AI-Based Prediction of Liver Metastasis in Colorectal Cancer (A Retrospective Study) (NCT07399236) | Clinical Trial Compass
RecruitingNot Applicable
AI-Based Prediction of Liver Metastasis in Colorectal Cancer (A Retrospective Study)
China1,500 participantsStarted 2015-01-01
Plain-language summary
This multicenter, retrospective study aims to develop and validate a multimodal deep learning model for predicting the risk of metachronous liver metastasis in patients with stage I-III colorectal cancer following curative resection. The model will integrate preoperative contrast-enhanced CT imaging, digitized histopathological whole-slide images, and standard clinical-pathological data.
The primary objective is to assess the model's discriminatory performance, measured by the area under the receiver operating characteristic curve (AUC), and to compare its predictive accuracy against traditional prognostic factors such as TNM staging and serum carcinoembryonic antigen levels. This research utilizes existing archival data; no direct patient contact or intervention is involved. The ultimate goal is to provide a robust, data-driven tool for improved risk stratification, which could potentially guide personalized surveillance strategies and adjuvant therapy decisions in the future.
Who can participate
Age range
18 Years – 75 Years
Sex
ALL
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Inclusion Criteria:
* Age 18-75 years, any gender.
* Histologically confirmed primary colon or rectal adenocarcinoma.
* Underwent curative radical resection (R0 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 or intraoperative exploration.
Exclusion Criteria:
* History of other malignant tumors.
* Previous history of liver surgery or liver transplantation.
* Missing clinical, imaging, or pathological data required for the study.
* Death within the perioperative period (within 30 days after surgery).
* Lack of regular follow-up information.
Questions worth asking your doctor
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
1Based on my diagnosis and history, is this trial worth exploring for me — or is there a standard treatment we should try first?
2What does this trial's phase tell us about how much is already known about its safety and benefit?
3What would taking part actually involve for me — visits, tests, time, and travel?
4What are the known and possible risks or side effects I should weigh, and how would they be monitored?
5If this trial isn't the right fit, what other options or trials would you suggest I look into?
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
Questions for the trial coordinator
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
1What does taking part actually involve week to week — how many visits, where, and how long does each one take?
2What costs are covered by the study, and what might I have to pay for myself, including travel, parking, or time off work?
3What happens during screening, and what happens if the study team confirms I don't meet the criteria after those tests?
4Who pays for the scans, blood work, and other tests the trial requires — the study, my insurance, or me?
5How will being in the trial affect my regular care, and will my own doctor stay informed and involved?
6Can I leave the trial at any point if I change my mind, and what would happen to my care if I do?
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
What they're measuring
1
Area Under the Receiver Operating Characteristic Curve (AUC)