UCSF

Background

Successful seizure onset zone (SOZ) localisation for epilepsy surgery often relies upon intracranial recordings. Accurate delineation requires anatomical detail yet influences of intracranial electrode density on clinical variables have not been systematically studied.

Methods

In this experimental study we compared SOZ localisation between spontaneously captured seizures on higher-density depth and grid electrode arrays (4-5 mm inter-electrode spacing) vs. lower-density resampled versions of those same seizures (8-10 mm spacing). Since traditional review of channel traces would reveal density conditions, we instead projected seizure activity data as heatmaps on patient brain reconstructions and hid electrode locations. Using a single-blinded randomised crossover design, six attending-level epileptologists viewed these visualisations from ten patients under both higher-density and lower-density conditions (n = 120 observations) and digitally annotated SOZs.

Findings

Inter-rater agreement between epileptologists on annotated margins was moderate (average Cohen's kappa: 0.47) and lower for the lower-density condition (p = 0.021, mixed effects model). Scorer confidence ratings did not differ between higher- and lower-density conditions (p = 0.410). The spatial extents of annotated SOZs for higher-density recordings were 25.4% larger on average (p = 0.011) and always closer to true SOZ extents in computer simulations, relative to lower-density.

Interpretation

Epileptologists using higher-density depth and subdural intracranial EEG recordings had higher inter-rater agreement and identified larger extents of SOZs compared to lower-density recordings. While further studies assessing surgical outcomes in more patients are needed, these results suggest higher densities of electrodes on already-implanted hardware may reveal sub-centimetre extensions and clearer functional contiguity of the SOZ(s) for better appraisals of pathophysiological margins in epilepsy surgery.

Funding

This work was supported by the National Institutes of Health through NINDS grant K23NS110920 and through a UCSF Weill Institute for Neurosciences Pilot Award.