caa a22 4500 445847832 CHVBK 20180317145404.0 cr unu---uuuuu 170323e20110601xx s 000 0 eng 10.1007/s10548-011-0173-2 doi (NATIONALLICENCE)springer-10.1007/s10548-011-0173-2 Evaluation of Algorithms for Intracranial EEG (iEEG) Source Imaging of Extended Sources: Feasibility of Using iEEG Source Imaging for Localizing Epileptogenic Zones in Secondary Generalized Epilepsy [Elektronische Daten] [Jae-Hyun Cho, Seung Hong, Young-Jin Jung, Hoon-Chul Kang, Heung Kim, Minah Suh, Ki-Young Jung, Chang-Hwan Im] Precise identification of epileptogenic zones in patients with intractable drug-resistant epilepsy is critical for successful epilepsy surgery. Numerous source-imaging algorithms for localizing epileptogenic zones based on scalp electroencephalography (EEG) and magnetoencephalography (MEG) have been developed and validated in simulation and experimental studies. Recently, intracranial EEG (iEEG)-based imaging of epileptogenic sources has attracted interest as a promising tool for presurgical evaluation of epilepsy; however, most iEEG studies have focused on localization of epileptogenic zones in focal epilepsy. In the present study, we investigated whether iEEG source imaging is a useful supplementary tool for identifying extended epileptogenic sources in secondary generalized epilepsy such as Lennox-Gastaut syndrome (LGS). To this end, we applied four different cortical source imaging algorithms, namely minimum norm estimation (MNE), low-resolution electromagnetic tomography (LORETA), standardized LORETA (sLORETA), and L p-norm estimation (p=1.5, referred to as Lp1.5), to artificial iEEG datasets generated assuming various source sizes and locations. We also applied these four algorithms to clinical ictal iEEG recordings acquired from a pediatric patient with LGS. Interestingly, the traditional MNE algorithm outperformed the other imaging algorithms in most of our experiments, particularly in cases when larger-sized sources were activated. Although sLORETA outperformed both LORETA and Lp1.5, its performance was not as good as that of MNE. Compared to the other algorithms, the performance of Lp1.5 decayed most rapidly as the source size increased. Our findings suggest that iEEG source imaging using MNE is a promising auxiliary tool for the identification of epileptogenic zones in secondary generalized epilepsy. We anticipate that our results will provide useful guidelines for selection of an appropriate imaging algorithm for iEEG source imaging studies. Springer Science+Business Media, LLC, 2011 Cortical source imaging nationallicence Localization of epileptogenic zone nationallicence Lennox-Gastaut syndrome nationallicence Intracranial electroencephalography nationallicence Ictal epileptiform activity nationallicence Inverse problem nationallicence Cho Jae-Hyun Department of Biomedical Engineering, Yonsei University, Wonju, South Korea aut Hong Seung Department of Neurology, Samsung Medical Center, Sungkyunkwan University, Seoul, Korea aut Jung Young-Jin Department of Biomedical Engineering, Yonsei University, Wonju, South Korea aut Kang Hoon-Chul Department of Pediatrics, Yonsei University College of Medicine, Seoul, Korea aut Kim Heung Department of Pediatrics, Yonsei University College of Medicine, Seoul, Korea aut Suh Minah Department of Biological Science, Sungkyunkwan University, Suwon, Korea aut Jung Ki-Young Department of Neurology, Korea University College of Medicine, Seoul, Korea aut Im Chang-Hwan Department of Biomedical Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-gu, 133-791, Seoul, South Korea aut Brain Topography Springer US; http://www.springer-ny.com 24/2(2011-06-01), 91-104 0896-0267 24:2<91 2011 24 10548 https://doi.org/10.1007/s10548-011-0173-2 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10548-011-0173-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Cho Jae-Hyun Department of Biomedical Engineering, Yonsei University, Wonju, South Korea aut NATIONALLICENCE 700 1- Hong Seung Department of Neurology, Samsung Medical Center, Sungkyunkwan University, Seoul, Korea aut NATIONALLICENCE 700 1- Jung Young-Jin Department of Biomedical Engineering, Yonsei University, Wonju, South Korea aut NATIONALLICENCE 700 1- Kang Hoon-Chul Department of Pediatrics, Yonsei University College of Medicine, Seoul, Korea aut NATIONALLICENCE 700 1- Kim Heung Department of Pediatrics, Yonsei University College of Medicine, Seoul, Korea aut NATIONALLICENCE 700 1- Suh Minah Department of Biological Science, Sungkyunkwan University, Suwon, Korea aut NATIONALLICENCE 700 1- Jung Ki-Young Department of Neurology, Korea University College of Medicine, Seoul, Korea aut NATIONALLICENCE 700 1- Im Chang-Hwan Department of Biomedical Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-gu, 133-791, Seoul, South Korea aut NATIONALLICENCE 773 0- Brain Topography Springer US; http://www.springer-ny.com 24/2(2011-06-01), 91-104 0896-0267 24:2<91 2011 24 10548 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer