[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100601505":3},{"organization":4,"armGroups":7,"interventions":8,"overallOfficials":7,"centralContacts":11,"locations":17,"responsibleParty":33,"collaborators":7,"id":35,"slug":36,"hasResults":37,"nctId":38,"briefTitle":39,"officialTitle":40,"acronym":41,"eligibilityCriteria":42,"healthyVolunteers":37,"sex":43,"minAge":44,"maxAge":45,"enrollmentInfo":46,"targetDuration":7,"studyType":49,"phases":7,"briefSummary":50,"conditions":51,"keywords":7,"overallStatus":20,"whyStopped":7,"lastUpdateSubmitDate":55,"lastUpdatePostDateStruct":56,"startDateStruct":59,"completionDateStruct":61,"leadSponsor":63,"locationsCount":64},{"fullName":5,"class":6},"Peking University First Hospital","OTHER",null,[9],{"type":6,"name":10,"description":10,"armGroupLabels":7,"otherNames":7},"observational diagnostic model development",[12],{"name":13,"role":14,"phone":15,"phoneExt":7,"email":16},"Zheng Zhang","CONTACT","+86 139 0137 1490","doczhz@aliyun.com",[18],{"facility":19,"status":20,"city":21,"state":7,"zip":22,"country":23,"countryCode":24,"cosmosGeoPoint":25,"geoPoint":30,"contacts":31},"Department of Urology, Peking University First Hospital","RECRUITING","Beijing","100034","China","CN",{"type":26,"coordinates":27},"Point",[28,29],116.39723,39.9075,{"lat":29,"lon":28},[32],{"name":13,"role":14,"phone":7,"phoneExt":7,"email":16},{"type":34,"investigatorFullName":7,"investigatorTitle":7,"investigatorAffiliation":7,"oldNameTitle":7,"oldOrganization":7},"SPONSOR","100601505","construction-of-a-deep-learning-based-precise-diagnostic-framework-for-bladder-tumors-using-ultrasound-a-multicenter-ambispective-cohort-study-100601505",false,"NCT07111364","Construction of a Deep Learning-Based Precise Diagnostic Framework for Bladder Tumors Using Ultrasound: A Multicenter, Ambispective Cohort Study","Construction of a Deep Learning-Based Precise Diagnostic Framework for Bladder Tumors Using Ultrasound","BCA-AI-US","Inclusion Criteria:① Suspected bladder mass detected by abdominal ultrasound (age ≥18 years);② Patients scheduled for surgical treatment of bladder tumors.\n\nExclusion Criteria:\n\n* Age \\>85 years;\n\n  * Patients unable to undergo abdominal\u002Ftransrectal ultrasound (e.g., uncooperative individuals, technically inadequate images);\n\n    * History of bladder tumor surgery, radiotherapy, chemotherapy, or systemic therapy within 3 months; ④ Patients with indwelling medical devices (e.g., double-J ureteral stents, urinary catheters);\n\n      * Failure to undergo bladder tumor surgery within 2 weeks post-ultrasound; ⑥ Non-urothelial carcinoma or pathologically unconfirmed diagnoses.","ALL","18 Years","85 Years",{"count":47,"type":48},400,"ESTIMATED","OBSERVATIONAL","This study aims to develop an ultrasound image-based deep learning system to enable automatic segmentation, T-staging, and pathological grading prediction of bladder tumors. It seeks to enhance the objectivity, accuracy, and efficiency of bladder cancer diagnosis, reduce reliance on physician experience, and provide support for precision medicine and resource optimization.",[52,53,54],"Deep Learning","Ultrasound","Bladder Cancer","2025-08-13",{"date":57,"type":58},"2025-08-17","ACTUAL",{"date":60,"type":58},"2025-05-27",{"date":62,"type":48},"2026-05-31",{"name":5,"class":6},1]