Abstracts

Rationale: A critical step towards optimizing direct modulation of refractory focal-onset epilepsy is to effectively interface Responsive Neurostimulation (RNS, NeuroPace, Inc) therapy depth electrodes with an extensive epileptogenic circuit. The objective of this work is to predict preoperatively the maximum extent to which direct stimulation therapy can propagate through an epileptic circuit for stabilizing refractory focal-onset epilepsy using a computationally intensive model.Methods: The modelling workflow consisted of five steps: 1) visualization of the epileptic circuit using novel diagnostic imaging techniques which included, Subtracted Post-Ictal DTI (spiDTI) to locate transient ictal-related changes of water diffusion in white matter in conjunction with Subtracted Ictal SPECT co-registered to MRI (SISCOM) to identify transient blood flow changes at the ictal onset; 2) virtual electrode lead placement using a patient-specific 3D model; 3) computation of Electric Potential and Electric Fields using finite element method analysis to model the volume of cortical activation using an activation function (AF). Such an AF was related to the second directional derivative of the Electric Potential in the direction of axon bundles. The AF was derived from the cable equation for axons. In addition, 4) distant cortical activation was predicted by strategically placing the AF volume seeds for creating a modulated circuit tractography (MCT) map. The pre-implant MCT map was used as a targeting template for placing up to two RNS depth leads intra-operatively. Finally, 5) Subtracted Activated SPECT (SAS) was utilized post-implantation to validate the maximal extent of epileptogenic regions influenced by stimulation therapy. The latter technique captured transient blood flow changes during delivery of neurostimulation therapy using a high therapeutic charge density, delivered through adjacent contacts without generating an after-discharge.Results: The model was generated for 4 RNS patients implanted at our institution post-FDA approval with at least one 4-contact depth lead. Our depth lead planning system generated irregular non-spherical AF-dependent volumes of cortical activation surrounding the depth contacts. The generated MCT map predicted the extent to which white matter connected epileptic sources were influenced during direct stimulation therapy. Validation of this map was demonstrated post-implantation for each patient employing RNS electrocorticography and SAS.Conclusions: This pre-implant modeling system and the post-implant SAS blood flow validation method offers the potential for predicting optimal depth electrode lead implant sites with a limited set of contacts for modulating the maximal extent of a refractory epileptogenic network.