[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100601941":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":10,"centralContacts":20,"locations":30,"responsibleParty":103,"collaborators":105,"id":113,"slug":114,"hasResults":115,"nctId":116,"briefTitle":117,"officialTitle":117,"acronym":118,"eligibilityCriteria":119,"healthyVolunteers":120,"sex":121,"minAge":122,"maxAge":10,"enrollmentInfo":123,"targetDuration":10,"studyType":126,"phases":10,"briefSummary":127,"conditions":128,"keywords":134,"overallStatus":33,"whyStopped":10,"lastUpdateSubmitDate":139,"lastUpdatePostDateStruct":140,"startDateStruct":143,"completionDateStruct":145,"leadSponsor":147,"locationsCount":148},{"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",[31,50,61,74,89],{"facility":32,"status":33,"city":34,"state":35,"zip":36,"country":37,"countryCode":38,"cosmosGeoPoint":39,"geoPoint":44,"contacts":45},"Meinian Onehealth Healthcare Holdings Co., Ltd","RECRUITING","Shanghai","Shanghai Municipality","200072","China","CN",{"type":40,"coordinates":41},"Point",[42,43],121.45806,31.22222,{"lat":43,"lon":42},[46],{"name":47,"role":23,"phone":48,"phoneExt":10,"email":49},"Qin Jianzeng Dr, M.D.","13602746909","qinjianzeng@126.com",{"facility":51,"status":33,"city":34,"state":35,"zip":52,"country":37,"countryCode":38,"cosmosGeoPoint":53,"geoPoint":55,"contacts":56},"Ruici Medical Examination Institution","200126",{"type":40,"coordinates":54},[42,43],{"lat":43,"lon":42},[57],{"name":58,"role":23,"phone":59,"phoneExt":10,"email":60},"Wang Liucheng Dr, M.D.","18601790221","wangliucheng@126.com",{"facility":5,"status":33,"city":34,"state":35,"zip":62,"country":37,"countryCode":38,"cosmosGeoPoint":63,"geoPoint":65,"contacts":66},"200433",{"type":40,"coordinates":64},[42,43],{"lat":43,"lon":42},[67,68,69,72],{"name":22,"role":23,"phone":24,"phoneExt":10,"email":25},{"name":27,"role":23,"phone":28,"phoneExt":10,"email":29},{"name":70,"role":71,"phone":10,"phoneExt":10,"email":10},"Jin Gang, M.D.","PRINCIPAL_INVESTIGATOR",{"name":22,"role":73,"phone":10,"phoneExt":10,"email":10},"SUB_INVESTIGATOR",{"facility":75,"status":33,"city":76,"state":77,"zip":78,"country":37,"countryCode":38,"cosmosGeoPoint":79,"geoPoint":83,"contacts":84},"Jiaxing University Affiliated Second Hospital","Jiaxing","Zhejiang","314000",{"type":40,"coordinates":80},[81,82],120.75,30.7522,{"lat":82,"lon":81},[85],{"name":86,"role":23,"phone":87,"phoneExt":10,"email":88},"Shen Yi Jue, M.D.","13605835645","dr.syj@163.com",{"facility":90,"status":33,"city":91,"state":77,"zip":92,"country":37,"countryCode":38,"cosmosGeoPoint":93,"geoPoint":97,"contacts":98},"Ningbo University Affiliated People's Hospital","Ningbo","315100",{"type":40,"coordinates":94},[95,96],121.54945,29.87819,{"lat":96,"lon":95},[99],{"name":100,"role":23,"phone":101,"phoneExt":10,"email":102},"Zhu Ke Lei, M.D.","13566636272","dr.zkl@163.com",{"type":104,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR",[106,109,111,112],{"name":107,"class":108},"The Affiliated People's Hospital of Ningbo University","OTHER_GOV",{"name":75,"class":110},"UNKNOWN",{"name":32,"class":110},{"name":51,"class":110},"100601941","artificial-intelligence-powered-low-dose-computed-tomography-for-screening-of-pancreatic-cancer-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":124,"type":125},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.",[129,130,131,132,133],"Pancreatic Cancer","Intraductal Papillary Mucinous Neoplasm","High-grade Pancreatic Intraepithelial Neoplasia","PDAC - Pancreatic Ductal Adenocarcinoma","Mucinous Cystic Neoplasm",[135,136,129,137,138],"Screening","Early Diagnosis","Artificial Intelligence","Computed Tomography","2025-08-05",{"date":141,"type":142},"2025-08-12","ACTUAL",{"date":144,"type":125},"2025-08-15",{"date":146,"type":125},"2032-12-30",{"name":5,"class":6},5]