OBJECTIVE: Assess the clinical utility of non-invasive distributed EEG source modelling in focal epilepsy. METHODS: 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'. RESULTS: 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). CONCLUSIONS: 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. SIGNIFICANCE: 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. Copyright 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
OBJECTIVE: Assess the clinical utility of non-invasive distributed EEG source modelling in focal epilepsy. METHODS: 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'. RESULTS: 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). CONCLUSIONS: 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. SIGNIFICANCE: 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. Copyright 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Authors: Kitti Kaiboriboon; Hans O Lüders; Mehdi Hamaneh; John Turnbull; Samden D Lhatoo Journal: Nat Rev Neurol Date: 2012-08-07 Impact factor: 42.937