Advanced neuroimaging in pediatric epilepsy surgery: state of the art and future perspectives.
Authors
Affiliations (8)
Affiliations (8)
- Neuroradiology Unit, IRCCS Istituto Giannina Gaslini, Genoa, Italy. [email protected].
- Neuroradiology Department, Hospital Garcia de Orta, Almada, Portugal.
- Neuroradiology Unit, IRCCS Istituto Giannina Gaslini, Genoa, Italy.
- Neurosurgery Unit, IRCCS Istituto Giannina Gaslini, Genoa, Italy.
- Child Neuropsychiatry Unit, IRCCS Istituto Giannina Gaslini, Genoa, Italy.
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, and Maternal-Child Sciences (DINOGMI), University of Genoa, Genoa, Italy.
- Neuroradiology Unit, IRCCS Istituto Giannina Gaslini, Genoa, Italy. [email protected].
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
Abstract
To review recent advances in structural MRI post-processing for pediatric drug-resistant epilepsy, with emphasis on artificial intelligence-driven and quantitative techniques, including MELD-Graph, MAP18, FLAT1, and SUPR-FLAIR, and to evaluate their impact on lesion detection, epileptogenic zone localization, and presurgical planning. Novel post-processing approaches were examined with respect to their computational foundations, imaging requirements, and diagnostic performance. Techniques employing machine learning, deep learning, voxel-based morphometry, cortical surface projection, and FLAIR/T1 ratio mapping were assessed for their applicability in children and their integration into multimodal evaluation pathways alongside electrophysiology and functional imaging. Advanced post-processing tools substantially increase sensitivity for detecting subtle cortical abnormalities, particularly in MRI-negative pediatric epilepsy. MELD-Graph identify features of focal cortical dysplasia through automated surface-based analysis and deep neural network classification, achieving notable lesion detection even when conventional MRI findings are normal. MAP18 provides complementary voxel-wise morphometric assessment, improving specificity and benefiting from optimized structural sequences. FLAT1 enhances lesion conspicuity by quantifying FLAIR/T1 signal relationships, while SUPR-FLAIR improves visualization of cortical signal abnormalities through normalized FLAIR intensity projection onto the cortical surface. When incorporated into multimodal diagnostic workflows, these methods refine epileptogenic zone localization, inform individualized surgical strategies, and can reduce reliance on invasive testing. Advanced structural MRI post-processing is transforming the neuroradiological evaluation of pediatric drug-resistant epilepsy. By revealing subtle cortical abnormalities not visible on conventional imaging, these tools support more precise lesion characterization and surgical planning. Ongoing efforts toward standardization, clinical validation, and workflow integration will be essential to ensure widespread adoption and maximize clinical impact within precision-medicine approaches to pediatric epilepsy.