[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100612189":3},{"organization":4,"armGroups":7,"interventions":22,"overallOfficials":28,"centralContacts":32,"locations":42,"responsibleParty":60,"collaborators":62,"id":69,"slug":10,"hasResults":70,"nctId":71,"briefTitle":72,"officialTitle":73,"acronym":10,"eligibilityCriteria":74,"healthyVolunteers":70,"sex":75,"minAge":76,"maxAge":77,"enrollmentInfo":78,"targetDuration":10,"studyType":81,"phases":10,"briefSummary":82,"conditions":83,"keywords":86,"overallStatus":45,"whyStopped":10,"lastUpdateSubmitDate":92,"lastUpdatePostDateStruct":93,"startDateStruct":96,"completionDateStruct":98,"leadSponsor":100,"locationsCount":101},{"fullName":5,"class":6},"The First Affiliated Hospital with Nanjing Medical University","OTHER",[8,14,18],{"label":9,"type":10,"description":11,"interventionNames":12},"Cohort 1 (Internal Derivation Cohort)",null,"Retrospective case-only cohort of adults with pathologically confirmed gastric cancer who underwent preoperative contrast-enhanced CT at the sponsoring institution. Existing CT images and clinical\u002Fpathology records will be used to train and test the AI model and to estimate diagnostic performance for T and N staging.",[13],"Diagnostic Test: CT scan",{"label":15,"type":10,"description":16,"interventionNames":17},"Cohort 2 (External Validation Cohort A)","Independent retrospective case-only cohort from an external hospital with the same inclusion\u002Fexclusion criteria. Used solely for external validation to assess reproducibility across sites and scanners.",[13],{"label":19,"type":10,"description":20,"interventionNames":21},"Cohort 3 (External Validation Cohort B)","A second independent retrospective validation cohort from another institution to further test generalizability.",[13],[23],{"type":24,"name":25,"description":26,"armGroupLabels":27,"otherNames":10},"DIAGNOSTIC_TEST","CT scan","preoperative contrast-enhanced CT",[9,15,19],[29],{"name":30,"affiliation":5,"role":31},"Zhang Yudong","PRINCIPAL_INVESTIGATOR",[33,38],{"name":34,"role":35,"phone":36,"phoneExt":10,"email":37},"Zhang Yudong, PHD, MD","CONTACT","+8618251966069","zhangyd3895@njmu.edu.cn",{"name":39,"role":35,"phone":40,"phoneExt":10,"email":41},"Qiong Li","+8618351977281","njmu_lq@163.com",[43],{"facility":44,"status":45,"city":46,"state":47,"zip":10,"country":48,"cosmosGeoPoint":49,"geoPoint":54,"contacts":55},"The First Affiliated Hospital of Nanjing Medical University","RECRUITING","Nanjing","Jiangsu","China",{"type":50,"coordinates":51},"Point",[52,53],118.77778,32.06167,{"lat":53,"lon":52},[56],{"name":57,"role":35,"phone":58,"phoneExt":10,"email":59},"Yue Wang","025-68306222","jsphkjwy@163.com",{"type":61,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR",[63,65,67],{"name":64,"class":6},"Jiangsu Cancer Institute & Hospital",{"name":66,"class":6},"Zhengzhou University",{"name":68,"class":6},"Peking University First Hospital","100612189",false,"NCT07250347","AI-Assisted Detection and Staging of Gastric Cancer Using Contrast-Enhanced CT","Langue and Imaging-integrated Foundation Model for Gastric Cancer Detection and Staging Via Contrast-Enhanced CT: a Multicenter Study","Inclusion Criteria:\n\n1. pathologically confirmed gastric cancer;\n2. preoperative contrast-enhanced CT performed;\n3. no evidence of distant metastasis on baseline staging;\n4. curative-intent management with complete postoperative histopathology.\n\nExclusion Criteria:\n\n1. prior treatment before surgery;\n2. non-diagnostic or poor-quality CT precluding evaluation.","ALL","18 Years","85 Years",{"count":79,"type":80},8000,"ESTIMATED","OBSERVATIONAL","Accurate preoperative assessment of gastric cancer stage guides eligibility for endoscopic resection, extent of gastrectomy and lymphadenectomy, selection for neoadjuvant therapy, and use of staging laparoscopy. Contrast-enhanced CT (CECT) is guideline-endorsed for initial staging, yet performance varies across institutions and readers. This study will evaluate an artificial-intelligence (AI) system that analyzes routine CECT to detect gastric cancer and assign four-class T stage (T1-T4) and N stage (N0-N3) .",[84,85],"Gastric Cancer Stage","Gastric Cancer Patients Undergoing Gastrectomy",[87,88,89,90,91],"Gastric cancer","stage","artificial-intelligence","detection","contrast-enhanced CT","2025-11-24",{"date":94,"type":95},"2025-11-26","ACTUAL",{"date":97,"type":95},"2025-08-01",{"date":99,"type":80},"2028-12-30",{"name":5,"class":6},1]