[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100605740":3},{"organization":4,"armGroups":7,"interventions":8,"overallOfficials":7,"centralContacts":12,"locations":18,"responsibleParty":33,"collaborators":7,"id":35,"slug":7,"hasResults":36,"nctId":37,"briefTitle":38,"officialTitle":38,"acronym":7,"eligibilityCriteria":39,"healthyVolunteers":40,"sex":41,"minAge":42,"maxAge":43,"enrollmentInfo":44,"targetDuration":7,"studyType":47,"phases":7,"briefSummary":48,"conditions":49,"keywords":7,"overallStatus":21,"whyStopped":7,"lastUpdateSubmitDate":54,"lastUpdatePostDateStruct":55,"startDateStruct":58,"completionDateStruct":60,"leadSponsor":62,"locationsCount":63},{"fullName":5,"class":6},"Peking University First Hospital","OTHER",null,[9],{"type":6,"name":10,"description":11,"armGroupLabels":7,"otherNames":7},"None intervention","this study is retrospective based on the CT images, which dose include any intervention.",[13],{"name":14,"role":15,"phone":16,"phoneExt":7,"email":17},"Zejin Ou","CONTACT","159 1494 4390","2411210230@bjmu.edu.cn",[19],{"facility":20,"status":21,"city":22,"state":7,"zip":7,"country":23,"cosmosGeoPoint":24,"geoPoint":29,"contacts":30},"Peking University First Hospital, Beijing,","RECRUITING","Beijing","China",{"type":25,"coordinates":26},"Point",[27,28],116.39723,39.9075,{"lat":28,"lon":27},[31],{"name":32,"role":15,"phone":7,"phoneExt":7,"email":17},"Peking University First Hospital Peking University First Hospital",{"type":34,"investigatorFullName":7,"investigatorTitle":7,"investigatorAffiliation":7,"oldNameTitle":7,"oldOrganization":7},"SPONSOR","100605740",false,"NCT07166445","Deep Learning for Automated Discrimination Between Stage T1-T2 and T3 Renal Cell Carcinoma on Contrast-Enhanced CT","Inclusion Criteria:\n\n1. Histopathologically confirmed renal cell carcinoma on postoperative specimen.\n2. Preoperative contrast-enhanced CT performed at our institution with slice thickness ≤ 1 mm and complete DICOM datasets.\n3. Postoperative pathologic staging clearly defined as pT1a-T2b or pT3a.\n4. CT image quality deemed adequate for analysis.\n\nExclusion Criteria:\n\n* 1\\. Pathologic subtype other than RCC. 2. Images with severe artifacts.",true,"ALL","18 Years","85 Years",{"count":45,"type":46},1000,"ESTIMATED","OBSERVATIONAL","This study aims to develop and validate a contrast-enhanced CT-based deep-learning model for automatic and accurate preoperative discrimination between T1-T2 and T3 renal cell carcinoma. By quantifying the model's diagnostic performance on an independent test set-using AUC, sensitivity, specificity, positive\u002Fnegative predictive values, and decision-curve analysis-we will establish a decision-support tool that can be seamlessly integrated into clinical PACS, thereby reducing staging errors, refining surgical planning, and improving patient outcomes.",[50,51,52,53],"Carcinoma, Renal Cell","Diagnostic Imaging","Pathology","Deep Learning","2025-09-03",{"date":56,"type":57},"2025-09-10","ACTUAL",{"date":59,"type":57},"2024-09-01",{"date":61,"type":46},"2027-12-01",{"name":5,"class":6},1]