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Poghosyan V, Algethami H, Alshahrani A, Asiri S, Aldosari MM. Association Between Magnetoencephalography-Localized Epileptogenic Zone, Surgical Resection Volume, and Postsurgical Seizure Outcome. J Clin Neurophysiol 2025; 42:73-80. [PMID: 38194636 DOI: 10.1097/wnp.0000000000001069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2024] Open
Abstract
PURPOSE Surgical resection of magnetoencephalography (MEG) dipole clusters, reconstructed from interictal epileptiform discharges, is associated with favorable seizure outcomes. However, the relation of MEG cluster resection to the surgical resection volume is not known nor is it clear whether this association is direct and causal, or it may be mediated by the resection volume or other predictive factors. This study aims to clarify these open questions and assess the diagnostic accuracy of MEG in our center. METHODS We performed a retrospective cohort study of 68 patients with drug-resistant epilepsy who underwent MEG followed by resective epilepsy surgery and had at least 12 months of postsurgical follow-up. RESULTS Good seizure outcomes were associated with monofocal localization (χ 2 = 6.94, P = 0.001; diagnostic odds ratio = 10.2) and complete resection of MEG clusters (χ 2 = 22.1, P < 0.001; diagnostic odds ratio = 42.5). Resection volumes in patients with and without removal of MEG clusters were not significantly different ( t = 0.18, P = 0.86; removed: M = 20,118 mm 3 , SD = 10,257; not removed: M = 19,566 mm 3 , SD = 10,703). Logistic regression showed that removal of MEG clusters predicts seizure-free outcome independent of the resection volume and other prognostic factors ( P < 0.001). CONCLUSIONS Complete resection of MEG clusters leads to favorable seizure outcomes without affecting the volume of surgical resection and independent of other prognostic factors. MEG can localize the epileptogenic zone with high accuracy. MEG interictal epileptiform discharges mapping should be used whenever feasible to improve postsurgical seizure outcomes.
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Affiliation(s)
- Vahe Poghosyan
- Department of Neurophysiology, National Neuroscience Institute, King Fahad Medical City, Riyadh, K.S.A.; and
| | - Hanin Algethami
- Department of Neurology, National Neuroscience Institute, King Fahad Medical City, Riyadh, K.S.A
| | - Ashwaq Alshahrani
- Department of Neurology, National Neuroscience Institute, King Fahad Medical City, Riyadh, K.S.A
| | - Safiyyah Asiri
- Department of Neurology, National Neuroscience Institute, King Fahad Medical City, Riyadh, K.S.A
| | - Mubarak M Aldosari
- Department of Neurology, National Neuroscience Institute, King Fahad Medical City, Riyadh, K.S.A
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Handiru VS, Selvan Suviseshamuthu E, Yue G, Allexandre D. Robust k-means-based Clustering of Independent Components Estimated from the EEG data. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2024; 2024:1-4. [PMID: 40039423 DOI: 10.1109/embc53108.2024.10782864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2025]
Abstract
In this study, we present a comprehensive investigation into the robust clustering of independent components (ICs) related to anticipatory postural control tasks in individuals with traumatic brain injury (TBI) using EEG data. Given the significance of accurately clustering the neural sources, our research evaluates the performance of various k-means clustering algorithms, including traditional, our modified approach of repeated k-means, and global k-means. This study aims to identify the optimal clustering approach that accurately locates the cortical sources germane to balance dysfunction and is computationally efficient. Our results highlight the superior performance of the global k-means algorithm in terms of clustering quality and computational runtime, demonstrating its application in a real-world dataset with noise.
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Mohanty D, Quach M. The Noninvasive Evaluation for Minimally Invasive Pediatric Epilepsy Surgery (MIPES): A Multimodal Exploration of the Localization-Based Hypothesis. JOURNAL OF PEDIATRIC EPILEPSY 2022. [DOI: 10.1055/s-0042-1760104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
AbstractMinimally invasive pediatric epilepsy surgery (MIPES) is a rising technique in the management of focal-onset drug-refractory epilepsy. Minimally invasive surgical techniques are based on small, focal interventions (such as parenchymal ablation or localized neuromodulation) leading to elimination of the seizure onset zone or interruption of the larger epileptic network. Precise localization of the seizure onset zone, demarcation of eloquent cortex, and mapping of the network leading to seizure propagation are required to achieve optimal outcomes. The toolbox for presurgical, noninvasive evaluation of focal epilepsy continues to expand rapidly, with a variety of options based on advanced imaging and electrophysiology. In this article, we will examine several of these diagnostic modalities from the standpoint of MIPES and discuss how each can contribute to the development of a localization-based hypothesis for potential surgical targets.
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Affiliation(s)
- Deepankar Mohanty
- Section of Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas
| | - Michael Quach
- Section of Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas
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Ntolkeras G, Tamilia E, AlHilani M, Bolton J, Ellen Grant P, Prabhu SP, Madsen JR, Stufflebeam SM, Pearl PL, Papadelis C. Presurgical accuracy of dipole clustering in MRI-negative pediatric patients with epilepsy: Validation against intracranial EEG and resection. Clin Neurophysiol 2022; 141:126-138. [PMID: 33875376 PMCID: PMC8803140 DOI: 10.1016/j.clinph.2021.01.036] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 01/21/2021] [Accepted: 01/27/2021] [Indexed: 01/24/2023]
Abstract
OBJECTIVE To assess the utility of interictal magnetic and electric source imaging (MSI and ESI) using dipole clustering in magnetic resonance imaging (MRI)-negative patients with drug resistant epilepsy (DRE). METHODS We localized spikes in low-density (LD-EEG) and high-density (HD-EEG) electroencephalography as well as magnetoencephalography (MEG) recordings using dipoles from 11 pediatric patients. We computed each dipole's level of clustering and used it to discriminate between clustered and scattered dipoles. For each dipole, we computed the distance from seizure onset zone (SOZ) and irritative zone (IZ) defined by intracranial EEG. Finally, we assessed whether dipoles proximity to resection was predictive of outcome. RESULTS LD-EEG had lower clusterness compared to HD-EEG and MEG (p < 0.05). For all modalities, clustered dipoles showed higher proximity to SOZ and IZ than scattered (p < 0.001). Resection percentage was higher in optimal vs. suboptimal outcome patients (p < 0.001); their proximity to resection was correlated to outcome (p < 0.001). No difference in resection percentage was seen for scattered dipoles between groups. CONCLUSION MSI and ESI dipole clustering helps to localize the SOZ and IZ and facilitate the prognostic assessment of MRI-negative patients with DRE. SIGNIFICANCE Assessing the MSI and ESI clustering allows recognizing epileptogenic areas whose removal is associated with optimal outcome.
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Affiliation(s)
- Georgios Ntolkeras
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Eleonora Tamilia
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michel AlHilani
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; The Hillingdon Hospital NHS Foundation Trust, London, United Kingdom
| | - Jeffrey Bolton
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - P Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Division of Neuroradiology, Department of Radiology, Boston Children's Hospital, Harvard Medical School, MA, USA
| | - Sanjay P Prabhu
- Division of Neuroradiology, Department of Radiology, Boston Children's Hospital, Harvard Medical School, MA, USA
| | - Joseph R Madsen
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Steven M Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Phillip L Pearl
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Christos Papadelis
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA; School of Medicine, Texas Christian University and University of North Texas Health Science Center, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA.
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Fujiwara H, Kadis DS, Greiner HM, Holland KD, Arya R, Aungaroon G, Fong SL, Arthur TM, Kremer KM, Lin N, Liu W, Mangano DO FT, Skoch J, Horn PS, Tenney JR. Clinical validation of magnetoencephalography network analysis for presurgical epilepsy evaluation. Clin Neurophysiol 2022; 142:199-208. [DOI: 10.1016/j.clinph.2022.07.506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 06/29/2022] [Accepted: 07/20/2022] [Indexed: 11/27/2022]
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Laohathai C, Ebersole JS, Mosher JC, Bagić AI, Sumida A, Von Allmen G, Funke ME. Practical Fundamentals of Clinical MEG Interpretation in Epilepsy. Front Neurol 2021; 12:722986. [PMID: 34721261 PMCID: PMC8551575 DOI: 10.3389/fneur.2021.722986] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 09/06/2021] [Indexed: 11/29/2022] Open
Abstract
Magnetoencephalography (MEG) is a neurophysiologic test that offers a functional localization of epileptic sources in patients considered for epilepsy surgery. The understanding of clinical MEG concepts, and the interpretation of these clinical studies, are very involving processes that demand both clinical and procedural expertise. One of the major obstacles in acquiring necessary proficiency is the scarcity of fundamental clinical literature. To fill this knowledge gap, this review aims to explain the basic practical concepts of clinical MEG relevant to epilepsy with an emphasis on single equivalent dipole (sECD), which is one the most clinically validated and ubiquitously used source localization method, and illustrate and explain the regional topology and source dynamics relevant for clinical interpretation of MEG-EEG.
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Affiliation(s)
- Christopher Laohathai
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School at UTHealth, Houston, TX, United States
- Department of Neurology, Saint Louis University, Saint Louis, MO, United States
| | - John S. Ebersole
- Northeast Regional Epilepsy Group, Atlantic Health Neuroscience Institute, Summit, NJ, United States
| | - John C. Mosher
- Department of Neurology, McGovern Medical School at UTHealth, Houston, TX, United States
| | - Anto I. Bagić
- University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), Department of Neurology, University of Pittsburgh Medical Center, Pittsburg, PA, United States
| | - Ai Sumida
- Department of Neurology, McGovern Medical School at UTHealth, Houston, TX, United States
| | - Gretchen Von Allmen
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School at UTHealth, Houston, TX, United States
| | - Michael E. Funke
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School at UTHealth, Houston, TX, United States
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Starnes K, Depositario-Cabacar D, Wong-Kisiel L. Presurgical Evaluation Strategies for Intractable Epilepsy of Childhood. Semin Pediatr Neurol 2021; 39:100915. [PMID: 34620457 DOI: 10.1016/j.spen.2021.100915] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Revised: 08/11/2021] [Accepted: 08/11/2021] [Indexed: 11/29/2022]
Abstract
For children who continue to experience seizures despite treatment with antiseizure medications, epilepsy surgery can be considered. The goals of the presurgical evaluation are to determine the best surgical approach to render a good outcome. In patients with drug resistant focal epilepsy, the epileptogenic zone defines the minimal brain volume which must be resected for surgical success and to delineate the relationship of this region with functional cortex. A number of noninvasive tools for these tasks have emerged over the past decade, and existing technologies have been revised and improved. In this review, we examine the recent published evidence for these techniques, specifically as applied to the pediatric population. Discussed herein are the diagnostic value of methods such as video electroencephalography, magnetic resonance imaging, and supportive neuroimaging techniques including single photon emission tomography, photon emission tomography, and magnetoencephalography. Functional testing including functional magnetic resonance imaging, electrical stimulation mapping, and transcranial magnetic stimulation are considered in the context of pediatric epilepsy. The application of emerging techniques to preoperative testing such as source localization, image post-processing, and artificial intelligence is covered. We summarize the relative value of presurgical testing based on patient characteristics, including lesional or nonlesional MRI, temporal or extratemporal epilepsy, and other factors relevant in pediatric epilepsy such as pathological substrate and age.
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Affiliation(s)
| | | | - Lily Wong-Kisiel
- Department of Neurology and Pediatrics, Mayo Clinic, Rochester, MN.
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Otsubo H, Ogawa H, Pang E, Wong SM, Ibrahim GM, Widjaja E. A review of magnetoencephalography use in pediatric epilepsy: an update on best practice. Expert Rev Neurother 2021; 21:1225-1240. [PMID: 33780318 DOI: 10.1080/14737175.2021.1910024] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Introduction: Magnetoencephalography (MEG) is a noninvasive technique that is used for presurgical evaluation of children with drug-resistant epilepsy (DRE).Areas covered: The contributions of MEG for localizing the epileptogenic zone are discussed, in particular in extra-temporal lobe epilepsy and focal cortical dysplasia, which are common in children, as well as in difficult to localize epilepsy such as operculo-insular epilepsy. Further, the authors review current evidence on MEG for mapping eloquent cortex, its performance, application in clinical practice, and potential challenges.Expert opinion: MEG could change the clinical management of children with DRE by directing placement of intracranial electrodes thereby enhancing their yield. With improved identification of a circumscribed epileptogenic zone, MEG could render more patients as suitable candidates for epilepsy surgery and increase utilization of surgery.
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Affiliation(s)
- Hiroshi Otsubo
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada
| | - Hiroshi Ogawa
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada
| | - Elizabeth Pang
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada.,Neuroscience and Mental Health, Hospital for Sick Children, Toronto, Canada
| | - Simeon M Wong
- Neuroscience and Mental Health, Hospital for Sick Children, Toronto, Canada
| | - George M Ibrahim
- Division of Neurosurgery, Hospital for Sick Children, Toronto, Canada.,Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada
| | - Elysa Widjaja
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada.,Neuroscience and Mental Health, Hospital for Sick Children, Toronto, Canada.,Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada
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Tamilia E, AlHilani M, Tanaka N, Tsuboyama M, Peters JM, Grant PE, Madsen JR, Stufflebeam SM, Pearl PL, Papadelis C. Assessing the localization accuracy and clinical utility of electric and magnetic source imaging in children with epilepsy. Clin Neurophysiol 2019; 130:491-504. [PMID: 30771726 DOI: 10.1016/j.clinph.2019.01.009] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 12/07/2018] [Accepted: 01/08/2019] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To evaluate the accuracy and clinical utility of conventional 21-channel EEG (conv-EEG), 72-channel high-density EEG (HD-EEG) and 306-channel MEG in localizing interictal epileptiform discharges (IEDs). METHODS Twenty-four children who underwent epilepsy surgery were studied. IEDs on conv-EEG, HD-EEG, MEG and intracranial EEG (iEEG) were localized using equivalent current dipoles and dynamical statistical parametric mapping (dSPM). We compared the localization error (ELoc) with respect to the ground-truth Irritative Zone (IZ), defined by iEEG sources, between non-invasive modalities and the distance from resection (Dres) between good- (Engel 1) and poor-outcomes. For each patient, we estimated the resection percentage of IED sources and tested whether it predicted outcome. RESULTS MEG presented lower ELoc than HD-EEG and conv-EEG. For all modalities, Dres was shorter in good-outcome than poor-outcome patients, but only the resection percentage of the ground-truth IZ and MEG-IZ predicted surgical outcome. CONCLUSIONS MEG localizes the IZ more accurately than conv-EEG and HD-EEG. MSI may help the presurgical evaluation in terms of patient's outcome prediction. The promising clinical value of ESI for both conv-EEG and HD-EEG prompts the use of higher-density EEG-systems to possibly achieve MEG performance. SIGNIFICANCE Localizing the IZ non-invasively with MSI/ESI facilitates presurgical evaluation and surgical prognosis assessment.
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Affiliation(s)
- Eleonora Tamilia
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michel AlHilani
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Naoaki Tanaka
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Sapporo Neuroimaging Research Group, Sapporo, Japan
| | - Melissa Tsuboyama
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jurriaan M Peters
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - P Ellen Grant
- Fetal-Neonatal Neuroimaging Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Joseph R Madsen
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, USA
| | - Steven M Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Phillip L Pearl
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Christos Papadelis
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
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