54th Child Neurology Society Annual Meeting in October at the Charlotte Convention Center Coverage

Review 3: EEG Biomarkers Guide Sirolimus Treatment in Tuberous Sclerosis Complex Infants

A multi-site Phase II clinical trial presented by Booth and colleagues from Los Angeles explores electroencephalography biomarkers for monitoring sirolimus treatment response in infants with tuberous sclerosis complex. This research, presented at the Child Neurology Society Annual Meeting, addresses a critical need for early intervention strategies in this genetic disorder strongly associated with epilepsy and neurodevelopmental disabilities.

Tuberous sclerosis complex, caused by mutations in TSC1 or TSC2 genes affecting the mTOR pathway, frequently manifests with early-onset seizures that can be refractory to conventional treatments. Sirolimus, an mTOR inhibitor, offers a targeted therapeutic approach by directly addressing the underlying molecular dysfunction. However, identifying reliable biomarkers to track treatment response in young infants has remained challenging, limiting optimization of early intervention strategies.

The investigators collected high-density electroencephalography recordings from nine infants with confirmed tuberous sclerosis complex at three developmental timepoints spanning from 6 to 24 months of age. Their comprehensive protocol included both resting state recordings and event-related potentials using visual and auditory stimuli. Data quality assessments demonstrated excellent feasibility, with an average of 615 seconds of resting state data collected per session and approximately 77% of data retained after artifact removal.

Event-related potential paradigms showed promising retention rates of 69% for visual evoked potentials and 70% for auditory evoked potentials, indicating that these measures can be successfully obtained even in very young children with neurodevelopmental concerns. The study’s preliminary success supports electroencephalography as a sensitive tool for tracking neurophysiological changes during treatment. Future analyses will focus on beta power changes and variations in sensory evoked response characteristics as potential biomarkers of treatment efficacy.

Reference: Ntolkeras G, Pimenta V, Makaram N, et al. EEG Network Analysis as a Prognostic Tool for Corpus Callosotomy in Pediatric Drug-Resistant Epilepsy. Presented at: Child Neurology Society Annual Meeting; October 2025; Charlotte, NC.

Review 4: Network Connectivity Predicts Corpus Callosotomy Success in Drug-Resistant Epilepsy

Research by Ntolkeras and colleagues from Brookline introduces novel electroencephalography- based connectivity biomarkers that predict surgical outcomes following corpus callosotomy in children with drug-resistant epilepsy. This study, presented at the Child Neurology Society Annual Meeting, addresses a critical clinical challenge where nearly half of patients experience limited benefit from this palliative surgical intervention.

The investigators analyzed preoperative scalp electroencephalography data from 32 children with drug-resistant epilepsy who underwent corpus callosotomy, with a median age of 10.5 years. Patients were stratified into three outcome categories based on seizure reduction: excellent responders with greater than 90% reduction, intermediate responders with 50-90% reduction, and poor responders with less than 50% improvement. The team computed functional connectivity metrics across five frequency bands, examining whole-brain, within-hemisphere, and between- hemisphere connectivity patterns.

Results revealed that presurgical brain connectivity strongly predicted postoperative outcomes. Children with higher functional connectivity across alpha, beta, and gamma frequency bands demonstrated significantly better surgical responses, with odds ratios ranging from 1.8 to 2.3. This hyperconnected state may indicate networks more amenable to disruption through callosal sectioning. The predictive model incorporating electroencephalography connectivity metrics with clinical characteristics achieved 84% accuracy in forecasting surgical outcomes.

Postoperative analyses provided mechanistic insights into treatment response. Patients achieving excellent outcomes showed significant decreases in whole-brain, between-hemisphere, and within-hemisphere connectivity following surgery. In contrast, those with suboptimal outcomes showed no significant connectivity changes, suggesting that successful corpus callosotomy fundamentally reorganizes brain networks. These findings offer a quantitative framework for surgical candidate selection that could significantly improve patient stratification.

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