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Pigorini A, Avanzini P, Barborica A, Bénar CG, David O, Farisco M, Keller CJ, Manfridi A, Mikulan E, Paulk AC, Roehri N, Subramanian A, Vulliémoz S, Zelmann R. Simultaneous invasive and non-invasive recordings in humans: A novel Rosetta stone for deciphering brain activity. J Neurosci Methods 2024; 408:110160. [PMID: 38734149 DOI: 10.1016/j.jneumeth.2024.110160] [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: 12/18/2023] [Revised: 04/10/2024] [Accepted: 05/01/2024] [Indexed: 05/13/2024]
Abstract
Simultaneous noninvasive and invasive electrophysiological recordings provide a unique opportunity to achieve a comprehensive understanding of human brain activity, much like a Rosetta stone for human neuroscience. In this review we focus on the increasingly-used powerful combination of intracranial electroencephalography (iEEG) with scalp electroencephalography (EEG) or magnetoencephalography (MEG). We first provide practical insight on how to achieve these technically challenging recordings. We then provide examples from clinical research on how simultaneous recordings are advancing our understanding of epilepsy. This is followed by the illustration of how human neuroscience and methodological advances could benefit from these simultaneous recordings. We conclude with a call for open data sharing and collaboration, while ensuring neuroethical approaches and argue that only with a true collaborative approach the promises of simultaneous recordings will be fulfilled.
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Affiliation(s)
- Andrea Pigorini
- Department of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, Milan, Italy; UOC Maxillo-facial Surgery and dentistry, Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, Milan, Italy.
| | - Pietro Avanzini
- Institute of Neuroscience, Consiglio Nazionale delle Ricerche, Parma, Italy
| | | | - Christian-G Bénar
- Aix Marseille Univ, Inserm, U1106, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Olivier David
- Aix Marseille Univ, Inserm, U1106, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Michele Farisco
- Centre for Research Ethics and Bioethics, Department of Public Health and Caring Sciences, Uppsala University, P.O. Box 256, Uppsala, SE 751 05, Sweden; Science and Society Unit Biogem, Biology and Molecular Genetics Institute, Via Camporeale snc, Ariano Irpino, AV 83031, Italy
| | - Corey J Keller
- Department of Psychiatry & Behavioral Sciences, Stanford University Medical Center, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University Medical Center, Stanford, CA 94305, USA; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA 94394, USA
| | - Alfredo Manfridi
- Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy
| | - Ezequiel Mikulan
- Department of Health Sciences, Università degli Studi di Milano, Milan, Italy
| | - Angelique C Paulk
- Department of Neurology and Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Nicolas Roehri
- EEG and Epilepsy Unit, Dpt of Clinical Neurosciences, Geneva University Hospitals and University of Geneva, Switzerland
| | - Ajay Subramanian
- Department of Psychiatry & Behavioral Sciences, Stanford University Medical Center, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University Medical Center, Stanford, CA 94305, USA; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA 94394, USA
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, Dpt of Clinical Neurosciences, Geneva University Hospitals and University of Geneva, Switzerland
| | - Rina Zelmann
- Department of Neurology and Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
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2
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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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3
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Optimizing EEG Source Reconstruction with Concurrent fMRI-Derived Spatial Priors. Brain Topogr 2022; 35:282-301. [PMID: 35142957 PMCID: PMC9098592 DOI: 10.1007/s10548-022-00891-3] [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: 06/30/2021] [Accepted: 01/31/2022] [Indexed: 02/01/2023]
Abstract
Reconstructing EEG sources involves a complex pipeline, with the inverse problem being the most challenging. Multiple inversion algorithms are being continuously developed, aiming to tackle the non-uniqueness of this problem, which has been shown to be partially circumvented by including prior information in the inverse models. Despite a few efforts, there are still current and persistent controversies regarding the inversion algorithm of choice and the optimal set of spatial priors to be included in the inversion models. The use of simultaneous EEG-fMRI data is one approach to tackle this problem. The spatial resolution of fMRI makes fMRI derived spatial priors very convenient for EEG reconstruction, however, only task activation maps and resting-state networks (RSNs) have been explored so far, overlooking the recent, but already accepted, notion that brain networks exhibit dynamic functional connectivity fluctuations. The lack of a systematic comparison between different source reconstruction algorithms, considering potentially more brain-informative priors such as fMRI, motivates the search for better reconstruction models. Using simultaneous EEG-fMRI data, here we compared four different inversion algorithms (minimum norm, MN; low resolution electromagnetic tomography, LORETA; empirical Bayes beamformer, EBB; and multiple sparse priors, MSP) under a Bayesian framework (as implemented in SPM), each with three different sets of priors consisting of: (1) those specific to the algorithm; (2) those specific to the algorithm plus fMRI task activation maps and RSNs; and (3) those specific to the algorithm plus fMRI task activation maps and RSNs and network modules of task-related dFC states estimated from the dFC fluctuations. The quality of the reconstructed EEG sources was quantified in terms of model-based metrics, namely the expectation of the posterior probability P(model|data) and variance explained of the inversion models, and the overlap/proportion of brain regions known to be involved in the visual perception tasks that the participants were submitted to, and RSN templates, with/within EEG source components. Model-based metrics suggested that model parsimony is preferred, with the combination MSP and priors specific to this algorithm exhibiting the best performance. However, optimal overlap/proportion values were found using EBB and priors specific to this algorithm and fMRI task activation maps and RSNs or MSP and considering all the priors (algorithm priors, fMRI task activation maps and RSNs and dFC state modules), respectively, indicating that fMRI spatial priors, including dFC state modules, might contain useful information to recover EEG source components reflecting neuronal activity of interest. Our main results show that providing fMRI spatial derived priors that reflect the dynamics of the brain might be useful to map neuronal activity more accurately from EEG-fMRI. Furthermore, this work paves the way towards a more informative selection of the optimal EEG source reconstruction approach, which may be critical in future studies.
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Zhang Y, Le S, Li H, Ji B, Wang MH, Tao J, Liang JQ, Zhang XY, Kang XY. MRI magnetic compatible electrical neural interface: From materials to application. Biosens Bioelectron 2021; 194:113592. [PMID: 34507098 DOI: 10.1016/j.bios.2021.113592] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 08/24/2021] [Indexed: 01/07/2023]
Abstract
Neural electrical interfaces are important tools for local neural stimulation and recording, which potentially have wide application in the diagnosis and treatment of neural diseases, as well as in the transmission of neural activity for brain-computer interface (BCI) systems. At the same time, magnetic resonance imaging (MRI) is one of the effective and non-invasive techniques for recording whole-brain signals, providing details of brain structures and also activation pattern maps. Simultaneous recording of extracellular neural signals and MRI combines two expressions of the same neural activity and is believed to be of great importance for the understanding of brain function. However, this combination makes requests on the magnetic and electronic performance of neural interface devices. MRI-compatibility refers here to a technological approach to simultaneous MRI and electrode recording or stimulation without artifacts in imaging. Trade-offs between materials magnetic susceptibility selection and electrical function should be considered. Herein, prominent trends in selecting materials of suitable magnetic properties are analyzed and material design, function and application of neural interfaces are outlined together with the remaining challenge to fabricate MRI-compatible neural interface.
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Affiliation(s)
- Yuan Zhang
- Laboratory for Neural Interface and Brain Computer Interface, Institute of AI and Robotics, Academy for Engineering and Technology, FUDAN University, 220 Handan Rd., Yangpu District, Shanghai, 200433, China; Ji Hua Laboratory, 28 Island Ring South Rd., Foshan City, 528200, China; Engineering Research Center of AI & Robotics, Ministry of Education, Shanghai Engineering Research Center of AI & Robotics, MOE Frontiers Center for Brain Science, Shanghai 200433, China; Research Center for Intelligent Sensing, Zhejiang Lab, Hangzhou, 311100, China; Yiwu Research Institute of Fudan University, Chengbei Road, Yiwu City, 322000, Zhejiang, China
| | - Song Le
- Laboratory for Neural Interface and Brain Computer Interface, Institute of AI and Robotics, Academy for Engineering and Technology, FUDAN University, 220 Handan Rd., Yangpu District, Shanghai, 200433, China; Ji Hua Laboratory, 28 Island Ring South Rd., Foshan City, 528200, China; Engineering Research Center of AI & Robotics, Ministry of Education, Shanghai Engineering Research Center of AI & Robotics, MOE Frontiers Center for Brain Science, Shanghai 200433, China; Research Center for Intelligent Sensing, Zhejiang Lab, Hangzhou, 311100, China; Yiwu Research Institute of Fudan University, Chengbei Road, Yiwu City, 322000, Zhejiang, China
| | - Hui Li
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen, 518055, China
| | - Bowen Ji
- Unmanned System Research Institute; Ministry of Education Key Laboratory of Micro/Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, 710072, China
| | - Ming-Hao Wang
- The MOE Engineering Research Center of Smart Microsensors and Microsystems, School of Electronics & Information, Hangzhou Dianzi University, Hangzhou, 310018, China
| | - Jin Tao
- State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin, 130033, China
| | - Jing-Qiu Liang
- State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin, 130033, China
| | - Xiao-Yong Zhang
- Institute of Science and Technology for Brain-inspired Intelligence, FUDAN University, Shanghai, 200433, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai 200433, China
| | - Xiao-Yang Kang
- Laboratory for Neural Interface and Brain Computer Interface, Institute of AI and Robotics, Academy for Engineering and Technology, FUDAN University, 220 Handan Rd., Yangpu District, Shanghai, 200433, China; Ji Hua Laboratory, 28 Island Ring South Rd., Foshan City, 528200, China; Engineering Research Center of AI & Robotics, Ministry of Education, Shanghai Engineering Research Center of AI & Robotics, MOE Frontiers Center for Brain Science, Shanghai 200433, China; Research Center for Intelligent Sensing, Zhejiang Lab, Hangzhou, 311100, China; Yiwu Research Institute of Fudan University, Chengbei Road, Yiwu City, 322000, Zhejiang, China.
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5
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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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6
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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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7
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Tehrani N, Wilson W, Pittman DJ, Mosher V, Peedicail JS, Aghakhani Y, Beers CA, Gaxiola-Valdez I, Singh S, Goodyear BG, Federico P. Localization of interictal discharge origin: A simultaneous intracranial electroencephalographic-functional magnetic resonance imaging study. Epilepsia 2021; 62:1105-1118. [PMID: 33782964 DOI: 10.1111/epi.16887] [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: 11/30/2020] [Revised: 03/07/2021] [Accepted: 03/08/2021] [Indexed: 01/02/2023]
Abstract
OBJECTIVE Scalp electroencephalographic (EEG)-functional magnetic resonance imaging (fMRI) studies suggest that the maximum blood oxygen level-dependent (BOLD) response to an interictal epileptiform discharge (IED) identifies the area of IED generation. However, the maximum BOLD response has also been reported in distant, seemingly irrelevant areas. Given the poor postoperative outcomes associated with extra-temporal lobe epilepsy, we hypothesized this finding is more common when analyzing extratemporal IEDs as compared to temporal IEDs. We further hypothesized that a subjective, holistic assessment of other significant BOLD clusters to identify the most clinically relevant cluster could be used to overcome this limitation and therefore better identify the likely origin of an IED. Specifically, we also considered the second maximum cluster and the cluster closest to the electrode contacts where the IED was observed. METHODS Maps of significant IED-related BOLD activation were generated for 48 different IEDs recorded from 33 patients who underwent intracranial EEG-fMRI. The locations of the maximum, second maximum, and closest clusters were identified for each IED. An epileptologist, blinded to these cluster assignments, selected the most clinically relevant BOLD cluster, taking into account all available clinical information. The distances between these BOLD clusters and their corresponding IEDs were then measured. RESULTS The most clinically relevant cluster was the maximum cluster for 56% (27/48) of IEDs, the second maximum cluster for 13% (6/48) of IEDs, and the closest cluster for 31% (15/48) of IEDs. The maximum clusters were closer to IED contacts for temporal than for extratemporal IEDs (p = .022), whereas the most clinically relevant clusters were not significantly different (p = .056). SIGNIFICANCE The maximum BOLD response to IEDs may not always be the most indicative of IED origin. We propose that available clinical information should be used in conjunction with EEG-fMRI data to identify a BOLD cluster representative of the IED origin.
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Affiliation(s)
- Negar Tehrani
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - William Wilson
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Daniel J Pittman
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Victoria Mosher
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Joseph S Peedicail
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Yahya Aghakhani
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Craig A Beers
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Ismael Gaxiola-Valdez
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Shaily Singh
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Bradley G Goodyear
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Paolo Federico
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Seaman Family MR Research Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.,Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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8
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Hawsawi HB, Papadaki A, Thornton JS, Carmichael DW, Lemieux L. Temperature Measurements in the Vicinity of Human Intracranial EEG Electrodes Exposed to Body-Coil RF for MRI at 1.5T. Front Neurosci 2020; 14:429. [PMID: 32477052 PMCID: PMC7235361 DOI: 10.3389/fnins.2020.00429] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Accepted: 04/07/2020] [Indexed: 11/13/2022] Open
Abstract
The application of intracranial electroencephalography (icEEG) recording during functional magnetic resonance imaging (icEEG-fMRI) has allowed the study of the hemodynamic correlates of epileptic activity and of the neurophysiological basis of the blood oxygen level-dependent (BOLD) signal. However, the applicability of this technique is affected by data quality issues such as signal drop out in the vicinity of the implanted electrodes. In our center we have limited the technique to a quadrature head transmit and receive RF coil following the results of a safety evaluation. The purpose of this study is to gather further safety-related evidence for performing icEEG-fMRI using a body RF-transmit coil, to allow the greater flexibility afforded by the use of modern, high-density receive arrays, and therefore parallel imaging with benefits such as reduced signal drop-out and distortion artifact. Specifically, we performed a set of empirical temperature measurements on a 1.5T Siemens Avanto MRI scanner with the body RF-transmit coil in a range of electrode and connector cable configurations. The observed RF-induced heating during a high-SAR sequence was maximum in the immediate vicinity of a depth electrode located along the scanner's central axis (range: 0.2-2.4°C) and below 0.5°C at the other electrodes. Also for the high-SAR sequence, we observed excessive RF-related heating in connection cable configurations that deviate from our recommended setup. For the low-SAR sequence, the maximum observed temperature increase across all configurations was 0.3°C. This provides good evidence to allow simultaneous icEEG-fMRI to be performed utilizing the body transmit coil on the 1.5T Siemens Avanto MRI scanner at our center with acceptable additional risk by following a well-defined protocol.
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Affiliation(s)
- Hassan B. Hawsawi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- MRI Unit, Epilepsy Society, Buckinghamshire, United Kingdom
- Administartion of Medical Physics, King Abdullah Medical City, Makkah, Saudi Arabia
| | - Anastasia Papadaki
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, Queen Square, London, United Kingdom
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - John S. Thornton
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, Queen Square, London, United Kingdom
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - David W. Carmichael
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, United Kingdom
- Wellcome EPSRC Centre for Medical Engineering, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Louis Lemieux
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- MRI Unit, Epilepsy Society, Buckinghamshire, United Kingdom
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