Presurgical thalamocortical connectivity is associated with response to vagus nerve stimulation in children with intractable epilepsy

Abstract

Although chronic vagus nerve stimulation (VNS) is an established treatment for medically-intractable childhood epilepsy, there is considerable heterogeneity in seizure response and little data are available to pre-operatively identify patients who may benefit from treatment. Since the therapeutic effect of VNS may be mediated by afferent projections to the thalamus, we tested the hypothesis that intrinsic thalamocortical connectivity is associated with seizure response following chronic VNS in children with epilepsy. Twenty-one children (ages 5–21years) with medically-intractable epilepsy underwent resting-state fMRI prior to implantation of VNS. Ten received sedation, while 11 did not. Whole brain connectivity to thalamic regions of interest was performed. Multivariate generalized linear models were used to correlate resting-state data with seizure outcomes, while adjusting for age and sedation status. A supervised support vector machine (SVM) algorithm was used to classify response to chronic VNS on the basis of intrinsic connectivity. Of the 21 subjects, 11 (52%) had 50% or greater improvement in seizure control after VNS. Enhanced connectivity of the thalami to the anterior cingulate cortex (ACC) and left insula was associated with greater VNS efficacy. Within our test cohort, SVM correctly classified response to chronic VNS with 86% accuracy. In an external cohort of 8 children, the predictive model correctly classified the seizure response with 88% accuracy. We find that enhanced intrinsic connectivity within thalamocortical circuitry is associated with seizure response following VNS. These results encourage the study of intrinsic connectivity to inform neural network-based, personalized treatment decisions for children with intractable epilepsy. Keywords: Functional connectivity, Intrinsic connectivity networks, Resting-state fMRI, Low frequency neural oscillations, VNS