Abstracts

Functional Connectivity Mapping in Pediatric Drug Resistant Epilepsy

Abstract number : 2.317
Submission category : 5. Neuro Imaging / 5B. Functional Imaging
Year : 2025
Submission ID : 75
Source : www.aesnet.org
Presentation date : 12/7/2025 12:00:00 AM
Published date :

Authors :
Presenting Author: Benjamin Edmonds, MD – Seattle Children's Hospital

Seth Friedman, PhD – Seattle Children's Hospital
mike Bindschlader, PhD – Seattle Children's Hospital
Andrew Poliakov, PhD – Seattle Children's Hospital
Edward Novotny, MD – Seattle Children's Hospital

Rationale: Epilepsy is a disorder of brain networks affecting 0.6% of children, with medications controlling only 70% of cases. As thalamically targeted intracranial devices become a more accepted therapy for drug-resistant epilepsy (DRE), understanding the neural networks involved is essential to identify effective targets. Given limitations of structural MRI and PET to highlight functional networks, we explore the possibility of using resting-state functional connectivity MRI (fcMRI) to evaluate epilepsy networks. Recently, fcMRI has been used to compare epilepsy types and distinguish network differences in adult epilepsy populations. However, such research is lacking in pediatric DRE. Therefore, we examined fcMRI data in a population of pediatric DRE patients, divided into focal (F) and generalized (G) cohorts, to explore whether differences in thalamic network connectivity can be used as a biomarker.  

Methods:

Retrospective analysis of all fcMRI studies with patients ≤ 18yo with DRE from 2021 to 2025 at Seattle Children’s HospitalInclusion criteria were anatomically intact MRI of the brain, and successful completion of two resting state fMRI trials with mild motion artifact and no other imaging artifacts. Twenty-five patients were included in the analysis (17 focal epilepsy, F, and 8 generalized epilepsy, G). MRI was performed on a 3T Siemens scanner using 64ch coil utilizing EPIBOLD sequences. FcMRI data analysis combined imaging trials using 1000 Functional Connectomes Project scripts based on AFNI and FSL software packages as previously published by our team1 

 

Connectivity maps, represented by correlation coefficient (CC) values, were generated using seed-based interregional networks (3mm resolution, 1 voxel seeds) in the anterior nucleus (AN), mediodorsal nucleus

Neuro Imaging