[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100567395":3},{"organization":4,"armGroups":7,"interventions":8,"overallOfficials":13,"centralContacts":17,"locations":23,"responsibleParty":37,"collaborators":7,"id":41,"slug":42,"hasResults":43,"nctId":44,"briefTitle":45,"officialTitle":45,"acronym":7,"eligibilityCriteria":46,"healthyVolunteers":47,"sex":48,"minAge":49,"maxAge":7,"enrollmentInfo":50,"targetDuration":7,"studyType":53,"phases":7,"briefSummary":54,"conditions":55,"keywords":57,"overallStatus":61,"whyStopped":7,"lastUpdateSubmitDate":62,"lastUpdatePostDateStruct":63,"startDateStruct":66,"completionDateStruct":68,"leadSponsor":70,"locationsCount":71},{"fullName":5,"class":6},"Chinese PLA General Hospital","OTHER",null,[9],{"type":10,"name":11,"description":12,"armGroupLabels":7,"otherNames":7},"DIAGNOSTIC_TEST","Artificial intelligence","Artificial intelligence (AI) tools developed through the training of large amounts of image data can assist with the analysis and interpretation of neuroimaging data of cerebral small vascular disease（CSVD）.",[14],{"name":15,"affiliation":5,"role":16},"Xin Lou, MD\u002FPhD","STUDY_CHAIR",[18],{"name":19,"role":20,"phone":21,"phoneExt":7,"email":22},"Chaobang Xie","CONTACT","18798120676","chaobangxie@163.com",[24],{"facility":5,"status":7,"city":25,"state":26,"zip":27,"country":26,"countryCode":28,"cosmosGeoPoint":29,"geoPoint":34,"contacts":35},"Beijing","China","100853","CN",{"type":30,"coordinates":31},"Point",[32,33],116.39723,39.9075,{"lat":33,"lon":32},[36],{"name":19,"role":20,"phone":21,"phoneExt":7,"email":22},{"type":38,"investigatorFullName":39,"investigatorTitle":40,"investigatorAffiliation":5,"oldNameTitle":7,"oldOrganization":7},"PRINCIPAL_INVESTIGATOR","Xin Lou","Deputy Director of Department of Radiology","100567395","intelligent-analysis-and-clinical-validation-of-cerebral-small-vessel-disease-on-magnetic-resonance-imaginga-multi-center-study-100567395",false,"NCT06667635","Intelligent Analysis and Clinical Validation of Cerebral Small Vessel Disease on Magnetic Resonance Imaging：A Multi-center Study","Inclusion Criteria:\n\n* ① Men and women age 40 years or older;\n\n  * At least one vascular risk factor has been identified, including hypertension, diabetes, hyperlipidemia, coronary heart disease, and chronic kidney disease；\n\n    * The patient performed two brain MRI Examinations simultaneously at a time interval of more than 6 months (≥6).\n\nExclusion Criteria:\n\n* ① The patient had no vascular risk factors；\n\n  * No clinical follow-up images;\n\n    * There are significant motion artifacts in the image, which cannot meet the",true,"ALL","40 Years",{"count":51,"type":52},1000,"ESTIMATED","OBSERVATIONAL","Cerebral small vessel disease (CSVD) accounts for 20% of ischemic strokes and is the most common cause of vascular cognitive impairment. Early identification of CSVD is critical for early intervention and improve clinical outcomes. Magnetic resonance imaging (MRI) may represent as a sensitive and robust tool to detect early changes in brain subtle structures and functions. The study is to investigate the comprehensive evaluation by using AI in early diagnosis and management of CSVD.",[56],"Cerebral Small Vessel Disease",[58,11,59,60],"Cerebral small vessel disease","Deep learning","Magnetic resonance imaging","NOT_YET_RECRUITING","2024-10-30",{"date":64,"type":65},"2024-10-31","ACTUAL",{"date":67,"type":52},"2024-11-01",{"date":69,"type":52},"2030-09-01",{"name":5,"class":6},1]