[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100564723":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":22,"centralContacts":27,"locations":38,"responsibleParty":55,"collaborators":32,"id":59,"slug":60,"hasResults":61,"nctId":62,"briefTitle":17,"officialTitle":63,"acronym":32,"eligibilityCriteria":64,"healthyVolunteers":65,"sex":66,"minAge":67,"maxAge":32,"enrollmentInfo":68,"targetDuration":32,"studyType":71,"phases":72,"briefSummary":74,"conditions":75,"keywords":83,"overallStatus":40,"whyStopped":32,"lastUpdateSubmitDate":88,"lastUpdatePostDateStruct":89,"startDateStruct":92,"completionDateStruct":93,"leadSponsor":95,"locationsCount":96},{"fullName":5,"class":6},"Changhai Hospital","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"Health Examination Cohort","EXPERIMENTAL","Asymptomatic participants in routine health examinations receive abdominal or chest non-contrast CT scans, categorized as follows:\n\n1. Meinian cohort\n2. Changhai cohort",[13],"Diagnostic Test: AI-Assisted Non-Contrast CT for Multi-Cancer Screening",[15],{"type":16,"name":17,"description":18,"armGroupLabels":19,"otherNames":20},"DIAGNOSTIC_TEST","AI-Assisted Non-Contrast CT for Multi-Cancer Screening","Participants identified by the AI model as having potential cancerous lesions, including those suspected of lung, liver, gastric, colorectal, esophageal, pancreatic, and breast cancer, will be required to undergo blood tests (for tumor markers) and additional imaging studies (such as contrast-enhanced CT, MRI, Endoscopy, etc.) to confirm the diagnosis of cancerous lesions.",[9],[21],"AI-MCScreen",[23],{"name":24,"affiliation":25,"role":26},"Jin Gang, M.D.","Department of general surgery, Changhai Hospital","STUDY_CHAIR",[28,34],{"name":29,"role":30,"phone":31,"phoneExt":32,"email":33},"Wang Beilei, M.D.","CONTACT","86-13774238083",null,"lilly_wang@126.com",{"name":35,"role":30,"phone":36,"phoneExt":32,"email":37},"Guo Shiwei, M.D.","86-18621500666","gestwa@163.com",[39],{"facility":5,"status":40,"city":41,"state":42,"zip":43,"country":44,"countryCode":45,"cosmosGeoPoint":46,"geoPoint":51,"contacts":52},"RECRUITING","Shanghai","Shanghai Municipality","200433","China","CN",{"type":47,"coordinates":48},"Point",[49,50],121.45806,31.22222,{"lat":50,"lon":49},[53,54],{"name":29,"role":30,"phone":31,"phoneExt":32,"email":33},{"name":24,"role":30,"phone":32,"phoneExt":32,"email":32},{"type":56,"investigatorFullName":57,"investigatorTitle":58,"investigatorAffiliation":5,"oldNameTitle":32,"oldOrganization":32},"SPONSOR_INVESTIGATOR","Guo ShiWei","Associated Professor at the Clinical Research Center","100564723","ai-assisted-non-contrast-ct-for-multi-cancer-screening-100564723",false,"NCT06632886","A Prospective Cohort Study Evaluating the Utility of Artificial Intelligence-Assisted Non-Contrast Computed Tomography for Multi-Cancer Screening in Asymptomatic Individuals Undergoing Routine Health Examinations","Inclusion Criteria:\n\n1. Subject is able and willing to provide informed consent and sign an informed consent form.\n2. Subject has undergone an abdominal or chest non-contrast CT scan.\n\nExclusion Criteria:\n\n1. Subject has been diagnosed with one of the following cancers within the last five years: lung, liver, stomach, colon, esophageal, pancreatic, or breast cancer;\n2. Subject has any medical condition that contraindicates high-resolution MRI\u002FCT\u002FEndoscopy;\n3. Subject cannot be followed up or is participating in other clinical trials.",true,"ALL","18 Years",{"count":69,"type":70},1000000,"ESTIMATED","INTERVENTIONAL",[73],"NA","Cancer poses a major public health challenge in China. Early detection can improve treatment outcomes and survival rates. In this study, we will conduct a large-scale, prospective, multi-center cohort study to evaluate the utility of AI-assisted non-contrast CT for multi-cancer screening.\n\nThe study aims to enroll 1 million asymptomatic participants undergoing routine health examinations, using an AI imaging model based on non-contrast CT to detect seven cancers such as lung, liver, gastric, colorectal, esophageal, pancreatic, and breast cancers. Positive cases will be required to be referred to Shanghai Changhai Hospital for further imaging and care based on National Comprehensive Cancer Network (NCCN) and American College of Radiology (ACR) guidelines. The goal is to assess the AI model's diagnostic performance for seven cancer types, especially for early-stage, resectable tumors.",[76,77,78,79,80,81,82],"Lung Cancers","Liver Cancer","Gastric Cancers","Colorectal, Cancer","Esophageal Cancer","Pancreatic Cancer","Breast Cancer",[84,85,86,87],"Screening","Early Diagnosis","Artificial Intelligence","Cancer","2024-10-07",{"date":90,"type":91},"2024-10-09","ACTUAL",{"date":88,"type":70},{"date":94,"type":70},"2027-10-07",{"name":57,"class":6},1]