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Dmytriw AA, Hadjinicolaou A, Ntolkeras G, Tamilia E, Pesce M, Berto LF, Grant PE, Pang E, Ahtam B. Magnetoencephalography for the pediatric population, indications, acquisition and interpretation for the clinician. Neuroradiol J 2024:19714009241260801. [PMID: 38864180 DOI: 10.1177/19714009241260801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2024] Open
Abstract
Magnetoencephalography (MEG) is an imaging technique that enables the assessment of cortical activity via direct measures of neurophysiology. It is a non-invasive and passive technique that is completely painless. MEG has gained increasing prominence in the field of pediatric neuroimaging. This dedicated review article for the pediatric population summarizes the fundamental technical and clinical aspects of MEG for the clinician. We discuss methods tailored for children to improve data quality, including child-friendly MEG facility environments and strategies to mitigate motion artifacts. We provide an in-depth overview on accurate localization of neural sources and different analysis methods, as well as data interpretation. The contemporary platforms and approaches of two quaternary pediatric referral centers are illustrated, shedding light on practical implementations in clinical settings. Finally, we describe the expanding clinical applications of MEG, including its pivotal role in presurgical evaluation of epilepsy patients, presurgical mapping of eloquent cortices (somatosensory and motor cortices, visual and auditory cortices, lateralization of language), its emerging relevance in autism spectrum disorder research and potential future clinical applications, and its utility in assessing mild traumatic brain injury. In conclusion, this review serves as a comprehensive resource of clinicians as well as researchers, offering insights into the evolving landscape of pediatric MEG. It discusses the importance of technical advancements, data acquisition strategies, and expanding clinical applications in harnessing the full potential of MEG to study neurological conditions in the pediatric population.
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Affiliation(s)
- Adam A Dmytriw
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA
- Division of Neuroradiology, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Aristides Hadjinicolaou
- Division of Neurology, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Department of Neurology, Division of Epilepsy and Clinical Neurophysiology, Boston Children's Hospital, Boston, MA, USA
| | - Georgios Ntolkeras
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - Eleonora Tamilia
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - Matthew Pesce
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - Laura F Berto
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - P Ellen Grant
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - Elizabeth Pang
- Division of Neurology, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Banu Ahtam
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
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Wang Z, Guo J, van 't Klooster M, Hoogteijling S, Jacobs J, Zijlmans M. Prognostic Value of Complete Resection of the High-Frequency Oscillation Area in Intracranial EEG: A Systematic Review and Meta-Analysis. Neurology 2024; 102:e209216. [PMID: 38560817 PMCID: PMC11175645 DOI: 10.1212/wnl.0000000000209216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 01/12/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND AND OBJECTIVES High-frequency oscillations (HFOs; ripples 80-250 Hz; fast ripples [FRs] 250-500 Hz) recorded with intracranial electrodes generated excitement and debate about their potential to localize epileptogenic foci. We performed a systematic review and meta-analysis on the prognostic value of complete resection of the HFOs-area (crHFOs-area) for epilepsy surgical outcome in intracranial EEG (iEEG) accessing multiple subgroups. METHODS We searched PubMed, Embase, and Web of Science for original research from inception to October 27, 2022. We defined favorable surgical outcome (FSO) as Engel class I, International League Against Epilepsy class 1, or seizure-free status. The prognostic value of crHFOs-area for FSO was assessed by (1) the pooled FSO proportion after crHFOs-area; (2) FSO for crHFOs-area vs without crHFOs-area; and (3) the predictive performance. We defined high combined prognostic value as FSO proportion >80% + FSO crHFOs-area >without crHFOs-area + area under the curve (AUC) >0.75 and examined this for the clinical subgroups (study design, age, diagnostic type, HFOs-identification method, HFOs-rate thresholding, and iEEG state). Temporal lobe epilepsy (TLE) was compared with extra-TLE through dichotomous variable analysis. Individual patient analysis was performed for sex, affected hemisphere, MRI findings, surgery location, and pathology. RESULTS Of 1,387 studies screened, 31 studies (703 patients) met our eligibility criteria. Twenty-seven studies (602 patients) analyzed FRs and 20 studies (424 patients) ripples. Pooled FSO proportion after crHFOs-area was 81% (95% CI 76%-86%) for FRs and 82% (73%-89%) for ripples. Patients with crHFOs-area achieved more often FSO than those without crHFOs-area (FRs odds ratio [OR] 6.38, 4.03-10.09, p < 0.001; ripples 4.04, 2.32-7.04, p < 0.001). The pooled AUCs were 0.81 (0.77-0.84) for FRs and 0.76 (0.72-0.79) for ripples. Combined prognostic value was high in 10 subgroups: retrospective, children, long-term iEEG, threshold (FRs and ripples) and automated detection and interictal (FRs). FSO after complete resection of FRs-area (crFRs-area) was achieved less often in people with TLE than extra-TLE (OR 0.37, 0.15-0.89, p = 0.006). Individual patient analyses showed that crFRs-area was seen more in patients with FSO with than without MRI lesions (p = 0.02 after multiple correction). DISCUSSION Complete resection of the brain area with HFOs is associated with good postsurgical outcome. Its prognostic value holds, especially for FRs, for various subgroups. The use of HFOs for extra-TLE patients requires further evidence.
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Affiliation(s)
- Ziyi Wang
- From the Department of Neurology and Neurosurgery (Z.W., J.G., M.v.t.K., S.H., M.Z.), University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Part of ERN EpiCARE, the Netherlands; Department of Pediatrics (J.J.), University of Calgary, Alberta Children's Hospital, Calgary, Canada; and Stichting Epilepsie Instellingen Nederland (SEIN) (M.Z.), Heemstede, the Netherlands
| | - Jiaojiao Guo
- From the Department of Neurology and Neurosurgery (Z.W., J.G., M.v.t.K., S.H., M.Z.), University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Part of ERN EpiCARE, the Netherlands; Department of Pediatrics (J.J.), University of Calgary, Alberta Children's Hospital, Calgary, Canada; and Stichting Epilepsie Instellingen Nederland (SEIN) (M.Z.), Heemstede, the Netherlands
| | - Maryse van 't Klooster
- From the Department of Neurology and Neurosurgery (Z.W., J.G., M.v.t.K., S.H., M.Z.), University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Part of ERN EpiCARE, the Netherlands; Department of Pediatrics (J.J.), University of Calgary, Alberta Children's Hospital, Calgary, Canada; and Stichting Epilepsie Instellingen Nederland (SEIN) (M.Z.), Heemstede, the Netherlands
| | - Sem Hoogteijling
- From the Department of Neurology and Neurosurgery (Z.W., J.G., M.v.t.K., S.H., M.Z.), University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Part of ERN EpiCARE, the Netherlands; Department of Pediatrics (J.J.), University of Calgary, Alberta Children's Hospital, Calgary, Canada; and Stichting Epilepsie Instellingen Nederland (SEIN) (M.Z.), Heemstede, the Netherlands
| | - Julia Jacobs
- From the Department of Neurology and Neurosurgery (Z.W., J.G., M.v.t.K., S.H., M.Z.), University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Part of ERN EpiCARE, the Netherlands; Department of Pediatrics (J.J.), University of Calgary, Alberta Children's Hospital, Calgary, Canada; and Stichting Epilepsie Instellingen Nederland (SEIN) (M.Z.), Heemstede, the Netherlands
| | - Maeike Zijlmans
- From the Department of Neurology and Neurosurgery (Z.W., J.G., M.v.t.K., S.H., M.Z.), University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Part of ERN EpiCARE, the Netherlands; Department of Pediatrics (J.J.), University of Calgary, Alberta Children's Hospital, Calgary, Canada; and Stichting Epilepsie Instellingen Nederland (SEIN) (M.Z.), Heemstede, the Netherlands
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Geller AS, Teale P, Kronberg E, Ebersole JS. Magnetoencephalography for Epilepsy Presurgical Evaluation. Curr Neurol Neurosci Rep 2024; 24:35-46. [PMID: 38148387 DOI: 10.1007/s11910-023-01328-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/13/2023] [Indexed: 12/28/2023]
Abstract
PURPOSE OF THE REVIEW Magnetoencephalography (MEG) is a functional neuroimaging technique that records neurophysiology data with millisecond temporal resolution and localizes it with subcentimeter accuracy. Its capability to provide high resolution in both of these domains makes it a powerful tool both in basic neuroscience as well as clinical applications. In neurology, it has proven useful in its ability to record and localize epileptiform activity. Epilepsy workup typically begins with scalp electroencephalography (EEG), but in many situations, EEG-based localization of the epileptogenic zone is inadequate. The complementary sensitivity of MEG can be crucial in such cases, and MEG has been adopted at many centers as an important resource in building a surgical hypothesis. In this paper, we review recent work evaluating the extent of MEG influence of presurgical evaluations, novel analyses of MEG data employed in surgical workup, and new MEG instrumentation that will likely affect the field of clinical MEG. RECENT FINDINGS MEG consistently contributes to presurgical evaluation and these contributions often change the plan for epilepsy surgery. Extensive work has been done to develop new analytic methods for localizing the source of epileptiform activity with MEG. Systems using optically pumped magnetometry (OPM) have been successfully deployed to record and localize epileptiform activity. MEG remains an important noninvasive tool for epilepsy presurgical evaluation. Continued improvements in analytic methodology will likely increase the diagnostic yield of the test. Novel instrumentation with OPM may contribute to this as well, and may increase accessibility of MEG by decreasing cost.
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Affiliation(s)
- Aaron S Geller
- Department of Neurology, CU Anschutz Medical School, Aurora, CO, USA.
| | - Peter Teale
- Department of Neurology, CU Anschutz Medical School, Aurora, CO, USA
| | - Eugene Kronberg
- Department of Neurology, CU Anschutz Medical School, Aurora, CO, USA
| | - John S Ebersole
- Department of Neurology, Atlantic Neuroscience Institute, Summit, NJ, USA
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Chericoni A, Ricci L, Ntolkeras G, Billardello R, Stone SSD, Madsen JR, Papadelis C, Grant PE, Pearl PL, Taffoni F, Rotenberg A, Tamilia E. Sleep Spindle Generation Before and After Epilepsy Surgery: A Source Imaging Study in Children with Drug-Resistant Epilepsy. Brain Topogr 2024; 37:88-101. [PMID: 37737957 DOI: 10.1007/s10548-023-01007-1] [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: 06/22/2023] [Accepted: 09/09/2023] [Indexed: 09/23/2023]
Abstract
INTRODUCTION Literature lacks studies investigating the cortical generation of sleep spindles in drug-resistant epilepsy (DRE) and how they evolve after resection of the epileptogenic zone (EZ). Here, we examined sleep EEGs of children with focal DRE who became seizure-free after focal epilepsy surgery, and aimed to investigate the changes in the spindle generation before and after the surgery using low-density scalp EEG and electrical source imaging (ESI). METHODS We analyzed N2-sleep EEGs from 19 children with DRE before and after surgery. We identified slow (8-12 Hz) and fast spindles (13-16 Hz), computed their spectral features and cortical generators through ESI and computed their distance from the EZ and irritative zone (IZ). We performed two-way ANOVA testing the effect of spindle type (slow vs. fast) and surgical phase (pre-surgery vs. post-surgery) on each feature. RESULTS Power, frequency and cortical activation of slow spindles increased after surgery (p < 0.005), while this was not seen for fast spindles. Before surgery, the cortical generators of slow spindles were closer to the EZ (57.3 vs. 66.2 mm, p = 0.007) and IZ (41.3 vs. 55.5 mm, p = 0.02) than fast spindle generators. CONCLUSIONS Our data indicate alterations in the EEG slow spindles after resective epilepsy surgery. Fast spindle generation on the contrary did not change after surgery. Although the study is limited by its retrospective nature, lack of healthy controls, and reduced cortical spatial sampling, our findings suggest a spatial relationship between the slow spindles and the epileptogenic generators.
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Affiliation(s)
- Assia Chericoni
- Fetal Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Lorenzo Ricci
- Department of Medicine and Surgery, Research Unit of Neurology, Neurobiology, Neurophysiology, University Campus Bio-Medico di Roma, Rome, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico di Roma, Via Alvaro del Portillo, 200, 00128, Rome, Italy
| | - Georgios Ntolkeras
- Fetal Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Roberto Billardello
- Fetal Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Advanced Robotics and Human-Centred Technologies - CREO Lab, Campus Bio-Medico di Roma, Rome, Italy
| | - Scellig S D Stone
- Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, USA
| | - Joseph R Madsen
- Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, USA
| | - Christos Papadelis
- Jane and John Justin Neurosciences Center, Cook children's Health Care System, Boston, TX, USA
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA
| | - P Ellen Grant
- Fetal Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Phillip L Pearl
- Division of Epilepsy and Clinical Neurophysiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Fabrizio Taffoni
- Advanced Robotics and Human-Centred Technologies - CREO Lab, Campus Bio-Medico di Roma, Rome, Italy
| | - Alexander Rotenberg
- Division of Epilepsy and Clinical Neurophysiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Eleonora Tamilia
- Fetal Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
- Division of Epilepsy and Clinical Neurophysiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
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Shin HJ, Kim SH, Kang HC, Lee JS, Kim HD. Surgical Treatment of Epilepsy with Bilateral MRI Abnormalities. World Neurosurg 2023; 180:e37-e45. [PMID: 37495100 DOI: 10.1016/j.wneu.2023.07.062] [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: 03/18/2023] [Revised: 07/12/2023] [Accepted: 07/13/2023] [Indexed: 07/28/2023]
Abstract
OBJECTIVE To investigate the surgical outcomes of patients with drug-resistant epilepsy and bilateral brain magnetic resonance imaging (MRI) abnormalities who had undergone various epilepsy surgeries. METHODS Patients with drug-resistant epilepsy and bilateral brain abnormalities on MRI who underwent epilepsy surgery at the Severance Children's Hospital between October 2003 and December 2021 were included. The age of seizure onset was 18 years or younger. Engel's classification was used to assess seizure outcomes at 1, 2, and 5 years after surgery. RESULTS A total of 40 patients met the inclusion criteria. The median age at surgery was 10.9 years (interquartile range [IQR] 6.9-15.1); the median interval to surgery was 7.1 years (IQR 2.7-11.5). One year after surgery, a favorable outcome of Engel class I-II was observed in 53% (21/40) of patients. At the 2- and 5-year follow-ups, 56% (20/36) and 63% (17/27) of patients showed good postoperative outcomes, respectively. CONCLUSIONS Approximately, half of the patients with bilateral brain MRI abnormalities achieved seizure freedom after epilepsy surgery. The existence of bilateral brain MRI abnormalities should not hinder resective epilepsy surgery.
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Affiliation(s)
- Hui Jin Shin
- Division of Pediatric Neurology, Department of Pediatrics, Epilepsy Research Institute, Severance Children's Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Se Hee Kim
- Division of Pediatric Neurology, Department of Pediatrics, Epilepsy Research Institute, Severance Children's Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Hoon-Chul Kang
- Division of Pediatric Neurology, Department of Pediatrics, Epilepsy Research Institute, Severance Children's Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Joon Soo Lee
- Division of Pediatric Neurology, Department of Pediatrics, Epilepsy Research Institute, Severance Children's Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Heung Dong Kim
- Division of Pediatric Neurology, Department of Pediatrics, Epilepsy Research Institute, Severance Children's Hospital, Yonsei University College of Medicine, Seoul, Korea; Department of Pediatrics, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.
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Owen TW, Janiukstyte V, Hall GR, Chowdhury FA, Diehl B, McEvoy A, Miserocchi A, de Tisi J, Duncan JS, Rugg-Gunn F, Wang Y, Taylor PN. Interictal magnetoencephalography abnormalities to guide intracranial electrode implantation and predict surgical outcome. Brain Commun 2023; 5:fcad292. [PMID: 37953844 PMCID: PMC10636564 DOI: 10.1093/braincomms/fcad292] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 08/24/2023] [Accepted: 10/24/2023] [Indexed: 11/14/2023] Open
Abstract
Intracranial EEG is the gold standard technique for epileptogenic zone localization but requires a preconceived hypothesis of the location of the epileptogenic tissue. This placement is guided by qualitative interpretations of seizure semiology, MRI, EEG and other imaging modalities, such as magnetoencephalography. Quantitative abnormality mapping using magnetoencephalography has recently been shown to have potential clinical value. We hypothesized that if quantifiable magnetoencephalography abnormalities were sampled by intracranial EEG, then patients' post-resection seizure outcome may be better. Thirty-two individuals with refractory neocortical epilepsy underwent magnetoencephalography and subsequent intracranial EEG recordings as part of presurgical evaluation. Eyes-closed resting-state interictal magnetoencephalography band power abnormality maps were derived from 70 healthy controls as a normative baseline. Magnetoencephalography abnormality maps were compared to intracranial EEG electrode implantation, with the spatial overlap of intracranial EEG electrode placement and cerebral magnetoencephalography abnormalities recorded. Finally, we assessed if the implantation of electrodes in abnormal tissue and subsequent resection of the strongest abnormalities determined by magnetoencephalography and intracranial EEG corresponded to surgical success. We used the area under the receiver operating characteristic curve as a measure of effect size. Intracranial electrodes were implanted in brain tissue with the most abnormal magnetoencephalography findings-in individuals that were seizure-free postoperatively (T = 3.9, P = 0.001) but not in those who did not become seizure-free. The overlap between magnetoencephalography abnormalities and electrode placement distinguished surgical outcome groups moderately well (area under the receiver operating characteristic curve = 0.68). In isolation, the resection of the strongest abnormalities as defined by magnetoencephalography and intracranial EEG separated surgical outcome groups well, area under the receiver operating characteristic curve = 0.71 and area under the receiver operating characteristic curve = 0.74, respectively. A model incorporating all three features separated surgical outcome groups best (area under the receiver operating characteristic curve = 0.80). Intracranial EEG is a key tool to delineate the epileptogenic zone and help render individuals seizure-free postoperatively. We showed that data-driven abnormality maps derived from resting-state magnetoencephalography recordings demonstrate clinical value and may help guide electrode placement in individuals with neocortical epilepsy. Additionally, our predictive model of postoperative seizure freedom, which leverages both magnetoencephalography and intracranial EEG recordings, could aid patient counselling of expected outcome.
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Affiliation(s)
- Thomas W Owen
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
| | - Vytene Janiukstyte
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
| | - Gerard R Hall
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
| | - Fahmida A Chowdhury
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Beate Diehl
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Andrew McEvoy
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Anna Miserocchi
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Jane de Tisi
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - John S Duncan
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Fergus Rugg-Gunn
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
| | - Yujiang Wang
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Peter N Taylor
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
- UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- National Hospital for Neurology & Neurosurgery, London WC1N 3BG, UK
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
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Chikara RK, Jahromi S, Tamilia E, Madsen JR, Stufflebeam SM, Pearl PL, Papadelis C. Electromagnetic source imaging predicts surgical outcome in children with focal cortical dysplasia. Clin Neurophysiol 2023; 153:88-101. [PMID: 37473485 PMCID: PMC10528204 DOI: 10.1016/j.clinph.2023.06.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 05/25/2023] [Accepted: 06/15/2023] [Indexed: 07/22/2023]
Abstract
OBJECTIVE To evaluate the diagnostic accuracy of electromagnetic source imaging (EMSI) in localizing spikes and predict surgical outcome in children with drug resistant epilepsy (DRE) due to focal cortical dysplasia (FCD). METHODS We retrospectively analyzed magnetoencephalography (MEG) and high-density (HD-EEG) data from 23 children with FCD-associated DRE who underwent intracranial EEG and surgery. We localized spikes using equivalent current dipole (ECD) fitting, dipole clustering, and dynamical statistical parametric mapping (dSPM) on EMSI, electric source imaging (ESI), and magnetic source imaging (MSI). We calculated the distance from the seizure onset zone (DSOZ) and resection (DRES). We estimated receiver operating characteristic (ROC) curves with Youden's index (J) to predict outcome. RESULTS EMSI presented shorter DSOZ (15.18 ± 9.06 mm) and DRES (8.56 ± 6.24 mm) compared to ESI (DSOZ: 25.04 ± 16.20 mm, p < 0.009; DRES: 18.88 ± 17.30 mm, p < 0.03) and MSI (DSOZ: 23.37 ± 8.98 mm, p < 0.03; DRES: 15.51 ± 10.11 mm, p < 0.02) for clustering in patients with good outcome. Clustering showed shorter DSOZ and DRES compared to ECD fitting and dSPM (p < 0.05). EMSI had higher performance as outcome predictor (J = 70.63%) compared to ESI (J = 41.27%) and MSI (J = 33.33%) for clustering. CONCLUSIONS EMSI provides superior localization and improved predictive performance than individual modalities. SIGNIFICANCE EMSI can help the surgical planning and facilitate the localization of epileptogenic foci.
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Affiliation(s)
- Rupesh Kumar Chikara
- Jane and John Justin Institute for Mind Health, Neuroscience Research, Cook Children's Health Care System, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA
| | - Saeed Jahromi
- Jane and John Justin Institute for Mind Health, Neuroscience Research, Cook Children's Health Care System, Fort Worth, TX, USA; Department of Bioengineering, 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
| | - Joseph R Madsen
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Steve M Stufflebeam
- Athinoula Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Phillip L Pearl
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Christos Papadelis
- Jane and John Justin Institute for Mind Health, Neuroscience Research, Cook Children's Health Care System, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA; School of Medicine, Texas Christian University, Fort Worth, TX, USA.
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8
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Corona L, Tamilia E, Perry MS, Madsen JR, Bolton J, Stone SSD, Stufflebeam SM, Pearl PL, Papadelis C. Non-invasive mapping of epileptogenic networks predicts surgical outcome. Brain 2023; 146:1916-1931. [PMID: 36789500 PMCID: PMC10151194 DOI: 10.1093/brain/awac477] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 11/03/2022] [Accepted: 11/30/2022] [Indexed: 02/16/2023] Open
Abstract
Epilepsy is increasingly considered a disorder of brain networks. Studying these networks with functional connectivity can help identify hubs that facilitate the spread of epileptiform activity. Surgical resection of these hubs may lead patients who suffer from drug-resistant epilepsy to seizure freedom. Here, we aim to map non-invasively epileptogenic networks, through the virtual implantation of sensors estimated with electric and magnetic source imaging, in patients with drug-resistant epilepsy. We hypothesize that highly connected hubs identified non-invasively with source imaging can predict the epileptogenic zone and the surgical outcome better than spikes localized with conventional source localization methods (dipoles). We retrospectively analysed simultaneous high-density electroencephalography (EEG) and magnetoencephalography data recorded from 37 children and young adults with drug-resistant epilepsy who underwent neurosurgery. Using source imaging, we estimated virtual sensors at locations where intracranial EEG contacts were placed. On data with and without spikes, we computed undirected functional connectivity between sensors/contacts using amplitude envelope correlation and phase locking value for physiologically relevant frequency bands. From each functional connectivity matrix, we generated an undirected network containing the strongest connections within sensors/contacts using the minimum spanning tree. For each sensor/contact, we computed graph centrality measures. We compared functional connectivity and their derived graph centrality of sensors/contacts inside resection for good (n = 22, ILAE I) and poor (n = 15, ILAE II-VI) outcome patients, tested their ability to predict the epileptogenic zone in good-outcome patients, examined the association between highly connected hubs removal and surgical outcome and performed leave-one-out cross-validation to support their prognostic value. We also compared the predictive values of functional connectivity with those of dipoles. Finally, we tested the reliability of virtual sensor measures via Spearman's correlation with intracranial EEG at population- and patient-level. We observed higher functional connectivity inside than outside resection (P < 0.05, Wilcoxon signed-rank test) for good-outcome patients, on data with and without spikes across different bands for intracranial EEG and electric/magnetic source imaging and few differences for poor-outcome patients. These functional connectivity measures were predictive of both the epileptogenic zone and outcome (positive and negative predictive values ≥55%, validated using leave-one-out cross-validation) outperforming dipoles on spikes. Significant correlations were found between source imaging and intracranial EEG measures (0.4 ≤ rho ≤ 0.9, P < 0.05). Our findings suggest that virtual implantation of sensors through source imaging can non-invasively identify highly connected hubs in patients with drug-resistant epilepsy, even in the absence of frank epileptiform activity. Surgical resection of these hubs predicts outcome better than dipoles.
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Affiliation(s)
- Ludovica Corona
- Jane and John Justin Institute for Mind Health, Cook Children's Health Care System, Fort Worth, TX 76104, USA
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX 76010, USA
| | - Eleonora Tamilia
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - M Scott Perry
- Jane and John Justin Institute for Mind Health, Cook Children's Health Care System, Fort Worth, TX 76104, USA
| | - Joseph R Madsen
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Jeffrey Bolton
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Scellig S D Stone
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Steve M Stufflebeam
- Athinoula Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
| | - Phillip L Pearl
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Christos Papadelis
- Jane and John Justin Institute for Mind Health, Cook Children's Health Care System, Fort Worth, TX 76104, USA
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX 76010, USA
- School of Medicine, Texas Christian University, Fort Worth, TX 76129, USA
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9
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Mohanty D, Quach M. The Noninvasive Evaluation for Minimally Invasive Pediatric Epilepsy Surgery (MIPES): A Multimodal Exploration of the Localization-Based Hypothesis. JOURNAL OF PEDIATRIC EPILEPSY 2022. [DOI: 10.1055/s-0042-1760104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
AbstractMinimally invasive pediatric epilepsy surgery (MIPES) is a rising technique in the management of focal-onset drug-refractory epilepsy. Minimally invasive surgical techniques are based on small, focal interventions (such as parenchymal ablation or localized neuromodulation) leading to elimination of the seizure onset zone or interruption of the larger epileptic network. Precise localization of the seizure onset zone, demarcation of eloquent cortex, and mapping of the network leading to seizure propagation are required to achieve optimal outcomes. The toolbox for presurgical, noninvasive evaluation of focal epilepsy continues to expand rapidly, with a variety of options based on advanced imaging and electrophysiology. In this article, we will examine several of these diagnostic modalities from the standpoint of MIPES and discuss how each can contribute to the development of a localization-based hypothesis for potential surgical targets.
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Affiliation(s)
- Deepankar Mohanty
- Section of Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas
| | - Michael Quach
- Section of Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas
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10
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Zhou Y, You J, Kumar U, Weiss SA, Bragin A, Engel J, Papadelis C, Li L. An approach for reliably identifying high-frequency oscillations and reducing false-positive detections. Epilepsia Open 2022; 7:674-686. [PMID: 36053171 PMCID: PMC9712470 DOI: 10.1002/epi4.12647] [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: 03/04/2022] [Accepted: 08/31/2022] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVE Aiming to improve the feasibility and reliability of using high-frequency oscillations (HFOs) for translational studies of epilepsy, we present a pipeline with features specifically designed to reject false positives for HFOs to improve the automatic HFO detector. METHODS We presented an integrated, multi-layered procedure capable of automatically rejecting HFOs from a variety of common false positives, such as motion, background signals, and sharp transients. This method utilizes a time-frequency contour approach that embeds three different layers including peak constraints, power thresholds, and morphological identification to discard false positives. Four experts were involved in rating detected HFO events that were randomly selected from different posttraumatic epilepsy (PTE) animals for a comprehensive evaluation. RESULTS The algorithm was run on 768-h recordings of intracranial electrodes in 48 PTE animals. A total of 453 917 HFOs were identified by initial HFO detection, of which 450 917 were implemented for HFO refinement and 203 531 events were retained. Random sampling was used to evaluate the performance of the detector. The HFO detection yielded an overall accuracy of 0.95 ± 0.03 , with precision, recall, and F1 scores of 0.92 ± 0.05 , 0.99 ± 0.01 , and 0.94 ± 0.03 , respectively. For the HFO classification, our algorithm obtained an accuracy of 0.97 ± 0.02 . For the inter-rater reliability of algorithm evaluation, the agreement among four experts was 0.94 ± 0.03 for HFO detection and 0.85 ± 0.04 for HFO classification. SIGNIFICANCE Our approach shows that a segregated pipeline design with a focus on false-positive rejection can improve the detection efficiency and provide reliable results. This pipeline does not require customization and uses fixed parameters, making it highly feasible and translatable for basic and clinical applications of epilepsy.
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Affiliation(s)
- Yufeng Zhou
- Department of Biomedical EngineeringUniversity of North TexasTexasUSA
| | - Jing You
- Department of Biomedical EngineeringUniversity of North TexasTexasUSA
| | - Udaya Kumar
- Department of NeurologyUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Shennan A Weiss
- Departments of Neurology, Department of Physiology and PharmacologyState University of New York DownstateBrooklynNew YorkUSA,Department of NeurologyNew York City Health + Hospitals/Kings CountyBrooklynNew YorkUSA
| | - Anatol Bragin
- Department of NeurologyUniversity of California Los AngelesLos AngelesCaliforniaUSA,Brain Research InstituteUniversity of CaliforniaLos AngelesCaliforniaUSA
| | - Jerome Engel
- Department of NeurologyUniversity of California Los AngelesLos AngelesCaliforniaUSA,Brain Research InstituteUniversity of CaliforniaLos AngelesCaliforniaUSA,Department of NeurobiologyDavid Geffen School of Medicine at UCLALos AngelesCaliforniaUSA,Department of Psychiatry and Biobehavioral SciencesDavid Geffen School of Medicine at UCLACaliforniaUSA
| | - Christos Papadelis
- Jane and John Justin Neurosciences CenterCook Children's Health Care SystemFort WorthTexasUSA,School of MedicineTexas Christian UniversityFort WorthTexasUSA,Department of BioengineeringUniversity of Texas at ArlingtonArlingtonTexasUSA
| | - Lin Li
- Department of Biomedical EngineeringUniversity of North TexasTexasUSA,Department of NeurologyUniversity of California Los AngelesLos AngelesCaliforniaUSA
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11
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Ntolkeras G, Tamilia E, AlHilani M, Bolton J, Ellen Grant P, Prabhu SP, Madsen JR, Stufflebeam SM, Pearl PL, Papadelis C. Presurgical accuracy of dipole clustering in MRI-negative pediatric patients with epilepsy: Validation against intracranial EEG and resection. Clin Neurophysiol 2022; 141:126-138. [PMID: 33875376 PMCID: PMC8803140 DOI: 10.1016/j.clinph.2021.01.036] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 01/21/2021] [Accepted: 01/27/2021] [Indexed: 01/24/2023]
Abstract
OBJECTIVE To assess the utility of interictal magnetic and electric source imaging (MSI and ESI) using dipole clustering in magnetic resonance imaging (MRI)-negative patients with drug resistant epilepsy (DRE). METHODS We localized spikes in low-density (LD-EEG) and high-density (HD-EEG) electroencephalography as well as magnetoencephalography (MEG) recordings using dipoles from 11 pediatric patients. We computed each dipole's level of clustering and used it to discriminate between clustered and scattered dipoles. For each dipole, we computed the distance from seizure onset zone (SOZ) and irritative zone (IZ) defined by intracranial EEG. Finally, we assessed whether dipoles proximity to resection was predictive of outcome. RESULTS LD-EEG had lower clusterness compared to HD-EEG and MEG (p < 0.05). For all modalities, clustered dipoles showed higher proximity to SOZ and IZ than scattered (p < 0.001). Resection percentage was higher in optimal vs. suboptimal outcome patients (p < 0.001); their proximity to resection was correlated to outcome (p < 0.001). No difference in resection percentage was seen for scattered dipoles between groups. CONCLUSION MSI and ESI dipole clustering helps to localize the SOZ and IZ and facilitate the prognostic assessment of MRI-negative patients with DRE. SIGNIFICANCE Assessing the MSI and ESI clustering allows recognizing epileptogenic areas whose removal is associated with optimal outcome.
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Affiliation(s)
- Georgios Ntolkeras
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Eleonora Tamilia
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michel AlHilani
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; The Hillingdon Hospital NHS Foundation Trust, London, United Kingdom
| | - Jeffrey Bolton
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - P Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Division of Neuroradiology, Department of Radiology, Boston Children's Hospital, Harvard Medical School, MA, USA
| | - Sanjay P Prabhu
- Division of Neuroradiology, Department of Radiology, Boston Children's Hospital, Harvard Medical School, MA, USA
| | - Joseph R Madsen
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Steven M Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Phillip L Pearl
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Christos Papadelis
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA; School of Medicine, Texas Christian University and University of North Texas Health Science Center, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA.
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12
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Ricci L, Matarrese M, Peters JM, Tamilia E, Madsen JR, Pearl PL, Papadelis C. Virtual implantation using conventional scalp EEG delineates seizure onset and predicts surgical outcome in children with epilepsy. Clin Neurophysiol 2022; 139:49-57. [PMID: 35526353 PMCID: PMC10026594 DOI: 10.1016/j.clinph.2022.04.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 04/04/2022] [Accepted: 04/08/2022] [Indexed: 11/16/2022]
Abstract
OBJECTIVE Delineation of the seizure onset zone (SOZ) is required in children with drug resistant epilepsy (DRE) undergoing neurosurgery. Intracranial EEG (icEEG) serves as gold standard but has limitations. Here, we examine the utility of virtual implantation with electrical source imaging (ESI) on ictal scalp EEG for mapping the SOZ and predict surgical outcome. METHODS We retrospectively analyzed EEG data from 35 children with DRE who underwent surgery and dichotomized into seizure-free (SF) and non-seizure-free (NSF). We estimated virtual sensors (VSs) at brain locations that matched icEEG implantation and compared ictal patterns at VSs vs icEEG. We calculated the agreement between VSs SOZ and clinically defined SOZ and built receiver operating characteristic (ROC) curves to test whether it predicted outcome. RESULTS Twenty-one patients were SF after surgery. Moderate agreement between virtual and icEEG patterns was observed (kappa = 0.45, p < 0.001). Virtual SOZ agreement with clinically defined SOZ was higher in SF vs NSF patients (66.6% vs 41.6%, p = 0.01). Anatomical concordance of virtual SOZ with clinically defined SOZ predicted outcome (AUC = 0.73; 95% CI: 0.57-0.89; sensitivity = 66.7%; specificity = 78.6%; accuracy = 71.4%). CONCLUSIONS Virtual implantation on ictal scalp EEG can approximate the SOZ and predict outcome. SIGNIFICANCE SOZ mapping with VSs may contribute to tailoring icEEG implantation and predict outcome.
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Affiliation(s)
- Lorenzo Ricci
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, University Campus Bio-Medico of Rome, Rome, Italy
| | - Margherita Matarrese
- Unit of Non-Linear Physics and Mathematical Modelling, Engineering Department, University Campus Bio-Medico of Rome, Rome, Italy; Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA
| | - Jurriaan M Peters
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Eleonora Tamilia
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Joseph R Madsen
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Phillip L Pearl
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Christos Papadelis
- Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA; School of Medicine, Texas Christian University, Fort Worth, TX, USA.
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13
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Billardello R, Ntolkeras G, Chericoni A, Madsen JR, Papadelis C, Pearl PL, Grant PE, Taffoni F, Tamilia E. Novel User-Friendly Application for MRI Segmentation of Brain Resection following Epilepsy Surgery. Diagnostics (Basel) 2022; 12:diagnostics12041017. [PMID: 35454065 PMCID: PMC9032020 DOI: 10.3390/diagnostics12041017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 04/10/2022] [Accepted: 04/13/2022] [Indexed: 11/16/2022] Open
Abstract
Delineation of resected brain cavities on magnetic resonance images (MRIs) of epilepsy surgery patients is essential for neuroimaging/neurophysiology studies investigating biomarkers of the epileptogenic zone. The gold standard to delineate the resection on MRI remains manual slice-by-slice tracing by experts. Here, we proposed and validated a semiautomated MRI segmentation pipeline, generating an accurate model of the resection and its anatomical labeling, and developed a graphical user interface (GUI) for user-friendly usage. We retrieved pre- and postoperative MRIs from 35 patients who had focal epilepsy surgery, implemented a region-growing algorithm to delineate the resection on postoperative MRIs and tested its performance while varying different tuning parameters. Similarity between our output and hand-drawn gold standards was evaluated via dice similarity coefficient (DSC; range: 0-1). Additionally, the best segmentation pipeline was trained to provide an automated anatomical report of the resection (based on presurgical brain atlas). We found that the best-performing set of parameters presented DSC of 0.83 (0.72-0.85), high robustness to seed-selection variability and anatomical accuracy of 90% to the clinical postoperative MRI report. We presented a novel user-friendly open-source GUI that implements a semiautomated segmentation pipeline specifically optimized to generate resection models and their anatomical reports from epilepsy surgery patients, while minimizing user interaction.
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Affiliation(s)
- Roberto Billardello
- Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Newborn Medicine Division, Department of Pediatrics, Boston Children’s Hospital, Boston, MA 02115, USA; (G.N.); (A.C.); (P.E.G.)
- Advanced Robotics and Human-Centered Technologies-CREO Lab, Università Campus Bio-Medico di Roma, 00128 Rome, Italy;
- Correspondence: (R.B.); (E.T.)
| | - Georgios Ntolkeras
- Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Newborn Medicine Division, Department of Pediatrics, Boston Children’s Hospital, Boston, MA 02115, USA; (G.N.); (A.C.); (P.E.G.)
- Baystate Children’s Hospital, Springfield, MA 01199, USA
| | - Assia Chericoni
- Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Newborn Medicine Division, Department of Pediatrics, Boston Children’s Hospital, Boston, MA 02115, USA; (G.N.); (A.C.); (P.E.G.)
- Advanced Robotics and Human-Centered Technologies-CREO Lab, Università Campus Bio-Medico di Roma, 00128 Rome, Italy;
| | - Joseph R. Madsen
- Epilepsy Surgery Program, Department of Neurosurgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA;
| | - Christos Papadelis
- Jane and John Justin Neurosciences Center, Cook Children’s Health Care System, Fort Worth, TX 76104, USA;
| | - Phillip L. Pearl
- Division of Epilepsy and Clinical Neurophysiology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA;
| | - Patricia Ellen Grant
- Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Newborn Medicine Division, Department of Pediatrics, Boston Children’s Hospital, Boston, MA 02115, USA; (G.N.); (A.C.); (P.E.G.)
| | - Fabrizio Taffoni
- Advanced Robotics and Human-Centered Technologies-CREO Lab, Università Campus Bio-Medico di Roma, 00128 Rome, Italy;
| | - Eleonora Tamilia
- Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Newborn Medicine Division, Department of Pediatrics, Boston Children’s Hospital, Boston, MA 02115, USA; (G.N.); (A.C.); (P.E.G.)
- Correspondence: (R.B.); (E.T.)
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14
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Abstract
PURPOSE OF REVIEW We review significant advances in epilepsy imaging in recent years. RECENT FINDINGS Structural MRI at 7T with optimization of acquisition and postacquisition image processing increases the diagnostic yield but artefactual findings remain a challenge. MRI analysis from multiple sites indicates different atrophy patterns and white matter diffusion abnormalities in temporal lobe and generalized epilepsies, with greater abnormalities close to the presumed seizure source. Structural and functional connectivity relate to seizure spread and generalization; longitudinal studies are needed to clarify the causal relationship of these associations. Diffusion MRI may help predict surgical outcome and network abnormalities extending beyond the epileptogenic zone. Three-dimensional multimodal imaging can increase the precision of epilepsy surgery, improve seizure outcome and reduce complications. Language and memory fMRI are useful predictors of postoperative deficits, and lead to risk minimization. FDG PET is useful for clinical studies and specific ligands probe the pathophysiology of neurochemical fluxes and receptor abnormalities. SUMMARY Improved structural MRI increases detection of abnormalities that may underlie epilepsy. Diffusion, structural and functional MRI indicate the widespread associations of epilepsy syndromes. These can assist stratification of surgical outcome and minimize risk. PET has continued utility clinically and for research into the pathophysiology of epilepsies.
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Affiliation(s)
- John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Karin Trimmel
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK
- Department of Neurology, Medical University of Vienna, Vienna, Austria
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15
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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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Papadelis C, Conrad SE, Song Y, Shandley S, Hansen D, Bosemani M, Malik S, Keator C, Perry MS. Case Report: Laser Ablation Guided by State of the Art Source Imaging Ends an Adolescent's 16-Year Quest for Seizure Freedom. Front Hum Neurosci 2022; 16:826139. [PMID: 35145387 PMCID: PMC8821813 DOI: 10.3389/fnhum.2022.826139] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/03/2022] [Indexed: 01/14/2023] Open
Abstract
Epilepsy surgery is the most effective therapeutic approach for children with drug resistant epilepsy (DRE). Recent advances in neurosurgery, such as the Laser Interstitial Thermal Therapy (LITT), improved the safety and non-invasiveness of this method. Electric and magnetic source imaging (ESI/MSI) plays critical role in the delineation of the epileptogenic focus during the presurgical evaluation of children with DRE. Yet, they are currently underutilized even in tertiary epilepsy centers. Here, we present a case of an adolescent who suffered from DRE for 16 years and underwent surgery at Cook Children's Medical Center (CCMC). The patient was previously evaluated in a level 4 epilepsy center and treated with multiple antiseizure medications for several years. Presurgical evaluation at CCMC included long-term video electroencephalography (EEG), magnetoencephalography (MEG) with simultaneous conventional EEG (19 channels) and high-density EEG (256 channels) in two consecutive sessions, MRI, and fluorodeoxyglucose - positron emission tomography (FDG-PET). Video long-term EEG captured nine focal-onset clinical seizures with a maximal evolution over the right frontal/frontal midline areas. MRI was initially interpreted as non-lesional. FDG-PET revealed a small region of hypometabolism at the anterior right superior temporal gyrus. ESI and MSI performed with dipole clustering showed a tight cluster of dipoles in the right anterior insula. The patient underwent intracranial EEG which indicated the right anterior insular as seizure onset zone. Eventually LITT rendered the patient seizure free (Engel 1; 12 months after surgery). Retrospective analysis of ESI and MSI clustered dipoles found a mean distance of dipoles from the ablated volume ranging from 10 to 25 mm. Our findings highlight the importance of recent technological advances in the presurgical evaluation and surgical treatment of children with DRE, and the underutilization of epilepsy surgery in children with DRE.
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Affiliation(s)
- Christos Papadelis
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States
- School of Medicine, Texas Christian University, University of North Texas Health Science Center, Fort Worth, TX, United States
- *Correspondence: Christos Papadelis orcid.org/0000-0001-6125-9217
| | - Shannon E. Conrad
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
| | - Yanlong Song
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States
| | - Sabrina Shandley
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
| | - Daniel Hansen
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
| | - Madhan Bosemani
- Department of Radiology, Cook Children's Medical Center, Fort Worth, TX, United States
| | - Saleem Malik
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
| | - Cynthia Keator
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
| | - M. Scott Perry
- Jane and John Justin Neuroscience Center, Cook Children's Health Care System, Fort Worth, TX, United States
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17
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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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Prognostic value of high-frequency oscillations combined with multimodal imaging methods for epilepsy surgery. Chin Med J (Engl) 2021; 135:1087-1095. [PMID: 35773966 PMCID: PMC9276102 DOI: 10.1097/cm9.0000000000001909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Background: The combination of high-frequency oscillations (HFOs) with single-mode imaging methods has been proved useful in identifying epileptogenic zones, whereas few studies have examined HFOs combined with multimodal imaging methods. The aim of this study was to evaluate the prognostic value of ripples, an HFO subtype with a frequency of 80 to 200 Hz is combined with multimodal imaging methods in predicting epilepsy surgery outcome. Methods: HFOs were analyzed in 21 consecutive medically refractory epilepsy patients who underwent epilepsy surgery. All patients underwent positron emission tomography (PET) and deep electrode implantation for stereo-electroencephalography (SEEG); 11 patients underwent magnetoencephalography (MEG). Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in predicting surgical outcome were calculated for ripples combined with PET, MEG, both PET and MEG, and PET combined with MEG. Kaplan-Meier survival analyses were conducted in each group to estimate prognostic value. Results: The study included 13 men and 8 women. Accuracy for ripples, PET, and MEG alone in predicting surgical outcome was 42.9%, 42.9%, and 81.8%, respectively. Accuracy for ripples combined with PET and MEG was the highest. Resection of regions identified by ripples, MEG dipoles, and combined PET findings was significantly associated with better surgical outcome (P < 0.05). Conclusions: Intracranial electrodes are essential to detect regions which generate ripples and to remove these areas which indicate good surgical outcome for medically intractable epilepsy. With the assistance of presurgical noninvasive imaging examinations, PET and MEG, for example, the SEEG electrodes would identify epileptogenic regions more effectively.
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Jahromi S, Matarrese MA, Tamilia E, Perry MS, Madsen JR, Pearl PL, Papadelis C. Mapping Propagation of Interictal Spikes, Ripples, and Fast Ripples in Intracranial EEG of Children with Refractory Epilepsy. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:194-197. [PMID: 34891270 PMCID: PMC8896264 DOI: 10.1109/embc46164.2021.9630250] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Studies on intracranial electroencephalography (icEEG) recordings of patients with drug resistant epilepsy (DRE) show that epilepsy biomarkers propagate in time across brain areas. Here, we propose a novel method that estimates critical features of these propagations for different epilepsy biomarkers (spikes, ripples, and fast ripples), and assess their common onset as a reliable biomarker of the epileptogenic zone (EZ). For each biomarker, an automatic algorithm ranked the icEEG electrodes according to their timing occurrence in propagations and finally dichotomized them as onset or spread. We validated our algorithm on icEEG recordings of 8 children with DRE having a good surgical outcome (Engel score = 1). We estimated the overlap of the onset, spread, and entire zone of propagation with the resection (RZ) and the seizure onset zone (SOZ). Spike and ripple propagations were seen in all patients, whereas fast ripple propagations were seen in 6 patients. Spike, ripple, and fast ripple propagations had a mean duration of 28.3 ± 24.3 ms, 38.7 ± 37 ms, and 25 ± 14 ms respectively. Onset electrodes predicted the RZ and SOZ with higher specificity compared to the entire zone for all three biomarkers (p<0.05). Overlap of spike and ripple onsets presented a higher specificity than each separate biomarker onset: for the SOZ, the onsets overlap was more specific (97.89 ± 2.36) than the ripple onset (p=0.031); for the RZ, the onsets overlap was more specific (98.48 ± 1.5) than the spike onset (p=0.016). Yet, the entire zone for spike and ripple propagations predicted the RZ with higher sensitivity compared to each biomarker's onset (or spread) (p<0.05). We present, for the first time, preliminary evidence from icEEG data that fast ripples propagate in time across large areas of the brain. The onsets overlap of spike and ripple propagations constitutes an extremely specific (but not sensitive) biomarker of the EZ, compared to areas of spread (and entire areas) in propagation.
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Affiliation(s)
- Saeed Jahromi
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA
- Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA
| | - Margherita A.G. Matarrese
- Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA
- Unit of Non-Linear Physics and Mathematical Modeling, Engineering Department, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Eleonora Tamilia
- Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - M Scott Perry
- Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA
| | - Joseph R Madsen
- Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Phillip L. Pearl
- Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Christos Papadelis
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA
- Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA
- Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
- School of Medicine, Texas Christian University and University of North Texas Health Science Center, Fort Worth, TX, USA
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20
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Starnes K, Depositario-Cabacar D, Wong-Kisiel L. Presurgical Evaluation Strategies for Intractable Epilepsy of Childhood. Semin Pediatr Neurol 2021; 39:100915. [PMID: 34620457 DOI: 10.1016/j.spen.2021.100915] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Revised: 08/11/2021] [Accepted: 08/11/2021] [Indexed: 11/29/2022]
Abstract
For children who continue to experience seizures despite treatment with antiseizure medications, epilepsy surgery can be considered. The goals of the presurgical evaluation are to determine the best surgical approach to render a good outcome. In patients with drug resistant focal epilepsy, the epileptogenic zone defines the minimal brain volume which must be resected for surgical success and to delineate the relationship of this region with functional cortex. A number of noninvasive tools for these tasks have emerged over the past decade, and existing technologies have been revised and improved. In this review, we examine the recent published evidence for these techniques, specifically as applied to the pediatric population. Discussed herein are the diagnostic value of methods such as video electroencephalography, magnetic resonance imaging, and supportive neuroimaging techniques including single photon emission tomography, photon emission tomography, and magnetoencephalography. Functional testing including functional magnetic resonance imaging, electrical stimulation mapping, and transcranial magnetic stimulation are considered in the context of pediatric epilepsy. The application of emerging techniques to preoperative testing such as source localization, image post-processing, and artificial intelligence is covered. We summarize the relative value of presurgical testing based on patient characteristics, including lesional or nonlesional MRI, temporal or extratemporal epilepsy, and other factors relevant in pediatric epilepsy such as pathological substrate and age.
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Affiliation(s)
| | | | - Lily Wong-Kisiel
- Department of Neurology and Pediatrics, Mayo Clinic, Rochester, MN.
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21
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Papadelis C, Perry MS. Localizing the Epileptogenic Zone with Novel Biomarkers. Semin Pediatr Neurol 2021; 39:100919. [PMID: 34620466 PMCID: PMC8501232 DOI: 10.1016/j.spen.2021.100919] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 08/09/2021] [Accepted: 08/11/2021] [Indexed: 01/01/2023]
Abstract
Several noninvasive methods, such as high-density EEG or magnetoencephalography, are currently used to delineate the epileptogenic zone (EZ) during the presurgical evaluation of patients with drug resistant epilepsy (DRE). Yet, none of these methods can reliably identify the EZ by their own. In most cases a multimodal approach is needed. Challenging cases often require the implantation of intracranial electrodes, either through stereo-taxic EEG or electro-corticography. Recently, a growing body of literature introduces novel biomarkers of epilepsy that can be used for analyzing both invasive as well as noninvasive electrophysiological data. Some of these biomarkers are able to delineate the EZ with high precision, augment the presurgical evaluation, and predict the surgical outcome of patients with DRE undergoing surgery. However, the use of these epilepsy biomarkers in clinical practice is limited. Here, we summarize and discuss the latest technological advances in the presurgical neurophysiological evaluation of children with DRE with emphasis on electric and magnetic source imaging, high frequency oscillations, and functional connectivity.
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Affiliation(s)
- Christos Papadelis
- Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX; School of Medicine, Texas Christian University and University of North Texas Health Science Center, Fort Worth, TX; Department of Bioengineering, University of Texas at Arlington, Arlington, TX; Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA.
| | - M Scott Perry
- Jane and John Justin Neurosciences Center, Cook Children’s Health Care System, Fort Worth, TX, USA
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22
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Migliorelli C, Romero S, Bachiller A, Aparicio J, Alonso JF, Mañanas MA, Antonio-Arce VS. Improving the ripple classification in focal pediatric epilepsy: identifying pathological high-frequency oscillations by Gaussian mixture model clustering. J Neural Eng 2021; 18. [PMID: 34384061 DOI: 10.1088/1741-2552/ac1d31] [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: 03/19/2021] [Accepted: 08/12/2021] [Indexed: 11/11/2022]
Abstract
Objective. High-frequency oscillations (HFOs) have emerged as a promising clinical biomarker for presurgical evaluation in childhood epilepsy. HFOs are commonly classified in stereo-encephalography as ripples (80-200 Hz) and fast ripples (200-500 Hz). Ripples are less specific and not so directly associated with epileptogenic activity because of their physiological and pathological origin. The aim of this paper is to distinguish HFOs in the ripple band and to improve the evaluation of the epileptogenic zone (EZ).Approach. This study constitutes a novel modeling approach evaluated in ten patients from Sant Joan de Deu Pediatric Hospital (Barcelona, Spain), with clearly-defined seizure onset zones (SOZ) during presurgical evaluation. A subject-by-subject basis analysis is proposed: a probabilistic Gaussian mixture model (GMM) based on the combination of specific ripple features is applied for estimating physiological and pathological ripple subpopulations.Main Results. Clear pathological and physiological ripples are identified. Features differ considerably among patients showing within-subject variability, suggesting that individual models are more appropriate than a traditional whole-population approach. The difference in rates inside and outside the SOZ for pathological ripples is significantly higher than when considering all the ripples. These significant differences also appear in signal segments without epileptiform activity. Pathological ripple rates show a sharp decline from SOZ to non-SOZ contacts and a gradual decrease with distance.Significance. This novel individual GMM approach improves ripple classification and helps to refine the delineation of the EZ, as well as being appropriate to investigate the interaction of epileptogenic and propagation networks.
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Affiliation(s)
- Carolina Migliorelli
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain.,Universitat Politecnica de Catalunya, Department of Automatic Control (ESAII), Biomedical Engineering Research Centre (CREB), Barcelona, Spain.,Institut de recerca pediatrica Hospital Sant Joan de Déu, Barcelona, Spain
| | - Sergio Romero
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain.,Universitat Politecnica de Catalunya, Department of Automatic Control (ESAII), Biomedical Engineering Research Centre (CREB), Barcelona, Spain.,Institut de recerca pediatrica Hospital Sant Joan de Déu, Barcelona, Spain
| | - Alejandro Bachiller
- Universitat Politecnica de Catalunya, Department of Automatic Control (ESAII), Biomedical Engineering Research Centre (CREB), Barcelona, Spain.,Institut de recerca pediatrica Hospital Sant Joan de Déu, Barcelona, Spain
| | - Javier Aparicio
- Universitary Hospital Sant Joan de Déu, Epilepsy Unit. Department of Neuropediatrics (member of the European Reference Network for rare and complex epilepsies EpiCARE), Barcelona, Spain
| | - Joan F Alonso
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain.,Universitat Politecnica de Catalunya, Department of Automatic Control (ESAII), Biomedical Engineering Research Centre (CREB), Barcelona, Spain.,Institut de recerca pediatrica Hospital Sant Joan de Déu, Barcelona, Spain
| | - Miguel A Mañanas
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain.,Universitat Politecnica de Catalunya, Department of Automatic Control (ESAII), Biomedical Engineering Research Centre (CREB), Barcelona, Spain.,Institut de recerca pediatrica Hospital Sant Joan de Déu, Barcelona, Spain
| | - Victoria San Antonio-Arce
- Universitary Hospital Sant Joan de Déu, Epilepsy Unit. Department of Neuropediatrics (member of the European Reference Network for rare and complex epilepsies EpiCARE), Barcelona, Spain.,Freiburg Epilepsy Center, Medical Center-University of Freiburg, Faculty of Medicine (member of the European Reference Network for rare and complex epilepsies EpiCARE), Freiburg, Germany
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23
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Changes in the Functional Brain Network of Children Undergoing Repeated Epilepsy Surgery: An EEG Source Connectivity Study. Diagnostics (Basel) 2021; 11:diagnostics11071234. [PMID: 34359317 PMCID: PMC8306224 DOI: 10.3390/diagnostics11071234] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 06/29/2021] [Accepted: 07/05/2021] [Indexed: 11/19/2022] Open
Abstract
About 30% of children with drug-resistant epilepsy (DRE) continue to have seizures after epilepsy surgery. Since epilepsy is increasingly conceptualized as a network disorder, understanding how brain regions interact may be critical for planning re-operation in these patients. We aimed to estimate functional brain connectivity using scalp EEG and its evolution over time in patients who had repeated surgery (RS-group, n = 9) and patients who had one successful surgery (seizure-free, SF-group, n = 12). We analyzed EEGs without epileptiform activity at varying time points (before and after each surgery). We estimated functional connectivity between cortical regions and their relative centrality within the network. We compared the pre- and post-surgical centrality of all the non-resected (untouched) regions (far or adjacent to resection) for each group (using the Wilcoxon signed rank test). In alpha, theta, and beta frequency bands, the post-surgical centrality of the untouched cortical regions increased in the SF group (p < 0.001) whereas they decreased (p < 0.05) or did not change (p > 0.05) in the RS group after failed surgeries; when re-operation was successful, the post-surgical centrality of far regions increased (p < 0.05). Our data suggest that removal of the epileptogenic focus in children with DRE leads to a gain in the network centrality of the untouched areas. In contrast, unaltered or decreased connectivity is seen when seizures persist after surgery.
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Xu N, Shan W, Qi J, Wu J, Wang Q. Presurgical Evaluation of Epilepsy Using Resting-State MEG Functional Connectivity. Front Hum Neurosci 2021; 15:649074. [PMID: 34276321 PMCID: PMC8283278 DOI: 10.3389/fnhum.2021.649074] [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: 01/03/2021] [Accepted: 06/07/2021] [Indexed: 11/21/2022] Open
Abstract
Epilepsy is caused by abnormal electrical discharges (clinically identified by electrophysiological recording) in a specific part of the brain [originating in only one part of the brain, namely, the epileptogenic zone (EZ)]. Epilepsy is now defined as an archetypical hyperexcited neural network disorder. It can be investigated through the network analysis of interictal discharges, ictal discharges, and resting-state functional connectivity. Currently, there is an increasing interest in embedding resting-state connectivity analysis into the preoperative evaluation of epilepsy. Among the various neuroimaging technologies employed to achieve brain functional networks, magnetoencephalography (MEG) with the excellent temporal resolution is an ideal tool for estimating the resting-state connectivity between brain regions, which can reveal network abnormalities in epilepsy. What value does MEG resting-state functional connectivity offer for epileptic presurgical evaluation? Regarding this topic, this paper introduced the origin of MEG and the workflow of constructing source-space functional connectivity based on MEG signals. Resting-state functional connectivity abnormalities correlate with epileptogenic networks, which are defined by the brain regions involved in the production and propagation of epileptic activities. This paper reviewed the evidence of altered epileptic connectivity based on low- or high-frequency oscillations (HFOs) and the evidence of the advantage of using simultaneous MEG and intracranial electroencephalography (iEEG) recordings. More importantly, this review highlighted that MEG-based resting-state functional connectivity has the potential to predict postsurgical outcomes. In conclusion, resting-state MEG functional connectivity has made a substantial progress toward serving as a candidate biomarker included in epileptic presurgical evaluations.
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Affiliation(s)
- Na Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wei Shan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jing Qi
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jianping Wu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Qun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
- Beijing Institute of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neuromodulation, Beijing, China
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25
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Tamilia E, Matarrese MAG, Ntolkeras G, Grant PE, Madsen JR, Stufflebeam SM, Pearl PL, Papadelis C. Noninvasive Mapping of Ripple Onset Predicts Outcome in Epilepsy Surgery. Ann Neurol 2021; 89:911-925. [PMID: 33710676 PMCID: PMC8229023 DOI: 10.1002/ana.26066] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 03/09/2021] [Accepted: 03/10/2021] [Indexed: 01/07/2023]
Abstract
OBJECTIVE Intracranial electroencephalographic (icEEG) studies show that interictal ripples propagate across the brain of children with medically refractory epilepsy (MRE), and the onset of this propagation (ripple onset zone [ROZ]) estimates the epileptogenic zone. It is still unknown whether we can map this propagation noninvasively. The goal of this study is to map ripples (ripple zone [RZ]) and their propagation onset (ROZ) using high-density EEG (HD-EEG) and magnetoencephalography (MEG), and to estimate their prognostic value in pediatric epilepsy surgery. METHODS We retrospectively analyzed simultaneous HD-EEG and MEG data from 28 children with MRE who underwent icEEG and epilepsy surgery. Using electric and magnetic source imaging, we estimated virtual sensors (VSs) at brain locations that matched the icEEG implantation. We detected ripples on VSs, defined the virtual RZ and virtual ROZ, and estimated their distance from icEEG. We assessed the predictive value of resecting virtual RZ and virtual ROZ for postsurgical outcome. Interictal spike localization on HD-EEG and MEG was also performed and compared with ripples. RESULTS We mapped ripple propagation in all patients with HD-EEG and in 27 (96%) patients with MEG. The distance from icEEG did not differ between HD-EEG and MEG when mapping the RZ (26-27mm, p = 0.6) or ROZ (22-24mm, p = 0.4). Resecting the virtual ROZ, but not virtual RZ or the sources of spikes, was associated with good outcome for HD-EEG (p = 0.016) and MEG (p = 0.047). INTERPRETATION HD-EEG and MEG can map interictal ripples and their propagation onset (virtual ROZ). Noninvasively mapping the ripple onset may augment epilepsy surgery planning and improve surgical outcome of children with MRE. ANN NEUROL 2021;89:911-925.
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Affiliation(s)
- Eleonora Tamilia
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of MedicineBoston Children's Hospital, Harvard Medical SchoolBostonMA
- Fetal‐Neonatal Neuroimaging and Developmental Science CenterBoston Children's Hospital, Harvard Medical SchoolBostonMA
| | - Margherita A. G. Matarrese
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of MedicineBoston Children's Hospital, Harvard Medical SchoolBostonMA
- Laboratory of Nonlinear Physics and Mathematical Modeling, Department of EngineeringUniversity Bio‐Medico Campus of RomeRomeItaly
| | - Georgios Ntolkeras
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of MedicineBoston Children's Hospital, Harvard Medical SchoolBostonMA
- Fetal‐Neonatal Neuroimaging and Developmental Science CenterBoston Children's Hospital, Harvard Medical SchoolBostonMA
| | - P. Ellen Grant
- Fetal‐Neonatal Neuroimaging and Developmental Science CenterBoston Children's Hospital, Harvard Medical SchoolBostonMA
| | - Joseph R. Madsen
- Epilepsy Surgery Program, Department of NeurosurgeryBoston Children's Hospital, Harvard Medical SchoolBostonMA
| | - Steve M. Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonMA
| | - Phillip L. Pearl
- Division of Epilepsy and Clinical Neurophysiology, Department of NeurologyBoston Children's Hospital, Harvard Medical SchoolBostonMA
| | - Christos Papadelis
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of MedicineBoston Children's Hospital, Harvard Medical SchoolBostonMA
- Jane and John Justin Neurosciences CenterCook Children's Health Care SystemFort WorthTX
- School of Medicine, Texas Christian University and University of North Texas Health Science CenterFort WorthTX
- Department of BioengineeringUniversity of Texas at ArlingtonArlingtonTX
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26
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Ricci L, Tamilia E, Alhilani M, Alter A, Scott Perry Μ, Madsen JR, Peters JM, Pearl PL, Papadelis C. Source imaging of seizure onset predicts surgical outcome in pediatric epilepsy. Clin Neurophysiol 2021; 132:1622-1635. [PMID: 34034087 PMCID: PMC8202024 DOI: 10.1016/j.clinph.2021.03.043] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 02/08/2021] [Accepted: 03/04/2021] [Indexed: 12/20/2022]
Abstract
Objective: To assess whether ictal electric source imaging (ESI) on low-density scalp EEG can approximate the seizure onset zone (SOZ) location and predict surgical outcome in children with refractory epilepsy undergoing surgery. Methods: We examined 35 children with refractory epilepsy. We dichotomized surgical outcome into seizure- and non-seizure-free. We identified ictal onsets recorded with scalp and intracranial EEG and localized them using equivalent current dipoles and standardized low-resolution magnetic tomography (sLORETA). We estimated the localization accuracy of scalp EEG as distance of scalp dipoles from intracranial dipoles. We also calculated the distances of scalp dipoles from resection, as well as their resection percentage and compared between seizure-free and non-seizure-free patients. We built receiver operating characteristic curves to test whether resection percentage predicted outcome. Results: Resection distance was lower in seizure-free patients for both dipoles (p = 0.006) and sLORETA (p = 0.04). Resection percentage predicted outcome with a sensitivity of 57.1% (95% CI, 34–78.2%), a specificity of 85.7% (95% CI, 57.2–98.2%) and an accuracy of 68.6% (95% CI, 50.7–83.5%) (p = 0.01). Conclusion: Ictal ESI performed on low-density scalp EEG can delineate the SOZ and predict outcome. Significance: Such an application may increase the number of children who are referred for epilepsy surgery and improve their outcome.
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Affiliation(s)
- Lorenzo Ricci
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, University Campus Bio-Medico of Rome, Rome, Italy
| | - Eleonora Tamilia
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michel Alhilani
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; The Hillingdon Hospital NHS Foundation Trust, London, UK
| | - Aliza Alter
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Μ Scott Perry
- Jane and John Justin 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
| | - Jurriaan M Peters
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, 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
| | - Christos Papadelis
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA; School of Medicine, Texas Christian University and University of North Texas Health Science Center, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA.
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27
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Bruder JC, Schmelzeisen C, Lachner-Piza D, Reinacher P, Schulze-Bonhage A, Jacobs J. Physiological Ripples Associated With Sleep Spindles Can Be Identified in Patients With Refractory Epilepsy Beyond Mesio-Temporal Structures. Front Neurol 2021; 12:612293. [PMID: 33643198 PMCID: PMC7902925 DOI: 10.3389/fneur.2021.612293] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 01/11/2021] [Indexed: 11/13/2022] Open
Abstract
Introduction: High frequency oscillations (HFO) are promising biomarkers of epileptic tissue. While group analysis suggested a correlation between surgical removal of HFO generating tissue and seizure free outcome, HFO could not predict seizure outcome on an individual patient level. One possible explanation is the lack of differentiation between physiological and epileptic HFO. In the mesio-temporal lobe, a proportion of physiological ripples can be identified by their association with scalp sleep spindles. Spike associated ripples in contrast can be considered epileptic. This study investigated whether categorizing ripples by the co-occurrence with sleep spindles or spikes improves outcome prediction after surgery. Additionally, it aimed to investigate whether spindle-ripple association is limited to the mesio-temporal lobe structures or visible across the whole brain. Methods: We retrospectively analyzed EEG of 31 patients with chronic intracranial EEG. Sleep spindles in scalp EEG and ripples and epileptic spikes in iEEG were automatically detected. Three ripple subtypes were obtained: SpindleR, Non-SpindleR, and SpikeR. Rate ratios between removed and non-removed brain areas were calculated. We compared the distinct ripple subtypes and their rates in different brain regions, inside and outside seizure onset areas and between patients with good and poor seizure outcome. Results: SpindleR were found across all brain regions. SpikeR had significantly higher rates in the SOZ than in Non-SOZ channels. A significant positive correlation between removal of ripple-events and good outcome was found for the mixed ripple group (rs = 0.43, p = 0.017) and for ripples not associated with spindles (rs=0.40, p = 0.044). Also, a significantly high proportion of spikes associated with ripples were removed in seizure free patients (p = 0.036). Discussion: SpindleR are found in mesio-temporal and neocortical structures, indicating that ripple-spindle-coupling might have functional importance beyond mesio-temporal structures. Overall, the proportion of SpindleR was low and separating spindle and spike associated ripples did not improve outcome prediction in our patient group. SpindleR analysis therefore can be a tool to identify physiological events but needs to be used in combination with other methods to have clinical relevance.
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Affiliation(s)
- Jonas C Bruder
- Department of Neuropediatrics and Muscular Disease, University Medical Center, Freiburg, Germany
| | - Christoph Schmelzeisen
- Department of Neuropediatrics and Muscular Disease, University Medical Center, Freiburg, Germany
| | - Daniel Lachner-Piza
- Department of Neuropediatrics and Muscular Disease, University Medical Center, Freiburg, Germany
| | - Peter Reinacher
- Stereotactic & Functional Neurosurgery, University Medical Center, Freiburg, Germany
| | | | - Julia Jacobs
- Department of Neuropediatrics and Muscular Disease, University Medical Center, Freiburg, Germany.,Epilepsy Center, University Medical Center, Freiburg, Germany
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Fan Y, Dong L, Liu X, Wang H, Liu Y. Recent advances in the noninvasive detection of high-frequency oscillations in the human brain. Rev Neurosci 2020; 32:305-321. [PMID: 33661582 DOI: 10.1515/revneuro-2020-0073] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 10/23/2020] [Indexed: 01/10/2023]
Abstract
In recent decades, a significant body of evidence based on invasive clinical research has showed that high-frequency oscillations (HFOs) are a promising biomarker for localization of the seizure onset zone (SOZ), and therefore, have the potential to improve postsurgical outcomes in patients with epilepsy. Emerging clinical literature has demonstrated that HFOs can be recorded noninvasively using methods such as scalp electroencephalography (EEG) and magnetoencephalography (MEG). Not only are HFOs considered to be a useful biomarker of the SOZ, they also have the potential to gauge disease severity, monitor treatment, and evaluate prognostic outcomes. In this article, we review recent clinical research on noninvasively detected HFOs in the human brain, with a focus on epilepsy. Noninvasively detected scalp HFOs have been investigated in various types of epilepsy. HFOs have also been studied noninvasively in other pathologic brain disorders, such as migraine and autism. Herein, we discuss the challenges reported in noninvasive HFO studies, including the scarcity of MEG and high-density EEG equipment in clinical settings, low signal-to-noise ratio, lack of clinically approved automated detection methods, and the difficulty in differentiating between physiologic and pathologic HFOs. Additional studies on noninvasive recording methods for HFOs are needed, especially prospective multicenter studies. Further research is fundamental, and extensive work is needed before HFOs can routinely be assessed in clinical settings; however, the future appears promising.
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Affiliation(s)
- Yuying Fan
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Liping Dong
- Library of China Medical University, Shenyang, China
| | - Xueyan Liu
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Hua Wang
- Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yunhui Liu
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, China
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Fast oscillations >40 Hz localize the epileptogenic zone: An electrical source imaging study using high-density electroencephalography. Clin Neurophysiol 2020; 132:568-580. [PMID: 33450578 DOI: 10.1016/j.clinph.2020.11.031] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 10/04/2020] [Accepted: 11/06/2020] [Indexed: 01/25/2023]
Abstract
OBJECTIVE Fast Oscillations (FO) >40 Hz are a promising biomarker of the epileptogenic zone (EZ). Evidence using scalp electroencephalography (EEG) remains scarce. We assessed if electrical source imaging of FO using 256-channel high-density EEG (HD-EEG) is useful for EZ identification. METHODS We analyzed HD-EEG recordings of 10 focal drug-resistant epilepsy patients with seizure-free postsurgical outcome. We marked FO candidate events at the time of epileptic spikes and verified them by screening for an isolated peak in the time-frequency plot. We performed electrical source imaging of spikes and FO within the Maximum Entropy of the Mean framework. Source localization maps were validated against the surgical cavity. RESULTS We identified FO in five out of 10 patients who had a superficial or intermediate deep generator. The maximum of the FO maps was localized inside the cavity in all patients (100%). Analysis with a reduced electrode coverage using the 10-10 and 10-20 system showed a decreased localization accuracy of 60% and 40% respectively. CONCLUSIONS FO recorded with HD-EEG localize the EZ. HD-EEG is better suited to detect and localize FO than conventional EEG approaches. SIGNIFICANCE This study acts as proof-of-concept that FO localization using 256-channel HD-EEG is a viable marker of the EZ.
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Abstract
Concise history of fascinating magnetoencephalography (MEG) technology and catalog of very selected milestone preclinical and clinical MEG studies are provided as the background. The focus is the societal context defining a journey of MEG to and through clinical practice and formation of the American Clinical MEG Society (ACMEGS). We aspired to provide an objective historic perspective and document contributions of many professionals while focusing on the role of ACMEGS in the growth and maturation of clinical MEG field. The ACMEGS was born (2006) out of inevitability to address two vital issues-fair reimbursement and proper clinical acceptance. A beacon of accountable MEG practice and utilization is now an expanding professional organization with the highest level of competence in practice of clinical MEG and clinical credibility. The ACMEGS facilitated a favorable disposition of insurances toward MEG in the United States by combining the national replication of the grassroots efforts and teaming up with the strategic partners-particularly the American Academy of Neurology (AAN), published two Position Statements (2009 and 2017), the world's only set of MEG Clinical Practice Guidelines (CPGs; 2011) and surveys of clinical MEG practice (2011 and 2020) and use (2020). In addition to the annual ACMEGS Course (2012), we directly engaged MEG practitioners through an Invitational Summit (2019). The Society remains focused on the improvements and expansion of clinical practice, education, clinical training, and constructive engagement of vendors in these issues and pivotal studies toward additional MEG indications. The ACMEGS not only had the critical role in the progress of Clinical MEG in the United States and beyond since 2006 but positioned itself as the field leader in the future.
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Nariai H, Hussain SA, Bernardo D, Motoi H, Sonoda M, Kuroda N, Asano E, Nguyen JC, Elashoff D, Sankar R, Bragin A, Staba RJ, Wu JY. Scalp EEG interictal high frequency oscillations as an objective biomarker of infantile spasms. Clin Neurophysiol 2020; 131:2527-2536. [PMID: 32927206 DOI: 10.1016/j.clinph.2020.08.013] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 07/25/2020] [Accepted: 08/04/2020] [Indexed: 12/21/2022]
Abstract
OBJECTIVE To investigate the diagnostic utility of high frequency oscillations (HFOs) via scalp electroencephalogram (EEG) in infantile spasms. METHODS We retrospectively analyzed interictal slow-wave sleep EEGs sampled at 2,000 Hz recorded from 30 consecutive patients who were suspected of having infantile spasms. We measured the rate of HFOs (80-500 Hz) and the strength of the cross-frequency coupling between HFOs and slow-wave activity (SWA) at 3-4 Hz and 0.5-1 Hz as quantified with modulation indices (MIs). RESULTS Twenty-three patients (77%) exhibited active spasms during the overnight EEG recording. Although the HFOs were detected in all children, increased HFO rate and MIs correlated with the presence of active spasms (p < 0.001 by HFO rate; p < 0.01 by MIs at 3-4 Hz; p = 0.02 by MIs at 0.5-1 Hz). The presence of active spasms was predicted by the logistic regression models incorporating HFO-related metrics (AUC: 0.80-0.98) better than that incorporating hypsarrhythmia (AUC: 0.61). The predictive performance of the best model remained favorable (87.5% accuracy) after a cross-validation procedure. CONCLUSIONS Increased rate of HFOs and coupling between HFOs and SWA are associated with active epileptic spasms. SIGNIFICANCE Scalp-recorded HFOs may serve as an objective EEG biomarker for active epileptic spasms.
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Affiliation(s)
- Hiroki Nariai
- Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, California, USA.
| | - Shaun A Hussain
- Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, California, USA
| | - Danilo Bernardo
- Department of Neurology, Division of Epilepsy, University of California, San Francisco, San Francisco, CA, USA
| | - Hirotaka Motoi
- Department of Pediatrics and Neurology, Children's Hospital of Michigan, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Masaki Sonoda
- Department of Pediatrics and Neurology, Children's Hospital of Michigan, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Naoto Kuroda
- Department of Pediatrics and Neurology, Children's Hospital of Michigan, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Eishi Asano
- Department of Pediatrics and Neurology, Children's Hospital of Michigan, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Jimmy C Nguyen
- Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, California, USA
| | - David Elashoff
- Department of Medicine, Statistics Core, University of California, Los Angeles, Los Angeles, California, USA
| | - Raman Sankar
- Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, California, USA
| | - Anatol Bragin
- Department of Neurology, UCLA Medical Center, David Geffen School of Medicine, Los Angeles, California, USA
| | - Richard J Staba
- Department of Neurology, UCLA Medical Center, David Geffen School of Medicine, Los Angeles, California, USA
| | - Joyce Y Wu
- Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, California, USA
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