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Thio BJ, Sinha N, Davis KA, Sinha SR, Grill WM. Stereo-EEG propagating source reconstruction identifies new surgical targets for epilepsy patients. Brain 2025; 148:764-775. [PMID: 40048618 DOI: 10.1093/brain/awae297] [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: 02/16/2024] [Revised: 07/25/2024] [Accepted: 08/23/2024] [Indexed: 03/18/2025] Open
Abstract
Epilepsy surgery can eliminate seizures in patients with drug-resistant focal epilepsy. Surgical intervention requires proper identification of the epileptic network and often involves implanting stereo-EEG electrodes in patients where non-invasive methods are insufficient. However, only ∼60% of patients achieve seizure-freedom following surgery. Quantitative methods have been developed to help improve surgical outcomes. However, previous quantitative methods that localized interictal spike and seizure activity using stereo-EEG recordings did not account for the propagation path encoded by the temporal dynamics of stereo-EEG recordings. Reconstructing the seizure propagation path can aid in determining whether a signal originated from the seizure onset or propagation zone, which directly informs treatment decisions. We developed a novel source reconstruction algorithm, Temporally Dependent Iterative Expansion (TEDIE), that accurately reconstructs propagating and expanding neural sources over time. TEDIE iteratively optimizes the number, location and size of neural sources to minimize the differences between the reconstructed and recorded stereo-EEG signals using temporal information to refine the reconstructions. The TEDIE output comprises a movie of seizure activity projected onto patient-specific brain anatomy. We analysed data from 46 epilepsy patients implanted with stereo-EEG electrodes at Duke Hospital (12 patients) and the Hospital of the University of Pennsylvania (34 patients). We reconstructed seizure recordings and found that TEDIE's seizure onset zone reconstructions were closer to the resected brain region for Engel 1 compared to Engel 2-4 patients, retrospectively validating the clinical utility of TEDIE. We also demonstrated that TEDIE has prospective clinical value, whereby metrics that can be determined presurgically accurately predict whether a patient would achieve seizure-freedom following surgery. Furthermore, we used TEDIE to delineate new potential surgical targets in 12/23 patients who are currently Engel 2-4. We validated TEDIE by accurately reconstructing various dynamic synthetic neural sources with known locations and sizes. TEDIE generated more accurate, focal and interpretable dynamic reconstructions of seizures compared to other algorithms (sLORETA and IRES). Our findings demonstrate that TEDIE is a promising clinical tool that can greatly improve epileptogenic zone localization and epilepsy surgery outcomes.
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Affiliation(s)
- Brandon J Thio
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Nishant Sinha
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Penn Epilepsy Center, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kathryn A Davis
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Penn Epilepsy Center, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Saurabh R Sinha
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Penn Epilepsy Center, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Warren M Grill
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
- Department of Electrical Engineering, Duke University, Durham, NC 27708, USA
- Department of Neurosurgery, Duke University, Durham, NC 27708, USA
- Department of Neurobiology, Duke University, Durham, NC 27708, USA
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Yu J, Li Y, Xie X, Cheng L, Zhu S, Sui L, Wu Y, Xie X, Xie H, Zhang X, Chen C, Liu Y. Outcome predictors in patients with temporal lobe epilepsy after temporal resective surgery. ACTA EPILEPTOLOGICA 2024; 6:43. [PMID: 40217443 PMCID: PMC11960222 DOI: 10.1186/s42494-024-00190-3] [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: 06/17/2024] [Accepted: 10/11/2024] [Indexed: 04/15/2025] Open
Abstract
BACKGROUND Temporal lobe epilepsy is one of the most common types of partial epilepsy. Although surgical treatment has led to significant improvements in seizure-free rates, nearly one-third of patients still have poor seizure control after surgery. Moreover, the long-term outcome is less favorable compared to short-term outcome, with 48-58% of patients experiencing seizures five years after surgery. The aim of this study was to investigate the surgical outcomes and the predictive value of prognostic factors associated with poor surgical outcomes in temporal lobe epilepsy patients receiving surgery. METHODS We retrospectively reviewed 94 patients undergoing temporal resective surgery in the Epilepsy Center of Guangdong Provincial Hospital of Traditional Chinese Medicine between July 2016 and July 2020. Patient information including age, gender, personal and family history, as well as preoperative and postoperative clinical data (clinical type and duration of disease) was collected. RESULTS The differences of postoperative clinical efficacy in both seizure free group and non-seizure free group patients were observed. A log-rank test was used for univariate analysis, and a Cox proportional hazard model was used for multivariate analysis. Ninety-four patients were followed up for at least 1 years. At 12 months of follow-up, 71 (75.5%) patients achieved Engel class I, 5 (5.3%) patients were classified as Engel class II, 5 (5.3%) patients were classified as Engel class III, and 13 (13.8%) patients were classified as Engel class IV. Univariate analysis and multivariate Cox regression analysis indicated that the postoperative EEG abnormalities were significantly correlated with seizure recurrence and were significant independent predictive factors, with a hazard ratio of 12.940. CONCLUSIONS The relapse rate in our study was similar to commonly reported overall rates in temporal lobe epilepsy patients receiving surgery. Anterior temporal lobectomy is a reliable treatment option for temporal lobe epilepsy patients. Postoperative electroencephalograph abnormalities are independent risk factors for poor surgical prognosis.
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Affiliation(s)
- Jiabin Yu
- Department of Epilepsy Center, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Yinchao Li
- Department of Neurology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 517108, Guangdong Province, China
| | - Xuan Xie
- Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Liming Cheng
- Brain Disease Function Department, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Shaofang Zhu
- Department of Epilepsy Center, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Lisen Sui
- Department of Epilepsy Center, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Youliang Wu
- Department of Epilepsy Center, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Xuemin Xie
- Department of Epilepsy Center, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Haitao Xie
- Department of Epilepsy Center, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Xiaojing Zhang
- Department of Epilepsy Center, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Chun Chen
- Brain Disease Function Department, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Yingying Liu
- Department of Neurology, Third Affiliated Hospital, Sun Yat-sen University, 600 Tianhe Road, Guangzhou, 510630, Guangdong, China.
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Aung T, Grinenko O, Li J, Mosher JC, Chauvel P, Gonzalez-Martinez J. Stereoelectroencephalography-guided laser ablation in neocortical epilepsy: Electrophysiological correlations and outcome. Epilepsia 2023; 64:2993-3012. [PMID: 37545378 DOI: 10.1111/epi.17739] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 08/03/2023] [Accepted: 08/04/2023] [Indexed: 08/08/2023]
Abstract
OBJECTIVE We aimed to study the correlation between seizure outcomes in patients with drug-resistant epilepsy (DRE) who underwent laser interstitial thermal therapy (LITT) and stereoelectroencephalographic electrophysiologic patterns with respect to the extent of laser ablation. METHODS We retrospectively analyzed 16 consecutive DRE patients who underwent LITT. A seizure onset zone (SOZ) was obtained from multidisciplinary patient management conferences and again was confirmed independently by two epileptologists based on conventional analysis. SOZs were retrospectively divided into localized, lobar and multilobar, and nonlocalized onset types. A posteriori-predicted epileptogenic zone (PEZ) was identified using the previously developed "EZ fingerprint" pipeline. The completeness of the SOZ and PEZ ablation was compared and correlated with the duration of seizure freedom (SF). RESULTS Of 16 patients, 11 had an a posteriori-identified PEZ. Three patients underwent complete ablation of SOZ with curative intent, and the other 13 with palliative intent. Of three patients with complete ablation of the SOZ, two had concordant PEZ and SOZ and achieved 40- and 46-month SF without seizure recurrence. The remaining patient, without any PEZ identified, had seizure recurrence within 1 month. Six of 13 patients with partial ablation of the SOZ and PEZ achieved mean seizure freedom of 19.8 months (range = 1-44) with subsequent seizure recurrence. The remaining seven patients had partial ablation of the SOZ without the PEZ identified or ablation outside the PEZ with seizure recurrence within 1-2 months, except one patient who had 40-month seizure freedom after ablation of periventricular heterotopia. SIGNIFICANCE Only complete ablation of the well-restricted SOZ concordant with the PEZ was associated with long-term SF, whereas partial ablation of the PEZ might lead to SF with eventual seizure recurrence. Failure to identify PEZ and ablation limited to the SOZ often led to 1-2 months of SF.
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Affiliation(s)
- Thandar Aung
- Department of Neurology, Epilepsy Center, Cleveland Clinic, Ohio, Cleveland, USA
- Department of Neurology, Epilepsy Center, University of Pittsburgh Medical Center, Pennsylvania, Pittsburgh, USA
| | - Olesya Grinenko
- Department of Neurology, Epilepsy Center, Cleveland Clinic, Ohio, Cleveland, USA
- Mercy Health Grand Rapids Medical Education, Michigan, Grand Rapids, USA
| | - Jian Li
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Massachusetts, Charlestown, USA
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Massachusetts, Boston, USA
| | - John C Mosher
- Department of Neurology, Texas Institute for Restorative Neurotechnologies, McGovern Medical School, University of Texas Health Science Center at Houston, Texas, Houston, USA
| | - Patrick Chauvel
- Department of Neurology, Epilepsy Center, Cleveland Clinic, Ohio, Cleveland, USA
- Department of Neurology, Epilepsy Center, University of Pittsburgh Medical Center, Pennsylvania, Pittsburgh, USA
| | - Jorge Gonzalez-Martinez
- Department of Neurology, Epilepsy Center, Cleveland Clinic, Ohio, Cleveland, USA
- Department of Neurology, Epilepsy Center, University of Pittsburgh Medical Center, Pennsylvania, Pittsburgh, USA
- Department of Neurosurgery, Epilepsy Center, University of Pittsburgh Medical Center, Pennsylvania, Pittsburgh, USA
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Merk T, Köhler R, Peterson V, Lyra L, Vanhoecke J, Chikermane M, Binns T, Li N, Walton A, Bush A, Sisterson N, Busch J, Lofredi R, Habets J, Huebl J, Zhu G, Yin Z, Zhao B, Merkl A, Bajbouj M, Krause P, Faust K, Schneider GH, Horn A, Zhang J, Kühn A, Richardson RM, Neumann WJ. Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants. RESEARCH SQUARE 2023:rs.3.rs-3212709. [PMID: 37790428 PMCID: PMC10543023 DOI: 10.21203/rs.3.rs-3212709/v1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Brain computer interfaces (BCI) provide unprecedented spatiotemporal precision that will enable significant expansion in how numerous brain disorders are treated. Decoding dynamic patient states from brain signals with machine learning is required to leverage this precision, but a standardized framework for identifying and advancing novel clinical BCI approaches does not exist. Here, we developed a platform that integrates brain signal decoding with connectomics and demonstrate its utility across 123 hours of invasively recorded brain data from 73 neurosurgical patients treated for movement disorders, depression and epilepsy. First, we introduce connectomics-informed movement decoders that generalize across cohorts with Parkinson's disease and epilepsy from the US, Europe and China. Next, we reveal network targets for emotion decoding in left prefrontal and cingulate circuits in DBS patients with major depression. Finally, we showcase opportunities to improve seizure detection in responsive neurostimulation for epilepsy. Our platform provides rapid, high-accuracy decoding for precision medicine approaches that can dynamically adapt neuromodulation therapies in response to the individual needs of patients.
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Soper DJ, Reich D, Ross A, Salami P, Cash SS, Basu I, Peled N, Paulk AC. Modular pipeline for reconstruction and localization of implanted intracranial ECoG and sEEG electrodes. PLoS One 2023; 18:e0287921. [PMID: 37418486 PMCID: PMC10328232 DOI: 10.1371/journal.pone.0287921] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 06/15/2023] [Indexed: 07/09/2023] Open
Abstract
Implantation of electrodes in the brain has been used as a clinical tool for decades to stimulate and record brain activity. As this method increasingly becomes the standard of care for several disorders and diseases, there is a growing need to quickly and accurately localize the electrodes once they are placed within the brain. We share here a protocol pipeline for localizing electrodes implanted in the brain, which we have applied to more than 260 patients, that is accessible to multiple skill levels and modular in execution. This pipeline uses multiple software packages to prioritize flexibility by permitting multiple different parallel outputs while minimizing the number of steps for each output. These outputs include co-registered imaging, electrode coordinates, 2D and 3D visualizations of the implants, automatic surface and volumetric localizations of the brain regions per electrode, and anonymization and data sharing tools. We demonstrate here some of the pipeline's visualizations and automatic localization algorithms which we have applied to determine appropriate stimulation targets, to conduct seizure dynamics analysis, and to localize neural activity from cognitive tasks in previous studies. Further, the output facilitates the extraction of information such as the probability of grey matter intersection or the nearest anatomic structure per electrode contact across all data sets that go through the pipeline. We expect that this pipeline will be a useful framework for researchers and clinicians alike to localize implanted electrodes in the human brain.
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Affiliation(s)
- Daniel J. Soper
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, United States of America
- Department of Neurology, Harvard Medical School, Boston, MA, United States of America
| | - Dustine Reich
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, United States of America
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States of America
| | - Alex Ross
- Department of Neurosurgery, University of Cincinnati College of Medicine, Cincinnati, OH, United States of America
| | - Pariya Salami
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, United States of America
- Department of Neurology, Harvard Medical School, Boston, MA, United States of America
| | - Sydney S. Cash
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, United States of America
- Department of Neurology, Harvard Medical School, Boston, MA, United States of America
| | - Ishita Basu
- Department of Neurosurgery, University of Cincinnati College of Medicine, Cincinnati, OH, United States of America
| | - Noam Peled
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - Angelique C. Paulk
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, United States of America
- Department of Neurology, Harvard Medical School, Boston, MA, United States of America
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Michalak AJ, Greenblatt A, Wu S, Tobochnik S, Dave H, Raghupathi R, Esengul YT, Guerra A, Tao JX, Issa NP, Cosgrove GR, Lega B, Warnke P, Chen HI, Lucas T, Sheth SA, Banks GP, Kwon CS, Feldstein N, Youngerman B, McKhann G, Davis KA, Schevon C. Seizure onset patterns predict outcome after stereo-electroencephalography-guided laser amygdalohippocampotomy. Epilepsia 2023; 64:1568-1581. [PMID: 37013668 PMCID: PMC10247471 DOI: 10.1111/epi.17602] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 03/29/2023] [Accepted: 03/31/2023] [Indexed: 04/05/2023]
Abstract
OBJECTIVE Stereotactic laser amygdalohippocampotomy (SLAH) is an appealing option for patients with temporal lobe epilepsy, who often require intracranial monitoring to confirm mesial temporal seizure onset. However, given limited spatial sampling, it is possible that stereotactic electroencephalography (stereo-EEG) may miss seizure onset elsewhere. We hypothesized that stereo-EEG seizure onset patterns (SOPs) may differentiate between primary onset and secondary spread and predict postoperative seizure control. In this study, we characterized the 2-year outcomes of patients who underwent single-fiber SLAH after stereo-EEG and evaluated whether stereo-EEG SOPs predict postoperative seizure freedom. METHODS This retrospective five-center study included patients with or without mesial temporal sclerosis (MTS) who underwent stereo-EEG followed by single-fiber SLAH between August 2014 and January 2022. Patients with causative hippocampal lesions apart from MTS or for whom the SLAH was considered palliative were excluded. An SOP catalogue was developed based on literature review. The dominant pattern for each patient was used for survival analysis. The primary outcome was 2-year Engel I classification or recurrent seizures before then, stratified by SOP category. RESULTS Fifty-eight patients were included, with a mean follow-up duration of 39 ± 12 months after SLAH. Overall 1-, 2-, and 3-year Engel I seizure freedom probability was 54%, 36%, and 33%, respectively. Patients with SOPs, including low-voltage fast activity or low-frequency repetitive spiking, had a 46% 2-year seizure freedom probability, compared to 0% for patients with alpha or theta frequency repetitive spiking or theta or delta frequency rhythmic slowing (log-rank test, p = .00015). SIGNIFICANCE Patients who underwent SLAH after stereo-EEG had a low probability of seizure freedom at 2 years, but SOPs successfully predicted seizure recurrence in a subset of patients. This study provides proof of concept that SOPs distinguish between hippocampal seizure onset and spread and supports using SOPs to improve selection of SLAH candidates.
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Affiliation(s)
- Andrew J. Michalak
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Adam Greenblatt
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, NY, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Shasha Wu
- Department of Neurology, University of Chicago, Chicago, NY, USA
| | - Steven Tobochnik
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Hina Dave
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Ramya Raghupathi
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, NY, USA
| | - Yasar T. Esengul
- Department of Neurology, University of Toledo College of Medicine, Toledo, OH, USA
| | - Antonio Guerra
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - James X. Tao
- Department of Neurology, University of Chicago, Chicago, NY, USA
| | - Naoum P. Issa
- Department of Neurology, University of Chicago, Chicago, NY, USA
| | - Garth R. Cosgrove
- Department of Neurosurgery, Brigham and Women’s Hospital, Boston, MA, USA
| | - Bradley Lega
- Department of Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Peter Warnke
- Department of Neurosurgery, University of Chicago, Chicago, NY, USA
| | - H. Isaac Chen
- Neurosurgery, Hospital of the University of Pennsylvania, Philadelphia, NY, USA
| | - Timothy Lucas
- Department of Neurosurgery & Biomedical Engineering, Ohio State University; Neurotech Institute, Columbus, OH, USA
| | - Sameer A. Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Garrett P. Banks
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Churl-Su Kwon
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Department of Neurosurgery, Columbia University Irving Medical Center, New York, NY, USA
- Department of Epidemiology, Columbia University Gertrude H Sergievsky Center, New York, NY, USA
| | - Neil Feldstein
- Department of Neurosurgery, Columbia University Irving Medical Center, New York, NY, USA
| | - Brett Youngerman
- Department of Neurosurgery, Columbia University Irving Medical Center, New York, NY, USA
| | - Guy McKhann
- Department of Neurosurgery, Columbia University Irving Medical Center, New York, NY, USA
| | - Kathryn A. Davis
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, NY, USA
| | - Catherine Schevon
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
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Miron G, Müller PM, Holtkamp M. Diagnostic and prognostic value of EEG patterns recorded on foramen ovale and epidural peg electrodes. Clin Neurophysiol 2022; 143:107-115. [DOI: 10.1016/j.clinph.2022.08.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 07/28/2022] [Accepted: 08/17/2022] [Indexed: 11/03/2022]
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Jiang H, Kokkinos V, Ye S, Urban A, Bagić A, Richardson M, He B. Interictal SEEG Resting-State Connectivity Localizes the Seizure Onset Zone and Predicts Seizure Outcome. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2200887. [PMID: 35545899 PMCID: PMC9218648 DOI: 10.1002/advs.202200887] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Indexed: 05/23/2023]
Abstract
Localization of epileptogenic zone currently requires prolonged intracranial recordings to capture seizure, which may take days to weeks. The authors developed a novel method to identify the seizure onset zone (SOZ) and predict seizure outcome using short-time resting-state stereotacticelectroencephalography (SEEG) data. In a cohort of 27 drug-resistant epilepsy patients, the authors estimated the information flow via directional connectivity and inferred the excitation-inhibition ratio from the 1/f power slope. They hypothesized that the antagonism of information flow at multiple frequencies between SOZ and non-SOZ underlying the relatively stable epilepsy resting state could be related to the disrupted excitation-inhibition balance. They found flatter 1/f power slope in non-SOZ regions compared to the SOZ, with dominant information flow from non-SOZ to SOZ regions. Greater differences in resting-state information flow between SOZ and non-SOZ regions are associated with favorable seizure outcome. By integrating a balanced random forest model with resting-state connectivity, their method localized the SOZ with an accuracy of 88% and predicted the seizure outcome with an accuracy of 92% using clinically determined SOZ. Overall, this study suggests that brief resting-state SEEG data can significantly facilitate the identification of SOZ and may eventually predict seizure outcomes without requiring long-term ictal recordings.
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Affiliation(s)
- Haiteng Jiang
- Department of Biomedical EngineeringCarnegie Mellon UniversityPittsburghPA15213USA
- Department of NeurobiologyAffiliated Mental Health Center & Hangzhou Seventh People's HospitalZhejiang University School of MedicineHangzhou310013P. R. China
- NHC and CAMS Key Laboratory of Medical NeurobiologyMOE Frontier Science Center for Brain Science and Brain‐machine IntegrationSchool of Brain Science and Brain MedicineZhejiang UniversityHangzhou310058P. R. China
| | - Vasileios Kokkinos
- University of Pittsburgh Comprehensive Epilepsy CenterDepartment of NeurologyUniversity of Pittsburgh School of MedicinePittsburghPA15232USA
- Massachusetts General HospitalBostonMA02114USA
| | - Shuai Ye
- Department of Biomedical EngineeringCarnegie Mellon UniversityPittsburghPA15213USA
| | - Alexandra Urban
- University of Pittsburgh Comprehensive Epilepsy CenterDepartment of NeurologyUniversity of Pittsburgh School of MedicinePittsburghPA15232USA
| | - Anto Bagić
- University of Pittsburgh Comprehensive Epilepsy CenterDepartment of NeurologyUniversity of Pittsburgh School of MedicinePittsburghPA15232USA
| | - Mark Richardson
- University of Pittsburgh Comprehensive Epilepsy CenterDepartment of NeurologyUniversity of Pittsburgh School of MedicinePittsburghPA15232USA
- Massachusetts General HospitalBostonMA02114USA
| | - Bin He
- Department of Biomedical EngineeringCarnegie Mellon UniversityPittsburghPA15213USA
- Neuroscience InstituteCarnegie Mellon UniversityPittsburghPA15213USA
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Lisgaras CP, Scharfman HE. Robust chronic convulsive seizures, high frequency oscillations, and human seizure onset patterns in an intrahippocampal kainic acid model in mice. Neurobiol Dis 2022; 166:105637. [PMID: 35091040 PMCID: PMC9034729 DOI: 10.1016/j.nbd.2022.105637] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 01/05/2022] [Accepted: 01/22/2022] [Indexed: 01/21/2023] Open
Abstract
Intrahippocampal kainic acid (IHKA) has been widely implemented to simulate temporal lobe epilepsy (TLE), but evidence of robust seizures is usually limited. To resolve this problem, we slightly modified previous methods and show robust seizures are common and frequent in both male and female mice. We employed continuous wideband video-EEG monitoring from 4 recording sites to best demonstrate the seizures. We found many more convulsive seizures than most studies have reported. Mortality was low. Analysis of convulsive seizures at 2-4 and 10-12 wks post-IHKA showed a robust frequency (2-4 per day on average) and duration (typically 20-30 s) at each time. Comparison of the two timepoints showed that seizure burden became more severe in approximately 50% of the animals. We show that almost all convulsive seizures could be characterized as either low-voltage fast or hypersynchronous onset seizures, which has not been reported in a mouse model of epilepsy and is important because these seizure types are found in humans. In addition, we report that high frequency oscillations (>250 Hz) occur, resembling findings from IHKA in rats and TLE patients. Pathology in the hippocampus at the site of IHKA injection was similar to mesial temporal lobe sclerosis and reduced contralaterally. In summary, our methods produce a model of TLE in mice with robust convulsive seizures, and there is variable progression. HFOs are robust also, and seizures have onset patterns and pathology like human TLE. SIGNIFICANCE: Although the IHKA model has been widely used in mice for epilepsy research, there is variation in outcomes, with many studies showing few robust seizures long-term, especially convulsive seizures. We present an implementation of the IHKA model with frequent convulsive seizures that are robust, meaning they are >10 s and associated with complex high frequency rhythmic activity recorded from 2 hippocampal and 2 cortical sites. Seizure onset patterns usually matched the low-voltage fast and hypersynchronous seizures in TLE. Importantly, there is low mortality, and both sexes can be used. We believe our results will advance the ability to use the IHKA model of TLE in mice. The results also have important implications for our understanding of HFOs, progression, and other topics of broad interest to the epilepsy research community. Finally, the results have implications for preclinical drug screening because seizure frequency increased in approximately half of the mice after a 6 wk interval, suggesting that the typical 2 wk period for monitoring seizure frequency is insufficient.
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Affiliation(s)
- Christos Panagiotis Lisgaras
- Departments of Child & Adolescent Psychiatry, Neuroscience & Physiology, and Psychiatry, and the Neuroscience Institute, New York University Langone Health, 550 First Ave., New York, NY 10016, United States of America; Center for Dementia Research, The Nathan Kline Institute for Psychiatric Research, New York State Office of Mental Health, 140 Old Orangeburg Road, Bldg. 35, Orangeburg, NY 10962, United States of America
| | - Helen E Scharfman
- Departments of Child & Adolescent Psychiatry, Neuroscience & Physiology, and Psychiatry, and the Neuroscience Institute, New York University Langone Health, 550 First Ave., New York, NY 10016, United States of America; Center for Dementia Research, The Nathan Kline Institute for Psychiatric Research, New York State Office of Mental Health, 140 Old Orangeburg Road, Bldg. 35, Orangeburg, NY 10962, United States of America.
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