AI-Assisted MRI Molecular Subtyping in Pediatric Brain Tumors

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/rhabdoid tumor (AT/RT), intracranial germ cell tumors, craniopharyngioma, and choroid plexus tumors. The study includes a retrospective cohort for model development and internal/external 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.

NCT Number	NCT07703605
Lead Sponsor	Huashan Hospital Collaborators: Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Quzhou Hospital Affiliated to Wenzhou Medical University, Ruitong Intelligent Medical (Shanghai) Technology Co., Ltd.
Conditions	Pediatric Brain Tumors, Glioma, Medulloblastoma, Ependymoma, Craniopharyngioma, Choroid Plexus Tumors
Enrollment	1,400 participants
Start Date	2026-07-15
Primary Completion	2029-12-30 (estimated)
Study Completion	2029-12-30 (estimated)
Updated on ClinicalTrials.gov	2026-07-23