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Cui D, Gao R, Xu C, Yan H, Zhang X, Yu T, Zhang G. Ictal onset stereoelectroencephalography patterns in temporal lobe epilepsy: type, distribution, and prognostic value. Acta Neurochir (Wien) 2022; 164:555-563. [PMID: 35041086 DOI: 10.1007/s00701-022-05122-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 01/11/2022] [Indexed: 12/19/2022]
Abstract
OBJECTIVE The aim of this study was to investigate the different ictal onset stereoelectroencephalography patterns (IOPs) in patients with drug-resistant temporal lobe epilepsy (TLE). We examined whether the IOPs relate to different TLE subtypes, MRI findings, and underlying pathologies, and we evaluated their prognostic value for predicting the surgical outcome. METHODS We retrospectively analyzed data from patients with TLE who underwent stereoelectroencephalography (SEEG) monitoring followed by surgical resection between January 2018 and January 2020. The SEEG recordings were independently analyzed by two epileptologists. RESULTS Forty-five patients were included in the study, and 61seizures were analyzed. Five IOPs were identified: low voltage fast activity (LVFA; 44.3%), spike-and-wave activity (16.4%), low frequency high-amplitude periodic spikes (LFPS; 18%), a burst of high-amplitude polyspikes (8.2%), and rhythmic sharp activity at ≤ 13 Hz (13.1%). Thirty-two patients were found to have a single IOP, while the other 13 patients had two or more IOPs. All five IOPs were found to occur in the medial temporal lobe epilepsy (MTLE), while four IOPs occurred in the lateral temporal lobe epilepsy (LTLE). The LFPS was a common IOP that could distinguish MTLE from LTLE (x2 = 7.046, p = 0.011). Among the MTLE patients, the LFPS was exclusively seen in cases of hippocampal sclerosis (x2 = 5.058, p = 0.038), while the LVFA was associated with nonspecific histology (x2 = 6.077, p = 0.023). The IOPs were not found to differ according to whether the MRI scans were positive or negative. After surgery, patients achieved the higher seizure-free rate at 81.8% and 77.8%, respectively, if the LFPS and LVFA were the predominant patterns. Multiple IOPs or a negative MRI did not indicate a poor prognosis. CONCLUSIONS Five distinct IOPs were identified in the patients with TLE. The differences found have important clinical implications and could provide complementary information for surgical decision-making, especially in MRI-negative patients.
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Affiliation(s)
- Deqiu Cui
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Runshi Gao
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Cuiping Xu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Hao Yan
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Xiaohua Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Tao Yu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Guojun Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China.
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Xu C, Zhang X, Yan X, Ma K, Wang X, Zhang X, Ni D, Qiao L, Yu T, Zhang G, Wang Y, Li Y. Multiple ictal onset patterns underlie seizure generation in seizure-free patients with temporal lobe epilepsy surgery: an SEEG study. Acta Neurochir (Wien) 2021; 163:3031-3037. [PMID: 34480655 PMCID: PMC8520514 DOI: 10.1007/s00701-021-04960-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 07/29/2021] [Indexed: 11/25/2022]
Abstract
PURPOSE Seizure originates from different pathological substrate; however, the same pathologies may have distinct mechanisms underlying seizure generation. We aimed to improve the understanding of such mechanisms in patients with temporal lobe epilepsy (TLE) by investigating the stereoelectroencephalography (SEEG) ictal onset patterns (IOPs). METHODS We analyzed data from a cohort of 19 consecutive patients explored by SEEG and had 1-3-year seizure-freedom following temporal lobe resection. RESULTS Six IOPs were identified. They were low voltage fast activity (LVFA) (36.5%), rhythmic spikes or spike-waves at low frequency and with high amplitude (34.1%), runs of spikes (10.6%), rhythmic sharp waves (8.2%), low frequency high amplitude repetitive spiking (LFRS) (7.1%), and delta activity (3.5%). All six patterns were found in patients with mesial temporal onset and only two patterns were found in patients with temporal neocortical onset. The most prevalent patterns for patients with mesial temporal onset were rhythmic spikes or spike-waves, followed by LVFA with a mean discharge rate 74 Hz. For patients with temporal neocortical onset, the most prevalent IOP pattern was LVFA with a mean discharge rate 35 Hz, followed by runs of spikes. Compared with Lateral TLE (LTLE), the duration between the onset of the IOPs to the onset of the symptom was longer for patients with MTLE (Mesial TLE) (MTLE:55.7 ± 50.6 s vs LTLE:19.5 ± 16.4 s). CONCLUSION Multiple IOPs underlie seizure generation in patients with TLE. However, the mesial and lateral temporal lobes share distinct IOPs.
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Affiliation(s)
- Cuiping Xu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China.
| | - Xiaohua Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China.
| | - Xiaoming Yan
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Kai Ma
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Xueyuan Wang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Xi Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Duanyu Ni
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Liang Qiao
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Tao Yu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Guojun Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Yuping Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yongjie Li
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China
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Sip V, Scholly J, Guye M, Bartolomei F, Jirsa V. Evidence for spreading seizure as a cause of theta-alpha activity electrographic pattern in stereo-EEG seizure recordings. PLoS Comput Biol 2021; 17:e1008731. [PMID: 33635864 PMCID: PMC7946361 DOI: 10.1371/journal.pcbi.1008731] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 03/10/2021] [Accepted: 01/21/2021] [Indexed: 02/07/2023] Open
Abstract
Intracranial electroencephalography is a standard tool in clinical evaluation of patients with focal epilepsy. Various early electrographic seizure patterns differing in frequency, amplitude, and waveform of the oscillations are observed. The pattern most common in the areas of seizure propagation is the so-called theta-alpha activity (TAA), whose defining features are oscillations in the θ - α range and gradually increasing amplitude. A deeper understanding of the mechanism underlying the generation of the TAA pattern is however lacking. In this work we evaluate the hypothesis that the TAA patterns are caused by seizures spreading across the cortex. To do so, we perform simulations of seizure dynamics on detailed patient-derived cortical surfaces using the spreading seizure model as well as reference models with one or two homogeneous sources. We then detect the occurrences of the TAA patterns both in the simulated stereo-electroencephalographic signals and in the signals of recorded epileptic seizures from a cohort of fifty patients, and we compare the features of the groups of detected TAA patterns to assess the plausibility of the different models. Our results show that spreading seizure hypothesis is qualitatively consistent with the evidence available in the seizure recordings, and it can explain the features of the detected TAA groups best among the examined models.
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Affiliation(s)
- Viktor Sip
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - Julia Scholly
- Assistance Publique - Hôpitaux de Marseille, Hôpital de la Timone, CEMEREM, Pôle d’Imagerie Médicale, CHU, Marseille, France
- Assistance Publique - Hôpitaux de Marseille, Hôpital de la Timone, Service de Neurophysiologie Clinique, CHU, Marseille, France
| | - Maxime Guye
- Assistance Publique - Hôpitaux de Marseille, Hôpital de la Timone, CEMEREM, Pôle d’Imagerie Médicale, CHU, Marseille, France
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
| | - Fabrice Bartolomei
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
- Assistance Publique - Hôpitaux de Marseille, Hôpital de la Timone, Service de Neurophysiologie Clinique, CHU, Marseille, France
| | - Viktor Jirsa
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
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Wang Y, Trevelyan AJ, Valentin A, Alarcon G, Taylor PN, Kaiser M. Mechanisms underlying different onset patterns of focal seizures. PLoS Comput Biol 2017; 13:e1005475. [PMID: 28472032 PMCID: PMC5417416 DOI: 10.1371/journal.pcbi.1005475] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2016] [Accepted: 03/23/2017] [Indexed: 02/07/2023] Open
Abstract
Focal seizures are episodes of pathological brain activity that appear to arise from a localised area of the brain. The onset patterns of focal seizure activity have been studied intensively, and they have largely been distinguished into two types-low amplitude fast oscillations (LAF), or high amplitude spikes (HAS). Here we explore whether these two patterns arise from fundamentally different mechanisms. Here, we use a previously established computational model of neocortical tissue, and validate it as an adequate model using clinical recordings of focal seizures. We then reproduce the two onset patterns in their most defining properties and investigate the possible mechanisms underlying the different focal seizure onset patterns in the model. We show that the two patterns are associated with different mechanisms at the spatial scale of a single ECoG electrode. The LAF onset is initiated by independent patches of localised activity, which slowly invade the surrounding tissue and coalesce over time. In contrast, the HAS onset is a global, systemic transition to a coexisting seizure state triggered by a local event. We find that such a global transition is enabled by an increase in the excitability of the "healthy" surrounding tissue, which by itself does not generate seizures, but can support seizure activity when incited. In our simulations, the difference in surrounding tissue excitability also offers a simple explanation of the clinically reported difference in surgical outcomes. Finally, we demonstrate in the model how changes in tissue excitability could be elucidated, in principle, using active stimulation. Taken together, our modelling results suggest that the excitability of the tissue surrounding the seizure core may play a determining role in the seizure onset pattern, as well as in the surgical outcome.
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Affiliation(s)
- Yujiang Wang
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
- Institute of Neurology, University College London, London, United Kingdom
| | - Andrew J Trevelyan
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Antonio Valentin
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Gonzalo Alarcon
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Comprehensive Epilepsy Center, Neuroscience Institute, Academic Health Systems, Hamad Medical Corporation, Doha, Qatar
| | - Peter N Taylor
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
- Institute of Neurology, University College London, London, United Kingdom
| | - Marcus Kaiser
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
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Wieser HG. Presurgical diagnosis of epilepsies – concepts and diagnostic tools. JOURNAL OF EPILEPTOLOGY 2016. [DOI: 10.1515/joepi-2016-0014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
SummaryIntroduction.Numerous reviews of the currently established concepts, strategies and diagnostic tools used in epilepsy surgery have been published. The focus concept which was initially developed by Forster, Penfield and Jasper and popularised and enriched by Lüders, is still fundamental for epilepsy surgery.Aim.To present different conceptual views of the focus concept and to discuss more recent network hypothesis, emphasizing so-called “critical modes of an epileptogenic circuit”.Method.A literature search was conducted using keywords: presurgical evaluation, epileptic focus concepts, cortical zones, diagnostic tools.Review and remarks.The theoretical concepts of the epileptic focus are opposed to the network hypothesis. The definitions of the various cortical zones have been conceptualized in the presurgical evaluation of candidates for epilepsy surgery: the seizure onset zone versus the epileptogenic zone, the symptomatogenic zone, the irritative and functional deficit zones are characterized. The epileptogenic lesion, the “eloquent cortex” and secondary epileptogenesis (mirror focus) are dealt with. The current diagnostic techniques used in the definition of these cortical zones, such as video-EEG monitoring, non-invasive and invasive EEG recording techniques, magnetic resonance imaging, ictal single photon emission computed tomography, and positron emission tomography, are discussed and illustrated. Potential modern surrogate markers of epileptogenicity, such asHigh frequency oscillations, Ictal slow waves/DC shifts, Magnetic resonance spectroscopy, Functional MRI,the use ofMagnetized nanoparticlesin MRI,Transcranial magnetic stimulation,Optical intrinsic signalimaging, andSeizure predictionare discussed. Particular emphasis is put on the EEG: Scalp EEG, semi-invasive and invasive EEG (Stereoelectroencephalography) and intraoperative electrocorticography are illustrated. Ictal SPECT and18F-FDG PET are very helpful and several other procedures, such as dipole source localization and spike-triggered functional MRI are already widely used. The most important lateralizing and localizing ictal signs and symptoms are summarized. It is anticipated that the other clinically valid surrogate markers of epileptogenesis and epileptogenicity will be further developed in the near future. Until then the concordance of the results of seizure semiology, localization of epileptogenicity by EEG and MRI remains the most important prerequisite for successful epilepsy surgery.Conclusions and future perspectives.Resective epilepsy surgery is a widely accepted and successful therapeutic approach, rendering up to 80% of selected patients seizure free. Although other therapies, such as radiosurgery, and responsive neurostimulation will increasingly play a role in patients with an unresectable lesion, it is unlikely that they will replace selective resective surgery. The hope is that new diagnostic techniques will be developed that permit more direct definition and measurement of the epileptogenic zone.
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