[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100623125":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":10,"centralContacts":20,"locations":26,"responsibleParty":44,"collaborators":10,"id":47,"slug":48,"hasResults":49,"nctId":50,"briefTitle":51,"officialTitle":52,"acronym":10,"eligibilityCriteria":53,"healthyVolunteers":49,"sex":54,"minAge":55,"maxAge":56,"enrollmentInfo":57,"targetDuration":10,"studyType":60,"phases":10,"briefSummary":61,"conditions":62,"keywords":64,"overallStatus":28,"whyStopped":10,"lastUpdateSubmitDate":69,"lastUpdatePostDateStruct":70,"startDateStruct":73,"completionDateStruct":74,"leadSponsor":76,"locationsCount":77},{"fullName":5,"class":6},"Tongji Hospital","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"Prospective Validation Cohort",null,"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.",[13],"Diagnostic Test: Multimodal Deep Learning Prediction Model",[15],{"type":16,"name":17,"description":18,"armGroupLabels":19,"otherNames":10},"DIAGNOSTIC_TEST","Multimodal Deep Learning Prediction Model","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.",[9],[21],{"name":22,"role":23,"phone":24,"phoneExt":10,"email":25},"Yang WU, M.D.","CONTACT","13636076910","255001907@qq.com",[27],{"facility":5,"status":28,"city":29,"state":30,"zip":10,"country":31,"countryCode":32,"cosmosGeoPoint":33,"geoPoint":38,"contacts":39},"RECRUITING","Wuhan","Hubei","China","CN",{"type":34,"coordinates":35},"Point",[36,37],114.26667,30.58333,{"lat":37,"lon":36},[40,41],{"name":22,"role":23,"phone":24,"phoneExt":10,"email":25},{"name":42,"role":43,"phone":10,"phoneExt":10,"email":10},"Wanguang Zhang, M.D.","PRINCIPAL_INVESTIGATOR",{"type":43,"investigatorFullName":45,"investigatorTitle":46,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"Wan-Guang Zhang","Prof.","100623125","prospective-validation-of-an-ai-model-for-predicting-liver-metastasis-in-colorectal-cancer-100623125",false,"NCT07392567","Prospective Validation of an AI Model for Predicting Liver Metastasis in Colorectal Cancer","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","Inclusion Criteria:\n\n* Age 18-75 years, any gender.\n* Clinical diagnosis of primary colon or rectal adenocarcinoma (Stage I-III). Scheduled to undergo curative radical resection for colorectal cancer.\n* Preoperative contrast-enhanced abdominal\u002Fpelvic CT scan performed within 1 month before surgery, with acceptable image quality.\n* No evidence of distant metastasis (including synchronous liver metastasis) on preoperative examination.\n* ECOG Performance Status of 0 or 1.\n* Patient or their legal representative voluntarily participates and provides written informed consent.\n\nExclusion Criteria:\n\n* Postoperative pathological confirmation of non-primary colorectal adenocarcinoma or presence of distant metastasis.\n* Intraoperative determination of non-R0 resection, or performance of palliative surgery\u002Fostomy only.\n* History of other malignant tumors.\n* Previous history of liver surgery or liver transplantation.\n* Death within the perioperative period (within 30 days after surgery).\n* Refusal to participate in follow-up, withdrawal of informed consent, or loss to follow-up.","ALL","18 Years","75 Years",{"count":58,"type":59},160,"ESTIMATED","OBSERVATIONAL","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.\n\nThe 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.",[63],"Colorectal Cancer Liver Metastasis",[65,66,67,68],"colorectal cancer liver metastasis","deep learning","multimodal","predictive model","2026-01-30",{"date":71,"type":72},"2026-02-06","ACTUAL",{"date":69,"type":72},{"date":75,"type":59},"2029-01-30",{"name":5,"class":6},1]