[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"high-grade-pancreatic-intraepithelial-neoplasia\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:high-grade-pancreatic-intraepithelial-neoplasia":47},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,1,0,[8],{"id":9,"slug":4,"hasResults":10,"nctId":11,"briefTitle":12,"officialTitle":12,"acronym":13,"eligibilityCriteria":14,"healthyVolunteers":15,"sex":16,"minAge":17,"maxAge":4,"enrollmentInfo":18,"targetDuration":4,"studyType":21,"phases":4,"briefSummary":22,"conditions":23,"keywords":29,"overallStatus":34,"whyStopped":4,"lastUpdateSubmitDate":35,"lastUpdatePostDateStruct":36,"startDateStruct":39,"completionDateStruct":41,"leadSponsor":43,"locationsCount":46},"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":19,"type":20},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.",[24,25,26,27,28],"Pancreatic Cancer","Intraductal Papillary Mucinous Neoplasm","High-grade Pancreatic Intraepithelial Neoplasia","PDAC - Pancreatic Ductal Adenocarcinoma","Mucinous Cystic Neoplasm",[30,31,24,32,33],"Screening","Early Diagnosis","Artificial Intelligence","Computed Tomography","RECRUITING","2025-08-05",{"date":37,"type":38},"2025-08-12","ACTUAL",{"date":40,"type":20},"2025-08-15",{"date":42,"type":20},"2032-12-30",{"name":44,"class":45},"Changhai Hospital","OTHER",5,""]