[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"intraductal-papillary-mucinous-neoplasm\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:intraductal-papillary-mucinous-neoplasm":24},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,5,0,[8,38,74,103,131],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":4,"enrollmentInfo":18,"targetDuration":4,"studyType":21,"phases":4,"briefSummary":22,"conditions":23,"keywords":4,"overallStatus":25,"whyStopped":4,"lastUpdateSubmitDate":26,"lastUpdatePostDateStruct":27,"startDateStruct":30,"completionDateStruct":32,"leadSponsor":34,"locationsCount":37},"100609587","intent-of-surgery-for-ipmn-100609587",false,"NCT07216521","Intent of Surgery for IPMN","Optimizing Preoperative Surgical Decision-making for Intraductal Papillary Mucinous Neoplasms: The Role of Intent of Surgery","Inclusion Criteria:\n\n* All patients (18 years old of greater) who underwent surgical resection for IPMN (including low-, high-grade dysplasia, or invasive carcinoma) between July 1, 2015 and July 1, 2025.\n\nExclusion Criteria:\n\n* Patients with concomitant pancreatic ductal adenocarcinoma (PDAC)","ALL","18 Years",{"count":19,"type":20},2000,"ESTIMATED","OBSERVATIONAL","This multicenter retrospective observational cohort study seeks to:\n\n1. Classify surgical intent in patients with resected Intraductal Papillary Mucinous Neoplasms (IPMN) and quantify the proportion of IPMN-associated cancers diagnosed as overt pancreatic cancer with incidental IPMN association on pathology.\n2. Compare clinicopathologic features and outcomes between surveillance-detected and incidentally detected IPMN-derived pancreatic cancers.\n3. Revise and redefine risk features limited to patients undergoing surgery for IPMN-related indications, identifying optimal predictors of malignant IPMN (high-grade dysplasia or invasive cancer).",[24],"Intraductal Papillary Mucinous Neoplasm","RECRUITING","2025-10-09",{"date":28,"type":29},"2025-10-14","ACTUAL",{"date":31,"type":29},"2025-09-15",{"date":33,"type":20},"2025-12",{"name":35,"class":36},"NYU Langone Health","OTHER",14,{"id":39,"slug":40,"hasResults":11,"nctId":41,"briefTitle":42,"officialTitle":43,"acronym":44,"eligibilityCriteria":45,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":4,"enrollmentInfo":46,"targetDuration":48,"studyType":21,"phases":4,"briefSummary":49,"conditions":50,"keywords":58,"overallStatus":25,"whyStopped":4,"lastUpdateSubmitDate":64,"lastUpdatePostDateStruct":65,"startDateStruct":67,"completionDateStruct":69,"leadSponsor":71,"locationsCount":73},"100384895","ucsf-panc-cyst-registry-100384895","NCT04291651","UCSF PANC Cyst Registry","Population-Based Analysis of Neoplastic Changes in Cystic Lesions of the Pancreas.","UCSF PCR","Inclusion Criteria:\n\n* The inclusion criteria for this study are intentionally broad. Eligible patients for prospective enrollment will include\n* Adults ≥ 30 years of age\n* Have a radiographic or endoscopic diagnosis of at least one pancreatic cysts regardless of treatment status,\n* No history of pancreatic cancer,\n* Can speak and read English,\n* Have access to a computer or mobile device (\\~95% of U.S. population); and\n* Are able to complete an electronic informed consent.\n\nExclusion Criteria:\n\n* Patients who don't speak English,\n* Don't have access to a computer or mobile device; or\n* Patients who have a cancer diagnosis.",{"count":47,"type":20},4000,"10 Years","Pancreatic cysts are found incidentally on 15-50% of CT and MRIs for all indications and their prevalence is increasing. Many of these cysts may be precursors to pancreatic cancer, and thus pose a substantial risk, however, the vast majority are benign. Increased detection of pancreatic cysts provides an opportunity to diagnose pancreatic malignancy at an early, curable stage yet also increases the potential to over-treat clinically insignificant lesions. This presents a clinical challenge to prevent unnecessary resection of indolent disease, with associated risks of infections, bleeding, diabetes, and costly disability. Unfortunately, there is little information on the epidemiology and natural history of pancreatic cysts to help guide management.",[51,52,53,54,55,24,56,57],"Pancreatic Cyst","Pancreatic Neoplasms","Pancreatic Cancer","Pancreatic Diseases","Pancreatic Intraductal Papillary Mucinous Neoplasm","Pancreatic Ductal Adenocarcinoma","Mucinous Cyst",[51,59,53,24,60,61,62,63],"Pancreatic Cystic Lesion","Serous Cystadenoma","Mucinous Cystic Neoplasm","Cancer Epidemiology","Early Detection Research","2025-09-16",{"date":66,"type":29},"2025-09-18",{"date":68,"type":29},"2019-10-08",{"date":70,"type":20},"2030-01-01",{"name":72,"class":36},"University of California, San Francisco",1,{"id":75,"slug":76,"hasResults":11,"nctId":77,"briefTitle":78,"officialTitle":78,"acronym":79,"eligibilityCriteria":80,"healthyVolunteers":81,"sex":16,"minAge":82,"maxAge":4,"enrollmentInfo":83,"targetDuration":4,"studyType":21,"phases":4,"briefSummary":85,"conditions":86,"keywords":89,"overallStatus":25,"whyStopped":4,"lastUpdateSubmitDate":94,"lastUpdatePostDateStruct":95,"startDateStruct":97,"completionDateStruct":99,"leadSponsor":101,"locationsCount":5},"100601941","artificial-intelligence-powered-low-dose-computed-tomography-for-screening-of-pancreatic-cancer-100601941","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,"50 Years",{"count":84,"type":20},400000,"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.",[53,24,87,88,61],"High-grade Pancreatic Intraepithelial Neoplasia","PDAC - Pancreatic Ductal Adenocarcinoma",[90,91,53,92,93],"Screening","Early Diagnosis","Artificial Intelligence","Computed Tomography","2025-08-05",{"date":96,"type":29},"2025-08-12",{"date":98,"type":20},"2025-08-15",{"date":100,"type":20},"2032-12-30",{"name":102,"class":36},"Changhai Hospital",{"id":104,"slug":105,"hasResults":11,"nctId":106,"briefTitle":107,"officialTitle":108,"acronym":109,"eligibilityCriteria":110,"healthyVolunteers":81,"sex":16,"minAge":17,"maxAge":4,"enrollmentInfo":111,"targetDuration":113,"studyType":21,"phases":4,"briefSummary":114,"conditions":115,"keywords":117,"overallStatus":25,"whyStopped":4,"lastUpdateSubmitDate":122,"lastUpdatePostDateStruct":123,"startDateStruct":125,"completionDateStruct":127,"leadSponsor":129,"locationsCount":130},"100565183","ai-powered-early-detection-for-pancreatic-cancer-via-non-contrast-ct-in-opportunistic-screening-cohort-100565183","NCT06638866","AI-powered Early Detection for Pancreatic Cancer Via Non-contrast CT in Opportunistic Screening Cohort","Artificial Intelligence-based Health Information Management System and Key Technology Study of Early Screening and Hierarchical Diagnosis and Treatment of Pancreatic Cancer","AI-PANC","Inclusion Criteria\n\n1\\. Individuals undergoing routine non-contrast chest and\u002For abdominal CT scans for non-pancreatic indications.\n\nExclusion Criteria\n\n1. History of pancreatic cancer;\n2. History of thoracic or abdominal surgery;\n3. Acute pancreatitis within 6 months;\n4. Patients referred for evaluation of suspected or confirmed pancreatic cancer.",{"count":112,"type":20},5000,"5 Years","Pancreatic ductal adenocarcinoma (PDAC) remains a therapeutic challenge with 5-year survival rates of 13%, primarily attributable to advanced-stage diagnosis (AJCC Stage III\u002FIV in \\>80% of cases). This prospective, observational, multi-center study will evaluate the performance of an AI-powered opportunistic screening system utilizing non-contrast computed tomography (NCCT) acquired during routine clinical encounters or health check-ups. The proposed AI model will perform automated detection of pancreatic parenchymal abnormalities, including PDAC and precursor lesions (intraductal papillary mucinous neoplasms \\[IPMN\\], mucinous cystic neoplasms \\[MCN\\]). Algorithm-positive cases will be independently reviewed by two radiologists. Highly suspected individuals will undergo further diagnostic verification, including serological tests and multimodal imaging confirmation. Patients with confirmed positive diagnosis will receive multidisciplinary consultation and specialized treatment, whereas those with negative results will undergo at least one-year clinical follow-up. This study will quantitatively evaluate the AI system's performance, and aims to advance PDAC early detection, improve patient outcomes, and make it accessible in underserved populations.",[53,56,116,24,61],"Pancreatic Intraepithelial Neoplasias",[118,91,92,53,119,120,121],"Early Screening","Pancreatic Lesion","PDAC","Non-contrast CT","2025-03-14",{"date":124,"type":29},"2025-03-19",{"date":126,"type":29},"2024-08-03",{"date":128,"type":20},"2030-12-31",{"name":102,"class":36},3,{"id":132,"slug":133,"hasResults":11,"nctId":134,"briefTitle":135,"officialTitle":136,"acronym":4,"eligibilityCriteria":137,"healthyVolunteers":81,"sex":16,"minAge":138,"maxAge":139,"enrollmentInfo":140,"targetDuration":4,"studyType":21,"phases":4,"briefSummary":141,"conditions":142,"keywords":143,"overallStatus":25,"whyStopped":4,"lastUpdateSubmitDate":147,"lastUpdatePostDateStruct":148,"startDateStruct":150,"completionDateStruct":152,"leadSponsor":154,"locationsCount":73},"100472596","exploring-biomarkers-of-the-carcinogenesis-of-intraductal-papillary-mucinous-neoplasm-ipmn-of-the-pancreas-100472596","NCT05433935","Exploring Biomarkers of the Carcinogenesis of Intraductal Papillary Mucinous Neoplasm (IPMN) of the Pancreas","A Prospective, Open Large Cohort Study of Intraductal Papillary Mucinous Neoplasm (IPMN) of the Pancreas","Inclusion Criteria:\n\n* clinically diagnosed as IPMN;\n* without other malignant tumor;\n* agree to sign informed consent.\n\nExclusion Criteria:\n\n* with mental disorders which can affect cognition and cooperation;\n* with serious blood diseases or taking drugs that can affect peripheral blood","0 Years","90 Years",{"count":112,"type":20},"This is a prospective, open large cohort study to explore biomarkers for detecting early carcinogenesis of IPMN.",[24],[144,145,146],"intraductal papillary mucinous neoplasm","biomarkers","prospective cohort","2023-01-26",{"date":149,"type":29},"2023-01-27",{"date":151,"type":29},"2022-07-01",{"date":153,"type":20},"2033-12-31",{"name":155,"class":36},"Zhejiang University"]