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Matarrese MAG, Loppini A, Fabbri L, Tamilia E, Perry MS, Madsen JR, Bolton J, Stone SSD, Pearl PL, Filippi S, Papadelis C. Spike propagation mapping reveals effective connectivity and predicts surgical outcome in epilepsy. Brain 2023; 146:3898-3912. [PMID: 37018068 PMCID: PMC10473571 DOI: 10.1093/brain/awad118] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 03/14/2023] [Accepted: 03/23/2023] [Indexed: 04/06/2023] Open
Abstract
Neurosurgical intervention is the best available treatment for selected patients with drug resistant epilepsy. For these patients, surgical planning requires biomarkers that delineate the epileptogenic zone, the brain area that is indispensable for the generation of seizures. Interictal spikes recorded with electrophysiological techniques are considered key biomarkers of epilepsy. Yet, they lack specificity, mostly because they propagate across brain areas forming networks. Understanding the relationship between interictal spike propagation and functional connections among the involved brain areas may help develop novel biomarkers that can delineate the epileptogenic zone with high precision. Here, we reveal the relationship between spike propagation and effective connectivity among onset and areas of spread and assess the prognostic value of resecting these areas. We analysed intracranial EEG data from 43 children with drug resistant epilepsy who underwent invasive monitoring for neurosurgical planning. Using electric source imaging, we mapped spike propagation in the source domain and identified three zones: onset, early-spread and late-spread. For each zone, we calculated the overlap and distance from surgical resection. We then estimated a virtual sensor for each zone and the direction of information flow among them via Granger causality. Finally, we compared the prognostic value of resecting these zones, the clinically-defined seizure onset zone and the spike onset on intracranial EEG channels by estimating their overlap with resection. We observed a spike propagation in source space for 37 patients with a median duration of 95 ms (interquartile range: 34-206), a spatial displacement of 14 cm (7.5-22 cm) and a velocity of 0.5 m/s (0.3-0.8 m/s). In patients with good surgical outcome (25 patients, Engel I), the onset had higher overlap with resection [96% (40-100%)] than early-spread [86% (34-100%), P = 0.01] and late-spread [59% (12-100%), P = 0.002], and it was also closer to resection than late-spread [5 mm versus 9 mm, P = 0.007]. We found an information flow from onset to early-spread in 66% of patients with good outcomes, and from early-spread to onset in 50% of patients with poor outcome. Finally, resection of spike onset, but not area of spike spread or the seizure onset zone, predicted outcome with positive predictive value of 79% and negative predictive value of 56% (P = 0.04). Spatiotemporal mapping of spike propagation reveals information flow from onset to areas of spread in epilepsy brain. Surgical resection of the spike onset disrupts the epileptogenic network and may render patients with drug resistant epilepsy seizure-free without having to wait for a seizure to occur during intracranial monitoring.
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Affiliation(s)
- Margherita A G Matarrese
- Jane and John Justin Institute for Mind Health Neurosciences Center, Cook Children’s Health Care System, Fort Worth, TX, USA
- Laboratory of Nonlinear Physics and Mathematical Modeling, Department of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy
- Department of Bioengineering, The University of Texas at Arlington, Arlington, TX, USA
| | - Alessandro Loppini
- Laboratory of Nonlinear Physics and Mathematical Modeling, Department of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Lorenzo Fabbri
- Jane and John Justin Institute for Mind Health Neurosciences Center, Cook Children’s Health Care System, Fort Worth, TX, USA
- Department of Bioengineering, The University of Texas at Arlington, Arlington, TX, USA
| | - Eleonora Tamilia
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - M Scott Perry
- Jane and John Justin Institute for Mind Health Neurosciences Center, Cook Children’s Health Care System, Fort Worth, TX, USA
| | - Joseph R Madsen
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Jeffrey Bolton
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Scellig S D Stone
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children’s 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
| | - Simonetta Filippi
- Laboratory of Nonlinear Physics and Mathematical Modeling, Department of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Christos Papadelis
- Jane and John Justin Institute for Mind Health Neurosciences Center, Cook Children’s Health Care System, Fort Worth, TX, USA
- Department of Bioengineering, The University of Texas at Arlington, Arlington, TX, USA
- School of Medicine, Texas Christian University, Fort Worth, TX, USA
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Tomlinson SB, Wong JN, Conrad EC, Kennedy BC, Marsh ED. Reproducibility of interictal spike propagation in children with refractory epilepsy. Epilepsia 2019; 60:898-910. [PMID: 31006860 PMCID: PMC6488404 DOI: 10.1111/epi.14720] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Revised: 02/11/2019] [Accepted: 03/13/2019] [Indexed: 01/03/2023]
Abstract
OBJECTIVE Interictal spikes are a characteristic feature of invasive electroencephalography (EEG) recordings in children with refractory epilepsy. Spikes frequently co-occur across multiple brain regions with discernable latencies, suggesting that spikes can propagate through distributed neural networks. The purpose of this study was to examine the long-term reproducibility of spike propagation patterns over hours to days of interictal recording. METHODS Twelve children (mean age 13.1 years) were retrospectively studied. A mean ± standard deviation (SD) of 47.2 ± 40.1 hours of interictal EEG recordings were examined per patient (range 17.5-166.5 hours). Interictal recordings were divided into 30-minute segments. Networks were extracted based on the frequency of spike coactivation between pairs of electrodes. For each 30-minute segment, electrodes were assigned a "Degree Preference (DP)" based on the tendency to appear upstream or downstream within propagation sequences. The consistency of DPs across segments ("DP-Stability") was quantified using the Spearman rank correlation. RESULTS Regions exhibited highly stable preferences to appear upstream, intermediate, or downstream in spike propagation sequences. Across networks, the mean ± SD DP-Stability was 0.88 ± 0.07, indicating that propagation patterns observed in 30-minute segments were representative of the patterns observed in the full interictal window. At the group level, regions involved in seizure generation appeared more upstream in spike propagation sequences. SIGNIFICANCE Interictal spike propagation is a highly reproducible output of epileptic networks. These findings shed new light on the spatiotemporal dynamics that may constrain the network mechanisms of refractory epilepsy.
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Affiliation(s)
- Samuel B. Tomlinson
- Division of Neurosurgery, Children’s Hospital of Philadelphia, Philadelphia, PA
- School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, NY
| | - Jeremy N. Wong
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Erin C. Conrad
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA
| | - Benjamin C. Kennedy
- Division of Neurosurgery, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - Eric D. Marsh
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA
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Tamilia E, Park EH, Percivati S, Bolton J, Taffoni F, Peters JM, Grant PE, Pearl PL, Madsen JR, Papadelis C. Surgical resection of ripple onset predicts outcome in pediatric epilepsy. Ann Neurol 2018; 84:331-346. [PMID: 30022519 DOI: 10.1002/ana.25295] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Revised: 07/05/2018] [Accepted: 07/06/2018] [Indexed: 12/31/2022]
Abstract
OBJECTIVE In patients with medically refractory epilepsy (MRE), interictal ripples (80-250Hz) are observed in large brain areas whose resection may be unnecessary for seizure freedom. This limits their utility as epilepsy biomarkers for surgery. We assessed the spatiotemporal propagation of interictal ripples on intracranial electroencephalography (iEEG) in children with MRE, compared it with the propagation of spikes, identified ripples that initiated propagation (onset-ripples), and evaluated their clinical value as epilepsy biomarkers. METHODS Twenty-seven children who underwent epilepsy surgery were studied. We identified propagation sequences of ripples and spikes across multiple iEEG contacts and calculated each ripple or spike latency from the propagation onset. We classified ripples and spikes into categories (ie, onset, spread, and isolated) based on their spatiotemporal characteristics and correlated their mean rate inside and outside resection with outcome (good outcome, Engel 1 versus poor outcome, Engel≥2). We determined, as onset-zone, spread-zone, and isolated-zone, the areas generating the corresponding ripple or spike category and evaluated the predictive value of their resection. RESULTS We observed ripple propagation in all patients and spike propagation in 25 patients. Mean rate of onset-ripples inside resection predicted the outcome (odds ratio = 5.37; p = 0.02) and correlated with Engel class (rho = -0.55; p = 0.003). Resection of the onset-ripple-zone was associated with good outcome (p = 0.047). No association was found for the spread-ripple-zone, isolated-ripple-zone, or any spike-zone. INTERPRETATION Interictal ripples propagate across iEEG contacts in children with MRE. The association between the onset-ripple-zone resection and good outcome indicates that onset-ripples are promising epilepsy biomarkers, which estimate the epileptogenic tissue better than spread-ripples or onset-spikes. Ann Neurol 2018;84:331-346.
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Affiliation(s)
- Eleonora Tamilia
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA.,Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA
| | - Eun-Hyoung Park
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, MA
| | - Stefania Percivati
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA.,Unit of Biomedical Robotics and Biomicrosystems, Engineering Department, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Jeffrey Bolton
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA
| | - Fabrizio Taffoni
- Unit of Biomedical Robotics and Biomicrosystems, Engineering Department, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Jurriaan M Peters
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA
| | - 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
| | - Phillip L Pearl
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA
| | - Joseph R Madsen
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, MA
| | - Christos Papadelis
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA.,Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA
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Khambhati AN, Bassett DS, Oommen BS, Chen SH, Lucas TH, Davis KA, Litt B. Recurring Functional Interactions Predict Network Architecture of Interictal and Ictal States in Neocortical Epilepsy. eNeuro 2017; 4:ENEURO.0091-16.2017. [PMID: 28303256 PMCID: PMC5343278 DOI: 10.1523/eneuro.0091-16.2017] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2016] [Revised: 01/09/2017] [Accepted: 01/10/2017] [Indexed: 01/10/2023] Open
Abstract
Human epilepsy patients suffer from spontaneous seizures, which originate in brain regions that also subserve normal function. Prior studies demonstrate focal, neocortical epilepsy is associated with dysfunction, several hours before seizures. How does the epileptic network perpetuate dysfunction during baseline periods? To address this question, we developed an unsupervised machine learning technique to disentangle patterns of functional interactions between brain regions, or subgraphs, from dynamic functional networks constructed from approximately 100 h of intracranial recordings in each of 22 neocortical epilepsy patients. Using this approach, we found: (1) subgraphs from ictal (seizure) and interictal (baseline) epochs are topologically similar, (2) interictal subgraph topology and dynamics can predict brain regions that generate seizures, and (3) subgraphs undergo slower and more coordinated fluctuations during ictal epochs compared to interictal epochs. Our observations suggest that seizures mark a critical shift away from interictal states that is driven by changes in the dynamical expression of strongly interacting components of the epileptic network.
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Affiliation(s)
- Ankit N. Khambhati
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104
- Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104
| | - Danielle S. Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104
- Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104
| | - Brian S. Oommen
- Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104
| | - Stephanie H. Chen
- Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104
| | - Timothy H. Lucas
- Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104
- Department of Neurosurgery, Hospital of the University of Pennsylvania, Philadelphia, PA 19104
| | - Kathryn A. Davis
- Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104
| | - Brian Litt
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104
- Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104
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5
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Tomlinson SB, Bermudez C, Conley C, Brown MW, Porter BE, Marsh ED. Spatiotemporal Mapping of Interictal Spike Propagation: A Novel Methodology Applied to Pediatric Intracranial EEG Recordings. Front Neurol 2016; 7:229. [PMID: 28066315 PMCID: PMC5165024 DOI: 10.3389/fneur.2016.00229] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Accepted: 11/30/2016] [Indexed: 12/19/2022] Open
Abstract
Synchronized cortical activity is implicated in both normative cognitive functioning and many neurologic disorders. For epilepsy patients with intractable seizures, irregular synchronization within the epileptogenic zone (EZ) is believed to provide the network substrate through which seizures initiate and propagate. Mapping the EZ prior to epilepsy surgery is critical for detecting seizure networks in order to achieve postsurgical seizure control. However, automated techniques for characterizing epileptic networks have yet to gain traction in the clinical setting. Recent advances in signal processing and spike detection have made it possible to examine the spatiotemporal propagation of interictal spike discharges across the epileptic cortex. In this study, we present a novel methodology for detecting, extracting, and visualizing spike propagation and demonstrate its potential utility as a biomarker for the EZ. Eighteen presurgical intracranial EEG recordings were obtained from pediatric patients ultimately experiencing favorable (i.e., seizure-free, n = 9) or unfavorable (i.e., seizure-persistent, n = 9) surgical outcomes. Novel algorithms were applied to extract multichannel spike discharges and visualize their spatiotemporal propagation. Quantitative analysis of spike propagation was performed using trajectory clustering and spatial autocorrelation techniques. Comparison of interictal propagation patterns revealed an increase in trajectory organization (i.e., spatial autocorrelation) among Sz-Free patients compared with Sz-Persist patients. The pathophysiological basis and clinical implications of these findings are considered.
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Affiliation(s)
- Samuel B Tomlinson
- Department of Pediatrics, Division of Child Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA; School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, NY, USA
| | - Camilo Bermudez
- Department of Pediatrics, Division of Child Neurology, Children's Hospital of Philadelphia , Philadelphia, PA , USA
| | - Chiara Conley
- Department of Pediatrics, Division of Child Neurology, Children's Hospital of Philadelphia , Philadelphia, PA , USA
| | - Merritt W Brown
- Department of Pediatrics, Division of Child Neurology, Children's Hospital of Philadelphia , Philadelphia, PA , USA
| | - Brenda E Porter
- Department of Neurology and Neurological Science, Stanford School of Medicine , Palo Alto, CA , USA
| | - Eric D Marsh
- Department of Pediatrics, Division of Child Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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6
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Lateralization of Epileptic Foci Through Causal Analysis of Scalp-EEG Interictal Spike Activity. J Clin Neurophysiol 2015; 32:57-65. [DOI: 10.1097/wnp.0000000000000120] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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7
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Matsuo T, Kawai K, Uno T, Kunii N, Miyakawa N, Usami K, Kawasaki K, Hasegawa I, Saito N. Simultaneous Recording of Single-Neuron Activities and Broad-Area Intracranial Electroencephalography: Electrode Design and Implantation Procedure. Oper Neurosurg (Hagerstown) 2013; 73:ons146-54. [DOI: 10.1227/01.neu.0000430327.48387.e1] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Abstract
BACKGROUND:
There has been growing interest in clinical single-neuron recording to better understand epileptogenicity and brain function. It is crucial to compare this new information, single-neuronal activity, with that obtained from conventional intracranial electroencephalography during simultaneous recording. However, it is difficult to implant microwires and subdural electrodes during a single surgical operation because the stereotactic frame hampers flexible craniotomy.
OBJECTIVE:
To describe newly designed electrodes and surgical techniques for implanting them with subdural electrodes that enable simultaneous recording from hippocampal neurons and broad areas of the cortical surface.
METHODS:
We designed a depth electrode that does not protrude into the dura and pulsates naturally with the brain. The length and tract of the depth electrode were determined preoperatively between the lateral subiculum and the lateral surface of the temporal lobe. A frameless navigation system was used to insert the depth electrode. Surface grids and ventral strips were placed before and after the insertion of the depth electrodes, respectively. Finally, a microwire bundle was inserted into the lumen of the depth electrode. We evaluated the precision of implantation, the recording stability, and the recording rate with microwire electrodes.
RESULTS:
Depth-microwire electrodes were placed with a precision of 3.6 mm. The mean successful recording rate of single- or multiple-unit activity was 14.8%, which was maintained throughout the entire recording period.
CONCLUSION:
We achieved simultaneous implantation of microwires, depth electrodes, and broad-area subdural electrodes. Our method enabled simultaneous and stable recording of hippocampal single-neuron activities and multichannel intracranial electroencephalography.
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Affiliation(s)
- Takeshi Matsuo
- Department of Neurosurgery, University of Tokyo Graduate School of Medicine, Tokyo, Japan
- Department of Physiology, Niigata University School of Medicine, Niigata, Japan
| | - Kensuke Kawai
- Department of Neurosurgery, University of Tokyo Graduate School of Medicine, Tokyo, Japan
| | - Takeshi Uno
- Department of Neurosurgery, University of Tokyo Graduate School of Medicine, Tokyo, Japan
| | - Naoto Kunii
- Department of Neurosurgery, University of Tokyo Graduate School of Medicine, Tokyo, Japan
| | - Naohisa Miyakawa
- Department of Physiology, Niigata University School of Medicine, Niigata, Japan
- Department of Ultrastructual Research, National Institute of Neuroscience, Kodaira, Japan
| | - Kenichi Usami
- Department of Neurosurgery, University of Tokyo Graduate School of Medicine, Tokyo, Japan
| | - Keisuke Kawasaki
- Department of Physiology, Niigata University School of Medicine, Niigata, Japan
| | - Isao Hasegawa
- Department of Physiology, Niigata University School of Medicine, Niigata, Japan
- Center for Transdisciplinary Research, Niigata University, Niigata, Japan
| | - Nobuhito Saito
- Department of Neurosurgery, University of Tokyo Graduate School of Medicine, Tokyo, Japan
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Gaspard N, Alkawadri R, Farooque P, Goncharova II, Zaveri HP. Automatic detection of prominent interictal spikes in intracranial EEG: validation of an algorithm and relationsip to the seizure onset zone. Clin Neurophysiol 2013; 125:1095-103. [PMID: 24269092 DOI: 10.1016/j.clinph.2013.10.021] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2013] [Revised: 10/21/2013] [Accepted: 10/27/2013] [Indexed: 11/25/2022]
Abstract
OBJECTIVE To develop an algorithm for the automatic quantitative description and detection of spikes in the intracranial EEG and quantify the relationship between prominent spikes and the seizure onset zone. METHODS An algorithm was developed for the quantification of time-frequency properties of spikes (upslope, instantaneous energy, downslope) and their statistical representation in a univariate generalized extreme value distribution. Its performance was evaluated in comparison to expert detection of spikes in intracranial EEG recordings from 10 patients. It was subsequently used in 18 patients to detect prominent spikes and quantify their spatial relationship to the seizure onset area. RESULTS The algorithm displayed an average sensitivity of 63.4% with a false detection rate of 3.2 per minute for the detection of individual spikes and an average sensitivity of 88.6% with a false detection rate of 1.4% for the detection of intracranial EEG contacts containing the most prominent spikes. Prominent spikes occurred closer to the seizure onset area than less prominent spikes but they overlapped with it only in a minority of cases (3/18). CONCLUSIONS Automatic detection and quantification of the morphology of spikes increases their utility to localize the seizure onset area. Prominent spikes tend to originate mostly from contacts located in the close vicinity of the seizure onset area rather than from within it. SIGNIFICANCE Quantitative analysis of time-frequency characteristics and spatial distribution of intracranial spikes provides complementary information that may be useful for the localization of the seizure-onset zone.
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Affiliation(s)
- Nicolas Gaspard
- Comprehensive Epilepsy Center and Computational Neurophysiology Laboratory, Dept. of Neurology, School of Medicine, Yale University, Yale-New Haven Hospital, New Haven, CT, USA.
| | - Rafeed Alkawadri
- Comprehensive Epilepsy Center and Computational Neurophysiology Laboratory, Dept. of Neurology, School of Medicine, Yale University, Yale-New Haven Hospital, New Haven, CT, USA
| | - Pue Farooque
- Comprehensive Epilepsy Center and Computational Neurophysiology Laboratory, Dept. of Neurology, School of Medicine, Yale University, Yale-New Haven Hospital, New Haven, CT, USA
| | - Irina I Goncharova
- Comprehensive Epilepsy Center and Computational Neurophysiology Laboratory, Dept. of Neurology, School of Medicine, Yale University, Yale-New Haven Hospital, New Haven, CT, USA
| | - Hitten P Zaveri
- Comprehensive Epilepsy Center and Computational Neurophysiology Laboratory, Dept. of Neurology, School of Medicine, Yale University, Yale-New Haven Hospital, New Haven, CT, USA
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9
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Lu Y, Yang L, Worrell GA, Brinkmann B, Nelson C, He B. Dynamic imaging of seizure activity in pediatric epilepsy patients. Clin Neurophysiol 2012; 123:2122-9. [PMID: 22608485 DOI: 10.1016/j.clinph.2012.04.021] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2012] [Revised: 04/19/2012] [Accepted: 04/20/2012] [Indexed: 11/19/2022]
Abstract
OBJECTIVE To investigate the feasibility of using noninvasive EEG source imaging approach to image continuous seizure activity in pediatric epilepsy patients. METHODS Nine pediatric patients with medically intractable epilepsy were included in this study. Eight of the patients had extratemporal lobe epilepsy and one had temporal lobe epilepsy. All of the patients underwent resective surgery and seven of them underwent intracranial EEG (iEEG) monitoring. The ictal EEG was analyzed using a noninvasive dynamic seizure imaging (DSI) approach. The DSI approach separates scalp EEGs into independent components and extracts the spatio-temporal ictal features to achieve dynamic imaging of seizure sources. Surgical resection and intracranial recordings were used to validate the noninvasive imaging results. RESULTS The DSI determined seizure onset zones (SOZs) in these patients were localized within or in close vicinity to the surgically resected region. In the seven patients with intracranial monitoring, the estimated seizure onset sources were concordant with the seizure onset zones of iEEG. The DSI also localized the multiple foci involved in the later seizure propagation, which were confirmed by the iEEG recordings. CONCLUSIONS Dynamic seizure imaging can noninvasively image the seizure activations in pediatric patients with both temporal and extratemporal lobe epilepsy. SIGNIFICANCE EEG seizure imaging can potentially be used to noninvasively image the SOZs and aid the pre-surgical planning in pediatric epilepsy patients.
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Affiliation(s)
- Yunfeng Lu
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
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Dai Y, Zhang W, Dickens DL, He B. Source connectivity analysis from MEG and its application to epilepsy source localization. Brain Topogr 2011; 25:157-66. [PMID: 22102157 DOI: 10.1007/s10548-011-0211-0] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2011] [Accepted: 11/08/2011] [Indexed: 11/30/2022]
Abstract
We report an approach to perform source connectivity analysis from MEG, and initially evaluate this approach to interictal MEG to localize epileptogenic foci and analyze interictal discharge propagations in patients with medically intractable epilepsy. Cortical activities were reconstructed from MEG using individual realistic geometry boundary element method head models. Directional connectivity among cortical regions of interest was then estimated using directed transfer function. The MEG source connectivity analysis method was implemented in the eConnectome software, which is open-source and freely available at http://econnectome.umn.edu . As an initial evaluation, the method was applied to study MEG interictal spikes from five epilepsy patients. Estimated primary epileptiform sources were consistent with surgically resected regions, suggesting the feasibility of using cortical source connectivity analysis from interictal MEG for potential localization of epileptiform activities.
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Affiliation(s)
- Yakang Dai
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, 55455, USA
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11
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Amini L, Jutten C, Achard S, David O, Kahane P, Vercueil L, Minotti L, Hossein-Zadeh GA, Soltanian-Zadeh H. Comparison of five directed graph measures for identification of leading interictal epileptic regions. Physiol Meas 2010; 31:1529-46. [PMID: 20952817 PMCID: PMC3368828 DOI: 10.1088/0967-3334/31/11/009] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Directed graphs (digraphs) derived from interictal periods of intracerebral EEG (iEEG) recordings can be used to estimate the leading interictal epileptic regions for presurgery evaluations. For this purpose, quantification of the emittance contribution of each node to the rest of digraph is important. However, the usual digraph measures are not very well suited for this quantification. Here, we compare the efficiency of recently introduced local information (LI) measure and a new measure called total global efficiency with classical measures like global efficiency, local efficiency and node degree. For evaluation, the estimated leading interictal epileptic regions based on five measures are compared with seizure onset zones obtained by visual inspection of epileptologists for five patients. The comparison revealed the superior performance of the LI measure. We showed efficiency of different digraph measures for the purpose of source and sink node identification.
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Affiliation(s)
- Ladan Amini
- CIPCE, Control and Intelligent Processing Center of Excellence
University of TehranSchool of Electrical and Computer Engineering Tehran 14395-515,IR
- GIPSA-lab, Grenoble Images Parole Signal Automatique
CNRS : UMR5216Université Joseph Fourier - Grenoble IUniversité Pierre Mendès-France - Grenoble IIUniversité Stendhal - Grenoble IIIInstitut Polytechnique de Grenoble961 rue de la Houille Blanche BP 46 F - 38402 GRENOBLE Cedex,FR
| | - Christian Jutten
- GIPSA-lab, Grenoble Images Parole Signal Automatique
CNRS : UMR5216Université Joseph Fourier - Grenoble IUniversité Pierre Mendès-France - Grenoble IIUniversité Stendhal - Grenoble IIIInstitut Polytechnique de Grenoble961 rue de la Houille Blanche BP 46 F - 38402 GRENOBLE Cedex,FR
- IUF, Institut Universitaire de France
Ministère de l'Enseignement Supérieur et de la Recherche ScientifiqueMaison des Universités, 103 Boulevard Saint-Michel, 75005 Paris,FR
| | - Sophie Achard
- GIPSA-lab, Grenoble Images Parole Signal Automatique
CNRS : UMR5216Université Joseph Fourier - Grenoble IUniversité Pierre Mendès-France - Grenoble IIUniversité Stendhal - Grenoble IIIInstitut Polytechnique de Grenoble961 rue de la Houille Blanche BP 46 F - 38402 GRENOBLE Cedex,FR
| | - Olivier David
- GIN, Grenoble Institut des Neurosciences
INSERM : U836CEAUniversité Joseph Fourier - Grenoble ICHU GrenobleUJF - Site Santé La Tronche BP 170 38042 Grenoble Cedex 9,FR
- Département de neuro-radiologie
CHU GrenobleUniversité Joseph Fourier - Grenoble IFR
| | - Philippe Kahane
- GIN, Grenoble Institut des Neurosciences
INSERM : U836CEAUniversité Joseph Fourier - Grenoble ICHU GrenobleUJF - Site Santé La Tronche BP 170 38042 Grenoble Cedex 9,FR
- Département de neurologie
CHU GrenobleUniversité Joseph Fourier - Grenoble IGrenoble,FR
| | - Laurent Vercueil
- GIN, Grenoble Institut des Neurosciences
INSERM : U836CEAUniversité Joseph Fourier - Grenoble ICHU GrenobleUJF - Site Santé La Tronche BP 170 38042 Grenoble Cedex 9,FR
- Département de neurologie
CHU GrenobleUniversité Joseph Fourier - Grenoble IGrenoble,FR
| | - Lorella Minotti
- GIN, Grenoble Institut des Neurosciences
INSERM : U836CEAUniversité Joseph Fourier - Grenoble ICHU GrenobleUJF - Site Santé La Tronche BP 170 38042 Grenoble Cedex 9,FR
- Département de neurologie
CHU GrenobleUniversité Joseph Fourier - Grenoble IGrenoble,FR
| | - Gh. Ali Hossein-Zadeh
- CIPCE, Control and Intelligent Processing Center of Excellence
University of TehranSchool of Electrical and Computer Engineering Tehran 14395-515,IR
| | - Hamid Soltanian-Zadeh
- CIPCE, Control and Intelligent Processing Center of Excellence
University of TehranSchool of Electrical and Computer Engineering Tehran 14395-515,IR
- Radiology Image Analysis Laboratory
Henry Ford Health SystemDetroit, MI 48202,US
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Lai Y, Zhang X, van Drongelen W, Korhman M, Hecox K, Ni Y, He B. Noninvasive cortical imaging of epileptiform activities from interictal spikes in pediatric patients. Neuroimage 2010; 54:244-52. [PMID: 20643212 DOI: 10.1016/j.neuroimage.2010.07.026] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2010] [Revised: 07/02/2010] [Accepted: 07/10/2010] [Indexed: 11/25/2022] Open
Abstract
Improved non-invasive localization of the epileptogenic foci prior to epilepsy surgery would improve surgical outcome in patients with partial seizure disorders. A critical component for the identification of the epileptogenic brain is the analysis of electrophysiological data obtained during ictal activity from prolonged intracranial recordings. The development of a noninvasive means to identify the seizure onset zone (SOZ) would thus play an important role in treating patients with intractable epilepsy. In the present study, we have investigated non-invasive imaging of epileptiform activity in patients with medically intractable epilepsy by means of a cortical potential imaging (CPI) technique. Eight pediatric patients (1M/7F, ages 4-14 years) with intractable partial epilepsy were studied. Each patient had multiple (6 to 14) interictal spikes (IIS) subjected to the CPI analysis. Realistic geometry boundary element head models were built using each individual's MRI in order to maximize the imaging precision. CPI analysis was performed on the IISs, and extrema in the estimated CPI images were compared with SOZs as determined from the ictal electrocorticogram (ECoG) recordings, as well as the resected areas in the patients and surgical outcomes. The distances between the maximum cortical activities of the IISs reflected by the estimated cortical potential distributions and the SOZs were determined to quantitatively evaluate the performance of the CPI in localizing the epileptogenic zone. Ictal ECoG recordings revealed that six patients exhibited a single epileptogenic focus while two patients had multiple foci. In each patient, the CPI results revealed an area of activity overlapping with the SOZs as identified by ictal ECoG. The distance from the extreme of the CPI images at the peak of IIS to the nearest intracranial electrode associated with the onset of the ictal activity was evaluated for each patient and the averaged distance was 4.6mm. In the group of patients studied, the CPI imaged epileptogenic foci were within the resected areas. According to the follow-up of the eight patients included, two were seizure free and six had substantial reduction in seizure frequency. These promising results demonstrate the potential for noninvasive localization of the epileptogenic focus from interictal scalp EEG recordings. Confirmation of our results may have a significant impact on the process of presurgical planning in pediatric patients with intractable epilepsy by dramatically reducing or potentially eliminating the use of intracranial recording.
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Affiliation(s)
- Yuan Lai
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
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Wilke C, van Drongelen W, Kohrman M, He B. Identification of epileptogenic foci from causal analysis of ECoG interictal spike activity. Clin Neurophysiol 2009; 120:1449-56. [PMID: 19616474 DOI: 10.1016/j.clinph.2009.04.024] [Citation(s) in RCA: 59] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2008] [Revised: 03/31/2009] [Accepted: 04/02/2009] [Indexed: 11/26/2022]
Abstract
OBJECTIVE In patients with intractable epilepsy, the use of interictal spikes as surrogate markers of the epileptogenic cortex has generated significant interest. Previous studies have suggested that the cortical generators of the interictal spikes are correlated with the epileptogenic cortex as identified from the ictal recordings. We hypothesize that causal analysis of the functional brain networks during interictal spikes are correlated with the clinically-defined epileptogenic zone. METHODS We employed a time-varying causality measure, the adaptive directed transfer function (ADTF), to identify the cortical sources of the interictal spike activity in eight patients with medically intractable neocortical-onset epilepsy. The results were then compared to the foci identified by the epileptologists. RESULTS In all eight patients, the majority of the ADTF-calculated source activity was observed within the clinically-defined SOZs. Furthermore, in three of the five patients with two separate epileptogenic foci, the calculated source activity was correlated with both cortical sites. CONCLUSIONS The ADTF method identified the cortical sources of the interictal spike activity as originating from the same cortical locations as the recorded ictal activity. SIGNIFICANCE Evaluation of the sources of the cortical networks obtained during interictal spikes may provide information as to the generators underlying the ictal activity.
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Affiliation(s)
- C Wilke
- University of Minnesota, Department of Biomedical Engineering, Minneapolis, MN 55455, USA
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