[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100582171":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":20,"centralContacts":21,"locations":27,"responsibleParty":46,"collaborators":20,"id":50,"slug":51,"hasResults":52,"nctId":53,"briefTitle":54,"officialTitle":55,"acronym":9,"eligibilityCriteria":56,"healthyVolunteers":57,"sex":58,"minAge":59,"maxAge":60,"enrollmentInfo":61,"targetDuration":20,"studyType":64,"phases":65,"briefSummary":67,"conditions":68,"keywords":70,"overallStatus":30,"whyStopped":20,"lastUpdateSubmitDate":73,"lastUpdatePostDateStruct":74,"startDateStruct":77,"completionDateStruct":78,"leadSponsor":80,"locationsCount":81},{"fullName":5,"class":6},"Zhejiang University","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"LEAF","EXPERIMENTAL","Patients diagnosed with liver cirrosis or those with extrahepatic malignant tumors will be enrolled within three weeks. Non-contrast chest and abdominal CT scans will be simultaneously reviewed by radiologists in routine clinical workflow and processed by LEAF in real-time. Daily logs of LEAF-positive alerts will be maintained by the research team. A prespecified clinical action committee composed of hepatobiliary surgeons and abdominal radiologists will review the case to assess whether the AI finding warrants communication to the treating physician of these patients. For patients with suspected malignant liver tumors, the committee's consensus on the presence of suspicious lesions will be communicated to their attending physicians, who will then decide whether additional diagnostic assessment is indicated according to standard clinical practice.",[13],"Device: LEAF(Liver tumor dEtection And classiFication AI)",[15],{"type":16,"name":17,"description":18,"armGroupLabels":19,"otherNames":20},"DEVICE","LEAF(Liver tumor dEtection And classiFication AI)","The LEAF (Liver tumor dEtection And classiFication AI) model will assist in image interpretation. Patients with positive results for liver malignancy while not reported in standard-of-care CT report will be reviewed by a prespecified clinical action committee composed of hepatobiliary surgeons and abdominal radiologists will review the case and decide whether the AI finding warrants communication to the treating physician of these patients. For patients with suspected malignant liver tumors, the committee's consensus on the presence of suspicious lesions will be communicated to their attending physicians, who will then decide whether additional diagnostic assessment is indicated according to standard clinical practice, while remaining blinded to the LEAF results. The standard radiology workflow will not be altered by the study, and LEAF will be evaluated as a risk-stratification and case-flagging tool rather than a replacement for radiologist interpretation.",[9],null,[22],{"name":23,"role":24,"phone":25,"phoneExt":20,"email":26},"Qi Zhang","CONTACT","13819137113","qi.zhang@zju.edu.cn",[28],{"facility":29,"status":30,"city":31,"state":32,"zip":33,"country":34,"countryCode":35,"cosmosGeoPoint":36,"geoPoint":41,"contacts":42},"the First Affiliated Hospital, School of Medicine, Zhejiang University","RECRUITING","Hangzhou","Zhejiang","310009","China","CN",{"type":37,"coordinates":38},"Point",[39,40],120.16142,30.29365,{"lat":40,"lon":39},[43],{"name":23,"role":24,"phone":44,"phoneExt":20,"email":45},"13858108798","Qizhang@zju.edu.cn",{"type":47,"investigatorFullName":48,"investigatorTitle":49,"investigatorAffiliation":5,"oldNameTitle":20,"oldOrganization":20},"PRINCIPAL_INVESTIGATOR","TingBo Liang","Professor","100582171","leaf-liver-tumor-detection-and-classification-ai-100582171",false,"NCT06859840","LEAF (Liver Tumor dEtection And classiFication AI)","Clinical Research on the Use of Non-contrast CT Combined With AI for Early Screening for Liver Malignancy","Inclusion Criteria:\n\nAge range 18 years and above;\n\nUnderwent non-contrast chest or abdominal CT examination with liver coverage;\n\nPatients with an established diagnosis of cirrhosis;\n\nPatients with an established diagnosis of extrahepatic cancer.\n\nExclusion criteria:\n\nPatients who have been diagnosed with malignant liver tumor;\n\nPatients who underwent liver transplantation;\n\nLow quality image, severe artifacts and noise.",true,"ALL","18 Years","90 Years",{"count":62,"type":63},2500,"ESTIMATED","INTERVENTIONAL",[66],"NA","This study aims to assess the feasibility of leveraging non-contrast CT and artificial intelligence to detect liver cancer in consecutive real-world patients. To this end, we deploy LEAF in a prospective real-world clinical setting for real-time monitoring, with a particular focus on flagging cases with liver cancer that may be missed by routine clinical workflow.",[69],"Liver Malignancy",[71,72],"Artificial Intelligence","liver malignancy","2026-07-16",{"date":75,"type":76},"2026-07-17","ACTUAL",{"date":75,"type":63},{"date":79,"type":63},"2026-11-10",{"name":5,"class":6},1]