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Afnan J, Cai Z, Lina JM, Abdallah C, Delaire E, Avigdor T, Ros V, Hedrich T, von Ellenrieder N, Kobayashi E, Frauscher B, Gotman J, Grova C. EEG/MEG source imaging of deep brain activity within the maximum entropy on the mean framework: Simulations and validation in epilepsy. Hum Brain Mapp 2024; 45:e26720. [PMID: 38994740 PMCID: PMC11240147 DOI: 10.1002/hbm.26720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 04/16/2024] [Accepted: 05/06/2024] [Indexed: 07/13/2024] Open
Abstract
Electro/Magneto-EncephaloGraphy (EEG/MEG) source imaging (EMSI) of epileptic activity from deep generators is often challenging due to the higher sensitivity of EEG/MEG to superficial regions and to the spatial configuration of subcortical structures. We previously demonstrated the ability of the coherent Maximum Entropy on the Mean (cMEM) method to accurately localize the superficial cortical generators and their spatial extent. Here, we propose a depth-weighted adaptation of cMEM to localize deep generators more accurately. These methods were evaluated using realistic MEG/high-density EEG (HD-EEG) simulations of epileptic activity and actual MEG/HD-EEG recordings from patients with focal epilepsy. We incorporated depth-weighting within the MEM framework to compensate for its preference for superficial generators. We also included a mesh of both hippocampi, as an additional deep structure in the source model. We generated 5400 realistic simulations of interictal epileptic discharges for MEG and HD-EEG involving a wide range of spatial extents and signal-to-noise ratio (SNR) levels, before investigating EMSI on clinical HD-EEG in 16 patients and MEG in 14 patients. Clinical interictal epileptic discharges were marked by visual inspection. We applied three EMSI methods: cMEM, depth-weighted cMEM and depth-weighted minimum norm estimate (MNE). The ground truth was defined as the true simulated generator or as a drawn region based on clinical information available for patients. For deep sources, depth-weighted cMEM improved the localization when compared to cMEM and depth-weighted MNE, whereas depth-weighted cMEM did not deteriorate localization accuracy for superficial regions. For patients' data, we observed improvement in localization for deep sources, especially for the patients with mesial temporal epilepsy, for which cMEM failed to reconstruct the initial generator in the hippocampus. Depth weighting was more crucial for MEG (gradiometers) than for HD-EEG. Similar findings were found when considering depth weighting for the wavelet extension of MEM. In conclusion, depth-weighted cMEM improved the localization of deep sources without or with minimal deterioration of the localization of the superficial sources. This was demonstrated using extensive simulations with MEG and HD-EEG and clinical MEG and HD-EEG for epilepsy patients.
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Affiliation(s)
- Jawata Afnan
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
- Integrated Program in Neuroscience, McGill University, Montréal, Québec, Canada
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Zhengchen Cai
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Jean-Marc Lina
- Physnum Team, Centre De Recherches Mathématiques, Montréal, Québec, Canada
- Electrical Engineering Department, École De Technologie Supérieure, Montréal, Québec, Canada
- Center for Advanced Research in Sleep Medicine, Sacré-Coeur Hospital, Montréal, Québec, Canada
| | - Chifaou Abdallah
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
- Integrated Program in Neuroscience, McGill University, Montréal, Québec, Canada
- Analytical Neurophysiology Lab, Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Edouard Delaire
- Multimodal Functional Imaging Lab, Department of Physics and Concordia School of Health, Concordia University, Montréal, Québec, Canada
| | - Tamir Avigdor
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
- Integrated Program in Neuroscience, McGill University, Montréal, Québec, Canada
- Analytical Neurophysiology Lab, Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Victoria Ros
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Tanguy Hedrich
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
| | - Nicolas von Ellenrieder
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Eliane Kobayashi
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
- Analytical Neurophysiology Lab, Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Jean Gotman
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Christophe Grova
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
- Physnum Team, Centre De Recherches Mathématiques, Montréal, Québec, Canada
- Multimodal Functional Imaging Lab, Department of Physics and Concordia School of Health, Concordia University, Montréal, Québec, Canada
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Tao X, Gao D, Zhang W, Liu T, Du B, Zhang S, Qin Y. A multimodal physiological dataset for driving behaviour analysis. Sci Data 2024; 11:378. [PMID: 38609440 PMCID: PMC11014944 DOI: 10.1038/s41597-024-03222-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 04/03/2024] [Indexed: 04/14/2024] Open
Abstract
Physiological signal monitoring and driver behavior analysis have gained increasing attention in both fundamental research and applied research. This study involved the analysis of driving behavior using multimodal physiological data collected from 35 participants. The data included 59-channel EEG, single-channel ECG, 4-channel EMG, single-channel GSR, and eye movement data obtained via a six-degree-of-freedom driving simulator. We categorized driving behavior into five groups: smooth driving, acceleration, deceleration, lane changing, and turning. Through extensive experiments, we confirmed that both physiological and vehicle data met the requirements. Subsequently, we developed classification models, including linear discriminant analysis (LDA), MMPNet, and EEGNet, to demonstrate the correlation between physiological data and driving behaviors. Notably, we propose a multimodal physiological dataset for analyzing driving behavior(MPDB). The MPDB dataset's scale, accuracy, and multimodality provide unprecedented opportunities for researchers in the autonomous driving field and beyond. With this dataset, we will contribute to the field of traffic psychology and behavior.
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Affiliation(s)
- Xiaoming Tao
- Tsinghua University, Department of Electronic Engineering, Beijing, 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), 100084, Beijing, China
| | - Dingcheng Gao
- Tsinghua University, Department of Electronic Engineering, Beijing, 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), 100084, Beijing, China
| | - Wenqi Zhang
- Tsinghua University, Department of Electronic Engineering, Beijing, 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), 100084, Beijing, China
| | - Tianqi Liu
- Tsinghua University, Department of Electronic Engineering, Beijing, 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), 100084, Beijing, China
| | - Bing Du
- University of Science and Technology Beijing, School of Computer and Communication Engineering, Beijing, 100083, China
| | - Shanghang Zhang
- National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, 100871, China
| | - Yanjun Qin
- Tsinghua University, Department of Electronic Engineering, Beijing, 100084, China.
- Beijing National Research Center for Information Science and Technology (BNRist), 100084, Beijing, China.
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Okamura A, Iida K, Hashizume A, Kagawa K, Seyama G, Horie N. Magnetoencephalographic spikes with small spikes on simultaneous electroencephalography have high spatial clustering in temporal lobe epilepsy. Epilepsy Res 2023; 192:107127. [PMID: 36963303 DOI: 10.1016/j.eplepsyres.2023.107127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 03/06/2023] [Accepted: 03/16/2023] [Indexed: 03/26/2023]
Abstract
OBJECTIVE To classify magnetoencephalographic (MEG) spikes according to the findings of simultaneous scalp electroencephalography (EEG) to study dipole estimation in patients with temporal lobe epilepsy. METHODS We analyzed MEG and simultaneous scalp EEG in 27 patients with intractable temporal lobe epilepsy. We classified MEG spikes into three groups (H-EM-spikes, L-EM-spikes, M-spikes) based on the amplitude of simultaneous EEG (50 μV or higher, lower than 50 μV, no spike morphology on EEG, respectively). We calculated parameters of the dipoles, such as goodness of fit (GOF), current moment, and location. RESULTS We detected 707 MEG spikes, consisting of 175 H-EM-spikes, 245 L-EM-spikes, and 287 M-spikes. Dipoles of H-EM-spikes showed the highest current moment among the three spike groups. Dipoles of L-EM-spikes showed the highest GOF, a moderate current moment, the highest density to cluster, and the highest proportion of being located in the temporal lobe among the three groups. Dipoles of M-spikes showed the lowest GOF and current moment among the three groups. CONCLUSIONS The characteristics of the dipoles of the MEG spikes differ depending on the simultaneous scalp EEG findings, though most of the MEG spikes were located in the temporal lobe. MEG spikes with concurrent small spikes on simultaneous scalp EEG may have higher spatial clustering in temporal lobe epilepsy.
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Affiliation(s)
- Akitake Okamura
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan; Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan
| | - Koji Iida
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan; Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan.
| | - Akira Hashizume
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan; Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan
| | - Kota Kagawa
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan; Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan
| | - Go Seyama
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan; Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan
| | - Nobutaka Horie
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
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Insular Involvement in Cases of Epilepsy Surgery Failure. Brain Sci 2022; 12:brainsci12020125. [PMID: 35203889 PMCID: PMC8870364 DOI: 10.3390/brainsci12020125] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 01/14/2022] [Accepted: 01/16/2022] [Indexed: 02/01/2023] Open
Abstract
Background: Epilepsy surgery failure is not uncommon, with several explanations having been proposed. In this series, we detail cases of epilepsy surgery failure subsequently attributed to insular involvement. Methods: We retrospectively identified patients investigated at the epilepsy monitoring units of two Canadian tertiary care centers (2004–2020). Included patients were adults who had undergone epilepsy surgeries with recurrence of seizures post-operatively and who were subsequently determined to have an insular epileptogenic focus. Clinical, electrophysiological, neuroimaging, and surgical data were synthesized. Results: We present 14 patients who demonstrated insular epileptic activity post-surgery-failure as detected by intracranial EEG, MEG, or seizure improvement after insular resection. Seven patients had manifestations evoking possible insular involvement prior to their first surgery. Most patients (8/14) had initial surgeries targeting the temporal lobe. Seizure recurrence ranged from the immediate post-operative period to one year. The main modality used to determine insular involvement was MEG (8/14). Nine patients underwent re-operations that included insular resection; seven achieved a favorable post-operative outcome (Engel I or II). Conclusions: Our series suggests that lowering the threshold for suspecting insular epilepsy may be necessary to improve epilepsy surgery outcomes. Detecting insular epilepsy post-surgery-failure may allow for re-operations which may lead to good outcomes.
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Iachim E, Vespa S, Baroumand AG, Danthine V, Vrielynck P, de Tourtchaninoff M, Fierain A, Ribeiro Vaz JG, Raftopoulos C, Ferrao Santos S, van Mierlo P, El Tahry R. Automated electrical source imaging with scalp EEG to define the insular irritative zone: Comparison with simultaneous intracranial EEG. Clin Neurophysiol 2021; 132:2965-2978. [PMID: 34715421 DOI: 10.1016/j.clinph.2021.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 08/13/2021] [Accepted: 09/16/2021] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To evaluate the accuracy of automatedinterictallow-density electrical source imaging (LD-ESI) to define the insular irritative zone (IZ) by comparing the simultaneous interictal ESI localization with the SEEG interictal activity. METHODS Long-term simultaneous scalp electroencephalography (EEG) and stereo-EEG (SEEG) with at least one depth electrode exploring the operculo-insular region(s) were analyzed. Automated interictal ESI was performed on the scalp EEG using standardized low-resolution brain electromagnetic tomography (sLORETA) and individual head models. A two-step analysis was performed: i) sublobar concordance betweencluster-based ESI localization and SEEG-based IZ; ii) time-locked ESI-/SEEG analysis. Diagnostic accuracy values were calculated using SEEG as reference standard. Subgroup analysis wascarried out, based onthe involvement of insular contacts in the seizure onset and patterns of insular interictal activity. RESULTS Thirty patients were included in the study. ESI showed an overall accuracy of 53% (C.I. 29-76%). Sensitivity and specificity were calculated as 53% (C.I. 29-76%), 55% (C.I. 23-83%) respectively. Higher accuracy was found in patients with frequent and dominant interictal insular spikes. CONCLUSIONS LD-ESI defines with good accuracy the insular implication in the IZ, which is not possible with classical interictalscalpEEG interpretation. SIGNIFICANCE Automated LD-ESI may be a valuable additional tool to characterize the epileptogenic zone in epilepsies with suspected insular involvement.
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Affiliation(s)
- Evelina Iachim
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania; Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Simone Vespa
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium.
| | - Amir G Baroumand
- Medical Image and Signal Processing Group (MEDISIP), Department of Electronics and Information Systems, Ghent University, Ghent, Belgium; Epilog NV, Ghent, Belgium
| | - Venethia Danthine
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium
| | - Pascal Vrielynck
- Epileptology and Clinical Neurophysiology, Centre Neurologique William Lennox, Ottignies, Belgium
| | - Marianne de Tourtchaninoff
- Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Alexane Fierain
- Epileptology and Clinical Neurophysiology, Centre Neurologique William Lennox, Ottignies, Belgium
| | - Jose Geraldo Ribeiro Vaz
- Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | | | - Susana Ferrao Santos
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium; Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Pieter van Mierlo
- Medical Image and Signal Processing Group (MEDISIP), Department of Electronics and Information Systems, Ghent University, Ghent, Belgium; Epilog NV, Ghent, Belgium
| | - Riëm El Tahry
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium; Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
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Bagić AI, Funke ME, Kirsch HE, Tenney JR, Zillgitt AJ, Burgess RC. The 10 Common Evidence-Supported Indications for MEG in Epilepsy Surgery: An Illustrated Compendium. J Clin Neurophysiol 2021; 37:483-497. [PMID: 33165222 DOI: 10.1097/wnp.0000000000000726] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Unfamiliarity with the indications for and benefits of magnetoencephalography (MEG) persists, even in the epilepsy community, and hinders its acceptance to clinical practice, despite the evidence. The wide treatment gap for patients with drug-resistant epilepsy and immense underutilization of epilepsy surgery had similar effects. Thus, educating referring physicians (epileptologists, neurologists, and neurosurgeons) both about the value of epilepsy surgery and about the potential benefits of MEG can achieve synergy and greatly improve the process of selecting surgical candidates. As a practical step toward a comprehensive educational process to benefit potential MEG users, current MEG referrers, and newcomers to MEG, the authors have elected to provide an illustrated guide to 10 everyday situations where MEG can help in the evaluation of people with drug-resistant epilepsy. They are as follows: (1) lacking or imprecise hypothesis regarding a seizure onset; (2) negative MRI with a mesial temporal onset suspected; (3) multiple lesions on MRI; (4) large lesion on MRI; (5) diagnostic or therapeutic reoperation; (6) ambiguous EEG findings suggestive of "bilateral" or "generalized" pattern; (7) intrasylvian onset suspected; (8) interhemispheric onset suspected; (9) insular onset suspected; and (10) negative (i.e., spikeless) EEG. Only their practical implementation and furtherance of personal and collective education will lead to the potentially impactful synergy of the two-MEG and epilepsy surgery. Thus, while fulfilling our mission as physicians, we must not forget that ignoring the wealth of evidence about the vast underutilization of epilepsy surgery - and about the usefulness and value of MEG in selecting surgical candidates - is far from benign neglect.
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Affiliation(s)
- Anto I Bagić
- University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), Department of Neurology, University of Pittsburgh Medical Center (UPMC), Pittsburgh, Pennsylvania, U.S.A
| | - Michael E Funke
- MEG Center, McGovern Medical School, UT Houston, Houston, Texas, U.S.A
| | - Heidi E Kirsch
- UCSF Biomagnetic Imaging Laboratory, UCSF, San Francisco, California, U.S.A
| | - Jeffrey R Tenney
- MEG Center, Cincinnati Children's Hospital Medical Center , Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, U.S.A
| | - Andrew J Zillgitt
- Department of Neurology, Beaumont Health Adult Comprehensive Epilepsy Center, Neurosicence Center, Royal Oak, Michigan, U.S.A.; and
| | - Richard C Burgess
- Magnetoencephalography Laboratory, Cleveland Clinic Epilepsy Center, Cleveland, Ohio, U.S.A
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Suhaimi NS, Mountstephens J, Teo J. EEG-Based Emotion Recognition: A State-of-the-Art Review of Current Trends and Opportunities. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2020; 2020:8875426. [PMID: 33014031 PMCID: PMC7516734 DOI: 10.1155/2020/8875426] [Citation(s) in RCA: 63] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 07/30/2020] [Accepted: 08/28/2020] [Indexed: 11/18/2022]
Abstract
Emotions are fundamental for human beings and play an important role in human cognition. Emotion is commonly associated with logical decision making, perception, human interaction, and to a certain extent, human intelligence itself. With the growing interest of the research community towards establishing some meaningful "emotional" interactions between humans and computers, the need for reliable and deployable solutions for the identification of human emotional states is required. Recent developments in using electroencephalography (EEG) for emotion recognition have garnered strong interest from the research community as the latest developments in consumer-grade wearable EEG solutions can provide a cheap, portable, and simple solution for identifying emotions. Since the last comprehensive review was conducted back from the years 2009 to 2016, this paper will update on the current progress of emotion recognition using EEG signals from 2016 to 2019. The focus on this state-of-the-art review focuses on the elements of emotion stimuli type and presentation approach, study size, EEG hardware, machine learning classifiers, and classification approach. From this state-of-the-art review, we suggest several future research opportunities including proposing a different approach in presenting the stimuli in the form of virtual reality (VR). To this end, an additional section devoted specifically to reviewing only VR studies within this research domain is presented as the motivation for this proposed new approach using VR as the stimuli presentation device. This review paper is intended to be useful for the research community working on emotion recognition using EEG signals as well as for those who are venturing into this field of research.
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Affiliation(s)
- Nazmi Sofian Suhaimi
- Faculty of Computing & Informatics, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu 88400, Sabah, Malaysia
| | - James Mountstephens
- Faculty of Computing & Informatics, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu 88400, Sabah, Malaysia
| | - Jason Teo
- Faculty of Computing & Informatics, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu 88400, Sabah, Malaysia
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Gonzalez-Martinez J. Epilepsy: Invasive Monitoring. Stereotact Funct Neurosurg 2020. [DOI: 10.1007/978-3-030-34906-6_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Alkawadri R, Burgess RC, Kakisaka Y, Mosher JC, Alexopoulos AV. Assessment of the Utility of Ictal Magnetoencephalography in the Localization of the Epileptic Seizure Onset Zone. JAMA Neurol 2019; 75:1264-1272. [PMID: 29889930 DOI: 10.1001/jamaneurol.2018.1430] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Importance Literature on ictal magnetoencephalography (MEG) in clinical practice and the relationship to other modalities is limited because of the brevity of routine studies. Objective To investigate the utility and reliability of ictal MEG in the localization of the epileptogenic zone. Design, Setting, and Participants A retrospective medical record review and prospective analysis of a novel ictal rhythm analysis method was conducted at a tertiary epilepsy center with a wide base of referrals for epilepsy surgery evaluation and included consecutive cases of patients who experienced epileptic seizures during routine MEG studies from March 2008 to February 2012. A total of 377 studies screened. Data were analyzed from November 2011 to October 2015. Main Outcomes and Measures Presurgical workup and interictal and ictal MEG data were reviewed. The localizing value of using extended-source localization of a narrow band identified visually at onset was analyzed. Results Of the 44 included patients, the mean (SD) age at the time of recording was 19.3 (14.9) years, and 25 (57%) were male. The mean duration of recording was 51.2 minutes. Seizures were provoked by known triggers in 3 patients and were spontaneous otherwise. Twenty-five patients (57%) had 1 seizure, 6 (14%) had 2, and 13 (30%) had 3 or more. Magnetoencephalography single equivalent current dipole analysis was possible in 29 patients (66%), of whom 8 (28%) had no clear interictal discharges. Sublobar concordance between ictal and interictal dipoles was seen in 18 of 21 patients (86%). Three patients (7%) showed clear ictal MEG patterns without electroencephalography changes. Ictal MEG dipoles correlated with the lobe of onset in 7 of 8 patients (88%) who underwent intracranial electroencephalography evaluations. Reasons for failure to identify ictal dipoles included diffuse or poor dipolar ictal patterns, no MEG changes, and movement artifact. Resection of areas containing a minimum-norm estimate of a narrow band at onset, not single equivalent current dipole, was associated with sustained seizure freedom. Conclusions and Significance Ictal MEG data can provide reliable localization, including in cases that are difficult to localize by other modalities. These findings support the use of extended-source localization for seizures recorded during MEG.
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Affiliation(s)
- Rafeed Alkawadri
- The Epilepsy Center at Cleveland Clinic Foundation, Cleveland, Ohio.,Yale Comprehensive Epilepsy Center, School of Medicine, Yale University, New Haven, Connecticut.,Yale Human Brain Mapping Program, School of Medicine, Yale University, New Haven, Connecticut
| | | | - Yosuke Kakisaka
- The Epilepsy Center at Cleveland Clinic Foundation, Cleveland, Ohio.,The Department of Pediatrics, Tohoku University School of Medicine, Sendai, Japan
| | - John C Mosher
- The Epilepsy Center at Cleveland Clinic Foundation, Cleveland, Ohio
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Sala-Padro J, Fong M, Rahman Z, Bartley M, Gill D, Dexter M, Bleasel A, Wong C. A study of perfusion changes with Insula Epilepsy using SPECT. Seizure 2019; 69:44-50. [PMID: 30974406 DOI: 10.1016/j.seizure.2019.03.021] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Revised: 03/12/2019] [Accepted: 03/27/2019] [Indexed: 11/28/2022] Open
Abstract
PURPOSE The non-invasive localisation of insular lobe epilepsy is a challenge. We aimed to determine if ictal SPECT is a reliable adjunctive test in insular cases and to explore its role in the tailoring of intracranial strategies. METHOD From a dataset of patients who underwent SEEG between December 2012 and December 2016, we collected patients with focal insular onset epilepsy. We examined semiology, EEG, PET and SPECT hyperperfusion pattern with SISCOM. We also reviewed relevant literature. RESULTS 5 patients were identified, 4 females, from a dataset of 51 patients. Median age of seizure onset was 8 years old (8 months to 10 years). All patients had an ictal SPECT during pre-surgical work-up: median injection time was 7 s (3-17 sec) from clinical onset, and median seizure duration was 42 s (11-85 sec). Insula cortex showed focal hyperaemia in four patients, all bilateral, with the greatest hyperperfusion contralateral to the ictal onset in two cases, using SISCOM threshold at 1.5 standard deviation. Other sites with hyperaemia included basal ganglia and middle temporal gyrus. The SEEG confirmed insular onset seizures in all the cases. All patients had epilepsy surgery and were seizure free at 21 to 50 months follow up. The results from the literature review showed frequent hyperperfusion in structures outside insula and frequently over the contralateral hemisphere. CONCLUSIONS This study highlights the technical limitations of SPECT when attempting to assess seizures arising from the insula. Our findings and the literature show ictal SPECT can be localising but falsely lateralising in seizures arising from the insula.
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Affiliation(s)
- Jacint Sala-Padro
- Epilepsy Unit, Department of Neurology, Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain.
| | - Michael Fong
- Epilepsy Unit, Department of Neurology, Westmead Hospital and Children's Hospital at Westmead, Hawkesbury Rd, Westmead, NSW, 2145, Australia
| | - Zebunnessa Rahman
- Epilepsy Unit, Department of Neurology, Westmead Hospital and Children's Hospital at Westmead, Hawkesbury Rd, Westmead, NSW, 2145, Australia; Westmead Clinical School, University of Sydney, Hawkesbury Rd, Westmead, NSW, 2145, Australia
| | - Melissa Bartley
- Epilepsy Unit, Department of Neurology, Westmead Hospital and Children's Hospital at Westmead, Hawkesbury Rd, Westmead, NSW, 2145, Australia
| | - Deepak Gill
- Epilepsy Unit, Department of Neurology, Westmead Hospital and Children's Hospital at Westmead, Hawkesbury Rd, Westmead, NSW, 2145, Australia; Westmead Clinical School, University of Sydney, Hawkesbury Rd, Westmead, NSW, 2145, Australia
| | - Mark Dexter
- Epilepsy Unit, Department of Neurology, Westmead Hospital and Children's Hospital at Westmead, Hawkesbury Rd, Westmead, NSW, 2145, Australia
| | - Andrew Bleasel
- Epilepsy Unit, Department of Neurology, Westmead Hospital and Children's Hospital at Westmead, Hawkesbury Rd, Westmead, NSW, 2145, Australia; Westmead Clinical School, University of Sydney, Hawkesbury Rd, Westmead, NSW, 2145, Australia
| | - Chong Wong
- Epilepsy Unit, Department of Neurology, Westmead Hospital and Children's Hospital at Westmead, Hawkesbury Rd, Westmead, NSW, 2145, Australia; Westmead Clinical School, University of Sydney, Hawkesbury Rd, Westmead, NSW, 2145, Australia
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Focal epilepsy without interictal spikes on scalp EEG: A common finding of uncertain significance. Epilepsy Res 2019; 150:1-6. [DOI: 10.1016/j.eplepsyres.2018.12.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 12/08/2018] [Accepted: 12/24/2018] [Indexed: 11/20/2022]
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Abstract
PURPOSE Most clinical magnetoencephalography (MEG) centers record both MEG and EEG, but model only MEG sources. This may be related to the belief that MEG spikes are more prevalent, MEG is more sensitive, or to proprietary software limitations. Biophysics would contend, however, that EEG, being sensitive to radial and tangential source orientations, would provide complementary data for analysis. METHODS We recorded 306 channels of MEG and 25 channels of EEG simultaneously in 297 consecutive patients over 3 years. We inspected the MEG and EEG recordings separately, identified spikes in both, determined whether their voltage and/or magnetometer magnetic fields were dipolar and thus model-worthy, and segregated them into types based on similar and distinct field topography. We placed for each patient their spike types into categories, including those with both a recognizable MEG and EEG signal and those with only an MEG and only an EEG signal. RESULTS Eighty-three percent of patients had spikes recorded, and these patients had an average of 2.7 spike types each. Fifty-six percent of spike types were present in both MEG and EEG. However, 36% of spike types were only evident in EEG, whereas 8% were noted in MEG alone. In 49% of patients with spikes, MEG review missed at least one spike type, whereas in 17% of patients, EEG review missed at least one spike type. CONCLUSIONS To obtain an optimal yield of diagnostic information, EEG should also be subjected to source analysis in any clinical MEG study. EEG and MEG data are indeed complementary.
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Yin C, Zhang X, Chen Z, Li X, Wu S, Lv P, Wang Y. Detection and localization of interictal ripples with magnetoencephalography in the presurgical evaluation of drug-resistant insular epilepsy. Brain Res 2018; 1706:147-156. [PMID: 30408475 DOI: 10.1016/j.brainres.2018.11.006] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Revised: 09/29/2018] [Accepted: 11/03/2018] [Indexed: 01/15/2023]
Abstract
Precise noninvasive presurgical localization of insular epilepsy is important. The objective of the present study was to detect and localize interictal high-frequency oscillations (HFOs) in patients with insular epilepsy at the source levels using magnetoencephalography (MEG). We investigated whether HFOs can delineate epileptogenic areas. We analysed MEG data with new accumulated source imaging (HFOs, 80-250 Hz ripples during spikes) and conventional dipole modelling (spikes) methods for localizing epileptic foci. We evaluated the relationship of the resection of focal brain regions containing interictal HFOs and the spikes with the postsurgical seizure outcome. Interictal HFOs were localized in the insular epileptogenic zone (EZ) in 18 out of 21 patients undergoing surgical treatment for clinically diagnosed insular epilepsy. While dipole clusters of spikes were involved in the insular EZ in 15 patients. Both the HFOs and the dipole cluster were localized in the insula in 14 patients. The seizure-free percentage was 87% for the resection of brain regions generating HFOs, whereas 80% for the resection of brain regions generating spikes. There was a much higher chance of freedom from seizures with complete resection of the HFO-generating regions than with partial resection or no resection (P = 0.031). No such difference was seen for spike-generating regions. Our results suggest that HFOs from insular epilepsy could be noninvasively detected and quantitatively assessed with MEG technology. MEG HFOs (ripples during spikes) may be valuable for the localization of the epileptogenic zone in insular epilepsy.
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Affiliation(s)
- Chunli Yin
- Department of Neurology, Hebei Medical University, Shijiazhuang 050017, China
| | - Xiating Zhang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Zheng Chen
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Xin Li
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Siqi Wu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China
| | - Peiyuan Lv
- Department of Neurology, Hebei Medical University, Shijiazhuang 050017, China; Department of Neurology, Hebei General Hospital, Shijiazhuang 050051, China.
| | - Yuping Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Beijing Key Laboratory of Neuromodulation, Beijing 100053, China; Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing 100053, China.
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The role of magnetoencephalography in the presurgical evaluation of patients with MRI-negative operculo-insular epilepsy. Seizure 2018; 61:104-110. [DOI: 10.1016/j.seizure.2018.07.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Revised: 06/30/2018] [Accepted: 07/08/2018] [Indexed: 10/28/2022] Open
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Diagnostic evaluation and surgical management of pediatric insular epilepsy utilizing magnetoencephalography and invasive EEG monitoring. Epilepsy Res 2018; 140:72-81. [DOI: 10.1016/j.eplepsyres.2017.12.011] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2017] [Revised: 11/28/2017] [Accepted: 12/11/2017] [Indexed: 11/21/2022]
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MEG May Reveal Hidden Population of Spikes in Epilepsy With Porencephalic Cyst/Encephalomalacia. J Clin Neurophysiol 2017; 34:546-549. [DOI: 10.1097/wnp.0000000000000362] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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Zerouali Y, Pouliot P, Robert M, Mohamed I, Bouthillier A, Lesage F, Nguyen DK. Magnetoencephalographic signatures of insular epileptic spikes based on functional connectivity. Hum Brain Mapp 2016; 37:3250-61. [PMID: 27220112 DOI: 10.1002/hbm.23238] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2015] [Revised: 04/19/2016] [Accepted: 04/21/2016] [Indexed: 11/10/2022] Open
Abstract
Failure to recognize insular cortex seizures has recently been identified as a cause of epilepsy surgeries targeting the temporal, parietal, or frontal lobe. Such failures are partly due to the fact that current noninvasive localization techniques fare poorly in recognizing insular epileptic foci. Our group recently demonstrated that magnetoencephalography (MEG) is sensitive to epileptiform spikes generated by the insula. In this study, we assessed the potential of distributed source imaging and functional connectivity analyses to distinguish insular networks underlying the generation of spikes. Nineteen patients with operculo-insular epilepsy were investigated. Each patient underwent MEG as well as T1-weighted magnetic resonance imaging (MRI) as part of their standard presurgical evaluation. Cortical sources of MEG spikes were reconstructed with the maximum entropy on the mean algorithm, and their time courses served to analyze source functional connectivity. The results indicate that the anterior and posterior subregions of the insula have specific patterns of functional connectivity mainly involving frontal and parietal regions, respectively. In addition, while their connectivity patterns are qualitatively similar during rest and during spikes, couplings within these networks are much stronger during spikes. These results show that MEG can establish functional connectivity-based signatures that could help in the diagnosis of different subtypes of insular cortex epilepsy. Hum Brain Mapp 37:3250-3261, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Younes Zerouali
- Département De Génie Électrique, École Polytechnique De Montréal, Montreal, Quebec, Canada.,Research Centre, Centre Hospitalier De L'Université De Montréal (CRCHUM), Montreal, Quebec, Canada
| | - Philippe Pouliot
- Département De Génie Électrique, École Polytechnique De Montréal, Montreal, Quebec, Canada.,Institut De Cardiologie De Montréal, Montreal, Quebec, Canada
| | - Manon Robert
- Research Centre, Centre Hospitalier De L'Université De Montréal (CRCHUM), Montreal, Quebec, Canada
| | - Ismail Mohamed
- Division of Neurology, Department of Pediatrics, IWK Health Centre, Halifax, Nova Scotia, Canada
| | - Alain Bouthillier
- Research Centre, Centre Hospitalier De L'Université De Montréal (CRCHUM), Montreal, Quebec, Canada
| | - Frédéric Lesage
- Département De Génie Électrique, École Polytechnique De Montréal, Montreal, Quebec, Canada.,Institut De Cardiologie De Montréal, Montreal, Quebec, Canada
| | - Dang K Nguyen
- Research Centre, Centre Hospitalier De L'Université De Montréal (CRCHUM), Montreal, Quebec, Canada.,Division of Neurology, Department of Medicine, CHUM - Hôpital Notre-Dame, Montreal, Quebec, Canada
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MEG-EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy. Brain Topogr 2015; 28:785-812. [PMID: 26016950 PMCID: PMC4600479 DOI: 10.1007/s10548-015-0437-3] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2014] [Accepted: 05/04/2015] [Indexed: 11/26/2022]
Abstract
The purpose of this study is to develop and quantitatively assess whether fusion of EEG and MEG (MEEG) data within the maximum entropy on the mean (MEM) framework increases the spatial accuracy of source localization, by yielding better recovery of the spatial extent and propagation pathway of the underlying generators of inter-ictal epileptic discharges (IEDs). The key element in this study is the integration of the complementary information from EEG and MEG data within the MEM framework. MEEG was compared with EEG and MEG when localizing single transient IEDs. The fusion approach was evaluated using realistic simulation models involving one or two spatially extended sources mimicking propagation patterns of IEDs. We also assessed the impact of the number of EEG electrodes required for an efficient EEG–MEG fusion. MEM was compared with minimum norm estimate, dynamic statistical parametric mapping, and standardized low-resolution electromagnetic tomography. The fusion approach was finally assessed on real epileptic data recorded from two patients showing IEDs simultaneously in EEG and MEG. Overall the localization of MEEG data using MEM provided better recovery of the source spatial extent, more sensitivity to the source depth and more accurate detection of the onset and propagation of IEDs than EEG or MEG alone. MEM was more accurate than the other methods. MEEG proved more robust than EEG and MEG for single IED localization in low signal-to-noise ratio conditions. We also showed that only few EEG electrodes are required to bring additional relevant information to MEG during MEM fusion.
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Mohamed IS, Gibbs SA, Robert M, Bouthillier A, Leroux JM, Khoa Nguyen D. The utility of magnetoencephalography in the presurgical evaluation of refractory insular epilepsy. Epilepsia 2013; 54:1950-9. [DOI: 10.1111/epi.12376] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/13/2013] [Indexed: 11/28/2022]
Affiliation(s)
- Ismail S. Mohamed
- Division of Neurology; Department of Pediatrics; IIWK Health Center; Halifax NS Canada
| | - Steve A. Gibbs
- Division of Neurology; Notre-Dame Hospital (CHUM); University of Montreal; Montreal QC Canada
| | - Manon Robert
- Department of Psychology; Neuropsychology and Cognition Research Center; University of Montreal, Montreal; QC Canada
| | - Alain Bouthillier
- Division of Neurosurgery; Notre-Dame Hospital (CHUM); University of Montreal, Montreal; QC Canada
| | - Jean-Maxime Leroux
- Department of Radiology; Notre-Dame Hospital (CHUM); University of Montreal, Montreal; QC Canada
| | - Dang Khoa Nguyen
- Division of Neurology; Notre-Dame Hospital (CHUM); University of Montreal; Montreal QC Canada
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