[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100601941":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":10,"centralContacts":20,"locations":30,"responsibleParty":102,"collaborators":104,"id":112,"slug":10,"hasResults":113,"nctId":114,"briefTitle":115,"officialTitle":115,"acronym":116,"eligibilityCriteria":117,"healthyVolunteers":118,"sex":119,"minAge":120,"maxAge":10,"enrollmentInfo":121,"targetDuration":10,"studyType":124,"phases":10,"briefSummary":125,"conditions":126,"keywords":132,"overallStatus":33,"whyStopped":10,"lastUpdateSubmitDate":137,"lastUpdatePostDateStruct":138,"startDateStruct":141,"completionDateStruct":143,"leadSponsor":145,"locationsCount":146},{"fullName":5,"class":6},"Changhai Hospital","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"AI-powered LDCT (LDCT+AI)",null,"Participants will undergo annual screening with the LDCT+AI system.",[13],"Diagnostic Test: Diagnostic Evaluation for Positive AI Findings",[15],{"type":16,"name":17,"description":18,"armGroupLabels":19,"otherNames":10},"DIAGNOSTIC_TEST","Diagnostic Evaluation for Positive AI Findings","MDT will review positive AI findings (including PDAC, pancreatic precursor lesions and benign lesion) cases to determine next steps: (1) Suspected PDAC and pancreatic precursor lesions are referred for hospital examination with diagnostic results collected; (2) Benign lesion cases receive personalized monitoring until endpoint events or study end; (3) Cases with positive AI findings but MDT-confirmed normal pancreatic issues receive at least one year of follow-up. If any abnormal results arise, management will transition to either plan (1) or (2).",[9],[21,26],{"name":22,"role":23,"phone":24,"phoneExt":10,"email":25},"Wang Bei Lei, M.D.","CONTACT","13774238083","lilly_wang@126.com",{"name":27,"role":23,"phone":28,"phoneExt":10,"email":29},"Guo Shi Wei, M.D.","18621500666","gestwa@163.com",[31,49,60,73,88],{"facility":32,"status":33,"city":34,"state":35,"zip":36,"country":37,"cosmosGeoPoint":38,"geoPoint":43,"contacts":44},"Meinian Onehealth Healthcare Holdings Co., Ltd","RECRUITING","Shanghai","Shanghai Municipality","200072","China",{"type":39,"coordinates":40},"Point",[41,42],121.45806,31.22222,{"lat":42,"lon":41},[45],{"name":46,"role":23,"phone":47,"phoneExt":10,"email":48},"Qin Jianzeng Dr, M.D.","13602746909","qinjianzeng@126.com",{"facility":50,"status":33,"city":34,"state":35,"zip":51,"country":37,"cosmosGeoPoint":52,"geoPoint":54,"contacts":55},"Ruici Medical Examination Institution","200126",{"type":39,"coordinates":53},[41,42],{"lat":42,"lon":41},[56],{"name":57,"role":23,"phone":58,"phoneExt":10,"email":59},"Wang Liucheng Dr, M.D.","18601790221","wangliucheng@126.com",{"facility":5,"status":33,"city":34,"state":35,"zip":61,"country":37,"cosmosGeoPoint":62,"geoPoint":64,"contacts":65},"200433",{"type":39,"coordinates":63},[41,42],{"lat":42,"lon":41},[66,67,68,71],{"name":22,"role":23,"phone":24,"phoneExt":10,"email":25},{"name":27,"role":23,"phone":28,"phoneExt":10,"email":29},{"name":69,"role":70,"phone":10,"phoneExt":10,"email":10},"Jin Gang, M.D.","PRINCIPAL_INVESTIGATOR",{"name":22,"role":72,"phone":10,"phoneExt":10,"email":10},"SUB_INVESTIGATOR",{"facility":74,"status":33,"city":75,"state":76,"zip":77,"country":37,"cosmosGeoPoint":78,"geoPoint":82,"contacts":83},"Jiaxing University Affiliated Second Hospital","Jiaxing","Zhejiang","314000",{"type":39,"coordinates":79},[80,81],120.75,30.7522,{"lat":81,"lon":80},[84],{"name":85,"role":23,"phone":86,"phoneExt":10,"email":87},"Shen Yi Jue, M.D.","13605835645","dr.syj@163.com",{"facility":89,"status":33,"city":90,"state":76,"zip":91,"country":37,"cosmosGeoPoint":92,"geoPoint":96,"contacts":97},"Ningbo University Affiliated People's Hospital","Ningbo","315100",{"type":39,"coordinates":93},[94,95],121.54945,29.87819,{"lat":95,"lon":94},[98],{"name":99,"role":23,"phone":100,"phoneExt":10,"email":101},"Zhu Ke Lei, M.D.","13566636272","dr.zkl@163.com",{"type":103,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR",[105,108,110,111],{"name":106,"class":107},"The Affiliated People's Hospital of Ningbo University","OTHER_GOV",{"name":74,"class":109},"UNKNOWN",{"name":32,"class":109},{"name":50,"class":109},"100601941",false,"NCT07117045","Artificial Intelligence-powered Low-Dose Computed Tomography for Screening of Pancreatic Cancer","AI-LDCT-PC","Inclusion Criteria:\n\n1. Age 50 years and above.\n2. Voluntary signing of informed consent.\n3. Completion of LDCT examination.\n\nExclusion Criteria:\n\n1. Previous history of pancreatic cancer.\n2. Abdominal inflammation or diagnosis of acute pancreatitis within 6 months.\n3. Poor image quality due to ascites, pancreatic trauma, thoracic\u002Fabdominal surgery, radiotherapy or chemotherapy.\n4. Research subjects unable to complete follow-up due to physical or other reasons.",true,"ALL","50 Years",{"count":122,"type":123},400000,"ESTIMATED","OBSERVATIONAL","Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with early diagnosis crucial for improving survival. Due to the absence of effective screening methods, most patients are diagnosed at advanced stages. The population undergoing low-dose computed tomography (LDCT) screening significantly overlaps with those at high risk for PDAC; however, traditional imaging methods have limited sensitivity for detecting pancreatic lesions. This study utilizes the Pancreatic Cancer Detection with Artificial Intelligence (PANDA) system to enhance LDCT for pancreatic cancer screening in a prospective, multicenter, observational cohort. PANDA will analyze LDCT images, followed by a multidisciplinary team (MDT) reassessment of abnormal interpretations. Based on MDT evaluation, individuals will be recalled for further examination, placed under a personalized follow-up plan, or monitored for at least one year. The primary outcomes include pancreatic cancer detection rate, positive predictive value, consensus rate, and recall rate, while secondary outcomes focus on early-stage cancers, resectable tumors, and safety indicators such as false positive rates and unnecessary procedures. This study aims to assess the effectiveness and safety of AI-assisted LDCT for PDAC detection, providing a practical solution for improving public health and enhancing early diagnostic capabilities.",[127,128,129,130,131],"Pancreatic Cancer","Intraductal Papillary Mucinous Neoplasm","High-grade Pancreatic Intraepithelial Neoplasia","PDAC - Pancreatic Ductal Adenocarcinoma","Mucinous Cystic Neoplasm",[133,134,127,135,136],"Screening","Early Diagnosis","Artificial Intelligence","Computed Tomography","2025-08-05",{"date":139,"type":140},"2025-08-12","ACTUAL",{"date":142,"type":123},"2025-08-15",{"date":144,"type":123},"2032-12-30",{"name":5,"class":6},5]