Clinical utility of distributed source modelling of interictal scalp EEG in focal epilepsy

Abstract

Assess the clinical utility of non-invasive distributed EEG source modelling in focal epilepsy. Interictal epileptiform discharges were recorded from eight patients - benign focal epilepsy of childhood (BFEC), four; mesial temporal lobe epilepsy (MTLE), four. EEG source localization (ESL) applied 48 forward-inverse-subspace set-ups: forward - standardized, leadfield-interpolated boundary element methods (BEMs, BEMi), finite element method (FEMi); inverse - minimum norm (MNLS), L1 norm (L1), low resolution electromagnetic tomography (LORETA), standardized LORETA (sLORETA); subspace- whole volume (3D), cortex with rotating sources (CxR), cortex with fixed sources (CxN), cortex with fixed extended sources (patch). Current density reconstruction (CDR) maxima defined 'best-fit'. From 19,200 CDR parameter results and 2304 CDR maps, the dominant variables on best-fit were inverse model and subspace constraint. The most clinically meaningful and statistically robust results came with sLORETA-CxR/patch (lower Rolandic in BFEC, basal temporal lobe in MTLE). Computation time was inverse model dependent: sub-second (MNLS, sLORETA), seconds (L1), minutes (LORETA). From the largest number of distributed ESL approaches compared in a clinical setting, an optimum modelling set-up for BFEC and MTLE incorporated sLORETA (inverse), CxR or patch (subspace), and either BEM or FEMi (forward). Computation is efficient and CDR results are reproducible. Distributed source modelling demonstrates clinical utility for the routine work-up of unilateral BFEC of the typical Rolandic variety, and unilateral MTLE secondary to hippocampal sclerosis.