HD-EEG source imaging with simultaneous SEEG recording in drug-resistant epilepsy.

Objective: This study aimed to assess the complementary role of high-density electroencephalography (HD-EEG)-based electrical source imaging (ESI) in localizing the seizure-onset zone (SOZ) during ictal events and the irritative zone (IZ) during the interictal period, using simultaneous acquired stereo-EEG (SEEG) recordings as a reference. In addition, we investigated the relationship of ictal cortical source activity with their scalp and intracranial EEG correlates, focusing on factors influencing ESI accuracy.

Methods: We enrolled 29 patients with drug-resistant epilepsy who underwent simultaneous HD-EEG and SEEG recordings. ESI was performed on ictal and interictal discharges of HD-EEG identified via SEEG, and localization accuracy was assessed relative to SEEG-defined sources. A linear mixed-effects model was applied to examine the influence of source depth and spike power on ESI accuracy. Concordance between ictal ESI and SEEG localizations was analyzed, along with associations with post-surgical outcomes.

Results: Synchronized rhythmic discharges, ranging from 1.95 to 8.77 Hz (mean 5.34 ± 2.14 Hz), but not the low-amplitude fast rhythms in SEEG were mandatory as references for ictal ESI. Ictal ESI periods (14.07 ± 4.62 mm) demonstrated significantly better localization accuracy than interictal ESI periods (17.38 ± 4.16 mm), with a shorter Euclidean distance between ESI dipoles and SEEG contacts. Both ictal spike power and source depth significantly influenced ESI accuracy. Patients with superficial or high-power discharges showed more precise localization. Concordant ictal ESI and SEEG results predicted favorable surgical outcomes (p = .006, n = 28).

Significance: Ictal ESI provides superior localization performance compared to interictal ESI. SEEG-informed analysis of ictal scalp EEG provides critical insights into SOZ characteristics, including location, depth, and spatial complexity. Simultaneous HD-EEG and SEEG recordings enhance the understanding of epileptogenic networks and support surgical decision-making in drug-resistant epilepsy.