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Rajaraman RR, Smith RJ, Oana S, Daida A, Shrey DW, Nariai H, Lopour BA, Hussain SA. Computational EEG attributes predict response to therapy for epileptic spasms. Clin Neurophysiol 2024; 163:39-46. [PMID: 38703698 DOI: 10.1016/j.clinph.2024.03.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 03/10/2024] [Accepted: 03/28/2024] [Indexed: 05/06/2024]
Abstract
OBJECTIVE We set out to evaluate whether response to treatment for epileptic spasms is associated with specific candidate computational EEG biomarkers, independent of clinical attributes. METHODS We identified 50 children with epileptic spasms, with pre- and post-treatment overnight video-EEG. After EEG samples were preprocessed in an automated fashion to remove artifacts, we calculated amplitude, power spectrum, functional connectivity, entropy, and long-range temporal correlations (LRTCs). To evaluate the extent to which each feature is independently associated with response and relapse, we conducted logistic and proportional hazards regression, respectively. RESULTS After statistical adjustment for the duration of epileptic spasms prior to treatment, we observed an association between response and stronger baseline and post-treatment LRTCs (P = 0.042 and P = 0.004, respectively), and higher post-treatment entropy (P = 0.003). On an exploratory basis, freedom from relapse was associated with stronger post-treatment LRTCs (P = 0.006) and higher post-treatment entropy (P = 0.044). CONCLUSION This study suggests that multiple EEG features-especially LRTCs and entropy-may predict response and relapse. SIGNIFICANCE This study represents a step toward a more precise approach to measure and predict response to treatment for epileptic spasms.
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Affiliation(s)
- Rajsekar R Rajaraman
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA
| | - Rachel J Smith
- Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Shingo Oana
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA
| | - Atsuro Daida
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA
| | - Daniel W Shrey
- Division of Pediatric Neurology, University of California, Irvine, Irvine, CA, USA; Department of Neurology, Children's Hospital of Orange County, Orange, CA, USA
| | - Hiroki Nariai
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA
| | - Beth A Lopour
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA
| | - Shaun A Hussain
- Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA.
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Zhang Y, Liu L, Ding Y, Chen X, Monsoor T, Daida A, Oana S, Hussain S, Sankar R, Fallah A, Santana-Gomez C, Engel J, Staba RJ, Speier W, Zhang J, Nariai H, Roychowdhury V. PyHFO: lightweight deep learning-powered end-to-end high-frequency oscillations analysis application. J Neural Eng 2024; 21:036023. [PMID: 38722308 PMCID: PMC11135143 DOI: 10.1088/1741-2552/ad4916] [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: 10/18/2023] [Revised: 04/19/2024] [Accepted: 05/09/2024] [Indexed: 05/29/2024]
Abstract
Objective. This study aims to develop and validate an end-to-end software platform, PyHFO, that streamlines the application of deep learning (DL) methodologies in detecting neurophysiological biomarkers for epileptogenic zones from EEG recordings.Approach. We introduced PyHFO, which enables time-efficient high-frequency oscillation (HFO) detection algorithms like short-term energy and Montreal Neurological Institute and Hospital detectors. It incorporates DL models for artifact and HFO with spike classification, designed to operate efficiently on standard computer hardware.Main results. The validation of PyHFO was conducted on three separate datasets: the first comprised solely of grid/strip electrodes, the second a combination of grid/strip and depth electrodes, and the third derived from rodent studies, which sampled the neocortex and hippocampus using depth electrodes. PyHFO demonstrated an ability to handle datasets efficiently, with optimization techniques enabling it to achieve speeds up to 50 times faster than traditional HFO detection applications. Users have the flexibility to employ our pre-trained DL model or use their EEG data for custom model training.Significance. PyHFO successfully bridges the computational challenge faced in applying DL techniques to EEG data analysis in epilepsy studies, presenting a feasible solution for both clinical and research settings. By offering a user-friendly and computationally efficient platform, PyHFO paves the way for broader adoption of advanced EEG data analysis tools in clinical practice and fosters potential for large-scale research collaborations.
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Affiliation(s)
- Yipeng Zhang
- Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, United States of America
| | - Lawrence Liu
- Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, United States of America
| | - Yuanyi Ding
- Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, United States of America
| | - Xin Chen
- Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, United States of America
| | - Tonmoy Monsoor
- Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, United States of America
| | - Atsuro Daida
- Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children’s Hospital, David Geffen School of Medicine, Los Angeles, CA, United States of America
| | - Shingo Oana
- Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children’s Hospital, David Geffen School of Medicine, Los Angeles, CA, United States of America
| | - Shaun Hussain
- Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children’s Hospital, David Geffen School of Medicine, Los Angeles, CA, United States of America
| | - Raman Sankar
- Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children’s Hospital, David Geffen School of Medicine, Los Angeles, CA, United States of America
| | - Aria Fallah
- Department of Neurosurgery, UCLA Medical Center, David Geffen School of Medicine, Los Angeles, CA, United States of America
| | - Cesar Santana-Gomez
- Department of Neurology, UCLA Medical Center, David Geffen School of Medicine, Los Angeles, CA 90095, United States of America
| | - Jerome Engel
- Department of Neurology, UCLA Medical Center, David Geffen School of Medicine, Los Angeles, CA 90095, United States of America
- Department of Neurobiology, University of California, Los Angeles, CA, United States of America
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, United States of America
| | - Richard J Staba
- Department of Neurology, UCLA Medical Center, David Geffen School of Medicine, Los Angeles, CA 90095, United States of America
| | - William Speier
- Department of Radiological Sciences, University of California, Los Angeles, Los Angeles, CA, United States of America
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States of America
| | - Jianguo Zhang
- Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, People’s Republic of China
| | - Hiroki Nariai
- Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children’s Hospital, David Geffen School of Medicine, Los Angeles, CA, United States of America
| | - Vwani Roychowdhury
- Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, United States of America
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Samfira IMA, Galanopoulou AS, Nariai H, Gursky JM, Moshé SL, Bardakjian BL. EEG-based spatiotemporal dynamics of fast ripple networks and hubs in infantile epileptic spasms. Epilepsia Open 2024; 9:122-137. [PMID: 37743321 PMCID: PMC10839371 DOI: 10.1002/epi4.12831] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 09/17/2023] [Indexed: 09/26/2023] Open
Abstract
OBJECTIVE Infantile epileptic spasms (IS) are epileptic seizures that are associated with increased risk for developmental impairments, adult epilepsies, and mortality. Here, we investigated coherence-based network dynamics in scalp EEG of infants with IS to identify frequency-dependent networks associated with spasms. We hypothesized that there is a network of increased fast ripple connectivity during the electrographic onset of clinical spasms, which is distinct from controls. METHODS We retrospectively analyzed peri-ictal and interictal EEG recordings of 14 IS patients. The data was compared with 9 age-matched controls. Wavelet phase coherence (WPC) was computed between 0.2 and 400 Hz. Frequency- and time-dependent brain networks were constructed using this coherence as the strength of connection between two EEG channels, based on graph theory principles. Connectivity was evaluated through global efficiency (GE) and channel-based closeness centrality (CC), over frequency and time. RESULTS GE in the fast ripple band (251-400 Hz) was significantly greater following the onset of spasms in all patients (P < 0.05). Fast ripple networks during the first 10s from spasm onset show enhanced anteroposterior gradient in connectivity (posterior > central > anterior, Kruskal-Wallis P < 0.001), with maximum CC over the centroparietal channels in 10/14 patients. Additionally, this anteroposterior gradient in CC connectivity is observed during spasms but not during the interictal awake or asleep states of infants with IS. In controls, anteroposterior gradient in fast ripple CC was noted during arousals and wakefulness but not during sleep. There was also a simultaneous decrease in GE in the 5-8 Hz range after the onset of spasms (P < 0.05), of unclear biological significance. SIGNIFICANCE We identified an anteroposterior gradient in the CC connectivity of fast ripple hubs during spasms. This anteroposterior gradient observed during spasms is similar to the anteroposterior gradient in the CC connectivity observed in wakefulness or arousals in controls, suggesting that this state change is related to arousal networks.
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Affiliation(s)
- Ioana M. A. Samfira
- Edward S. Rogers Sr. Department of Electrical and Computer EngineeringUniversity of TorontoTorontoOntarioCanada
| | - Aristea S. Galanopoulou
- Saul R. Korey Department of Neurology and Comprehensive Einstein/Montefiore Epilepsy CenterAlbert Einstein College of MedicineBronxNew YorkUSA
- Isabelle Rapin Division of Child NeurologyAlbert Einstein College of MedicineBronxNew YorkUSA
- Dominick P. Purpura Department of NeuroscienceAlbert Einstein College of MedicineBronxNew YorkUSA
| | - Hiroki Nariai
- Department of PediatricsUCLA Mattel Children's HospitalLos AngelesCaliforniaUSA
| | - Jonathan M. Gursky
- Saul R. Korey Department of Neurology and Comprehensive Einstein/Montefiore Epilepsy CenterAlbert Einstein College of MedicineBronxNew YorkUSA
| | - Solomon L. Moshé
- Saul R. Korey Department of Neurology and Comprehensive Einstein/Montefiore Epilepsy CenterAlbert Einstein College of MedicineBronxNew YorkUSA
- Isabelle Rapin Division of Child NeurologyAlbert Einstein College of MedicineBronxNew YorkUSA
- Dominick P. Purpura Department of NeuroscienceAlbert Einstein College of MedicineBronxNew YorkUSA
- Department of PediatricsEinstein College of MedicineBronxNew YorkUSA
| | - Berj L. Bardakjian
- Edward S. Rogers Sr. Department of Electrical and Computer EngineeringUniversity of TorontoTorontoOntarioCanada
- Institute of Biomedical EngineeringUniversity of TorontoTorontoOntarioCanada
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Cserpan D, Guidi G, Alessandri B, Fedele T, Rüegger A, Pisani F, Sarnthein J, Ramantani G. Scalp high-frequency oscillations differentiate neonates with seizures from healthy neonates. Epilepsia Open 2023; 8:1491-1502. [PMID: 37702021 PMCID: PMC10690668 DOI: 10.1002/epi4.12827] [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: 06/29/2023] [Accepted: 09/02/2023] [Indexed: 09/14/2023] Open
Abstract
OBJECTIVE We aimed to investigate (1) whether an automated detector can capture scalp high-frequency oscillations (HFO) in neonates and (2) whether scalp HFO rates can differentiate neonates with seizures from healthy neonates. METHODS We considered 20 neonates with EEG-confirmed seizures and four healthy neonates. We applied a previously validated automated HFO detector to determine scalp HFO rates in quiet sleep. RESULTS Etiology in neonates with seizures included hypoxic-ischemic encephalopathy in 11 cases, structural vascular lesions in 6, and genetic causes in 3. The HFO rates were significantly higher in neonates with seizures (0.098 ± 0.091 HFO/min) than in healthy neonates (0.038 ± 0.025 HFO/min; P = 0.02) with a Hedge's g value of 0.68 indicating a medium effect size. The HFO rate of 0.1 HFO/min/ch yielded the highest Youden index in discriminating neonates with seizures from healthy neonates. In neonates with seizures, etiology, status epilepticus, EEG background activity, and seizure patterns did not significantly impact HFO rates. SIGNIFICANCE Neonatal scalp HFO can be detected automatically and differentiate neonates with seizures from healthy neonates. Our observations have significant implications for neuromonitoring in neonates. This is the first step in establishing neonatal HFO as a biomarker for neonatal seizures.
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Affiliation(s)
- Dorottya Cserpan
- Department of NeuropediatricsUniversity Children's HospitalZurichSwitzerland
| | - Greta Guidi
- Department of NeuropediatricsUniversity Children's HospitalZurichSwitzerland
| | - Beatrice Alessandri
- Department of NeuropediatricsUniversity Children's HospitalZurichSwitzerland
| | - Tommaso Fedele
- Department of NeuropediatricsUniversity Children's HospitalZurichSwitzerland
| | - Andrea Rüegger
- Department of NeuropediatricsUniversity Children's HospitalZurichSwitzerland
| | - Francesco Pisani
- Department of Human Neurosciences, Child Neurology and Psychiatry UnitSapienza University of RomeRomeItaly
| | - Johannes Sarnthein
- Department of NeurosurgeryUniversity Hospital ZurichZurichSwitzerland
- University of ZurichZurichSwitzerland
| | - Georgia Ramantani
- Department of NeuropediatricsUniversity Children's HospitalZurichSwitzerland
- University of ZurichZurichSwitzerland
- Children's Research CenterUniversity Children's HospitalZurichSwitzerland
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Brain Complexity Predicts Response to Adrenocorticotropic Hormone in Infantile Epileptic Spasms Syndrome: A Retrospective Study. Neurol Ther 2022; 12:129-144. [PMID: 36327095 PMCID: PMC9837343 DOI: 10.1007/s40120-022-00412-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 10/10/2022] [Indexed: 11/06/2022] Open
Abstract
INTRODUCTION Infantile epileptic spasms syndrome (IESS) is an age-specific and severe epileptic encephalopathy. Although adrenocorticotropic hormone (ACTH) is currently considered the preferred first-line treatment, it is not always effective and may cause side effects. Therefore, seeking a reliable biomarker to predict the treatment response could benefit clinicians in modifying treatment options. METHODS In this study, the complexities of electroencephalogram (EEG) recordings from 15 control subjects and 40 patients with IESS before and after ACTH therapy were retrospectively reviewed using multiscale entropy (MSE). These 40 patients were divided into responders and nonresponders according to their responses to ACTH. RESULTS The EEG complexities of the patients with IESS were significantly lower than those of the healthy controls. A favorable response to treatment showed increasing complexity in the γ band but exhibited a reduction in the β/α-frequency band, and again significantly elevated in the δ band, wherein the latter was prominent in the parieto-occipital regions in particular. Greater reduction in complexity was significantly linked with poorer prognosis in general. Occipital EEG complexities in the γ band revealed optimized performance in recognizing response to the treatment, corresponding to the area under the receiver operating characteristic curves as 0.8621, while complexities of the δ band served as a fair predictor of unfavorable outcomes globally. CONCLUSION We suggest that optimizing frequency-specific complexities over critical brain regions may be a promising strategy to facilitate predicting treatment response in IESS.
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Buchhalter J, Neuray C, Cheng JY, D’Cruz O, Datta AN, Dlugos D, French J, Haubenberger D, Hulihan J, Klein P, Komorowski RW, Kramer L, Lothe A, Nabbout R, Perucca E, der Ark PV. EEG Parameters as Endpoints in Epilepsy Clinical Trials- An Expert Panel Opinion Paper. Epilepsy Res 2022; 187:107028. [DOI: 10.1016/j.eplepsyres.2022.107028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 08/29/2022] [Accepted: 09/26/2022] [Indexed: 11/30/2022]
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Romero Milà B, Remakanthakurup Sindhu K, Mytinger JR, Shrey DW, Lopour BA. EEG biomarkers for the diagnosis and treatment of infantile spasms. Front Neurol 2022; 13:960454. [PMID: 35968272 PMCID: PMC9366674 DOI: 10.3389/fneur.2022.960454] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 06/28/2022] [Indexed: 11/13/2022] Open
Abstract
Early diagnosis and treatment are critical for young children with infantile spasms (IS), as this maximizes the possibility of the best possible child-specific outcome. However, there are major barriers to achieving this, including high rates of misdiagnosis or failure to recognize the seizures, medication failure, and relapse. There are currently no validated tools to aid clinicians in assessing objective diagnostic criteria, predicting or measuring medication response, or predicting the likelihood of relapse. However, the pivotal role of EEG in the clinical management of IS has prompted many recent studies of potential EEG biomarkers of the disease. These include both visual EEG biomarkers based on human visual interpretation of the EEG and computational EEG biomarkers in which computers calculate quantitative features of the EEG. Here, we review the literature on both types of biomarkers, organized based on the application (diagnosis, treatment response, prediction, etc.). Visual biomarkers include the assessment of hypsarrhythmia, epileptiform discharges, fast oscillations, and the Burden of AmplitudeS and Epileptiform Discharges (BASED) score. Computational markers include EEG amplitude and power spectrum, entropy, functional connectivity, high frequency oscillations (HFOs), long-range temporal correlations, and phase-amplitude coupling. We also introduce each of the computational measures and provide representative examples. Finally, we highlight remaining gaps in the literature, describe practical guidelines for future biomarker discovery and validation studies, and discuss remaining roadblocks to clinical implementation, with the goal of facilitating future work in this critical area.
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Affiliation(s)
- Blanca Romero Milà
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- Department of Electronics and Biomedical Engineering, Universitat de Barcelona, Barcelona, Spain
| | | | - John R. Mytinger
- Division of Pediatric Neurology, Department of Pediatrics, Nationwide Children's Hospital, The Ohio State University, Columbus, OH, United States
| | - Daniel W. Shrey
- Division of Neurology, Children's Hospital Orange County, Orange, CA, United States
- Department of Pediatrics, University of California, Irvine, Irvine, CA, United States
| | - Beth A. Lopour
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- *Correspondence: Beth A. Lopour
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8
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Koshiyama D, Miyakoshi M, Tanaka-Koshiyama K, Sprock J, Light GA. High-power gamma-related delta phase alteration in schizophrenia patients at rest. Psychiatry Clin Neurosci 2022; 76:179-186. [PMID: 35037330 DOI: 10.1111/pcn.13331] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 12/12/2021] [Accepted: 01/03/2022] [Indexed: 11/30/2022]
Abstract
AIM Information processing is supported by the cortico-cortical transmission of neural oscillations across brain regions. Recent studies have demonstrated that the rhythmic firing of neural populations is not random but is governed by interactions with other frequency bands. Specifically, the amplitude of gamma-band oscillations is associated with the phase of lower frequency oscillations in support of short and long-range communications among networks. This cross-frequency relation is thought to reflect the temporal coordination of neural communication. While schizophrenia patients show abnormal oscillatory responses across multiple frequencies at rest, it is unclear whether the functional relationships among frequency bands are intact. This study aimed to characterize the lower frequency (delta/theta, 1-8 Hz) phase and the amplitude of gamma oscillations in healthy subjects and schizophrenia patients at rest. METHODS Low frequency-phase (delta- and theta- band) angles and gamma-band amplitude relationships were assessed in 142 schizophrenia patients and 128 healthy subjects. RESULTS Significant low-frequency phase alteration related to high-power gamma was detected across broadly distributed scalp regions in both healthy subjects and patients. In patients, delta phase synchronization related to high-power gamma was significantly decreased at the frontocentral, right middle temporal, and left temporoparietal electrodes but significantly increased at the left parietal electrode. CONCLUSIONS High-power gamma-related delta phase alteration may reflect a core pathophysiologic abnormality in schizophrenia. Data-driven measures of functional relationships among frequency bands may prove useful in the development of novel therapeutics. Future studies are needed to determine whether these alterations are specific to schizophrenia or appear in other neuropsychiatric patient populations.
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Affiliation(s)
- Daisuke Koshiyama
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
| | - Makoto Miyakoshi
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, California, USA
| | | | - Joyce Sprock
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, California, USA
| | - Gregory A Light
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, California, USA
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Cserpan D, Gennari A, Gaito L, Lo Biundo SP, Tuura R, Sarnthein J, Ramantani G. Scalp HFO rates are higher for larger lesions. Epilepsia Open 2022; 7:496-503. [PMID: 35357778 PMCID: PMC9436296 DOI: 10.1002/epi4.12596] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 03/23/2022] [Accepted: 03/28/2022] [Indexed: 11/30/2022] Open
Abstract
High‐frequency oscillations (HFO) in scalp EEG are a new and promising noninvasive epilepsy biomarker, providing added prognostic value, particularly in pediatric lesional epilepsy. However, it is unclear if lesion characteristics, such as lesion volume, depth, type, and localization, impact scalp HFO rates. We analyzed scalp EEG from 13 children and adolescents with focal epilepsy associated with focal cortical dysplasia (FCD), low‐grade tumors, or hippocampal sclerosis. We applied a validated automated detector to determine HFO rates in bipolar channels. We identified the lesion characteristics in MRI. Larger lesions defined by MRI volumetric analysis corresponded to higher cumulative scalp HFO rates (P = .01) that were detectable in a higher number of channels (P = .05). Both superficial and deep lesions generated HFO detectable in the scalp EEG. Lesion type (FCD vs tumor) and lobar localization (temporal vs extratemporal) did not affect scalp HFO rates in our study. Our observations support that all lesions may generate HFO detectable in scalp EEG, irrespective of their characteristics, whereas larger epileptogenic lesions generate higher scalp HFO rates over larger areas that are thus more accessible to detection. Our study provides crucial insight into scalp HFO detectability in pediatric lesional epilepsy, facilitating their implementation as an epilepsy biomarker in a clinical setting.
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Affiliation(s)
- Dorottya Cserpan
- Department of Neuropediatrics University Children's Hospital Zurich Switzerland
| | - Antonio Gennari
- Department of Neuropediatrics University Children's Hospital Zurich Switzerland
- MR‐Research Centre University Children's Hospital Zurich Switzerland
| | - Luca Gaito
- Department of Neuropediatrics University Children's Hospital Zurich Switzerland
- Department of Neurosurgery University Hospital Zurich Switzerland
| | | | - Ruth Tuura
- MR‐Research Centre University Children's Hospital Zurich Switzerland
- University of Zurich Switzerland
- Children’s Research Centre University Children's Hospital Zurich Switzerland
| | - Johannes Sarnthein
- Department of Neurosurgery University Hospital Zurich Switzerland
- University of Zurich Switzerland
| | - Georgia Ramantani
- Department of Neuropediatrics University Children's Hospital Zurich Switzerland
- University of Zurich Switzerland
- Children’s Research Centre University Children's Hospital Zurich Switzerland
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10
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Wada K, Sonoda M, Firestone E, Sakakura K, Kuroda N, Takayama Y, Iijima K, Iwasaki M, Mihara T, Goto T, Asano E, Miyazaki T. Sevoflurane-based enhancement of phase-amplitude coupling and localization of the epileptogenic zone. Clin Neurophysiol 2022; 134:1-8. [PMID: 34922194 PMCID: PMC8766927 DOI: 10.1016/j.clinph.2021.11.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 10/05/2021] [Accepted: 11/03/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Phase-amplitude coupling between high-frequency (≥150 Hz) and delta (3-4 Hz) oscillations - modulation index (MI) - is a promising, objective biomarker of epileptogenicity. We determined whether sevoflurane anesthesia preferentially enhances this metric within the epileptogenic zone. METHODS This is an observational study of intraoperative electrocorticography data from 621 electrodes chronically implanted into eight patients with drug-resistant, focal epilepsy. All patients were anesthetized with sevoflurane during resective surgery, which subsequently resulted in seizure control. We classified 'removed' and 'retained' brain sites as epileptogenic and non-epileptogenic, respectively. Mixed model analysis determined which anesthetic stage optimized MI-based classification of epileptogenic sites. RESULTS MI increased as a function of anesthetic stage, ranging from baseline (i.e., oxygen alone) to 2.0 minimum alveolar concentration (MAC) of sevoflurane, preferentially at sites showing higher initial MI values. This phenomenon was accentuated just prior to sevoflurane reaching 2.0 MAC, at which time, the odds of a site being classified as epileptogenic were enhanced by 86.6 times for every increase of 1.0 MI. CONCLUSIONS Intraoperative MI best localized the epileptogenic zone immediately before sevoflurane reaching 2.0 MAC in this small cohort of patients. SIGNIFICANCE Prospective, large cohort studies are warranted to determine whether sevoflurane anesthesia can reduce the need for extraoperative, invasive evaluation.
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Affiliation(s)
- Keiko Wada
- Department of Anesthesiology, National Center Hospital, National Center of Neurology and Psychiatry, Kodaira, Tokyo 1878551, Japan,Department of Anesthesiology and Critical Care, Yokohama City University Graduate School of Medicine, Yokohama, 2360004, Japan
| | - Masaki Sonoda
- Department of Pediatrics, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA,Department of Neurosurgery, Yokohama City University Graduate School of Medicine, Yokohama 2360004, Japan
| | - Ethan Firestone
- Department of Pediatrics, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA,Department of Physiology, Wayne State University, Detroit, MI 48201, USA
| | - Kazuki Sakakura
- Department of Pediatrics, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA,Department of Neurosurgery, University of Tsukuba, Tsukuba, 3058575, Japan
| | - Naoto Kuroda
- Department of Pediatrics, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA,Department of Epileptology, Tohoku University Graduate School of Medicine, Sendai 9808575, Japan
| | - Yutaro Takayama
- Department of Neurosurgery, Yokohama City University Graduate School of Medicine, Yokohama 2360004, Japan,Department of Neurosurgery, National Center Hospital, National Center of Neurology and Psychiatry, Kodaira, Tokyo 1878551, Japan
| | - Keiya Iijima
- Department of Neurosurgery, National Center Hospital, National Center of Neurology and Psychiatry, Kodaira, Tokyo 1878551, Japan
| | - Masaki Iwasaki
- Department of Neurosurgery, National Center Hospital, National Center of Neurology and Psychiatry, Kodaira, Tokyo 1878551, Japan
| | - Takahiro Mihara
- Department of Anesthesiology and Critical Care, Yokohama City University Graduate School of Medicine, Yokohama, 2360004, Japan,Department of Health Data Science, Yokohama City University Graduate School of Data Science, Yokohama, 2360027, Japan
| | - Takahisa Goto
- Department of Anesthesiology and Critical Care, Yokohama City University Graduate School of Medicine, Yokohama, 2360004, Japan
| | - Eishi Asano
- Department of Pediatrics, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA,Department of Neurology, Children’s Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, MI 48201, USA,E.A. and T.M. share the senior authorship. Corresponding Authors: Eishi Asano, M.D., Ph.D., M.S. (C.R.D.S.A.), Address: Division of Pediatric Neurology, Children’s Hospital of Michigan, Wayne State University. 3901 Beaubien St., Detroit, MI, 48201, USA, Phone: +1-313-745-5547, FAX: +1-313-745-9435, and Tomoyuki Miyazaki, M.D., Ph.D., Address: Department of Physiology/Anesthesiology, Yokohama City University Graduate School of Medicine. 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, Japan, Phone: +81-45-787-2918, FAX: +81-45-787-2917,
| | - Tomoyuki Miyazaki
- Department of Anesthesiology and Critical Care, Yokohama City University Graduate School of Medicine, Yokohama, 2360004, Japan,Department of Physiology, Yokohama City University Graduate School of Medicine, Yokohama 2360004, Japan,E.A. and T.M. share the senior authorship. Corresponding Authors: Eishi Asano, M.D., Ph.D., M.S. (C.R.D.S.A.), Address: Division of Pediatric Neurology, Children’s Hospital of Michigan, Wayne State University. 3901 Beaubien St., Detroit, MI, 48201, USA, Phone: +1-313-745-5547, FAX: +1-313-745-9435, and Tomoyuki Miyazaki, M.D., Ph.D., Address: Department of Physiology/Anesthesiology, Yokohama City University Graduate School of Medicine. 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, Japan, Phone: +81-45-787-2918, FAX: +81-45-787-2917,
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11
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Windhager PF, Marcu AV, Trinka E, Bathke A, Höller Y. Are High Frequency Oscillations in Scalp EEG Related to Age? Front Neurol 2022; 12:722657. [PMID: 35153968 PMCID: PMC8829347 DOI: 10.3389/fneur.2021.722657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 12/20/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND High-frequency oscillations (HFOs) have received much attention in recent years, particularly in the clinical context. In addition to their application as a marker for pathological changes in patients with epilepsy, HFOs have also been brought into context with several physiological mechanisms. Furthermore, recent studies reported a relation between an increase of HFO rate and age in invasive EEG recordings. The present study aimed to investigate whether this relation can be replicated in scalp-EEG. METHODS We recorded high-density EEG from 11 epilepsy patients at rest as well as during motor performance. Manual detection of HFOs was performed by two independent raters following a standardized protocol. Patients were grouped by age into younger (<25 years) and older (>50 years) participants. RESULTS No significant difference of HFO-rates was found between groups [U = 10.5, p = 0.429, r = 0.3]. CONCLUSIONS Lack of replicability of the age effect of HFOs may be due to the local propagation patterns of age-related HFOs occurring in deep structures. However, limitations such as small sample size, decreased signal-to-noise ratio as compared to invasive recordings, as well as HFO-mimicking artifacts must be considered.
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Affiliation(s)
- Philipp Franz Windhager
- Department of Neurology, Christian-Doppler Medical Centre and Centre for Cognitive Neuroscience, Paracelsus Medical University, Salzburg, Austria,*Correspondence: Philipp Franz Windhager
| | - Adrian V. Marcu
- Department of Neurology, Christian-Doppler Medical Centre and Centre for Cognitive Neuroscience, Paracelsus Medical University, Salzburg, Austria
| | - Eugen Trinka
- Department of Neurology, Christian-Doppler Medical Centre and Centre for Cognitive Neuroscience, Paracelsus Medical University, Salzburg, Austria,Neuroscience Institute, Christian Doppler University Hospital, Paracelsus Medical University, Salzburg, Austria
| | - Arne Bathke
- Department of Mathematics, Paris Lodron University Salzburg, Salzburg, Austria
| | - Yvonne Höller
- Faculty of Psychology, University of Akureyri, Akureyri, Iceland
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12
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Cserpan D, Rosch R, Pietro Lo Biundo S, Sarnthein J, Ramantani G. Variation of scalp EEG high frequency oscillation rate with sleep stage and time spent in sleep in patients with pediatric epilepsy. Clin Neurophysiol 2022; 135:117-125. [DOI: 10.1016/j.clinph.2021.12.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 11/07/2021] [Accepted: 12/14/2021] [Indexed: 12/15/2022]
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13
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Dong Y, Xu R, Zhang Y, Shi Y, Du K, Jia T, Wang J, Wang F. Different Frequency Bands in Various Regions of the Brain Play Different Roles in the Onset and Wake-Sleep Stages of Infantile Spasms. Front Pediatr 2022; 10:878099. [PMID: 35633963 PMCID: PMC9135356 DOI: 10.3389/fped.2022.878099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 04/20/2022] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE The study aimed to identify the signatures of brain networks using electroencephalogram (EEG) in patients with infantile spasms (IS). METHODS Scalp EEGs of subjects with IS were prospectively collected in the first year of life (n = 8; age range 4-8 months; 3 males, 5 females). Ten minutes of ictal and interictal EEGs were clipped and filtered into different EEG frequency bands. The values of each pair of EEG channels were directly compared between ictal with interictal onsets and the sleep-wake phase to calculate IS brain network attributes: characteristic path length (CPL), node degree (ND), clustering coefficient (CC), and betweenness centrality (BC). RESULTS CPL, ND, and CC of the fast waves decreased while BC increased. CPL and BC of the slow waves decreased, while ND and CC increased during the IS ictal onset (P < 0.05). CPL of the alpha decreased, and BC increased during the waking time (P < 0.05). CONCLUSION The transmission capability of the fast waves, the local connectivity, and the defense capability of the slow waves during the IS ictal onset were enhanced. The alpha band played the most important role in both the global and local networks during the waking time. These may represent the brain network signatures of IS.
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Affiliation(s)
- Yan Dong
- Henan Provincial Key Laboratory of Child Brain Injury, Department of Pediatrics, Third Associated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Ruijuan Xu
- Henan Provincial Key Laboratory of Child Brain Injury, Department of Pediatrics, Third Associated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Yaodong Zhang
- Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Henan Neurodevelopment Engineering Research Center for Children, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Yali Shi
- Henan Provincial Key Laboratory of Child Brain Injury, Department of Pediatrics, Third Associated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Kaixian Du
- Henan Provincial Key Laboratory of Child Brain Injury, Department of Pediatrics, Third Associated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Tianming Jia
- Henan Provincial Key Laboratory of Child Brain Injury, Department of Pediatrics, Third Associated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Jun Wang
- Department of Children's Rehabilitation, Third Associated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Fang Wang
- Department of Medical Record Management, Third Associated Hospital of Zheng Zhou University, Zhengzhou, China
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14
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High-frequency oscillations in scalp EEG: A systematic review of methodological choices and clinical findings. Clin Neurophysiol 2022; 137:46-58. [DOI: 10.1016/j.clinph.2021.12.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 12/13/2021] [Accepted: 12/21/2021] [Indexed: 02/08/2023]
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15
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Iimura Y, Mitsuhashi T, Suzuki H, Ueda T, Nishioka K, Otsubo H, Sugano H. Delineation of the epileptogenic zone by Phase-amplitude coupling in patients with Bottom of Sulcus Dysplasia. Seizure 2021; 94:23-25. [PMID: 34837729 DOI: 10.1016/j.seizure.2021.11.006] [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: 08/29/2021] [Revised: 11/17/2021] [Accepted: 11/18/2021] [Indexed: 11/16/2022] Open
Abstract
PURPOSE The removal of the bottom of sulcus dysplasia (BOSD) often includes the gyral crown; however, this method has been controversial. We hypothesized that the epileptogenic zone of the BOSD does not include the gyral crown. To reveal the depth and extent of the epileptogenic zone of the BOSD, we applied the two electrophysiological modalities: (1) the occurrence rate (OR) of high-frequency oscillations (HFOs) and (2) modulation index (MI), reflecting the strength of phase-amplitude coupling between HFOs and slow oscillations. METHODS We investigated the ripples [80-200 Hz] and fast ripples [200-300 Hz]) in HFOs and MI (HFOs [80-300 Hz] and slow oscillations [3-4 Hz]). We opened the sulcus at the BOSD and implanted the subdural electrodes directly over the MRI visible lesion. All patients (n = 3) underwent lesionectomy and the gyral crown was preserved. RESULTS Pathological findings demonstrated focal cortical dysplasia type IIb and seizure freedom was achieved. The OR of the HFOs was not significantly different between the BOSD and the gyral crown. In contrast, the MI between HFOs and slow oscillations in the BOSD was significantly higher than that in the gyral crown. CONCLUSION High MI values distinguished the epileptogenic BOSD from the non-epileptogenic gyral crowns. MI could be a more informative biomarker of epileptogenicity than the OR of HFOs in a subset of patients with the BOSD.
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Affiliation(s)
- Yasushi Iimura
- Department of Neurosurgery, Epilepsy Center, Juntendo University, Tokyo, Japan
| | - Takumi Mitsuhashi
- Department of Neurosurgery, Epilepsy Center, Juntendo University, Tokyo, Japan
| | - Hiroharu Suzuki
- Department of Neurosurgery, Epilepsy Center, Juntendo University, Tokyo, Japan
| | - Tetsuya Ueda
- Department of Neurosurgery, Epilepsy Center, Juntendo University, Tokyo, Japan
| | - Kazuki Nishioka
- Department of Neurosurgery, Epilepsy Center, Juntendo University, Tokyo, Japan
| | - Hiroshi Otsubo
- Department of Neurosurgery, Epilepsy Center, Juntendo University, Tokyo, Japan; Division of Neurology, The Hospital for Sick Children, Toronto, Canada
| | - Hidenori Sugano
- Department of Neurosurgery, Epilepsy Center, Juntendo University, Tokyo, Japan.
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16
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Miyakoshi M, Nariai H, Rajaraman RR, Bernardo D, Shrey DW, Lopour BA, Sim MS, Staba RJ, Hussain SA. Automated preprocessing and phase-amplitude coupling analysis of scalp EEG discriminates infantile spasms from controls during wakefulness. Epilepsy Res 2021; 178:106809. [PMID: 34823159 DOI: 10.1016/j.eplepsyres.2021.106809] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 10/26/2021] [Accepted: 11/02/2021] [Indexed: 10/19/2022]
Abstract
OBJECTIVE Delta-gamma phase-amplitude coupling in EEG is useful for localizing epileptic sources and to evaluate severity in children with infantile spasms. We (1) develop an automated EEG preprocessing pipeline to clean data using artifact subspace reconstruction (ASR) and independent component (IC) analysis (ICA) and (2) evaluate delta-gamma modulation index (MI) as a method to distinguish children with epileptic spasms (cases) from normal controls during sleep and awake. METHODS Using 400 scalp EEG datasets (200 sleep, 200 awake) from 100 subjects, we calculated MI after applying high-pass and line-noise filters (Clean 0), and after ASR followed by either conservative (Clean 1) or stringent (Clean 2) artifactual IC rejection. Classification of cases and controls using MI was evaluated with Receiver Operating Characteristics (ROC) to obtain area under curve (AUC). RESULTS The artifact rejection algorithm reduced raw signal variance by 29-45% and 38-60% for Clean 1 and Clean 2, respectively. MI derived from sleep data, with or without preprocessing, robustly classified the groups (all AUC > 0.98). In contrast, group classification using MI derived from awake data was successful only after Clean 2 (AUC = 0.85). CONCLUSIONS We have developed an automated EEG preprocessing pipeline to perform artifact rejection and quantify delta-gamma modulation index.
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Affiliation(s)
- Makoto Miyakoshi
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, United States
| | - Hiroki Nariai
- David Geffen School of Medicine, Department of Pediatrics, University of California Los Angeles, United States.
| | - Rajsekar R Rajaraman
- David Geffen School of Medicine, Department of Pediatrics, University of California Los Angeles, United States
| | | | - Daniel W Shrey
- Children's Hospital of Orange County, Neurology, University of California, Irvine, Pediatrics, United States
| | - Beth A Lopour
- Henry Samueli School of Engineering, University of California Irvine, United States
| | - Myung Shin Sim
- Division of General Internal Medicine and Health Services Research, Department of Medicine Statistics Core, University of California Los Angeles, United States
| | - Richard J Staba
- David Geffen School of Medicine, Department of Neurology, University of California Los Angeles, United States
| | - Shaun A Hussain
- David Geffen School of Medicine, Department of Pediatrics, University of California Los Angeles, United States
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17
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Bandopadhyay R, Singh T, Ghoneim MM, Alshehri S, Angelopoulou E, Paudel YN, Piperi C, Ahmad J, Alhakamy NA, Alfaleh MA, Mishra A. Recent Developments in Diagnosis of Epilepsy: Scope of MicroRNA and Technological Advancements. BIOLOGY 2021; 10:1097. [PMID: 34827090 PMCID: PMC8615191 DOI: 10.3390/biology10111097] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 10/21/2021] [Accepted: 10/21/2021] [Indexed: 12/18/2022]
Abstract
Epilepsy is one of the most common neurological disorders, characterized by recurrent seizures, resulting from abnormally synchronized episodic neuronal discharges. Around 70 million people worldwide are suffering from epilepsy. The available antiepileptic medications are capable of controlling seizures in around 60-70% of patients, while the rest remain refractory. Poor seizure control is often associated with neuro-psychiatric comorbidities, mainly including memory impairment, depression, psychosis, neurodegeneration, motor impairment, neuroendocrine dysfunction, etc., resulting in poor prognosis. Effective treatment relies on early and correct detection of epileptic foci. Although there are currently a few well-established diagnostic techniques for epilepsy, they lack accuracy and cannot be applied to patients who are unsupportive or harbor metallic implants. Since a single test result from one of these techniques does not provide complete information about the epileptic foci, it is necessary to develop novel diagnostic tools. Herein, we provide a comprehensive overview of the current diagnostic tools of epilepsy, including electroencephalography (EEG) as well as structural and functional neuroimaging. We further discuss recent trends and advances in the diagnosis of epilepsy that will enable more effective diagnosis and clinical management of patients.
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Affiliation(s)
- Ritam Bandopadhyay
- Department of Pharmacology, School of Pharmaceutical Sciences, Lovely Professional University, Phagwara 144411, Punjab, India;
| | - Tanveer Singh
- Department of Neuroscience and Experimental Therapeutics, College of Medicine, Texas A&M University Health Science Center, Bryan, TX 77807, USA;
| | - Mohammed M. Ghoneim
- Department of Pharmacy Practice, College of Pharmacy, AlMaarefa University, Ad Diriyah 13713, Saudi Arabia;
| | - Sultan Alshehri
- Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia;
| | - Efthalia Angelopoulou
- Department of Biological Chemistry, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (E.A.); (C.P.)
| | - Yam Nath Paudel
- Neuropharmacology Research Strength, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Bandar Sunway, Subang Jaya 47500, Selangor, Malaysia;
| | - Christina Piperi
- Department of Biological Chemistry, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (E.A.); (C.P.)
| | - Javed Ahmad
- Department of Pharmaceutics, College of Pharmacy, Najran University, Najran 11001, Saudi Arabia;
| | - Nabil A. Alhakamy
- Department of Pharmaceutics, Faculty of Pharmacy, King Abdulaziz University, Jeddah 21589, Saudi Arabia; (N.A.A.); (M.A.A.)
| | - Mohamed A. Alfaleh
- Department of Pharmaceutics, Faculty of Pharmacy, King Abdulaziz University, Jeddah 21589, Saudi Arabia; (N.A.A.); (M.A.A.)
- Vaccines and Immunotherapy Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Awanish Mishra
- Department of Pharmacology, School of Pharmaceutical Sciences, Lovely Professional University, Phagwara 144411, Punjab, India;
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER)—Guwahati, Changsari, Guwahati 781101, Assam, India
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18
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Trollmann R, Borggräfe I, Müller-Felber W, Brandl U. Pädiatrische epileptische Enzephalopathien mit Manifestation oberhalb des Neugeborenenalters: ein Up-date. KLIN NEUROPHYSIOL 2021. [DOI: 10.1055/a-1528-3511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
ZusammenfassungEntwicklungs-und epileptische Enzephalopathien manifestieren sich überwiegend bereits im Säuglings-und frühen Kleinkindesalter. Mit der neuen ILAE-Klassifikation der Epilepsien konnten epileptische Enzephalopathien sowohl hinsichtlich des elektroklinischen Phänotyps als auch des ätiologischen Spektrums und assoziierter Komorbiditäten genauer definiert werden. Einige elektroklinischer Entitäten wie das West-Syndrom oder das Dravet-Syndrom können auf der Basis ihres Genotyps inzwischen als spezifische Enzephalopathien klassifiziert werden. Das EEG stellt eine wichtige Zusatzdiagnostik in der Abklärung einer epileptischen Enzephalopathie dar. Es hat einen besonderen Stellenwert für die Diagnose von Komplikationen wie z. B. subklinischer Anfälle oder eines Status epilepticus sowie für ein adäquates Therapiemonitoring. Der Betrag fasst anhand ausgewählter pädiatrischer Epilepsiesyndrome aktuelle Aspekte zur Komplexität der pädiatrischen epileptischen Enzephalopathien und den Stellenwert der EEG-Diagnostik zusammen.
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Affiliation(s)
- Regina Trollmann
- Abteilung Neuropädiatrie und Sozialpädiatrisches Zentrum, Kinder-und Jugendklinik am Universitätsklinikum, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen
| | - Ingo Borggräfe
- Abteilung für Pädiatrische Neurologie, Entwicklungsneurologie und Sozialpädiatrie, Dr. von Haunersches Kinderspital, LMU Klinikum München, München
- Interdisziplinäres Epilepsiezentrum, LMU Klinikum München, München
| | - Wolfgang Müller-Felber
- Abteilung für Pädiatrische Neurologie, Entwicklungsneurologie und Sozialpädiatrie, Dr. von Haunersches Kinderspital, LMU Klinikum München, München
| | - Ulrich Brandl
- Klinik für Neuropädiatrie, Universitätsklinikum Jena, Jena
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19
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Wang W, Li H, Yan J, Zhang H, Li X, Zheng S, Wang J, Xing Y, Cheng L, Li D, Lai H, Qu J, Loh HH, Fang F, Yang X. Automatic detection of interictal ripples on scalp EEG to evaluate the effect and prognosis of ACTH therapy in patients with infantile spasms. Epilepsia 2021; 62:2240-2251. [PMID: 34309835 DOI: 10.1111/epi.17018] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 07/12/2021] [Accepted: 07/13/2021] [Indexed: 12/22/2022]
Abstract
OBJECTIVE We aimed to explore the feasibility of using scalp-recorded high-frequency oscillations (HFOs) to evaluate the efficacy and prognosis of adrenocorticotropic hormone (ACTH) treatment in patients with infantile spasms. METHODS Thirty-nine children with infantile spasms were enrolled and divided into seizure-free and non-seizure-free groups after ACTH treatment. Patients who were seizure-free were further divided into relapse and non-relapse subgroups based on the observations made during a 6-month follow-up period. Scalp ripples were detected and compared during the interictal periods before and after 2 weeks of treatment. RESULTS After ACTH treatment, the number and channels of ripples were significantly lower, whereas the percentage decrease in the number, spectral power, and channels of ripples was significantly higher in the seizure-free group than in the non-seizure-free group. In addition, the relapse subgroup showed higher number and spectral power and wider distribution of ripples than did the non-relapse subgroup. Changes in HFOs in terms of number, spectral power, and channel of ripples were closely related to the severity of epilepsy and can indicate disease susceptibility. SIGNIFICANCE Scalp HFOs can be used as an effective biomarker to monitor the effect and evaluate the prognosis of ACTH therapy in patients with infantile spasms.
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Affiliation(s)
- Wei Wang
- Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China.,Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Hua Li
- Department of Neurology, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Jiaqing Yan
- College of Electrical and Control Engineering, North China University of Technology, Beijing, China
| | - Herui Zhang
- Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Xiaonan Li
- Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China.,Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Su Zheng
- Department of Neurology, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Jiaoyang Wang
- Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China.,Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Yue Xing
- Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Lipeng Cheng
- Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China.,Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Donghong Li
- The Third Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Huanling Lai
- Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Junda Qu
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Horace H Loh
- Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Fang Fang
- Department of Neurology, National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Xiaofeng Yang
- Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, China.,Bioland Laboratory Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
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20
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Smith RJ, Hu DK, Shrey DW, Rajaraman R, Hussain SA, Lopour BA. Computational characteristics of interictal EEG as objective markers of epileptic spasms. Epilepsy Res 2021; 176:106704. [PMID: 34218209 DOI: 10.1016/j.eplepsyres.2021.106704] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 05/26/2021] [Accepted: 06/23/2021] [Indexed: 10/21/2022]
Abstract
OBJECTIVE Favorable neurodevelopmental outcomes in epileptic spasms (ES) are tied to early diagnosis and prompt treatment, but uncertainty in the identification of the disease can delay this process. Therefore, we investigated five categories of computational electroencephalographic (EEG) measures as markers of ES. METHODS We measured 1) amplitude, 2) power spectra, 3) Shannon entropy and permutation entropy, 4) long-range temporal correlations, via detrended fluctuation analysis (DFA) and 5) functional connectivity using cross-correlation and phase lag index (PLI). EEG data were analyzed from ES patients (n = 40 patients) and healthy controls (n = 20 subjects), with multiple blinded measurements during wakefulness and sleep for each patient. RESULTS In ES patients, EEG amplitude was significantly higher in all electrodes when compared to controls. Shannon and permutation entropy were lower in ES patients than control subjects. The DFA intercept values in ES patients were significantly higher than control subjects, while DFA exponent values were not significantly different between the groups. EEG functional connectivity networks in ES patients were significantly stronger than controls when based on both cross-correlation and PLI. Significance for all statistical tests was p < 0.05, adjusted for multiple comparisons using the Benjamini-Hochberg procedure as appropriate. Finally, using logistic regression, a multi-attribute classifier was derived that accurately distinguished cases from controls (area under curve of 0.96). CONCLUSIONS Computational EEG features successfully distinguish ES patients from controls in a large, blinded study. SIGNIFICANCE These objective EEG markers, in combination with other clinical factors, may speed the diagnosis and treatment of the disease, thereby improving long-term outcomes.
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Affiliation(s)
- Rachel J Smith
- Department of Biomedical Engineering, University of California, Irvine, CA, United States
| | - Derek K Hu
- Department of Biomedical Engineering, University of California, Irvine, CA, United States
| | - Daniel W Shrey
- Division of Neurology, Children's Hospital of Orange County, Orange, CA, United States; Department of Pediatrics, University of California, Irvine, CA, United States
| | - Rajsekar Rajaraman
- Division of Pediatric Neurology, University of California, Los Angeles, CA, United States
| | - Shaun A Hussain
- Division of Pediatric Neurology, University of California, Los Angeles, CA, United States
| | - Beth A Lopour
- Department of Biomedical Engineering, University of California, Irvine, CA, United States.
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21
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Iimura Y, Sugano H, Mitsuhashi T, Ueda T, Karagiozov K, Abe S, Otsubo H. Case Report: Subtotal Hemispherotomy Modulates the Epileptic Spasms in Aicardi Syndrome. Front Neurol 2021; 12:683729. [PMID: 34248825 PMCID: PMC8264546 DOI: 10.3389/fneur.2021.683729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 06/02/2021] [Indexed: 12/02/2022] Open
Abstract
The mechanism of epileptic spasms (ES) in Aicardi syndrome (AS) remains obscure. We compared intraoperative high-frequency oscillations (HFOs) and phase-amplitude coupling (PAC) before and after subtotal hemispherotomy in a 3-month-old girl with drug-resistant ES secondary to AS. Fetal ultrasonography showing corpus callosum agenesis, bilateral ventricular dilatation, and a large choroid plexus cyst confirmed AS diagnosis. Her ES started when she was 1 month old and had ten series of clustered ES per day despite phenobarbital and vitamin B6 treatment. After subtotal hemispherotomy, her ES dramatically improved. We analyzed two intraoperative electrocorticography modalities: (1), occurrence rate (OR) of HFOs; (2), PAC of HFOs and slow wave bands in the frontal, central, and parietal areas. We hypothesized that HFOs and PAC could be the biomarkers for efficacy of subtotal hemispherotomy in AS with ES. PAC in all three areas and OR of HFOs in the frontal and parietal areas significantly decreased, while OR of HFOs in the central area remained unchanged after subtotal hemispherotomy. We have demonstrated the usefulness of evaluating intraoperative HFOs and PAC to assess subtotal hemispherotomy effectiveness in AS patients with ES. Disconnecting the thalamocortical and subcortical pathways in the epileptic network plays a role in controlling ES generation.
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Affiliation(s)
- Yasushi Iimura
- Department of Neurosurgery, Epilepsy Center, Juntendo University, Tokyo, Japan
| | - Hidenori Sugano
- Department of Neurosurgery, Epilepsy Center, Juntendo University, Tokyo, Japan
| | - Takumi Mitsuhashi
- Department of Neurosurgery, Epilepsy Center, Juntendo University, Tokyo, Japan
| | - Tetsuya Ueda
- Department of Neurosurgery, Epilepsy Center, Juntendo University, Tokyo, Japan
| | - Kostadin Karagiozov
- Department of Neurosurgery, Epilepsy Center, Juntendo University, Tokyo, Japan
| | - Shimpei Abe
- Department of Pediatrics, Epilepsy Center, Juntendo University, Tokyo, Japan
| | - Hiroshi Otsubo
- Department of Neurosurgery, Epilepsy Center, Juntendo University, Tokyo, Japan.,Division of Neurology, The Hospital for Sick Children, Toronto, ON, Canada
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22
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Kobayashi K, Shibata T, Tsuchiya H, Akiyama T. Exclusion of the Possibility of "False Ripples" From Ripple Band High-Frequency Oscillations Recorded From Scalp Electroencephalogram in Children With Epilepsy. Front Hum Neurosci 2021; 15:696882. [PMID: 34211382 PMCID: PMC8239160 DOI: 10.3389/fnhum.2021.696882] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 05/24/2021] [Indexed: 11/24/2022] Open
Abstract
Aim Ripple-band epileptic high-frequency oscillations (HFOs) can be recorded by scalp electroencephalography (EEG), and tend to be associated with epileptic spikes. However, there is a concern that the filtration of steep waveforms such as spikes may cause spurious oscillations or “false ripples.” We excluded such possibility from at least some ripples by EEG differentiation, which, in theory, enhances high-frequency signals and does not generate spurious oscillations or ringing. Methods The subjects were 50 pediatric patients, and ten consecutive spikes during sleep were selected for each patient. Five hundred spike data segments were initially reviewed by two experienced electroencephalographers using consensus to identify the presence or absence of ripples in the ordinary filtered EEG and an associated spectral blob in time-frequency analysis (Session A). These EEG data were subjected to numerical differentiation (the second derivative was denoted as EEG″). The EEG″ trace of each spike data segment was shown to two other electroencephalographers who judged independently whether there were clear ripple oscillations or uncertain ripple oscillations or an absence of oscillations (Session B). Results In Session A, ripples were identified in 57 spike data segments (Group A-R), but not in the other 443 data segments (Group A-N). In Session B, both reviewers identified clear ripples (strict criterion) in 11 spike data segments, all of which were in Group A-R (p < 0.0001 by Fisher’s exact test). When the extended criterion that included clear and/or uncertain ripples was used in Session B, both reviewers identified 25 spike data segments that fulfilled the criterion: 24 of these were in Group A-R (p < 0.0001). Discussion We have demonstrated that real ripples over scalp spikes exist in a certain proportion of patients. Ripples that were visualized consistently using both ordinary filters and the EEG″ method should be true, but failure to clarify ripples using the EEG″ method does not mean that true ripples are absent. Conclusion The numerical differentiation of EEG data provides convincing evidence that HFOs were detected in terms of the presence of such unusually fast oscillations over the scalp and the importance of this electrophysiological phenomenon.
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Affiliation(s)
- Katsuhiro Kobayashi
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital, Okayama, Japan
| | - Takashi Shibata
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital, Okayama, Japan
| | - Hiroki Tsuchiya
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital, Okayama, Japan
| | - Tomoyuki Akiyama
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital, Okayama, Japan
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23
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Oguri M, Okanishi T, Kanai S, Baba S, Nishimura M, Ogo K, Himoto T, Okanari K, Maegaki Y, Enoki H, Fujimoto A. Phase Lag Analyses on Ictal Scalp Electroencephalography May Predict Outcomes of Corpus Callosotomy for Epileptic Spasms. Front Neurol 2021; 11:576087. [PMID: 33424739 PMCID: PMC7793812 DOI: 10.3389/fneur.2020.576087] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 11/11/2020] [Indexed: 11/13/2022] Open
Abstract
Objective: We aimed to clarify the patterns of ictal power and phase lag among bilateral hemispheres on scalp electroencephalography (EEG) recorded pre-operatively during epileptic spasms (ESs) and the correlation with the outcomes following corpus callosotomy. Methods: We enrolled 17 patients who underwent corpus callosotomy for ESs before 20 years of age. After corpus callosotomy, seven patients did not experience further ESs (favorable outcome group), and the remaining 10 patients had ongoing ESs (unfavorable outcome group). We used pre-operative scalp EEG data from monopolar montages using the average reference. The relative power spectrum (PS), ictal power laterality (IPL) among the hemispheres, and phase lag, calculated by the cross-power spectrum (CPS) among symmetrical electrodes (i.e., F3 and F4), were analyzed in the EEG data of ESs from 143 pre-operative scalp video-EEG records. Analyses were conducted separately in each frequency band from the delta, theta, alpha, beta, and gamma range. We compared the means of those data in each patient between favorable and unfavorable outcome groups. Results: Among all frequency bands, no significant differences were seen in the individual mean relative PSs in the favorable and unfavorable outcome group. Although the mean IPLs in each patient tended to be high in the unfavorable outcome group, no significant differences were found. The mean CPSs in the delta, theta, and gamma frequency bands were significantly higher in the unfavorable than in the favorable outcome group. Using the Youden index, the optimal cutoff points of those mean CPS values for unfavorable outcomes were 64.00 in the delta band (sensitivity: 100%, specificity: 80%), 74.20 in the theta band (100, 80%), and 82.05 in the gamma band (100, 80%). Subanalyses indicated that those CPS differences originated from pairs of symmetrical electrodes in the bilateral frontal and temporal areas. Significance: Ictal power and laterality of the ictal power in each frequency band were not associated with the outcomes of CC; however, the phase lags seen in the delta, theta, and gamma frequency bands were larger in the unfavorable than in the favorable outcome group. The phase lags may predict outcomes of CC for ESs on pre-surgical scalp-ictal EEGs.
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Affiliation(s)
- Masayoshi Oguri
- Department of Medical Technology, Kagawa Prefectural University of Health Sciences, Takamatsu, Japan
| | - Tohru Okanishi
- Division of Child Neurology, Faculty of Medicine, Institute of Neurological Sciences, Tottori University, Yonago, Japan.,Department of Child Neurology, Seirei-Hamamatsu General Hospital, Hamamatsu, Japan
| | - Sotaro Kanai
- Division of Child Neurology, Faculty of Medicine, Institute of Neurological Sciences, Tottori University, Yonago, Japan.,Department of Child Neurology, Seirei-Hamamatsu General Hospital, Hamamatsu, Japan
| | - Shimpei Baba
- Department of Child Neurology, Seirei-Hamamatsu General Hospital, Hamamatsu, Japan
| | - Mitsuyo Nishimura
- Department of Clinical Laboratory, University of Tsukuba Hospital, Tsukuba, Japan
| | - Kaoru Ogo
- Department of Medical Technology, Kagawa Prefectural University of Health Sciences, Takamatsu, Japan
| | - Takashi Himoto
- Department of Medical Technology, Kagawa Prefectural University of Health Sciences, Takamatsu, Japan
| | - Kazuo Okanari
- Department of Pediatrics, Faculty of Medicine, Oita University, Yufu, Japan
| | - Yoshihiro Maegaki
- Division of Child Neurology, Faculty of Medicine, Institute of Neurological Sciences, Tottori University, Yonago, Japan
| | - Hideo Enoki
- Department of Child Neurology, Seirei-Hamamatsu General Hospital, Hamamatsu, Japan
| | - Ayataka Fujimoto
- Comprehensive Epilepsy Center, Seirei-Hamamatsu General Hospital, Hamamatsu, Japan
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