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Yang Y, Luo S, Wang W, Gao X, Yao X, Wu T. From bench to bedside: Overview of magnetoencephalography in basic principle, signal processing, source localization and clinical applications. Neuroimage Clin 2024; 42:103608. [PMID: 38653131 PMCID: PMC11059345 DOI: 10.1016/j.nicl.2024.103608] [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: 11/22/2023] [Revised: 04/14/2024] [Accepted: 04/16/2024] [Indexed: 04/25/2024]
Abstract
Magnetoencephalography (MEG) is a non-invasive technique that can precisely capture the dynamic spatiotemporal patterns of the brain by measuring the magnetic fields arising from neuronal activity along the order of milliseconds. Observations of brain dynamics have been used in cognitive neuroscience, the diagnosis of neurological diseases, and the brain-computer interface (BCI). In this study, we outline the basic principle, signal processing, and source localization of MEG, and describe its clinical applications for cognitive assessment, the diagnoses of neurological diseases and mental disorders, preoperative evaluation, and the BCI. This review not only provides an overall perspective of MEG, ranging from practical techniques to clinical applications, but also enhances the prevalent understanding of neural mechanisms. The use of MEG is expected to lead to significant breakthroughs in neuroscience.
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Affiliation(s)
- Yanling Yang
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China; College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Shichang Luo
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China; College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Wenjie Wang
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China; College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Xiumin Gao
- School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Xufeng Yao
- College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China.
| | - Tao Wu
- College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China
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2
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Noorizadeh N, Varner JA, Birg L, Williard T, Rezaie R, Wheless J, Narayana S. Comparing the efficacy of awake and sedated MEG to TMS in mapping hand sensorimotor cortex in a clinical cohort. Neuroimage Clin 2024; 41:103562. [PMID: 38215622 PMCID: PMC10821581 DOI: 10.1016/j.nicl.2024.103562] [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: 08/28/2023] [Revised: 11/19/2023] [Accepted: 01/07/2024] [Indexed: 01/14/2024]
Abstract
Non-invasive methods such as Transcranial Magnetic Stimulation (TMS) and magnetoencephalography (MEG) aid in the pre-surgical evaluation of patients with epilepsy or brain tumor to identify sensorimotor cortices. MEG requires sedation in children or patients with developmental delay. However, TMS can be applied to awake patients of all ages with any cognitive abilities. In this study, we compared the efficacy of TMS with MEG (in awake and sedated states) in identifying the hand sensorimotor areas in patients with epilepsy or brain tumors. We identified 153 patients who underwent awake- (n = 98) or sedated-MEG (n = 55), along with awake TMS for hand sensorimotor mapping as part of their pre-surgical evaluation. TMS involved stimulating the precentral gyrus and recording electromyography responses, while MEG identified the somatosensory cortex during median nerve stimulation. Awake-MEG had a success rate of 92.35 % and TMS had 99.49 % (p-value = 0.5517). However, in the sedated-MEG cohort, TMS success rate of 95.61 % was significantly higher compared to MEG's 58.77 % (p-value = 0.0001). Factors affecting mapping success were analyzed. Logistic regression across the entire cohort identified patient sedation as the lone significant predictor, contrary to age, lesion, metal, and number of antiseizure medications (ASMs). A subsequent analysis replaced sedation with anesthetic drug dosage, revealing no significant predictors impacting somatosensory mapping success under sedation. This study yields insights into the utility of TMS and MEG in mapping hand sensorimotor cortices and underscores the importance of considering factors that influence eloquent cortex mapping limitations during sedation.
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Affiliation(s)
- Negar Noorizadeh
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN, United States; Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, United States
| | - Jackie Austin Varner
- Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, United States
| | - Liliya Birg
- Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, United States
| | - Theresa Williard
- Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, United States
| | - Roozbeh Rezaie
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN, United States; Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, United States
| | - James Wheless
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN, United States; Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, United States
| | - Shalini Narayana
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN, United States; Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, United States; Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, United States.
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Fred AL, Kumar SN, Kumar Haridhas A, Ghosh S, Purushothaman Bhuvana H, Sim WKJ, Vimalan V, Givo FAS, Jousmäki V, Padmanabhan P, Gulyás B. A Brief Introduction to Magnetoencephalography (MEG) and Its Clinical Applications. Brain Sci 2022; 12:brainsci12060788. [PMID: 35741673 PMCID: PMC9221302 DOI: 10.3390/brainsci12060788] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/01/2022] [Accepted: 06/08/2022] [Indexed: 11/30/2022] Open
Abstract
Magnetoencephalography (MEG) plays a pivotal role in the diagnosis of brain disorders. In this review, we have investigated potential MEG applications for analysing brain disorders. The signal-to-noise ratio (SNRMEG = 2.2 db, SNREEG < 1 db) and spatial resolution (SRMEG = 2−3 mm, SREEG = 7−10 mm) is higher for MEG than EEG, thus MEG potentially facilitates accurate monitoring of cortical activity. We found that the direct electrophysiological MEG signals reflected the physiological status of neurological disorders and play a vital role in disease diagnosis. Single-channel connectivity, as well as brain network analysis, using MEG data acquired during resting state and a given task has been used for the diagnosis of neurological disorders such as epilepsy, Alzheimer’s, Parkinsonism, autism, and schizophrenia. The workflow of MEG and its potential applications in the diagnosis of disease and therapeutic planning are also discussed. We forecast that computer-aided algorithms will play a prominent role in the diagnosis and prediction of neurological diseases in the future. The outcome of this narrative review will aid researchers to utilise MEG in diagnostics.
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Affiliation(s)
- Alfred Lenin Fred
- Department of CSE, Mar Ephraem College of Engineering and Technology, Marthandam 629171, Tamil Nadu, India; (A.L.F.); (F.A.S.G.)
| | | | - Ajay Kumar Haridhas
- Department of ECE, Mar Ephraem College of Engineering and Technology, Marthandam 629171, Tamil Nadu, India;
| | - Sayantan Ghosh
- Department of Integrative Biology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India;
| | - Harishita Purushothaman Bhuvana
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
| | - Wei Khang Jeremy Sim
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
| | - Vijayaragavan Vimalan
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
| | - Fredin Arun Sedly Givo
- Department of CSE, Mar Ephraem College of Engineering and Technology, Marthandam 629171, Tamil Nadu, India; (A.L.F.); (F.A.S.G.)
| | - Veikko Jousmäki
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Aalto NeuroImaging, Department of Neuroscience and Biomedical Engineering, Aalto University, 12200 Espoo, Finland
| | - Parasuraman Padmanabhan
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
- Correspondence: (P.P.); (B.G.)
| | - Balázs Gulyás
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
- Department of Clinical Neuroscience, Karolinska Institute, 17176 Stockholm, Sweden
- Correspondence: (P.P.); (B.G.)
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Zhang C, Liu W, Zhang J, Zhang X, Huang P, Sun B, Zhan S, Cao C. Utility of magnetoencephalography combined with stereo-electroencephalography in resective epilepsy surgery: a 2-year follow-up. Seizure 2022; 97:94-101. [DOI: 10.1016/j.seizure.2022.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 03/14/2022] [Accepted: 03/16/2022] [Indexed: 11/25/2022] Open
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Resting-State MEG Source Space Network Metrics Associated with the Duration of Temporal Lobe Epilepsy. Brain Topogr 2021; 34:731-744. [PMID: 34652579 DOI: 10.1007/s10548-021-00875-9] [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: 05/26/2020] [Accepted: 09/28/2021] [Indexed: 10/20/2022]
Abstract
To evaluate the relationship between the network metrics of 68 brain regions and duration of temporal lobe epilepsy (TLE). Magnetoencephalography (MEG) data from 53 patients with TLE (28 left TLE, 25 right TLE) were recorded between seizures at resting state and analyzed in six frequency bands: delta (0.1-4 Hz), theta (4-8 Hz), lower alpha (8-10 Hz), upper alpha (10-13 Hz), beta (13-30 Hz), and lower gamma (30-48 Hz). Three local network metrics, betweenness centrality, nodal degree, and nodal efficiency, were chosen to analyze the functional brain network. In Left, Right, and All (Left + Right) TLE groups, different metrics provide significant positive or negative correlations with the duration of TLE, in different frequency bands, and in different brain regions. In the Left TLE group, significant correlation between TLE duration and metric exists in the delta, beta, or lower gamma band, with network betweenness centrality, nodal degree, or nodal efficiency, in left caudal middle frontal, left middle temporal, or left supramarginal. In the Right TLE group, significant correlation exists in lower gamma or delta band, with nodal degree, or nodal efficiency, in left precuneus or right temporal pole. In the All TLE group, the significant correlation exists in delta, theta, beta, or lower gamma band, with nodal degree, or betweenness centrality, in either left or right hemisphere. Network metrics for some specific brain regions changed in patients with TLE as the duration of their TLE increased. Further researching these changes may be important for studying the pathogenesis, presurgical evaluation, and clinical treatment of long-term TLE.
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Gao R, Yu T, Xu C, Zhang X, Yan X, Ni D, Zhang X, Ma K, Qiao L, Zhu J, Wang X, Ren Z, Zhang X, Zhang G, Li Y. The value of magnetoencephalography for stereo-EEG-guided radiofrequency thermocoagulation in MRI-negative epilepsy. Epilepsy Res 2020; 163:106322. [PMID: 32278277 DOI: 10.1016/j.eplepsyres.2020.106322] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Revised: 02/24/2020] [Accepted: 03/19/2020] [Indexed: 12/31/2022]
Abstract
OBJECTIVE Magnetoencephalography (MEG) is valuable for guiding resective surgery in patients with epilepsy. However, its value for minimally invasive treatment is still unknown. This study aims to evaluate the value of MEG for stereo-electroencephalogram (EEG)-guided radiofrequency thermocoagulation (SEEG-guided RF-TC) in magnetic resonance imaging (MRI)-negative epilepsies. METHODS An observational cohort study was performed and 19 MRI-negative patients who underwent SEEG-guided RF-TC in our epilepsy center were included. In addition, 16 MRI-positive patients were included as a reference group. Semiology, electrophysiology, and imaging information were collected. To evaluate the value of locating the MEG cluster, the proportion of the RF-TC contacts located in the MEG cluster out of all contacts used to perform RF-TC in each patient was calculated. All patients underwent the standard SEEG-guided RF-TC procedure and were followed up after the treatment. RESULTS Nineteen MRI-negative patients were divided into two groups based on the existence of MEG clusters; 10 patients with MEG clusters were in group I and nine patients without any MEG cluster were in group II. No significant difference was observed in terms of age, sex, type of seizures, or number of SEEG electrodes implanted. The median of the proportion of contacts in the MEG cluster was 77.0 % (IQR 57.7-100.0 %). The follow-up results showed that the probability of being seizure-free at one year after RFTC in MRI-negative patients with an MEG cluster was 30.0 % (95 % CI 11.6-77.3 %), significantly (p = 0.014) higher than that in patients without an MEG cluster; there was no significant difference when compared with MRI-positive patients. CONCLUSION This is the first study to evaluate the value of MEG in SEEG-guided RF-TC in MRI-negative epilepsies. MEG is a useful supplement for patients with MRI-negative epilepsy. MEG can be applied in minimally invasive treatment. MEG clusters can help identify better candidates and provide a valuable target for SEEG-guided RF-TC, which leads to better outcomes.
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Affiliation(s)
- Runshi Gao
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Tao Yu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Cuiping Xu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xiating Zhang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xiaoming Yan
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Duanyu Ni
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xiaohua Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Kai Ma
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Liang Qiao
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jin Zhu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xueyuan Wang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Zhiwei Ren
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xi Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Guojun Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yongjie Li
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
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Role of Functional Imaging Techniques to Assess Motor and Language Cortical Plasticity in Glioma Patients: A Systematic Review. Neural Plast 2019; 2019:4056436. [PMID: 31814822 PMCID: PMC6878806 DOI: 10.1155/2019/4056436] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 10/05/2019] [Indexed: 01/19/2023] Open
Abstract
Cerebral plasticity is the ability of the central nervous system to reorganize itself in response to different injuries. The reshaping of functional areas is a crucial mechanism to compensate for damaged function. It is acknowledged that functional remodeling of cortical areas may occur also in glioma patients. Principal limits of previous investigations on cortical plasticity of motor and language functions included scarce reports of longitudinal evaluations and limited sample sizes. This systematic review is aimed at elucidating cortical brain plasticity for motor and language functions, in adult glioma patients, by means of preoperative and intraoperative mapping techniques. We systematically reviewed the literature for prospective studies, assessing cortical plasticity of motor and language functions in low-grade and high-grade gliomas. Eight longitudinal studies investigated cortical plasticity, evaluated by motor and language task-based functional MRI (fMRI), motor navigated transcranial magnetic stimulation (n-TMS), and intraoperative mapping with cortical direct electrocortical stimulation (DES) of language and motor function. Motor function reorganization appeared relatively limited and mostly characterized by intrahemispheric functional changes, including secondary motor cortices. On the other hand, a high level of functional reshaping was found for language function in DES studies. Occurrence of cortical functional reorganization of language function was described focusing on the intrahemispheric recruitment of perilesional areas. However, the association between these functional patterns and recovery of motor and language deficits still remains partially clear. A number of relevant methodological issues possibly affecting the finding generalization emerged, such as the complexity of plasticity outcome measures and the lack of large longitudinal studies. Future studies are required to further confirm these evidences on cortical plasticity in larger samples, combining both functional imaging and intraoperative mapping techniques in longitudinally evaluations.
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Gofshteyn JS, Le T, Kessler S, Kamens R, Carr C, Gaetz W, Bloy L, Roberts TPL, Schwartz ES, Marsh ED. Synthetic aperture magnetometry and excess kurtosis mapping of Magnetoencephalography (MEG) is predictive of epilepsy surgical outcome in a large pediatric cohort. Epilepsy Res 2019; 155:106151. [PMID: 31247475 PMCID: PMC6699633 DOI: 10.1016/j.eplepsyres.2019.106151] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Revised: 05/23/2019] [Accepted: 06/09/2019] [Indexed: 12/23/2022]
Abstract
OBJECTIVE Resective surgery is the most effective treatment option for patients with refractory epilepsy; however identification of patients who will benefit from epilepsy surgery remains challenging. Synthetic aperture magnetometry and excess kurtosis mapping (SAM(g2)) of magnetoencephalography (MEG) is a non-invasive tool that warrants further examination in the pediatric epilepsy population. Here, we examined the utility of MEG with SAM(g2) to determine if MEG epileptiform foci correlates with surgical outcome and to develop a predictive model incorporating MEG information to best assess likelihood of seizure improvement/freedom from resective surgery. METHODS 564 subjects who had MEG at the Children's Hospital of Philadelphia between 2010-2015 were screened. Clinical epilepsy history and prior electrographic records were extracted and reviewed and correlated with MEG findings. MEG assessments were made by both a neurologist and neuroradiologist. Predictive models were developed to assess the utility of MEG in determining Engel class at one year and five years after resective epilepsy surgery. RESULTS The number of MEG spike foci was highly associated with Engel class outcome at both one year and five years; however, using MEG data in isolation was not significantly predictive of 5 year surgical outcome. When combined with clinical factors; scalp EEG (single ictal onset zone), MRI (lesional or not), age and sex in a logistic regression model MEG foci was significant for Engel class outcome at both 1 year (p = 0.03) and 5 years (0.02). The percent correctly classified for Engel class at one year was 78.43% and the positive predictive value was 71.43. SIGNIFICANCE MEG using SAM(g2) analysis in an important non-invasive tool in the identification of those patients who will benefit most from surgery. Integrating MEG data analysis into pre-surgical evaluation can help to predict epilepsy outcome after resective surgery in the pediatric population if utilized with skilled interpretation.
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Affiliation(s)
- J S Gofshteyn
- Division of Pediatric Neurology, Department of Pediatrics, Weill Cornell Medicine, New York, NY, United States; New-York Presbyterian Hospital, New York, NY, United States
| | - T Le
- Division of Pediatric Neurology, The Children's Hospital of Philadelphia, United States
| | - S Kessler
- Division of Pediatric Neurology, The Children's Hospital of Philadelphia, United States; Departments of Neurology and Pediatrics, Perelman School of Medicine at the University of Pennsylvania, United States
| | - R Kamens
- Division of Pediatric Neurology, The Children's Hospital of Philadelphia, United States
| | - C Carr
- Division of Pediatric Neurology, The Children's Hospital of Philadelphia, United States
| | - W Gaetz
- Division of Neuroradiology, Department of Radiology, The Children's Hospital of Philadelphia, United States; Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, United States
| | - L Bloy
- Division of Neuroradiology, Department of Radiology, The Children's Hospital of Philadelphia, United States; Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, United States
| | - T P L Roberts
- Division of Neuroradiology, Department of Radiology, The Children's Hospital of Philadelphia, United States; Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, United States
| | - E S Schwartz
- Division of Neuroradiology, Department of Radiology, The Children's Hospital of Philadelphia, United States; Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, United States
| | - E D Marsh
- Division of Pediatric Neurology, The Children's Hospital of Philadelphia, United States; Departments of Neurology and Pediatrics, Perelman School of Medicine at the University of Pennsylvania, United States.
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Lin Y, Zhang Z, Zhang X, Yang Y, Huang Z, Zhu Y, Li L, Hu N, Zhang J, Wang Y. Lateralization Value of Low Frequency Band Beamformer Magnetoencephalography Source Imaging in Temporal Lobe Epilepsy. Front Neurol 2018; 9:829. [PMID: 30344505 PMCID: PMC6182046 DOI: 10.3389/fneur.2018.00829] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2018] [Accepted: 09/18/2018] [Indexed: 01/02/2023] Open
Abstract
Objective: In presurgical evaluation of temporal lobe epilepsy (TLE), selection of the resection side is challenging when bilateral temporal epileptiform discharges or structural abnormalities are present. We aim to evaluate the lateralization value of beamformer analysis of magnetoencephalography (MEG) in TLE. Methods: MEG data from 14 TLE patients were analyzed through beamformer analysis. We measured the hemispherical power distribution of beamformer sources and calculated the lateralization index (LI). We calculated the LI at multiple frequencies to explore the frequency dependency and at the delta frequency to define laterality. LI values ranging from -1 to -0.05 indicated right hemispheric dominance. LI values ranging from 0.05 to 1 indicated left hemispheric dominance. LI values ranging from -0.05 to 0.05 defined bilaterality. We measured the power of beamformer sources with a 9-s duration to explore time dependency. Results: The beamformer analysis showed that 10/14 patients had power dominance ipsilateral to resection. The delta frequency band had a higher lateralization value than other frequency bands. A time-dependent power fluctuation was found in the delta frequency band. Conclusions: MEG beamformer analysis, especially in the delta band, might efficiently provide additional information regarding lateralization in TLE.
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Affiliation(s)
- Yicong Lin
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China
| | - Zhiguo Zhang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Xiating Zhang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China
| | - Yingxue Yang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China
| | - Zhaoyang Huang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China
| | - Yu Zhu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China
| | - Liping Li
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China
| | - Ningning Hu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China
| | - Junpeng Zhang
- Department of Medical Information Engineering, Sichuan University, Chengdu, China
| | - Yuping Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China.,Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
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Raghavan M, Li Z, Carlson C, Anderson CT, Stout J, Sabsevitz DS, Swanson SJ, Binder JR. MEG language lateralization in partial epilepsy using dSPM of auditory event-related fields. Epilepsy Behav 2017; 73:247-255. [PMID: 28662463 DOI: 10.1016/j.yebeh.2017.06.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Revised: 05/19/2017] [Accepted: 06/05/2017] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Methods employed to determine hemispheric language dominance using magnetoencephalography (MEG) have differed significantly across studies in the choice of language-task, the nature of the physiological response studied, recording hardware, and source modeling methods. Our goal was to determine whether an analysis based on distributed source modeling can replicate the results of prior studies that have used dipole-modeling of event-related fields (ERFs) generated by an auditory word-recognition task to determine language dominance in patients with epilepsy. METHODS We analyzed data from 45 adult patients with drug-resistant partial epilepsy who performed an auditory word-recognition task during MEG recording and also completed a language fMRI study as part of their evaluation for epilepsy surgery. Source imaging of auditory ERFs was performed using dynamic statistical parametric mapping (dSPM). Language laterality indices (LIs) were calculated for four regions of interest (ROIs) by counting above-threshold activations within a 300-600ms time window after stimulus onset. Language laterality (LL) classifications based on these LIs were compared to the results from fMRI. RESULTS The most lateralized MEG responses to language stimuli were observed in a parietal region that included the angular and supramarginal gyri (AngSmg). In this region, using a half-maximal threshold, source activations were left dominant in 32 (71%) patients, right dominant in 8 (18%), and symmetric in 5 patients (11%). The best agreement between MEG and fMRI on the ternary classification of regional language dominance into left, right, or symmetric groups was also found at the AngSmg ROI (69%). This was followed by the whole-hemisphere and temporal ROIs (both 62%). The frontal ROI showed the least agreement with fMRI (51%). Gross discordances between MEG and FMRI findings were disproportionately of the type where MEG favored atypical right-hemispheric language in a patient with right-hemispheric seizure origin (p<0.05 at three of the four ROIs). SIGNIFICANCE In a parietal region that includes the angular and supramarginal gyri, language laterality estimates based on dSPM of ERFs during auditory word-recognition shows a degree of MEG-fMRI concordance that is comparable to previously published estimates for MEG-Wada concordance using dipole counting methods and the same task. Our data also suggest that MEG language laterality estimates based on this task may be influenced by the laterality of epileptic networks in some patients. This has not been reported previously and deserves further study.
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Affiliation(s)
- Manoj Raghavan
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA.
| | - Zhimin Li
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Chad Carlson
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | | | - Jeffrey Stout
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - David S Sabsevitz
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Sara J Swanson
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Jeffrey R Binder
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
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Magnetoencephalography for brain electrophysiology and imaging. Nat Neurosci 2017; 20:327-339. [DOI: 10.1038/nn.4504] [Citation(s) in RCA: 418] [Impact Index Per Article: 59.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2016] [Accepted: 01/17/2017] [Indexed: 12/18/2022]
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12
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Ahmed R, Rutka JT. The role of MEG in pre-surgical evaluation of epilepsy: current use and future directions. Expert Rev Neurother 2016; 16:795-801. [DOI: 10.1080/14737175.2016.1181544] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Raheel Ahmed
- Division of Neurosurgery, The Hospital for Sick Children, Toronto, Canada
| | - James T. Rutka
- Division of Neurosurgery, The Hospital for Sick Children, Toronto, Canada
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13
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Mouthaan BE, Rados M, Barsi P, Boon P, Carmichael DW, Carrette E, Craiu D, Cross JH, Diehl B, Dimova P, Fabo D, Francione S, Gaskin V, Gil-Nagel A, Grigoreva E, Guekht A, Hirsch E, Hecimovic H, Helmstaedter C, Jung J, Kalviainen R, Kelemen A, Kimiskidis V, Kobulashvili T, Krsek P, Kuchukhidze G, Larsson PG, Leitinger M, Lossius MI, Luzin R, Malmgren K, Mameniskiene R, Marusic P, Metin B, Özkara C, Pecina H, Quesada CM, Rugg-Gunn F, Rydenhag B, Ryvlin P, Scholly J, Seeck M, Staack AM, Steinhoff BJ, Stepanov V, Tarta-Arsene O, Trinka E, Uzan M, Vogt VL, Vos SB, Vulliémoz S, Huiskamp G, Leijten FSS, Van Eijsden P, Braun KPJ. Current use of imaging and electromagnetic source localization procedures in epilepsy surgery centers across Europe. Epilepsia 2016; 57:770-6. [PMID: 27012361 DOI: 10.1111/epi.13347] [Citation(s) in RCA: 68] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/01/2016] [Indexed: 12/01/2022]
Abstract
OBJECTIVE In 2014 the European Union-funded E-PILEPSY project was launched to improve awareness of, and accessibility to, epilepsy surgery across Europe. We aimed to investigate the current use of neuroimaging, electromagnetic source localization, and imaging postprocessing procedures in participating centers. METHODS A survey on the clinical use of imaging, electromagnetic source localization, and postprocessing methods in epilepsy surgery candidates was distributed among the 25 centers of the consortium. A descriptive analysis was performed, and results were compared to existing guidelines and recommendations. RESULTS Response rate was 96%. Standard epilepsy magnetic resonance imaging (MRI) protocols are acquired at 3 Tesla by 15 centers and at 1.5 Tesla by 9 centers. Three centers perform 3T MRI only if indicated. Twenty-six different MRI sequences were reported. Six centers follow all guideline-recommended MRI sequences with the proposed slice orientation and slice thickness or voxel size. Additional sequences are used by 22 centers. MRI postprocessing methods are used in 16 centers. Interictal positron emission tomography (PET) is available in 22 centers; all using 18F-fluorodeoxyglucose (FDG). Seventeen centers perform PET postprocessing. Single-photon emission computed tomography (SPECT) is used by 19 centers, of which 15 perform postprocessing. Four centers perform neither PET nor SPECT in children. Seven centers apply magnetoencephalography (MEG) source localization, and nine apply electroencephalography (EEG) source localization. Fourteen combinations of inverse methods and volume conduction models are used. SIGNIFICANCE We report a large variation in the presurgical diagnostic workup among epilepsy surgery centers across Europe. This diversity underscores the need for high-quality systematic reviews, evidence-based recommendations, and harmonization of available diagnostic presurgical methods.
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Affiliation(s)
- Brian E Mouthaan
- Department of (Child) Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Matea Rados
- Department of (Child) Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Péter Barsi
- MR Research Center, Semmelweis University, Budapest, Hungary
| | - Paul Boon
- Department of Neurology, Reference Center for Refractory Epilepsy, Ghent University Hospital, Ghent, Belgium
| | - David W Carmichael
- University College London Institute of Child Health, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom
| | - Evelien Carrette
- Department of Neurology, Reference Center for Refractory Epilepsy, Ghent University Hospital, Ghent, Belgium
| | - Dana Craiu
- Pediatric Neurology Clinic, "Alexandru Obregia" Clinical Psychiatric Hospital, Bucharest, Romania.,Department 6, Pediatric Neurology Clinic, "Carol Davila" University of Medicine, Bucharest, Romania
| | - J Helen Cross
- University College London Institute of Child Health, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom
| | - Beate Diehl
- National Hospital for Neurology and Neurosurgery, University College London Hospitals, London, United Kingdom.,Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom
| | - Petia Dimova
- Department of Neurosurgery, Epilepsy Surgery Center, St. Ivan Rilski University Hospital, Sofia, Bulgaria
| | - Daniel Fabo
- National Institute of Clinical Neurosciences, Budapest, Hungary
| | - Stefano Francione
- Claudio Munari Epilepsy Surgery Center, Niguarda Hospital, Milan, Italy
| | - Vladislav Gaskin
- Moscow Research and Clinical Center for Neuropsychiatry of the Healthcare Department of Moscow, Moscow, Russia.,Department of Neurology and Neurosurgery of Russian National Research Medical University, Moscow, Russia
| | - Antonio Gil-Nagel
- Department of Neuroimaging, Center for Biomedical Technology, Technical University of Madrid, Pozuelo de Alarcón, Spain
| | - Elena Grigoreva
- Scientific Research Institute of Emergency Care named after N.V. Sklifosovsky, Moscow, Russia
| | - Alla Guekht
- Moscow Research and Clinical Center for Neuropsychiatry of the Healthcare Department of Moscow, Moscow, Russia.,Department of Neurology and Neurosurgery of Russian National Research Medical University, Moscow, Russia
| | - Edouard Hirsch
- Medical and Surgical Epilepsy Unit, Hautepierre Hospital, University of Strasbourg, Strasbourg, France
| | - Hrvoje Hecimovic
- Department of Neurology, Zagreb Epilepsy Center, University Hospital, Zagreb, Croatia
| | - Christoph Helmstaedter
- Department of Epileptology, University Medical Center, University of Bonn, Bonn, Germany
| | - Julien Jung
- Department of Functional Neurology and Epileptology, Institute of Epilepsies (IDEE), Hospices Civils de Lyon, Lyon, France
| | - Reetta Kalviainen
- Department of Neurology, Kuopio University Hospital, Kuopio, Finland.,School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Anna Kelemen
- National Institute of Clinical Neurosciences, Budapest, Hungary
| | - Vasilios Kimiskidis
- Laboratory of Clinical Neurophysiology, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Teia Kobulashvili
- Department of Neurology, Christian-Doppler-Klinik, Paracelsus Medical University, and Center for Cognitive Neuroscience, Salzburg, Austria
| | - Pavel Krsek
- Department of Pediatric Neurology, 2nd Faculty of Medicine, Motol University Hospital, Charles University in Prague, Prague, Czech Republic
| | - Giorgi Kuchukhidze
- Department of Neurology, Christian-Doppler-Klinik, Paracelsus Medical University, and Center for Cognitive Neuroscience, Salzburg, Austria.,Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Pål G Larsson
- Department of Neurosurgery, Clinic of Surgery and Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Markus Leitinger
- Department of Neurology, Christian-Doppler-Klinik, Paracelsus Medical University, and Center for Cognitive Neuroscience, Salzburg, Austria
| | - Morten I Lossius
- Department of Complex Epilepsy, National Center for Epilepsy (SSE), Oslo, Norway
| | - Roman Luzin
- Moscow Research and Clinical Center for Neuropsychiatry of the Healthcare Department of Moscow, Moscow, Russia.,Department of Neurology and Neurosurgery of Russian National Research Medical University, Moscow, Russia
| | - Kristina Malmgren
- Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Ruta Mameniskiene
- Clinic of Neurology and Neurosurgery, Faculty of Medicine, Vilnius University, Vilnius, Lithuania.,Center of Neurology, Vilnius University Hospital Santariškių Klinikos, Vilnius, Lithuania
| | - Petr Marusic
- Department of Neurology, 2nd Faculty of Medicine, Motol University Hospital, Charles University in Prague, Prague, Czech Republic
| | - Baris Metin
- Department of Psychology, Uskudar University, Uskudar, Istanbul, Turkey
| | - Cigdem Özkara
- Division of Clinical Electro-Neurophysiology, Department of Neurology, Cerrahpaa Medical Faculty, Istanbul University, Istanbul, Turkey
| | - Hrvoje Pecina
- Department of Neurology, Zagreb Epilepsy Center, University Hospital, Zagreb, Croatia
| | - Carlos M Quesada
- Department of Epileptology, University Medical Center, University of Bonn, Bonn, Germany
| | - Fergus Rugg-Gunn
- National Hospital for Neurology and Neurosurgery, University College London Hospitals, London, United Kingdom.,Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom
| | - Bertil Rydenhag
- Clinic of Neurology and Neurosurgery, Faculty of Medicine, Vilnius University, Vilnius, Lithuania.,Center of Neurology, Vilnius University Hospital Santariškių Klinikos, Vilnius, Lithuania
| | - Philippe Ryvlin
- Department of Clinical Neurosciences, Lausanne University Hospital, Lausanne, Switzerland
| | - Julia Scholly
- Medical and Surgical Epilepsy Unit, Hautepierre Hospital, University of Strasbourg, Strasbourg, France
| | - Margitta Seeck
- EEG and Epilepsy Unit, Department of Clinical Neurosciences, University Hospital of Geneva, Geneva, Switzerland
| | | | | | - Valentin Stepanov
- Scientific Research Institute of Emergency Care named after N.V. Sklifosovsky, Moscow, Russia
| | - Oana Tarta-Arsene
- Pediatric Neurology Clinic, "Alexandru Obregia" Clinical Psychiatric Hospital, Bucharest, Romania.,Department 6, Pediatric Neurology Clinic, "Carol Davila" University of Medicine, Bucharest, Romania
| | - Eugen Trinka
- Department of Neurology, Christian-Doppler-Klinik, Paracelsus Medical University, and Center for Cognitive Neuroscience, Salzburg, Austria
| | - Mustafa Uzan
- Division of Clinical Electro-Neurophysiology, Department of Neurology, Cerrahpaa Medical Faculty, Istanbul University, Istanbul, Turkey
| | - Viola L Vogt
- Department of Epileptology, University Medical Center, University of Bonn, Bonn, Germany
| | - Sjoerd B Vos
- Translational Imaging Group, CMIC, University College London, London, United Kingdom.,MRI Unit, Epilepsy Society, Chalfont St Peter, United Kingdom
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, Department of Clinical Neurosciences, University Hospital of Geneva, Geneva, Switzerland
| | - Geertjan Huiskamp
- Department of (Child) Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Frans S S Leijten
- Department of (Child) Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Pieter Van Eijsden
- Department of (Child) Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Kees P J Braun
- Department of (Child) Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
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Migliorelli C, Alonso JF, Romero S, Mañanas MA, Nowak R, Russi A. Influence of metallic artifact filtering on MEG signals for source localization during interictal epileptiform activity. J Neural Eng 2016; 13:026029. [DOI: 10.1088/1741-2560/13/2/026029] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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15
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Willemse RB, Hillebrand A, Ronner HE, Vandertop WP, Stam CJ. Magnetoencephalographic study of hand and foot sensorimotor organization in 325 consecutive patients evaluated for tumor or epilepsy surgery. NEUROIMAGE-CLINICAL 2015; 10:46-53. [PMID: 26693401 PMCID: PMC4660376 DOI: 10.1016/j.nicl.2015.11.002] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/14/2015] [Revised: 10/30/2015] [Accepted: 11/04/2015] [Indexed: 01/27/2023]
Abstract
Objectives The presence of intracranial lesions or epilepsy may lead to functional reorganization and hemispheric lateralization. We applied a clinical magnetoencephalography (MEG) protocol for the localization of the contralateral and ipsilateral S1 and M1 of the foot and hand in patients with non-lesional epilepsy, stroke, developmental brain injury, traumatic brain injury and brain tumors. We investigated whether differences in activation patterns could be related to underlying pathology. Methods Using dipole fitting, we localized the sources underlying sensory and motor evoked magnetic fields (SEFs and MEFs) of both hands and feet following unilateral stimulation of the median nerve (MN) and posterior tibial nerve (PTN) in 325 consecutive patients. The primary motor cortex was localized using beamforming following a self-paced repetitive motor task for each hand and foot. Results The success rate for motor and sensory localization for the feet was significantly lower than for the hands (motor_hand 94.6% versus motor_feet 81.8%, p < 0.001; sensory_hand 95.3% versus sensory_feet 76.0%, p < 0.001). MN and PTN stimulation activated 86.6% in the contralateral S1, with ipsilateral activation < 0.5%. Motor cortex activation localized contralaterally in 76.1% (5.2% ipsilateral, 7.6% bilateral and 11.1% failures) of all motor MEG recordings. The ipsilateral motor responses were found in 43 (14%) out of 308 patients with motor recordings (range: 8.3–50%, depending on the underlying pathology), and had a higher occurrence in the foot than in the hand (motor_foot 44.8% versus motor_hand 29.6%, p = 0.031). Ipsilateral motor responses tended to be more frequent in patients with a history of stroke, traumatic brain injury (TBI) or developmental brain lesions (p = 0.063). Conclusions MEG localization of sensorimotor cortex activation was more successful for the hand compared to the foot. In patients with neural lesions, there were signs of brain reorganization as measured by more frequent ipsilateral motor cortical activation of the foot in addition to the traditional sensory and motor activation patterns in the contralateral hemisphere. The presence of ipsilateral neural reorganization, especially around the foot motor area, suggests that careful mapping of the hand and foot in both contralateral and ipsilateral hemispheres prior to surgery might minimize postoperative deficits. Using MEG, S1 and M1 responses of the hand and foot were mapped in patients with brain tumors or epilepsy. Localization of the hand was more successful than of the foot. Ipsilateral S1 responses were rarely seen but ipsilateral M1 responses differed by underlying pathology and limb. Results indicate that differential sensorimotor re-organization can occur in the presence of pathology. Ipsilateral and contralateral mapping of the hand and foot should be done to minimize postsurgical dysfunction.
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Affiliation(s)
- Ronald B Willemse
- Neurosurgical Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands
| | - Hanneke E Ronner
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands
| | - W Peter Vandertop
- Neurosurgical Center Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands
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