[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100645498":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":10,"centralContacts":15,"locations":10,"responsibleParty":21,"collaborators":25,"id":33,"slug":34,"hasResults":35,"nctId":36,"briefTitle":37,"officialTitle":38,"acronym":10,"eligibilityCriteria":39,"healthyVolunteers":35,"sex":40,"minAge":41,"maxAge":42,"enrollmentInfo":43,"targetDuration":10,"studyType":46,"phases":10,"briefSummary":47,"conditions":48,"keywords":55,"overallStatus":61,"whyStopped":10,"lastUpdateSubmitDate":62,"lastUpdatePostDateStruct":63,"startDateStruct":66,"completionDateStruct":68,"leadSponsor":70,"locationsCount":10},{"fullName":5,"class":6},"Huashan Hospital","OTHER",[8,12],{"label":9,"type":10,"description":11,"interventionNames":10},"Retrospective Cohort",null,"Pediatric patients younger than 18 years who underwent first surgical treatment for one of the target brain tumors between January 1, 2020 and December 31, 2025, with available preoperative MRI and postoperative pathological confirmation. Data from this cohort will be used for model development and validation.",{"label":13,"type":10,"description":14,"interventionNames":10},"Prospective Cohort","Consecutively enrolled pediatric patients younger than 18 years meeting eligibility criteria from July 15, 2026 onward. Data from this cohort will be used for prospective validation of AI diagnostic performance.",[16],{"name":17,"role":18,"phone":19,"phoneExt":10,"email":20},"Lei Jin","CONTACT","86-21-52887200","ozlei91@126.com",{"type":22,"investigatorFullName":23,"investigatorTitle":24,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","Jinsong Wu","Prof",[26,28,31],{"name":27,"class":6},"Xinhua Hospital, Shanghai Jiao Tong University School of Medicine",{"name":29,"class":30},"Quzhou Hospital Affiliated to Wenzhou Medical University","UNKNOWN",{"name":32,"class":30},"Ruitong Intelligent Medical (Shanghai) Technology Co., Ltd.","100645498","ai-assisted-mri-molecular-subtyping-in-pediatric-brain-tumors-100645498",false,"NCT07703605","AI-Assisted MRI Molecular Subtyping in Pediatric Brain Tumors","AI-Assisted Presurgical MRI Molecular Subtyping for Pediatric Brain Tumors: A Single-Center Ambispective Clinical Cohort Study","Inclusion Criteria:\n\n* Age younger than 18 years at the time of index surgery.\n* Evaluated at a participating study center and scheduled for first surgical treatment of a suspected target pediatric brain tumor.\n* Preoperative brain MRI available before surgery, including at minimum T1-weighted, contrast-enhanced T1-weighted, T2-weighted, and FLAIR sequences in DICOM format; MRI preferably performed within 7 days before surgery and before biopsy or tumor-directed therapy.\n* Postoperative histopathology confirming one of the following target tumor categories: glioma, medulloblastoma, ependymoma, atypical teratoid\u002Frhabdoid tumor, intracranial germ cell tumors, craniopharyngioma, or choroid plexus tumors.\n* For the prospective cohort, written informed consent provided by a parent or legal guardian, with child assent obtained when appropriate according to age, understanding, and local ethics requirements.\n\nExclusion Criteria:\n\n* Postoperative pathology confirming a non-target tumor type.\n* Recurrent tumor, repeat surgery, or prior tumor-directed surgery before the index surgery.\n* Preoperative MRI of inadequate quality for analysis, including severe motion artifact, severe susceptibility\u002Fmetal artifact, or incomplete field of view.\n* Prior biopsy, radiotherapy, chemotherapy, or other tumor-directed treatment before the index preoperative MRI that is judged to substantially affect imaging interpretation.\n* Concurrent malignant disease other than the target brain tumor.\n* Inability to comply with follow-up requirements in the prospective cohort, in the investigator's judgment, because of severe comorbidity or other practical limitations.","ALL","0 Years","17 Years",{"count":44,"type":45},1400,"ESTIMATED","OBSERVATIONAL","This multicenter observational cohort study aims to develop and validate an artificial intelligence (AI)-assisted diagnostic system for preoperative molecular subtyping of pediatric brain tumors using routine magnetic resonance imaging (MRI). The study will include seven major pediatric brain tumor categories: glioma, medulloblastoma, ependymoma, atypical teratoid\u002Frhabdoid tumor (AT\u002FRT), intracranial germ cell tumors, craniopharyngioma, and choroid plexus tumors.\n\nThe study includes a retrospective cohort for model development and internal\u002Fexternal validation, and a prospective cohort for further validation. Retrospective data will be collected from pediatric patients who underwent first surgical treatment between January 1, 2020 and December 31, 2025. Prospective enrollment will begin on July 15, 2026, with an anticipated sample size of 150 participants. The AI system will analyze preoperative MRI sequences, including T1-weighted, contrast-enhanced T1-weighted, T2-weighted, and FLAIR images, to predict key molecular markers and integrated diagnostic categories. The primary objective is to evaluate the diagnostic performance of the AI system for prespecified molecular prediction tasks using postoperative histopathology and molecular testing as the reference standard. Secondary objectives include assessing agreement with integrated diagnosis, comparing performance against blinded radiologists, and exploring prognostic associations of AI-predicted subgroups.",[49,50,51,52,53,54],"Pediatric Brain Tumors","Glioma","Medulloblastoma","Ependymoma","Craniopharyngioma","Choroid Plexus Tumors",[56,57,58,59,60],"Artificial Intelligence","Molecular Subtyping","Diagnostic Performance","Deep Learning","Pediatric Neuro-Oncology","NOT_YET_RECRUITING","2026-07-21",{"date":64,"type":65},"2026-07-23","ACTUAL",{"date":67,"type":45},"2026-07-15",{"date":69,"type":45},"2029-12-30",{"name":5,"class":6}]