Intraoperative Metabolomic-Guided Precision Surgery for Pediatric Brain Tumors: A Systematic Review of Multi-Modal Molecular Imaging Platforms and Artificial Intelligence Integration
Abstract
Background
Pediatric brain tumors are the leading cause of cancer death in children, with surgical resection critical for survival and neurodevelopment. Intraoperative molecular imaging has advanced in adults but remains limited in pediatrics. This review examines the availability of intraoperative metabolomic imaging, AI integration, and multi-modal imaging in pediatric brain tumor surgery.
Methods
Literature search was done in PubMed, Scopus, Web of Science, and Embase from 2010-2025. Included studies addressed intraoperative molecular imaging in pediatrics, metabolomic neurosurgery approaches, or AI application in pediatric brain tumor care.
Results
Of 2,847 articles, 75 met criteria. Pediatric intraoperative imaging mainly uses magnetic resonance imaging (21 studies), with limited metabolomic approaches (16 studies). Mass spectrometry shows promise for real-time tissue characterization but mainly in adults. AI in pediatric neuroimaging improved tumor segmentation and outcome prediction in 15 studies. Key gaps: (1) limited pediatric metabolomic databases, (2) lack of real-time metabolomic platforms for developing brains, (3) limited neurodevelopment integration in surgical planning, (4) no standard protocols for multi-modal integration.
Discussion
The review highlights opportunities to advance intraoperative molecular imaging in pediatric neurosurgery via metabolomic-guided and AI-integrated approaches. Future research should develop pediatric-specific metabolomic platforms, age-specific biomarker libraries, and integrated decision-support systems considering oncological and neurodevelopment outcomes.
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