[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100573839":3},{"organization":4,"armGroups":7,"interventions":7,"overallOfficials":7,"centralContacts":8,"locations":18,"responsibleParty":43,"collaborators":7,"id":47,"slug":48,"hasResults":49,"nctId":50,"briefTitle":51,"officialTitle":52,"acronym":7,"eligibilityCriteria":53,"healthyVolunteers":49,"sex":54,"minAge":55,"maxAge":56,"enrollmentInfo":57,"targetDuration":60,"studyType":61,"phases":7,"briefSummary":62,"conditions":63,"keywords":65,"overallStatus":21,"whyStopped":7,"lastUpdateSubmitDate":71,"lastUpdatePostDateStruct":72,"startDateStruct":75,"completionDateStruct":77,"leadSponsor":79,"locationsCount":80},{"fullName":5,"class":6},"The First Affiliated Hospital with Nanjing Medical University","OTHER",null,[9,14],{"name":10,"role":11,"phone":12,"phoneExt":7,"email":13},"Shao Pengfei, Professor","CONTACT","+8613851925825","spf032@hotmail.com",{"name":15,"role":11,"phone":16,"phoneExt":7,"email":17},"Miao Haoqi, Postgraduate","+8613276636957","mhq@stu.njmu.edu.cn",[19,33],{"facility":20,"status":21,"city":22,"state":23,"zip":24,"country":25,"countryCode":26,"cosmosGeoPoint":27,"geoPoint":32,"contacts":7},"The First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial People's Hospital)","RECRUITING","Nanjing","Jiangsu","210000","China","CN",{"type":28,"coordinates":29},"Point",[30,31],118.77778,32.06167,{"lat":31,"lon":30},{"facility":20,"status":34,"city":22,"state":23,"zip":35,"country":25,"countryCode":26,"cosmosGeoPoint":36,"geoPoint":38,"contacts":39},"NOT_YET_RECRUITING","210036",{"type":28,"coordinates":37},[30,31],{"lat":31,"lon":30},[40,41],{"name":10,"role":11,"phone":12,"phoneExt":7,"email":13},{"name":15,"role":11,"phone":16,"phoneExt":42,"email":7},"mhq@stu.njmu.e",{"type":44,"investigatorFullName":45,"investigatorTitle":46,"investigatorAffiliation":5,"oldNameTitle":7,"oldOrganization":7},"SPONSOR_INVESTIGATOR","Shao Pengfei","chief physician","100573839","the-value-of-a-convolutional-neural-network-based-renal-artery-perfusion-model-in-predicting-renal-function-after-partial-nephrectomy-a-prospective-study-100573839",false,"NCT06751498","The Value of a Convolutional Neural Network-Based Renal Artery Perfusion Model in Predicting Renal Function After Partial Nephrectomy: A Prospective Study","The Value of a Renal Artery Perfusion Model Based on Convolutional Neural Network in Predicting Renal Function After Partial Nephrectomy: A Prospective, Single-Center Study","Inclusion Criteria:\n\n* people with stage cT1 renal tumors confirmed by preoperative CT or MR\n* people who are proposed to undergoing partial nephrectomy\n* localized renal tumors without lymph node and distant metastases as defined by NCCN guidelines\n* ECOG score of 0 or 1\n* Life expectancy greater than 10 years\n\nExclusion Criteria:\n\n* people with surgically unresectable lesions\n* people with Abnormal preoperative renal function, eGFR(estimated by CKD-EPI)\\\u003C90ml\u002Fmin\u002F1.73m2\n* people who receive preoperative molecular targeted therapy, immunotherapy, chemotherapy\n* people with any contraindications to surgery\n* people who convert to radical nephrectomy during surgery\n* people who receive molecular targeted therapy, immunotherapy or chemotherapy during the postoperative follow-up period\n* people with serious systemic disease","ALL","18 Years","80 Years",{"count":58,"type":59},300,"ESTIMATED","1 Year","OBSERVATIONAL","The goal of this observational study is to develop a CNN-based machine module to predict postoperative fractional renal function in people who are proposed to undergo partial nephrectomy. The main question it aims to answer is:\n\n• Does this machine learning model accurately predict renal function after partial nephrectomy?",[64],"Renal Cell Cancer",[66,67,68,69,70],"Articicial Intelligence","convolutional neural network","renal arterial perfusion model","partial nephrectomy","fractional renal function","2025-04-14",{"date":73,"type":74},"2025-04-17","ACTUAL",{"date":76,"type":74},"2025-01-01",{"date":78,"type":59},"2028-01-01",{"name":45,"class":6},2]