[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100579485":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":10,"centralContacts":10,"locations":25,"responsibleParty":57,"collaborators":59,"id":74,"slug":75,"hasResults":76,"nctId":77,"briefTitle":78,"officialTitle":79,"acronym":10,"eligibilityCriteria":80,"healthyVolunteers":76,"sex":81,"minAge":82,"maxAge":10,"enrollmentInfo":83,"targetDuration":10,"studyType":86,"phases":10,"briefSummary":87,"conditions":88,"keywords":10,"overallStatus":28,"whyStopped":10,"lastUpdateSubmitDate":90,"lastUpdatePostDateStruct":91,"startDateStruct":94,"completionDateStruct":96,"leadSponsor":98,"locationsCount":99},{"fullName":5,"class":6},"Ruijin Hospital","OTHER",[8,13,16],{"label":9,"type":10,"description":10,"interventionNames":11},"pancreatic ductal adenocarcinoma",null,[12],"Device: ROSE-AI diagnostic system",{"label":14,"type":10,"description":10,"interventionNames":15},"pancreatic neuroendocrine tumor",[12],{"label":17,"type":10,"description":10,"interventionNames":18},"non-neoplastic benign lesions",[12],[20],{"type":21,"name":22,"description":23,"armGroupLabels":24,"otherNames":10},"DEVICE","ROSE-AI diagnostic system","All samples were obtained due to the necessity for disease treatment and in accordance with routine clinical workflows. After the pathological diagnoses were confirmed by the pathology departments of the hospitals affiliated with the respective endoscopic centers, the eligible pancreatic puncture Diff-Quik stained smears were borrowed and transferred to Ruijin Hospital Affiliated to School of Medicine, Shanghai Jiao Tong University. There, the self-developed \"Zhiying Shunxi\" system was used to capture corresponding traditional light microscope RGB images. After the imaging was completed, all specimens were returned to the endoscopic centers from which they originated. Using the RGB images as input, an artificial intelligence algorithm was developed to assist in differentiating solid pancreatic lesions.",[17,9,14],[26,46],{"facility":27,"status":28,"city":29,"state":30,"zip":31,"country":32,"countryCode":33,"cosmosGeoPoint":34,"geoPoint":39,"contacts":40},"Ruijin Hospital, Shanghai Jiaotong University School of Medicine","RECRUITING","Shanghai","Shanghai Municipality","200000","China","CN",{"type":35,"coordinates":36},"Point",[37,38],121.45806,31.22222,{"lat":38,"lon":37},[41],{"name":42,"role":43,"phone":44,"phoneExt":10,"email":45},"Duowu Zou, MD","CONTACT","+8613901617608","zdw_pi@126.com",{"facility":47,"status":28,"city":29,"state":30,"zip":48,"country":32,"countryCode":33,"cosmosGeoPoint":49,"geoPoint":51,"contacts":52},"Department of Gastroenterolog, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine","200025",{"type":35,"coordinates":50},[37,38],{"lat":38,"lon":37},[53],{"name":54,"role":43,"phone":55,"phoneExt":10,"email":56},"Taojing Ran, MD","8615601942397","rantaojing@163.com",{"type":58,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR",[60,62,64,66,68,70,72],{"name":61,"class":6},"Second Affiliated Hospital of Soochow University",{"name":63,"class":6},"Fudan University",{"name":65,"class":6},"Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine",{"name":67,"class":6},"The Third Xiangya Hospital of Central South University",{"name":69,"class":6},"Shanghai 10th People's Hospital",{"name":71,"class":6},"Affiliated Hospital of Jiangnan University",{"name":73,"class":6},"Jiangyin People's Hospital","100579485","endoscopic-ultrasound-guided-fine-needle-aspiration-of-solid-pancreatic-lesions-with-rapid-staining-of-cytological-smears-followed-by-whole-slide-scanning-and-artificial-intelligence-diagnosis-a-prospective-multicenter-study-100579485",false,"NCT06824909","Endoscopic Ultrasound-guided Fine-needle Aspiration of Solid Pancreatic Lesions With Rapid Staining of Cytological Smears Followed by Whole Slide Scanning and Artificial Intelligence Diagnosis: A Prospective, Multicenter Study.","内镜超声穿刺胰腺实性占位细胞涂片快速染色后全玻片扫描及人工智能诊断：一项前瞻性、多中心研究","Inclusion Criteria:\n\n* A dated and signed informed consent form A commitment to abide by the research procedures and cooperate throughout the entire study Subjects aged 18 and above, regardless of gender Diagnosis or suspicion of a solid pancreatic space-occupying lesion based on imaging studies (B-mode ultrasound, CT, or MRI)\n\nExclusion Criteria:\n\n* Unable or refusing to sign the informed consent form Unable to suspend anticoagulation\u002Fantiplatelet therapy Pregnant or lactating Having a mental illness or other medical conditions that are unsuitable for undergoing FNA\u002FB biopsy Presence of coagulation disorders (PLT \\\u003C 50 × 10\\^3\u002Fμl, INR \\> 1.5) Pancreatic cystic lesions Non-diagnostic EUS-FNA\u002FB specimens Having less than 8 microscopic fields of interest (ROI) in the digital pathology images of the entire Diff-Quik smear slide","ALL","18 Years",{"count":84,"type":85},1500,"ESTIMATED","OBSERVATIONAL","The objective of this observational study is to investigate whether the self-developed whole slide scanning and artificial intelligence diagnostic system for pancreatic solid lesion puncture cytopathology (hereinafter referred to as the \"Zhiying Shunxi\" ROSE-AI diagnostic system) can promptly and accurately diagnose solid pancreatic lesions (SPLs). The main question it aims to answer is:\n\nBy utilizing optical imaging technology to capture RGB images of Diff-Quik stained smears from pancreatic punctures, can the development of artificial intelligence algorithms assist in differentiating solid pancreatic space-occupying diseases (such as pancreatic ductal adenocarcinoma, pancreatic neuroendocrine tumors, and non-neoplastic benign lesions)?\n\nResearchers will compare the diagnoses of SPLs made by the ROSE-AI system with the actual pathological diagnoses of the SPLs themselves to determine whether the ROSE-AI system can effectively diagnose SPLs.",[89],"Pancreatic Disease","2025-02-08",{"date":92,"type":93},"2025-02-13","ACTUAL",{"date":95,"type":93},"2024-12-31",{"date":97,"type":85},"2027-06-30",{"name":5,"class":6},2]