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Gotman J. Has recording of seizures become obsolete? Rev Neurol (Paris) 2023; 179:872-876. [PMID: 36906456 DOI: 10.1016/j.neurol.2023.01.726] [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: 12/12/2022] [Accepted: 01/04/2023] [Indexed: 03/11/2023]
Abstract
Some patients with medically intractable epilepsy are considered for surgical treatment. In some surgical candidates, the investigation includes the placement of intracerebral electrodes and long-term monitoring to find the region of seizure onset. This region is the primary determinant of the surgical resection but about one-third of patients are not offered surgery after electrode implantation and among those operated only about 55% are seizure free after five years. This paper discusses why the primary reliance on the seizure onset maybe suboptimal and may be in part responsible for the relatively low surgical success rate. It also proposes to consider some interictal markers that may have advantages over seizure onset and may be easier to obtain.
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Affiliation(s)
- J Gotman
- Montreal Neurological Institute, McGill University, 3801 University Street, Montréal, Québec H3A 2B4, Canada.
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2
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Steinbrenner M, McDowell A, Centeno M, Moeller F, Perani S, Lorio S, Maziero D, Carmichael DW. Camera-based Prospective Motion Correction in Paediatric Epilepsy Patients Enables EEG-fMRI Localization Even in High-motion States. Brain Topogr 2023; 36:319-337. [PMID: 36939987 PMCID: PMC10164016 DOI: 10.1007/s10548-023-00945-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 02/14/2023] [Indexed: 03/21/2023]
Abstract
BACKGROUND EEG-fMRI is a useful additional test to localize the epileptogenic zone (EZ) particularly in MRI negative cases. However subject motion presents a particular challenge owing to its large effects on both MRI and EEG signal. Traditionally it is assumed that prospective motion correction (PMC) of fMRI precludes EEG artifact correction. METHODS Children undergoing presurgical assessment at Great Ormond Street Hospital were included into the study. PMC of fMRI was done using a commercial system with a Moiré Phase Tracking marker and MR-compatible camera. For retrospective EEG correction both a standard and a motion educated EEG artefact correction (REEGMAS) were compared to each other. RESULTS Ten children underwent simultaneous EEG-fMRI. Overall head movement was high (mean RMS velocity < 1.5 mm/s) and showed high inter- and intra-individual variability. Comparing motion measured by the PMC camera and the (uncorrected residual) motion detected by realignment of fMRI images, there was a five-fold reduction in motion from its prospective correction. Retrospective EEG correction using both standard approaches and REEGMAS allowed the visualization and identification of physiological noise and epileptiform discharges. Seven of 10 children had significant maps, which were concordant with the clinical EZ hypothesis in 6 of these 7. CONCLUSION To our knowledge this is the first application of camera-based PMC for MRI in a pediatric clinical setting. Despite large amount of movement PMC in combination with retrospective EEG correction recovered data and obtained clinically meaningful results during high levels of subject motion. Practical limitations may currently limit the widespread use of this technology.
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Affiliation(s)
- Mirja Steinbrenner
- School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK.,Department of Neurology and Experimental Neurology, Epilepsy Center Berlin-Brandenburg, Charité-Universitätsmedizin Berlin, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Amy McDowell
- Developmental Imaging and Biophysics, UCL Institute of Child Health, University College London, 30 Guilford St, London, WC1N 1EH, UK
| | - Maria Centeno
- Developmental Imaging and Biophysics, UCL Institute of Child Health, University College London, 30 Guilford St, London, WC1N 1EH, UK.,Epilepsy Unit, Neurology Department, Hospital Clinic Barcelona/IDIBAPS, Villarroel 170., Barcelona, 08036, Spain
| | - Friederike Moeller
- Department of Clinical Neurophysiology, Great Ormond Street Hospital, Great Ormond Street, London, WC1N 3JH, UK
| | - Suejen Perani
- Department of Basic and Clinical Neuroscience, KCL Institute of Psychiatry, Psychology & Neuroscience, 16 De Crespigny Park, London, SE5 8AF, UK
| | - Sara Lorio
- School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - Danilo Maziero
- Department of Radiation Medicine & Applied Sciences, University of California, San Diego Health, San Diego, CA, USA
| | - David W Carmichael
- School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK. .,Developmental Imaging and Biophysics, UCL Institute of Child Health, University College London, 30 Guilford St, London, WC1N 1EH, UK.
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3
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Wang L, Zhu W, Wang R, Li W, Liang G, Ji Z, Dong X, Shi X. Suppressing interferences of EIT on synchronous recording EEG based on comb filter for seizure detection. Front Neurol 2022; 13:1070124. [DOI: 10.3389/fneur.2022.1070124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 11/18/2022] [Indexed: 12/03/2022] Open
Abstract
Background and objectiveThe purpose of this study was to eliminate the interferences of electrical impedance tomography (EIT) on synchronous recording electroencephalography (EEG) for seizure detection.MethodsThe simulated EIT signal generated by COMSOL Multiphysics was superimposed on the clinical EEG signal obtained from the CHB-MIT Scalp EEG Database, and then the spectrum features of superimposed mixed signals were analyzed. According to the spectrum analysis, in addition to high-frequency interference at 51.2 kHz related to the drive current, there was also low-frequency interference caused by switching of electrode pairs, which were used to inject drive current. A low pass filter and a comb filter were used to suppress the high-frequency interference and low-frequency interference, respectively. Simulation results suggested the low-pass filter and comb filter working together effectively filtered out the interference of EIT on EEG in the process of synchronous monitoring.ResultsAs a result, the normal EEG and epileptic EEG could be recognized effectively. Pearson correlation analysis further confirmed the interference of EIT on EEG was effectively suppressed.ConclusionsThis study provides a simple and effective interference suppression method for the synchronous monitoring of EIT and EEG, which could be served as a reference for the synchronous monitoring of EEG and other medical electromagnetic devices.
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Ikemoto S, von Ellenrieder N, Gotman J. EEG-fMRI of epileptiform discharges: non-invasive investigation of the whole brain. Epilepsia 2022; 63:2725-2744. [PMID: 35822919 DOI: 10.1111/epi.17364] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 07/08/2022] [Accepted: 07/11/2022] [Indexed: 02/01/2023]
Abstract
Simultaneous EEG-fMRI is a unique and non-invasive method for investigating epileptic activity. Interictal epileptiform discharge-related EEG-fMRI provides cortical and subcortical blood oxygen level-dependent (BOLD) signal changes specific to epileptic discharges. As a result, EEG-fMRI has revealed insights into generators and networks involved in epileptic activity in different types of epilepsy, demonstrating-for instance-the implication of the thalamus in human generalized spike and wave discharges and the role of the Default Mode Network (DMN) in absences and focal epilepsy, and proposed a mechanism for the cortico-subcortical interactions in Lennox-Gastaut syndrome discharges. EEG-fMRI can find deep sources of epileptic activity not available to scalp EEG or MEG and provides critical new information to delineate the epileptic focus when considering surgical treatment or electrode implantation. In recent years, methodological advances, such as artifact removal and automatic detection of events have rendered this method easier to implement, and its clinical potential has since been established by evidence of the impact of BOLD response on clinical decision-making and of the relationship between concordance of BOLD responses with extent of resection and surgical outcome. This review presents the recent developments in EEG-fMRI methodology and EEG-fMRI studies in different types of epileptic disorders as follows: EEG-fMRI acquisition, gradient and pulse artifact removal, statistical analysis, clinical applications, pre-surgical evaluation, altered physiological state in generalized genetic epilepsy, and pediatric EEG-fMRI studies.
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Affiliation(s)
- Satoru Ikemoto
- Montreal Neurological Institute and Hospital, 3801 Rue University, Montreal, QC, Canada.,The Jikei University School of Medicine, Department of Pediatrics, 3-25-8 Nishi-Shimbashi, Minato-ku, Tokyo, Japan
| | | | - Jean Gotman
- Montreal Neurological Institute and Hospital, 3801 Rue University, Montreal, QC, Canada
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Warbrick T. Simultaneous EEG-fMRI: What Have We Learned and What Does the Future Hold? SENSORS 2022; 22:s22062262. [PMID: 35336434 PMCID: PMC8952790 DOI: 10.3390/s22062262] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 03/11/2022] [Accepted: 03/13/2022] [Indexed: 02/01/2023]
Abstract
Simultaneous EEG-fMRI has developed into a mature measurement technique in the past 25 years. During this time considerable technical and analytical advances have been made, enabling valuable scientific contributions to a range of research fields. This review will begin with an introduction to the measurement principles involved in EEG and fMRI and the advantages of combining these methods. The challenges faced when combining the two techniques will then be considered. An overview of the leading application fields where EEG-fMRI has made a significant contribution to the scientific literature and emerging applications in EEG-fMRI research trends is then presented.
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Affiliation(s)
- Tracy Warbrick
- Brain Products GmbH, Zeppelinstrasse 7, 82205 Gilching, Germany
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6
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Mirandola L, Ballotta D, Talami F, Giovannini G, Pavesi G, Vaudano AE, Meletti S. Temporal Lobe Spikes Affect Distant Intrinsic Connectivity Networks. Front Neurol 2021; 12:746468. [PMID: 34975714 PMCID: PMC8718871 DOI: 10.3389/fneur.2021.746468] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 11/22/2021] [Indexed: 11/22/2022] Open
Abstract
Objective: To evaluate local and distant blood oxygen level dependent (BOLD) signal changes related to interictal epileptiform discharges (IED) in drug-resistant temporal lobe epilepsy (TLE). Methods: Thirty-three TLE patients undergoing EEG–functional Magnetic Resonance Imaging (fMRI) as part of the presurgical workup were consecutively enrolled. First, a single-subject spike-related analysis was performed: (a) to verify the BOLD concordance with the presumed Epileptogenic Zone (EZ); and (b) to investigate the Intrinsic Connectivity Networks (ICN) involvement. Then, a group analysis was performed to search for common BOLD changes in TLE. Results: Interictal epileptiform discharges were recorded in 25 patients and in 19 (58%), a BOLD response was obtained at the single-subject level. In 42% of the cases, BOLD changes were observed in the temporal lobe, although only one patient had a pure concordant finding, with a single fMRI cluster overlapping (and limited to) the EZ identified by anatomo-electro-clinical correlations. In the remaining 58% of the cases, BOLD responses were localized outside the temporal lobe and the presumed EZ. In every patient, with a spike-related fMRI map, at least one ICN appeared to be involved. Four main ICNs were preferentially involved, namely, motor, visual, auditory/motor speech, and the default mode network. At the single-subject level, EEG–fMRI proved to have high specificity (above 65%) in detecting engagement of an ICN and the corresponding ictal/postictal symptom, and good positive predictive value (above 67%) in all networks except the visual one. Finally, in the group analysis of BOLD changes related to IED revealed common activations at the right precentral gyrus, supplementary motor area, and middle cingulate gyrus. Significance: Interictal temporal spikes affect several distant extra-temporal areas, and specifically the motor/premotor cortex. EEG–fMRI in patients with TLE eligible for surgery is recommended not for strictly localizing purposes rather it might be useful to investigate ICNs alterations at the single-subject level.
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Affiliation(s)
- Laura Mirandola
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, “San Giovanni Bosco” Hospital, Torino, Italy
- *Correspondence: Laura Mirandola ; ; orcid.org/0000-0002-1626-2932
| | - Daniela Ballotta
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Francesca Talami
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Giada Giovannini
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Azienda Ospedaliero-Universitaria of Modena, Ospedale Civile Baggiovara (OCB) Hospital, Modena, Italy
- PhD Program in Clinical and Experimental Medicine, University of Modena and Reggio Emilia, Modena, Italy
| | - Giacomo Pavesi
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Neurosurgery Unit, Azienda Ospedaliero-Universitaria of Modena, Ospedale Civile Baggiovara (OCB) Hospital, Modena, Italy
| | - Anna Elisabetta Vaudano
- Neurology Unit, Azienda Ospedaliero-Universitaria of Modena, Ospedale Civile Baggiovara (OCB) Hospital, Modena, Italy
| | - Stefano Meletti
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Azienda Ospedaliero-Universitaria of Modena, Ospedale Civile Baggiovara (OCB) Hospital, Modena, Italy
- Stefano Meletti ; orcid.org/0000-0003-0334-539X
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7
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Koupparis A, von Ellenrieder N, Khoo HM, Zazubovits N, Nguyen DK, Hall JA, Dudley RWR, Dubeau F, Gotman J. Association of EEG-fMRI Responses and Outcome After Epilepsy Surgery. Neurology 2021; 97:e1523-e1536. [PMID: 34400584 PMCID: PMC8575131 DOI: 10.1212/wnl.0000000000012660] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 08/04/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES To assess the utility of EEG-fMRI for epilepsy surgery, we evaluated surgical outcome in relation to the resection of the most significant EEG-fMRI response. METHODS Patients with postoperative neuroimaging and follow-up of at least 1 year were included. In EEG-fMRI responses, we defined as primary the cluster with the highest absolute t value located in the cortex and evaluated 3 levels of confidence for the results. The threshold for low confidence was t ≥ 3.1 (p < 0.005); the one for medium confidence corresponded to correction for multiple comparisons with a false discovery rate of 0.05; and a result reached high confidence when the primary cluster was much more significant than the next highest cluster. Concordance with the resection was determined by comparison to postoperative neuroimaging. RESULTS We evaluated 106 epilepsy surgeries in 84 patients. An increasing association between concordance and surgical outcome with higher levels of confidence was demonstrated. If the peak response was not resected, the surgical outcome was likely to be poor: for the high confidence level, no patient had a good outcome; for the medium and low levels, only 18% and 28% had a good outcome. The positive predictive value remained low for all confidence levels, indicating that removing the maximum cluster did not ensure seizure freedom. DISCUSSION Resection of the primary EEG-fMRI cluster, especially in high confidence cases, is necessary to obtain a good outcome but not sufficient. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that failure to resect the primary EEG-fMRI cluster is associated with poorer epilepsy surgery outcomes.
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Affiliation(s)
- Andreas Koupparis
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada.
| | - Nicolás von Ellenrieder
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
| | - Hui Ming Khoo
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
| | - Natalja Zazubovits
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
| | - Dang Khoa Nguyen
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
| | - Jeffery A Hall
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
| | - Roy W R Dudley
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
| | - Francois Dubeau
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
| | - Jean Gotman
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
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8
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Chaudhary UJ, Centeno M, Carmichael DW, Diehl B, Walker MC, Duncan JS, Lemieux L. Mapping Epileptic Networks Using Simultaneous Intracranial EEG-fMRI. Front Neurol 2021; 12:693504. [PMID: 34621233 PMCID: PMC8490636 DOI: 10.3389/fneur.2021.693504] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 07/20/2021] [Indexed: 11/29/2022] Open
Abstract
Background: Potentially curative epilepsy surgery can be offered if a single, discrete epileptogenic zone (EZ) can be identified. For individuals in whom there is no clear concordance between clinical localization, scalp EEG, and imaging data, intracranial EEG (icEEG) may be needed to confirm a predefined hypothesis regarding irritative zone (IZ), seizure onset zone (SOZ), and EZ prior to surgery. However, icEEG has limited spatial sampling and may fail to reveal the full extent of epileptogenic network if predefined hypothesis is not correct. Simultaneous icEEG-fMRI has been safely acquired in humans and allows exploration of neuronal activity at the whole-brain level related to interictal epileptiform discharges (IED) captured intracranially. Methods: We report icEEG-fMRI in eight patients with refractory focal epilepsy who had resective surgery and good postsurgical outcome. Surgical resection volume in seizure-free patients post-surgically reflects confirmed identification of the EZ. IEDs on icEEG were classified according to their topographic distribution and localization (Focal, Regional, Widespread, and Non-contiguous). We also divided IEDs by their location within the surgical resection volume [primary IZ (IZ1) IED] or outside [secondary IZ (IZ2) IED]. The distribution of fMRI blood oxygen level-dependent (BOLD) changes associated with individual IED classes were assessed over the whole brain using a general linear model. The concordance of resulting BOLD map was evaluated by comparing localization of BOLD clusters with surgical resection volume. Additionally, we compared the concordance of BOLD maps and presence of BOLD clusters in remote brain areas: precuneus, cuneus, cingulate, medial frontal, and thalamus for different IED classes. Results: A total of 38 different topographic IED classes were identified across the 8 patients: Focal (22) and non-focal (16, Regional = 9, Widespread = 2, Non-contiguous = 5). Twenty-nine IEDs originated from IZ1 and 9 from IZ2. All IED classes were associated with BOLD changes. BOLD maps were concordant with the surgical resection volume for 27/38 (71%) IED classes, showing statistical global maximum BOLD cluster or another cluster in the surgical resection volume. The concordance of BOLD maps with surgical resection volume was greater (p < 0.05) for non-focal (87.5%, 14/16) as compared to Focal (59%, 13/22) IED classes. Additionally, BOLD clusters in remote cortical and deep brain areas were present in 84% (32/38) of BOLD maps, more commonly (15/16; 93%) for non-focal IED-related BOLD maps. Conclusions: Simultaneous icEEG-fMRI can reveal BOLD changes at the whole-brain level for a wide range of IEDs on icEEG. BOLD clusters within surgical resection volume and remote brain areas were more commonly seen for non-focal IED classes, suggesting that a wider hemodynamic network is at play.
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Affiliation(s)
- Umair J Chaudhary
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, United Kingdom.,Magnetic Resonance Imaging (MRI) Unit, Epilepsy Society, Chalfont St. Peter, United Kingdom.,Neurology Department, University Hospital Coventry and Warwickshire, Coventry, United Kingdom
| | - Maria Centeno
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, United Kingdom.,Magnetic Resonance Imaging (MRI) Unit, Epilepsy Society, Chalfont St. Peter, United Kingdom.,Epilepsy Unit, Neurology Department, Hospital Clinic Barcelona, Barcelona, Spain
| | - David W Carmichael
- Imaging and Biophysics Unit, University College London (UCL) Institute of Child Health, London, United Kingdom
| | - Beate Diehl
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, United Kingdom.,Magnetic Resonance Imaging (MRI) Unit, Epilepsy Society, Chalfont St. Peter, United Kingdom.,Clinical Neurophysiology, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Matthew C Walker
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, United Kingdom.,Magnetic Resonance Imaging (MRI) Unit, Epilepsy Society, Chalfont St. Peter, United Kingdom
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, United Kingdom.,Magnetic Resonance Imaging (MRI) Unit, Epilepsy Society, Chalfont St. Peter, United Kingdom
| | - Louis Lemieux
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, United Kingdom.,Magnetic Resonance Imaging (MRI) Unit, Epilepsy Society, Chalfont St. Peter, United Kingdom
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9
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Vaudano AE, Mirandola L, Talami F, Giovannini G, Monti G, Riguzzi P, Volpi L, Michelucci R, Bisulli F, Pasini E, Tinuper P, Di Vito L, Gessaroli G, Malagoli M, Pavesi G, Cardinale F, Tassi L, Lemieux L, Meletti S. fMRI-Based Effective Connectivity in Surgical Remediable Epilepsies: A Pilot Study. Brain Topogr 2021; 34:632-650. [PMID: 34152513 DOI: 10.1007/s10548-021-00857-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 06/13/2021] [Indexed: 11/24/2022]
Abstract
Simultaneous EEG-fMRI can contribute to identify the epileptogenic zone (EZ) in focal epilepsies. However, fMRI maps related to Interictal Epileptiform Discharges (IED) commonly show multiple regions of signal change rather than focal ones. Dynamic causal modeling (DCM) can estimate effective connectivity, i.e. the causal effects exerted by one brain region over another, based on fMRI data. Here, we employed DCM on fMRI data in 10 focal epilepsy patients with multiple IED-related regions of BOLD signal change, to test whether this approach can help the localization process of EZ. For each subject, a family of competing deterministic, plausible DCM models were constructed using IED as autonomous input at each node, one at time. The DCM findings were compared to the presurgical evaluation results and classified as: "Concordant" if the node identified by DCM matches the presumed focus, "Discordant" if the node is distant from the presumed focus, or "Inconclusive" (no statistically significant result). Furthermore, patients who subsequently underwent intracranial EEG recordings or surgery were considered as having an independent validation of DCM results. The effective connectivity focus identified using DCM was Concordant in 7 patients, Discordant in two cases and Inconclusive in one. In four of the 6 patients operated, the DCM findings were validated. Notably, the two Discordant and Invalidated results were found in patients with poor surgical outcome. Our findings provide preliminary evidence to support the applicability of DCM on fMRI data to investigate the epileptic networks in focal epilepsy and, particularly, to identify the EZ in complex cases.
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Affiliation(s)
- A E Vaudano
- Neurology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Via Giardini 1355, 41100, Modena, Italy. .,Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.
| | - L Mirandola
- Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - F Talami
- Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - G Giovannini
- Neurology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Via Giardini 1355, 41100, Modena, Italy.,Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - G Monti
- Neurology Unit, AUSL Modena, Ospedale Ramazzini, Carpi, MO, Italy
| | - P Riguzzi
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Unit of Neurology, Bellaria Hospital, Bologna, Italy
| | - L Volpi
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Unit of Neurology, Bellaria Hospital, Bologna, Italy
| | - R Michelucci
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Unit of Neurology, Bellaria Hospital, Bologna, Italy
| | - F Bisulli
- Department of Biomedical and NeuroMotor Sciences (DIBINEM), University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Epilepsy Center (Reference Center for Rare and Complex Epilepsies - EpiCARE), Bologna, Italy
| | - E Pasini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Unit of Neurology, Bellaria Hospital, Bologna, Italy
| | - P Tinuper
- Department of Biomedical and NeuroMotor Sciences (DIBINEM), University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Epilepsy Center (Reference Center for Rare and Complex Epilepsies - EpiCARE), Bologna, Italy
| | - L Di Vito
- Department of Biomedical and NeuroMotor Sciences (DIBINEM), University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Epilepsy Center (Reference Center for Rare and Complex Epilepsies - EpiCARE), Bologna, Italy
| | - G Gessaroli
- Neurology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Via Giardini 1355, 41100, Modena, Italy
| | - M Malagoli
- Neuroradiology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy
| | - G Pavesi
- Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.,Neurosurgery Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy
| | - F Cardinale
- "Claudio Munari" Epilepsy Surgery Center, Niguarda Hospital, Milan, Italy
| | - L Tassi
- "Claudio Munari" Epilepsy Surgery Center, Niguarda Hospital, Milan, Italy
| | - L Lemieux
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - S Meletti
- Neurology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Via Giardini 1355, 41100, Modena, Italy.,Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
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10
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Wang J, Jing B, Liu R, Li D, Wang W, Wang J, Lei J, Xing Y, Yan J, Loh HH, Lu G, Yang X. Characterizing the seizure onset zone and epileptic network using EEG-fMRI in a rat seizure model. Neuroimage 2021; 237:118133. [PMID: 33951515 DOI: 10.1016/j.neuroimage.2021.118133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 04/07/2021] [Accepted: 04/26/2021] [Indexed: 11/26/2022] Open
Abstract
Accurate epileptogenic zone (EZ) or seizure onset zone (SOZ) localization is crucial for epilepsy surgery optimization. Previous animal and human studies on epilepsy have reported that changes in blood oxygen level-dependent (BOLD) signals induced by epileptic events could be used as diagnostic markers for EZ or SOZ localization. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) recording is gaining interest as a non-invasive tool for preoperative epilepsy evaluation. However, EEG-fMRI studies have reported inconsistent and ambiguous findings. Therefore, it remains unclear whether BOLD responses can be used for accurate EZ or SOZ localization. In this study, we used simultaneous EEG-fMRI recording in a rat model of 4-aminopyridine-induced acute focal seizures to assess the spatial concordance between individual BOLD responses and the SOZ. This was to determine the optimal use of simultaneous EEG-fMRI recording in the SOZ localization. We observed a high spatial consistency between BOLD responses and the SOZ. Further, dynamic BOLD responses were consistent with the regions where the seizures were propagated. These results suggested that simultaneous EEG-fMRI recording could be used as a noninvasive clinical diagnostic technique for localizing the EZ or SOZ and could be an effective tool for mapping epileptic networks.
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Affiliation(s)
- Junling Wang
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China; Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Bin Jing
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Ru Liu
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China; Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Donghong Li
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China; Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Wei Wang
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China; Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jiaoyang Wang
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China; Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jianfeng Lei
- Core Facilities Center, Capital Medical University, Beijing, China
| | - Yue Xing
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China; Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jiaqing Yan
- College of Electrical and Control Engineering, North China University of Technology, Beijing, China
| | - Horace H Loh
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Guangming Lu
- Department of Medical Imaging, Jinling Hospital, Southern Medical University, Nanjing, China; Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Xiaofeng Yang
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing Institute of Brain Disorders, Beijing, China; Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China.
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11
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Sadjadi SM, Ebrahimzadeh E, Shams M, Seraji M, Soltanian-Zadeh H. Localization of Epileptic Foci Based on Simultaneous EEG-fMRI Data. Front Neurol 2021; 12:645594. [PMID: 33986718 PMCID: PMC8110922 DOI: 10.3389/fneur.2021.645594] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 03/11/2021] [Indexed: 02/01/2023] Open
Abstract
Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) enables a non-invasive investigation of the human brain function and evaluation of the correlation of these two important modalities of brain activity. This paper explores recent reports on using advanced simultaneous EEG–fMRI methods proposed to map the regions and networks involved in focal epileptic seizure generation. One of the applications of EEG and fMRI combination as a valuable clinical approach is the pre-surgical evaluation of patients with epilepsy to map and localize the precise brain regions associated with epileptiform activity. In the process of conventional analysis using EEG–fMRI data, the interictal epileptiform discharges (IEDs) are visually extracted from the EEG data to be convolved as binary events with a predefined hemodynamic response function (HRF) to provide a model of epileptiform BOLD activity and use as a regressor for general linear model (GLM) analysis of the fMRI data. This review examines the methodologies involved in performing such studies, including techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. It then discusses the results reported for patients with primary generalized epilepsy and patients with different types of focal epileptic disorders. An important matter that these results have brought to light is that the brain regions affected by interictal epileptic discharges might not be limited to the ones where they have been generated. The developed methods can help reveal the regions involved in or affected by a seizure onset zone (SOZ). As confirmed by the reviewed literature, EEG–fMRI provides information that comes particularly useful when evaluating patients with refractory epilepsy for surgery.
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Affiliation(s)
- Seyyed Mostafa Sadjadi
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Elias Ebrahimzadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.,Neuroimage Signal and Image Analysis Group, School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Mohammad Shams
- Neural Engineering Laboratory, Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, United States
| | - Masoud Seraji
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, United States.,Behavioral and Neural Sciences Graduate Program, Rutgers University, Newark, NJ, United States
| | - Hamid Soltanian-Zadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.,Neuroimage Signal and Image Analysis Group, School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.,Medical Image Analysis Laboratory, Departments of Radiology and Research Administration, Henry Ford Health System, Detroit, MI, United States
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