrollment.
Who may be able to join
- Age 18-75 years, any gender.
- Clinical diagnosis of primary colon or rectal adenocarcinoma (Stage I-III). Scheduled to undergo curative radical resection for colorectal cancer.
- Preoperative contrast-enhanced abdominal/pelvic CT scan performed within 1 month before surgery, with acceptable image quality.
- No evidence of distant metastasis (including synchronous liver metastasis) on preoperative examination.
- ECOG Performance Status of 0 or 1.
- Patient or their legal representative voluntarily participates and provides written informed consent.
Who cannot join
- Postoperative pathological confirmation of non-primary colorectal adenocarcinoma or presence of distant metastasis.
- Intraoperative determination of non-R0 resection, or performance of palliative surgery/ostomy only.
- History of other malignant tumors.
- Previous history of liver surgery or liver transplantation.
- Death within the perioperative period (within 30 days after surgery).
- Refusal to participate in follow-up, withdrawal of informed consent, or loss to follow-up.
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
Yang WU, M.D., 13636076910, 255001907@qq.com
Wanguang Zhang, M.D.
About this study
Official title: A Multicenter, Prospective, Observational Study for the Validation of a Multimodal Deep Learning Model to Predict Metachronous Liver Metastasis in Patients With Colorectal Cancer After Curative Resection
This is a prospective, multicenter, observational study designed to validate the predictive accuracy of a pre-developed multimodal deep learning model. The model integrates preoperative contrast-enhanced CT scans, digitized postoperative pathology images, and standard clinical data to estimate the risk of liver metastasis within two years after curative surgery in patients with stage I-III colorectal cancer.
The primary objective is to evaluate the model's performance in an independent, prospectively enrolled patient cohort. Participants will receive standard-of-care treatment according to clinical guidelines. The study involves no experimental interventions; it solely involves the collection and analysis of routinely generated clinical data. The goal is to assess the model's potential for clinical translation by providing a reliable tool for stratifying patients' risk of liver metastasis, which could inform personalized surveillance strategies.
- Conditions
- Colorectal Cancer Liver Metastasis
- Being tested
- Multimodal Deep Learning Prediction Model
- Keywords
- colorectal cancer liver metastasis, deep learning, multimodal, predictive model
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Multimodal Deep Learning Prediction ModelDiagnostic test
This is a non-therapeutic, prognostic study. The intervention under investigation is the application of a pre-specified multimodal deep learning model that integrates preoperative CT imaging, digital pathology, and clinical data to stratify patients' risk of developing metachronous liver metastasis. This model functions as a prognostic tool and is not used to guide patient management in this study. Its performance is being evaluated prospectively against the actual clinical outcomes.
| Study group | Role | What they receive |
|---|---|---|
| Prospective Validation Cohort | This single cohort consists of patients with stage I-III colorectal cancer who are prospectively enrolled after undergoing curative resection. No interventions are administered as part of this study. The cohort is used for the external validation of the pre-defined multimodal deep learning model's performance in predicting the risk of metachronous liver metastasis. All patients receive standard of care treatment and follow-up according to clinical guidelines. Receives: Diagnostic Test: Multimodal Deep Learning Prediction Model |
What is being measured
The primary outcome is the main question the study is designed to answer.
Area Under the Receiver Operating Characteristic Curve (AUC)
The discriminatory performance of the pre-specified multimodal deep learning model for predicting the occurrence of metachronous liver metastasis within 2 years after curative resection. The model integrates preoperative contrast-enhanced CT, digital pathology, and clinical data. Performance is evaluated on the entire prospectively enrolled validation cohort.
Measured: 2 years after surgery
Secondary outcomes (1)
Liver Metastasis-Free Survival (LMFS) by Risk Group
The difference in liver metastasis-free survival between the high-risk and low-risk groups, as stratified by the model. LMFS is defined as the time from surgery to the first radiological diagnosis of liver metastasis.
Measured: From the date of surgery until the date of first documented liver metastasis or last follow-up, assessed up to 3 years.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted6 Feb 2026
- Study start30 Jan 2026
- Primary completion30 Jan 2028 (estimated)
- Study completion30 Jan 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Colorectal Cancer Liver MetastasisStudies 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
- 160 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
- NCT07392567
- Sponsor's protocol ID
- TJ-IRB202601017
- Status last verified
- Jan 2026
- First submitted
- 30 Jan 2026
- Last updated
- 6 Feb 2026
- 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 6 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Multicenter, Prospective, Observational Study for the Validation of a Multimodal Deep Learning Model to Predict Metachronous Liver Metastasis in Patients With Colorectal Cancer After Curative Resection
- ClinicalTrials.gov ID
- NCT07392567
- Acronym / sponsor ID
- TJ-IRB202601017
- Conditions
- Colorectal Cancer Liver Metastasis
- Keywords
- colorectal cancer liver metastasis, deep learning, multimodal, predictive model
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 160 participants (estimated)
- Lead sponsor
- Tongji HospitalUniversity, hospital or other
- Study start
- 30 Jan 2026 (actual)
- Primary completion
- 30 Jan 2028 (estimated)
- Study completion
- 30 Jan 2029 (estimated)
- First posted
- 6 Feb 2026 (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 is a prospective, multicenter, observational study designed to validate the predictive accuracy of a pre-developed multimodal deep learning model. The model integrates preoperative contrast-enhanced CT scans, digitized postoperative pathology images, and standard clinical data to estimate the risk of liver metastasis within two years after curative surgery in patients with stage I-III colorectal cancer.
The primary objective is to evaluate the model's performance in an independent, prospectively enrolled patient cohort. Participants will receive standard-of-care treatment according to clinical guidelines. The study involves no experimental interventions; it solely involves the collection and analysis of routinely generated clinical data. The goal is to assess the model's potential for clinical translation by providing a reliable tool for stratifying patients' risk of liver metastasis, which could inform personalized surveillance strategies.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Prospective Validation Cohort | – | Diagnostic Test: Multimodal Deep Learning Prediction ModelThis single cohort consists of patients with stage I-III colorectal cancer who are prospectively enrolled after undergoing curative resection. No interventions are administered as part of this study. The cohort is used for the external validation of the pre-defined multimodal deep learning model's performance in predicting the risk of metachronous liver metastasis. All patients receive standard of care treatment and follow-up according to clinical guidelines. |
Who may qualify
- Ages
- 18 to 75 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- This study population consists of adult patients (aged 18-75) with newly diagnosed, stage I-III primary colorectal cancer who are scheduled to undergo curative resection at one of the participating clinical centers. This prospective cohort will be used for the independent validation of a pre-developed multimodal deep learning model designed to predict the risk of metachronous liver metastasis. All participants will provide informed consent prior to enrollment.
Key inclusion criteria (6 listed)
- Age 18-75 years, any gender.
- Clinical diagnosis of primary colon or rectal adenocarcinoma (Stage I-III). Scheduled to undergo curative radical resection for colorectal cancer.
- Preoperative contrast-enhanced abdominal/pelvic CT scan performed within 1 month before surgery, with acceptable image quality.
- No evidence of distant metastasis (including synchronous liver metastasis) on preoperative examination.
- ECOG Performance Status of 0 or 1.
Key exclusion criteria (6 listed)
- Postoperative pathological confirmation of non-primary colorectal adenocarcinoma or presence of distant metastasis.
- Intraoperative determination of non-R0 resection, or performance of palliative surgery/ostomy only.
- History of other malignant tumors.
- Previous history of liver surgery or liver transplantation.
- Death within the perioperative period (within 30 days after surgery).
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 |
|---|---|---|
| Multimodal Deep Learning Prediction ModelThis is a non-therapeutic, prognostic study. The intervention under investigation is the application of a pre-specified multimodal deep learning model that integrates preoperative CT imaging, digital pathology, and clinical data to stratify patients' risk of developing metachronous liver metastasis. This model functions as a prognostic tool and is not used to guide patient management in this study. Its performance is being evaluated prospectively against the actual clinical outcomes. | Diagnostic test | Prospective Validation Cohort |
Primary outcome
Area Under the Receiver Operating Characteristic Curve (AUC)
Time frame: 2 years after surgery
The discriminatory performance of the pre-specified multimodal deep learning model for predicting the occurrence of metachronous liver metastasis within 2 years after curative resection. The model integrates preoperative contrast-enhanced CT, digital pathology, and clinical data. Performance is evaluated on the entire prospectively enrolled validation cohort.
1 secondary outcome
Liver Metastasis-Free Survival (LMFS) by Risk Group
Time frame: From the date of surgery until the date of first documented liver metastasis or last follow-up, assessed up to 3 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 6 Feb 2026.
- 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 Colorectal Cancer Liver Metastasis, 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 6 inclusion and 6 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 6 Feb 2026. 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. (13636076910, 255001907@qq.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Area Under the Receiver Operating Characteristic Curve (AUC) (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 6 Feb 2026.