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Yao L, Cheng N, Chen AQ, Wang X, Gao M, Kong QX, Kong Y. Advances in Neuroimaging and Multiple Post-Processing Techniques for Epileptogenic Zone Detection of Drug-Resistant Epilepsy. J Magn Reson Imaging 2024; 60:2309-2331. [PMID: 38014782 DOI: 10.1002/jmri.29157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/14/2023] [Accepted: 11/15/2023] [Indexed: 11/29/2023] Open
Abstract
Among the approximately 20 million patients with drug-resistant epilepsy (DRE) worldwide, the vast majority can benefit from surgery to minimize seizure reduction and neurological impairment. Precise preoperative localization of epileptogenic zone (EZ) and complete resection of the lesions can influence the postoperative prognosis. However, precise localization of EZ is difficult, and the structural and functional alterations in the brain caused by DRE vary by etiology. Neuroimaging has emerged as an approach to identify the seizure-inducing structural and functional changes in the brain, and magnetic resonance imaging (MRI) and positron emission tomography (PET) have become routine noninvasive imaging tools for preoperative evaluation of DRE in many epilepsy treatment centers. Multimodal neuroimaging offers unique advantages in detecting EZ, especially in improving the detection rate of patients with negative MRI or PET findings. This approach can characterize the brain imaging characteristics of patients with DRE caused by different etiologies, serving as a bridge between clinical and pathological findings and providing a basis for individualized clinical treatment plans. In addition to the integration of multimodal imaging modalities and the development of special scanning sequences and image post-processing techniques for early and precise localization of EZ, the application of deep machine learning for extracting image features and deep learning-based artificial intelligence have gradually improved diagnostic efficiency and accuracy. These improvements can provide clinical assistance for precisely outlining the scope of EZ and indicating the relationship between EZ and functional brain areas, thereby enabling standardized and precise surgery and ensuring good prognosis. However, most existing studies have limitations imposed by factors such as their small sample sizes or hypothesis-based study designs. Therefore, we believe that the application of neuroimaging and post-processing techniques in DRE requires further development and that more efficient and accurate imaging techniques are urgently needed in clinical practice. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Lei Yao
- Clinical Medical College, Jining Medical University, Jining, China
| | - Nan Cheng
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, China
| | - An-Qiang Chen
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, China
| | - Xun Wang
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, China
| | - Ming Gao
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, China
| | - Qing-Xia Kong
- Department of Neurology, Affiliated Hospital of Jining Medical University, Jining, China
| | - Yu Kong
- Medical Imaging Department, Affiliated Hospital of Jining Medical University, Jining, China
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Zhang Q, Yin C, Fang X, Ou Y, Ma D, Tuerxun S. Application of magnetoencephalography in epilepsy. Heliyon 2024; 10:e38841. [PMID: 39430539 PMCID: PMC11490854 DOI: 10.1016/j.heliyon.2024.e38841] [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: 04/15/2024] [Revised: 09/30/2024] [Accepted: 10/01/2024] [Indexed: 10/22/2024] Open
Abstract
Magnetoencephalography (MEG) is a non-invasive neuroimaging technique that can detect whole-brain neuroelectromagnetic signals in real-time in a single measurement. Due to excellent temporal and spatial resolution and integration of computed tomography or magnetic resonance imaging data, MEG allows signal source analysis. It can pinpoint epileptic foci as well as functional brain regions, reducing the necessity for invasive electrode implantation.
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Affiliation(s)
- Qingyan Zhang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute of Beihang University, Hangzhou 310000, China
| | - Chuanming Yin
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute of Beihang University, Hangzhou 310000, China
| | - Xiujie Fang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute of Beihang University, Hangzhou 310000, China
| | - Yunwei Ou
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Danyue Ma
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute of Beihang University, Hangzhou 310000, China
| | - Shabier Tuerxun
- Department of Neurology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830000, China
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3
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Varner JA, Rezaie R, Noorizadeh N, Boop FA, Fulton SP, Klimo P, Shimony N, Wheless JW, Narayana S. Transcranial magnetic stimulation and magnetoencephalography are feasible alternatives to invasive methods in optimizing responsive neurostimulation device placement. Epilepsy Res 2024; 206:107426. [PMID: 39128278 DOI: 10.1016/j.eplepsyres.2024.107426] [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: 05/13/2024] [Revised: 07/24/2024] [Accepted: 08/05/2024] [Indexed: 08/13/2024]
Abstract
Responsive neurostimulation (RNS) is a treatment option for patients with refractory epilepsy when surgical resection is not possible due to overlap of the irritative zone and eloquent cortex. Presurgical evaluations for RNS placement typically rely on invasive methods. This study investigated the potential of transcranial magnetic stimulation (TMS) and magnetoencephalography (MEG) to provide key presurgical information non-invasively. We hypothesized that these non-invasive methods may assist in optimizing RNS placement by providing useful information for seizure localization by MEG and eloquent cortex mapping by TMS. A retrospective chart review identified nine patients who underwent RNS placement (mean age = 20.4 years [SD = 5.6], two-thirds were female). Characterization of the irritative zone using MEG was successful in eight of nine patients. Non-invasive mapping of relevant eloquent cortex was attempted in all patients. TMS was successful in eight of nine patients, and MEG was successful in two of six patients. Importantly, patients mapped with non-invasive modalities experienced an average seizure reduction of 77 % at their most recent clinic visit, compared to 75 % seizure reduction in those with invasive evaluations, indicating appropriate RNS placement. These data demonstrate that TMS and MEG can provide key information for RNS and may be feasible alternatives to invasive methods for assisting in decision making regarding RNS placement. Non-invasive methods for determining RNS placement have a high rate of success when data from multiple non-invasive modalities converge and can inform more accurate placement of intracranial electrodes prior to RNS placement or mitigate their need.
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Affiliation(s)
- J Austin Varner
- Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, USA
| | - Roozbeh Rezaie
- Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, USA; Department of Pediatrics, Division of Pediatric Neurology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Negar Noorizadeh
- Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, USA; Department of Pediatrics, Division of Pediatric Neurology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Frederick A Boop
- Department of Neurosurgery, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Stephen P Fulton
- Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, USA; Department of Pediatrics, Division of Pediatric Neurology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Paul Klimo
- Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, USA; Department of Neurosurgery, University of Tennessee Health Science Center, Memphis, TN, USA; Department of Surgery, St. Jude Children's Research Hospital, Memphis, TN, USA; Department of Neurosurgery, Semmes Murphey Clinic, Memphis, TN, USA
| | - Nir Shimony
- Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, USA; Department of Neurosurgery, University of Tennessee Health Science Center, Memphis, TN, USA; Department of Surgery, St. Jude Children's Research Hospital, Memphis, TN, USA; Department of Neurosurgery, Semmes Murphey Clinic, Memphis, TN, USA; Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - James W Wheless
- Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, USA; Department of Pediatrics, Division of Pediatric Neurology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Shalini Narayana
- Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, USA; Department of Pediatrics, Division of Pediatric Neurology, University of Tennessee Health Science Center, Memphis, TN, USA; Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, USA.
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4
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Chauvel P. The Voyage of SEEG. J Clin Neurophysiol 2024; 41:399-401. [PMID: 38935651 DOI: 10.1097/wnp.0000000000001048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2024] Open
Abstract
SUMMARY It took 50 years for stereoelectroencephalography (SEEG) to cross the Atlantic. Conceived and designed before the advent of computers and modern technology, this method turned out to be perfectly suited to brain imaging and modern video and electrophysiological tools. It eventually benefited from robotics and signal processing. However, a critical step remains accurate electrode implantation, which is based on individual patients' noninvasive phase I data. A limiting factor, especially in MRI-negative cases, is a thorough perictal and postictal clinical testing for ensuring meaningful electroclinical correlations. Adapted epilepsy monitoring units' architecture and specific technicians and nurses training are required to improve the granularity of information needed to generate valid hypotheses on localization. SEEG interpretation is based on a knowledge base in neural networks, cognitive/behavioral neuroscience, and electrophysiology quite distinct from electroencephalography. Tailored to the needs of focal epilepsy complexity exploration, SEEG does not fit well with simplification. Specific teaching and development of clinical research inside the epilepsy monitoring units will help to flatten the team learning curve and to build knowledge base from shared clinical experience.
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Affiliation(s)
- Patrick Chauvel
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, U.S.A
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Dmytriw AA, Hadjinicolaou A, Ntolkeras G, Tamilia E, Pesce M, Berto LF, Grant PE, Pang E, Ahtam B. Magnetoencephalography for the pediatric population, indications, acquisition and interpretation for the clinician. Neuroradiol J 2024:19714009241260801. [PMID: 38864180 DOI: 10.1177/19714009241260801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2024] Open
Abstract
Magnetoencephalography (MEG) is an imaging technique that enables the assessment of cortical activity via direct measures of neurophysiology. It is a non-invasive and passive technique that is completely painless. MEG has gained increasing prominence in the field of pediatric neuroimaging. This dedicated review article for the pediatric population summarizes the fundamental technical and clinical aspects of MEG for the clinician. We discuss methods tailored for children to improve data quality, including child-friendly MEG facility environments and strategies to mitigate motion artifacts. We provide an in-depth overview on accurate localization of neural sources and different analysis methods, as well as data interpretation. The contemporary platforms and approaches of two quaternary pediatric referral centers are illustrated, shedding light on practical implementations in clinical settings. Finally, we describe the expanding clinical applications of MEG, including its pivotal role in presurgical evaluation of epilepsy patients, presurgical mapping of eloquent cortices (somatosensory and motor cortices, visual and auditory cortices, lateralization of language), its emerging relevance in autism spectrum disorder research and potential future clinical applications, and its utility in assessing mild traumatic brain injury. In conclusion, this review serves as a comprehensive resource of clinicians as well as researchers, offering insights into the evolving landscape of pediatric MEG. It discusses the importance of technical advancements, data acquisition strategies, and expanding clinical applications in harnessing the full potential of MEG to study neurological conditions in the pediatric population.
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Affiliation(s)
- Adam A Dmytriw
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA
- Division of Neuroradiology, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Aristides Hadjinicolaou
- Division of Neurology, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Department of Neurology, Division of Epilepsy and Clinical Neurophysiology, Boston Children's Hospital, Boston, MA, USA
| | - Georgios Ntolkeras
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - Eleonora Tamilia
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - Matthew Pesce
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - Laura F Berto
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - P Ellen Grant
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - Elizabeth Pang
- Division of Neurology, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Banu Ahtam
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
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Okamura A, Hashizume A, Kagawa K, Seyama G, Yoshino A, Yamawaki S, Horie N, Iida K. Magnetoencephalographic detection of synchronized epileptic activity between the hippocampus and insular cortex. Epilepsy Behav Rep 2024; 26:100669. [PMID: 38699062 PMCID: PMC11063376 DOI: 10.1016/j.ebr.2024.100669] [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: 02/17/2024] [Revised: 04/05/2024] [Accepted: 04/17/2024] [Indexed: 05/05/2024] Open
Abstract
Most magnetoencephalographic signals are derived from synchronized activity in the brain surface cortex. By contrast, the contribution of synchronized activity in the deep brain to magnetoencephalography (MEG) has remained unclear. We compared stereotactic electroencephalography (sEEG) with simultaneous MEG findings in a patient with temporal lobe epilepsy to determine the conditions under which MEG could also detect sEEG findings. The synchrony and similarity of the waves were evaluated using visual inspection and wavelet coherence. A 45-year-old woman with intractable temporal lobe epilepsy underwent sEEG and MEG simultaneously to determine the laterality and precise location of the epileptic focus. When spike-and-waves were seen in the right hippocampal head alone, no distinct spike-and-waves were observed visually in the right temporal MEG. The seizure then spread to the right insula on sEEG with a rhythmic theta frequency while synchronous activity was observed in the right temporal MEG channels. When polyspikes appeared in the right hippocampus, the right temporal MEG showed electrical activity with relatively high similarity to that of the right hippocampal head and insular cortex but less similarity to that of the right lateral temporal lobe cortex. MEG might detect epileptic activity synchronized between the hippocampus and insular cortex.
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Affiliation(s)
- Akitake Okamura
- Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Akira Hashizume
- Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Kota Kagawa
- Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Go Seyama
- Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Atsuo Yoshino
- Center for Brain, Mind and KANSEI Science Research, Hiroshima University, Hiroshima, Japan
| | - Shigeto Yamawaki
- Center for Brain, Mind and KANSEI Science Research, Hiroshima University, Hiroshima, Japan
| | - Nobutaka Horie
- Department of Neurosurgery, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Koji Iida
- Epilepsy Center, Hiroshima University Hospital, Hiroshima, Japan
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Wang W, Huang Q, Zhou Q, Han J, Zhang X, Li L, Lin Y, Wang Y. Multimodal non-invasive evaluation in MRI-negative epilepsy patients. Epilepsia Open 2024; 9:765-775. [PMID: 38258486 PMCID: PMC10984307 DOI: 10.1002/epi4.12896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 12/15/2023] [Accepted: 12/24/2023] [Indexed: 01/24/2024] Open
Abstract
Presurgical evaluation is still challenging for MRI-negative epilepsy patients. As non-invasive modalities are the easiest acceptable and economic methods in determining the epileptogenic zone, we analyzed the localization value of common non-invasive methods in MRI-negative epilepsy patients. In this study, we included epilepsy patients undergoing presurgical evaluation with presurgical negative MRI. MRI post-processing was performed using a Morphometric Analysis Program (MAP) on T1-weighted volumetric MRI. The relationship between MAP, magnetoencephalography (MEG), scalp electroencephalogram (EEG), and seizure outcomes was analyzed to figure out the localization value of different non-invasive methods. Eighty-six patients were included in this study. Complete resection of the MAP-positive regions or the MEG-positive regions was positively associated with seizure freedom (p = 0.028 and 0.007, respectively). When an area is co-localized by MAP and MEG, the resection of the area was significantly associated with seizure freedom (p = 0.006). However, neither the EEG lateralization nor the EEG localization showed statistical association with the surgical outcome (p = 0.683 and 0.505, respectively). In conclusion, scalp EEG had a limited role in presurgical localization and predicting seizure outcome, combining MAP and MEG results can significantly improve the localization of epileptogenic lesions and have a positive association with seizure-free outcome. PLAIN LANGUAGE SUMMARY: Due to the lack of obvious structure abnormalities on neuroimaging examinations, the identification of epilepsy lesions in MRI-negative epilepsy patients can be difficult. In this study, we intended to use non-invasive examinations to explore the potential epileptic lesions in MRI-negative epilepsy patients and to determine the results accuracy by comparing the neuroimaging results with the epilepsy surgery outcomes. A total of 86 epilepsy patients without obvious structure lesions on MRI were included, and we found that the combinations of different non-invasive examinations and neuroimaging post-processing methods are significantly associated with the seizure freedom results of epilepsy surgery.
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Affiliation(s)
- Wei Wang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Qian Huang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Qilin Zhou
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Jiaqi Han
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Xiating Zhang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Liping Li
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Yicong Lin
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Yuping Wang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of NeuromodulationBeijingChina
- Center of Epilepsy, Beijing Institute for Brain DisordersCapital Medical UniversityBeijingChina
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Fonseca N, Bowerman J, Askari P, Proskovec AL, Feltrin FS, Veltkamp D, Early H, Wagner BC, Davenport EM, Maldjian JA. Magnetoencephalography Atlas Viewer for Dipole Localization and Viewing. J Imaging 2024; 10:80. [PMID: 38667978 PMCID: PMC11051542 DOI: 10.3390/jimaging10040080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 03/19/2024] [Accepted: 03/27/2024] [Indexed: 04/28/2024] Open
Abstract
Magnetoencephalography (MEG) is a noninvasive neuroimaging technique widely recognized for epilepsy and tumor mapping. MEG clinical reporting requires a multidisciplinary team, including expert input regarding each dipole's anatomic localization. Here, we introduce a novel tool, the "Magnetoencephalography Atlas Viewer" (MAV), which streamlines this anatomical analysis. The MAV normalizes the patient's Magnetic Resonance Imaging (MRI) to the Montreal Neurological Institute (MNI) space, reverse-normalizes MNI atlases to the native MRI, identifies MEG dipole files, and matches dipoles' coordinates to their spatial location in atlas files. It offers a user-friendly and interactive graphical user interface (GUI) for displaying individual dipoles, groups, coordinates, anatomical labels, and a tri-planar MRI view of the patient with dipole overlays. It evaluated over 273 dipoles obtained in clinical epilepsy subjects. Consensus-based ground truth was established by three neuroradiologists, with a minimum agreement threshold of two. The concordance between the ground truth and MAV labeling ranged from 79% to 84%, depending on the normalization method. Higher concordance rates were observed in subjects with minimal or no structural abnormalities on the MRI, ranging from 80% to 90%. The MAV provides a straightforward MEG dipole anatomic localization method, allowing a nonspecialist to prepopulate a report, thereby facilitating and reducing the time of clinical reporting.
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Affiliation(s)
- N.C.d. Fonseca
- MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (P.A.); (A.L.P.); (F.S.F.); (D.V.); (H.E.); (E.M.D.); (J.A.M.)
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (J.B.); (B.C.W.)
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Jason Bowerman
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (J.B.); (B.C.W.)
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Pegah Askari
- MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (P.A.); (A.L.P.); (F.S.F.); (D.V.); (H.E.); (E.M.D.); (J.A.M.)
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (J.B.); (B.C.W.)
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Biomedical Engineering Department, University of Texas Arlington, Arlington, TX 76019, USA
- Biomedical Engineering Department, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Amy L. Proskovec
- MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (P.A.); (A.L.P.); (F.S.F.); (D.V.); (H.E.); (E.M.D.); (J.A.M.)
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (J.B.); (B.C.W.)
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Fabricio Stewan Feltrin
- MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (P.A.); (A.L.P.); (F.S.F.); (D.V.); (H.E.); (E.M.D.); (J.A.M.)
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Daniel Veltkamp
- MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (P.A.); (A.L.P.); (F.S.F.); (D.V.); (H.E.); (E.M.D.); (J.A.M.)
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Heather Early
- MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (P.A.); (A.L.P.); (F.S.F.); (D.V.); (H.E.); (E.M.D.); (J.A.M.)
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Ben C. Wagner
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (J.B.); (B.C.W.)
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Elizabeth M. Davenport
- MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (P.A.); (A.L.P.); (F.S.F.); (D.V.); (H.E.); (E.M.D.); (J.A.M.)
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (J.B.); (B.C.W.)
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Biomedical Engineering Department, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Joseph A. Maldjian
- MEG Center of Excellence, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (P.A.); (A.L.P.); (F.S.F.); (D.V.); (H.E.); (E.M.D.); (J.A.M.)
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; (J.B.); (B.C.W.)
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Biomedical Engineering Department, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
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9
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Huang Q, Xie P, Zhou J, Ding H, Liu Z, Li T, Guan Y, Wang M, Wang J, Teng P, Zhu M, Ma K, Wu H, Luan G, Zhai F. Predictors of seizure outcomes in stereo-electroencephalography-guided radio-frequency thermocoagulation for MRI-negative epilepsy. Ther Adv Chronic Dis 2024; 15:20406223241236258. [PMID: 38496233 PMCID: PMC10943718 DOI: 10.1177/20406223241236258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 02/14/2024] [Indexed: 03/19/2024] Open
Abstract
Background One-third of intractable epilepsy patients have no visually identifiable focus for neurosurgery based on imaging tests [magnetic resonance imaging (MRI)-negative cases]. Stereo-electroencephalography-guided radio-frequency thermocoagulation (SEEG-guided RF-TC) is utilized in the clinical treatment of epilepsy to lower the incidence of complications post-open surgery. Objective This study aimed to identify prognostic factors and long-term seizure outcomes in SEEG-guided RF-TC for patients with MRI-negative epilepsy. Design This was a single-center retrospective cohort study. Methods We included 30 patients who had undergone SEEG-guided RF-TC at Sanbo Brain Hospital, Capital Medical University, from April 2015 to December 2019. The probability of remaining seizure-free and the plotted survival curves were analyzed. Prognostic factors were analyzed using log-rank tests in univariate analysis and the Cox regression model in multivariate analysis. Results With a mean time of 31.07 ± 2.64 months (median 30.00, interquartile range: 18.00-40.00 months), 11 out of 30 patients (36.7%) were classified as International League Against Epilepsy class 1 in the last follow-up. The mean time of remaining seizure-free was 21.33 ± 4.55 months [95% confidence interval (CI) 12.41-30.25], and the median time was 3.00 ± 0.54 months (95% CI 1.94-4.06). Despite falling in the initial year, the probability of remaining seizure-free gradually stabilizes in the subsequent years. The patients were more likely to obtain seizure freedom when the epileptogenic zone was located in the insular lobe or with one focus on the limbic system (p = 0.034, hazard ratio 5.019, 95% CI 1.125-22.387). Conclusion Our findings may be applied to guide individualized surgical interventions and help clinicians make better decisions.
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Affiliation(s)
- Qi Huang
- Department of Neurosurgery, Center of Epilepsy, Sanbo Brain Hospital, Capital Medical University, Haidian District, Beijing, China
| | - Pandeng Xie
- Department of Neurosurgery, Center of Epilepsy, Sanbo Brain Hospital, Capital Medical University, Haidian District, Beijing, China
| | - Jian Zhou
- Department of Neurosurgery, Center of Epilepsy, Sanbo Brain Hospital, Capital Medical University, Haidian District, Beijing, China
| | - Haoran Ding
- Department of Neurosurgery, Center of Epilepsy, Sanbo Brain Hospital, Capital Medical University, Haidian District, Beijing, China
| | - Zhao Liu
- Department of Neurosurgery, Center of Epilepsy, Sanbo Brain Hospital, Capital Medical University, Haidian District, Beijing, China
| | - Tianfu Li
- Department of Brain Institute, Center of Epilepsy, Sanbo Brain Hospital, Capital Medical University, Haidian District, Beijing, China
- Department of Neurology, Center of Epilepsy, Beijing Institute for Brain Disorders, Sanbo Brain Hospital, Capital Medical University, Haidian District, Beijing, China
| | - Yuguang Guan
- Department of Neurosurgery, Center of Epilepsy, Sanbo Brain Hospital, Capital Medical University, Haidian District, Beijing, China
| | - Mengyang Wang
- Department of Neurology, Center of Epilepsy, Beijing Institute for Brain Disorders, Sanbo Brain Hospital, Capital Medical University, Haidian District, Beijing, China
| | - Jing Wang
- Department of Neurology, Center of Epilepsy, Beijing Institute for Brain Disorders, Sanbo Brain Hospital, Capital Medical University, Haidian District, Beijing, China
| | - Pengfei Teng
- Department of Magnetoencephalography, Sanbo Brain Hospital, Capital Medical University, Haidian District, Beijing, China
| | - Mingwang Zhu
- Department of Radiology, Sanbo Brain Hospital, Capital Medical University, Haidian District, Beijing, China
| | - Kaiqiang Ma
- Department of Neurosurgery, Center of Epilepsy, Sanbo Brain Hospital, Capital Medical University, Haidian District, Beijing, China
| | - Han Wu
- Department of Neurosurgery, Center of Epilepsy, Sanbo Brain Hospital, Capital Medical University, Haidian District, Beijing, China
| | - Guoming Luan
- Department of Neurosurgery, Center of Epilepsy, Sanbo Brain Hospital, Capital Medical University, XiangshanYikesong 50, Haidian District, Beijing 100093, China
| | - Feng Zhai
- Department of Neurosurgery, Center of Epilepsy, Sanbo Brain Hospital, Capital Medical University, XiangshanYikesong 50, Haidian District, Beijing 100093, China
- Department of Functional Neurosurgery, Neurological Center, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing 100045, China
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10
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Feys O, De Tiège X. From cryogenic to on-scalp magnetoencephalography for the evaluation of paediatric epilepsy. Dev Med Child Neurol 2024; 66:298-306. [PMID: 37421175 DOI: 10.1111/dmcn.15689] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/28/2023] [Accepted: 06/02/2023] [Indexed: 07/09/2023]
Abstract
Magnetoencephalography (MEG) is a neurophysiological technique based on the detection of brain magnetic fields. Whole-head MEG systems typically house a few hundred sensors requiring cryogenic cooling in a rigid one-size-fits-all (commonly adult-sized) helmet to keep a thermal insulation space. This leads to an increased brain-to-sensor distance in children, because of their smaller head circumference, and decreased signal-to-noise ratio. MEG allows detection and localization of interictal and ictal epileptiform discharges, and pathological high frequency oscillations, as a part of the presurgical assessment of children with refractory focal epilepsy, where electroencephalography is not contributive. MEG can also map the eloquent cortex before surgical resection. MEG also provides insights into the physiopathology of both generalized and focal epilepsy. On-scalp recordings based on cryogenic-free sensors have demonstrated their use in the field of childhood focal epilepsy and should become a reference technique for diagnosing epilepsy in the paediatric population. WHAT THIS PAPER ADDS: Magnetoencephalography (MEG) contributes to the diagnosis and understanding of paediatric epilepsy. On-scalp MEG recordings demonstrate some advantages over cryogenic MEG.
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Affiliation(s)
- Odile Feys
- Department of Neurology, Université libre de Bruxelles, Hôpital Universitaire de Bruxelles, Hôpital Erasme, Bruxelles, Belgium
- Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles, Université libre de Bruxelles, ULB Neuroscience Institute, Bruxelles, Belgium
| | - Xavier De Tiège
- Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles, Université libre de Bruxelles, ULB Neuroscience Institute, Bruxelles, Belgium
- Department of Translational Neuroimaging, Université libre de Bruxelles, Hôpital Universitaire de Bruxelles, Hôpital Erasme, Bruxelles, Belgium
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11
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Lahtinen J, Koulouri A, Rampp S, Wellmer J, Wolters C, Pursiainen S. Standardized hierarchical adaptive Lp regression for noise robust focal epilepsy source reconstructions. Clin Neurophysiol 2024; 159:24-40. [PMID: 38244372 DOI: 10.1016/j.clinph.2023.12.001] [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: 08/10/2023] [Revised: 11/02/2023] [Accepted: 12/02/2023] [Indexed: 01/22/2024]
Abstract
OBJECTIVE To investigate the ability of standardization to reduce source localization errors and measurement noise uncertainties for hierarchical Bayesian algorithms with L1- and L2-norms as priors in electroencephalography and magnetoencephalography of focal epilepsy. METHODS Description of the standardization methodology relying on the Hierarchical Bayesian framework, referred to as the Standardized Hierarchical Adaptive Lp-norm Regularization (SHALpR). The performance was tested using real data from two focal epilepsy patients. Simulated data that resembled the available real data was constructed for further localization and noise robustness investigation. RESULTS The proposed algorithms were compared to their non-standardized counterparts, Standardized low-resolution brain electromagnetic tomography, Standardized Shrinking LORETA-FOCUSS, and Dynamic statistical parametric maps. Based on the simulations, the standardized Hierarchical adaptive algorithm using L2-norm was noise robust for 10 dB signal-to-noise ratio (SNR), whereas the L1-norm prior worked robustly also with 5 dB SNR. The accuracy of the standardized L1-normed methodology to localize focal activity was under 1 cm for both patients. CONCLUSIONS Numerical results of the proposed methodology display improved localization and noise robustness. The proposed methodology also outperformed the compared methods when dealing with real data. SIGNIFICANCE The proposed standardized methodology, especially when employing the L1-norm, could serve as a valuable assessment tool in surgical decision-making.
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Affiliation(s)
- Joonas Lahtinen
- Faculty of Information Technology and Communication Sciences, Tampere University, Tampere 33720, Finland.
| | - Alexandra Koulouri
- Faculty of Information Technology and Communication Sciences, Tampere University, Tampere 33720, Finland.
| | - Stefan Rampp
- Department of Neurosurgery, University Hospital Halle (Saale), Halle 06097, Germany; Department of Neurosurgery, University Hospital Erlangen, Erlangen 91054, Germany; Department of Neuroradiology, University Hospital Erlangen, Erlangen 91054, Germany.
| | - Jörg Wellmer
- Ruhr-Epileptology, Department of Neurology, University Hospital Knappschaftskrankenhaus, Ruhr-University, Bochum44892, Germany.
| | - Carsten Wolters
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster 48149, Germany; Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster 48149, Germany.
| | - Sampsa Pursiainen
- Faculty of Information Technology and Communication Sciences, Tampere University, Tampere 33720, Finland.
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12
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Piastra MC, Oostenveld R, Homölle S, Han B, Chen Q, Oostendorp T. How to assess the accuracy of volume conduction models? A validation study with stereotactic EEG data. Front Hum Neurosci 2024; 18:1279183. [PMID: 38410258 PMCID: PMC10894995 DOI: 10.3389/fnhum.2024.1279183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 01/25/2024] [Indexed: 02/28/2024] Open
Abstract
Introduction Volume conduction models of the human head are used in various neuroscience fields, such as for source reconstruction in EEG and MEG, and for modeling the effects of brain stimulation. Numerous studies have quantified the accuracy and sensitivity of volume conduction models by analyzing the effects of the geometrical and electrical features of the head model, the sensor model, the source model, and the numerical method. Most studies are based on simulations as it is hard to obtain sufficiently detailed measurements to compare to models. The recording of stereotactic EEG during electric stimulation mapping provides an opportunity for such empirical validation. Methods In the study presented here, we used the potential distribution of volume-conducted artifacts that are due to cortical stimulation to evaluate the accuracy of finite element method (FEM) volume conduction models. We adopted a widely used strategy for numerical comparison, i.e., we fixed the geometrical description of the head model and the mathematical method to perform simulations, and we gradually altered the head models, by increasing the level of detail of the conductivity profile. We compared the simulated potentials at different levels of refinement with the measured potentials in three epilepsy patients. Results Our results show that increasing the level of detail of the volume conduction head model only marginally improves the accuracy of the simulated potentials when compared to in-vivo sEEG measurements. The mismatch between measured and simulated potentials is, throughout all patients and models, maximally 40 microvolts (i.e., 10% relative error) in 80% of the stimulation-recording combination pairs and it is modulated by the distance between recording and stimulating electrodes. Discussion Our study suggests that commonly used strategies used to validate volume conduction models based solely on simulations might give an overly optimistic idea about volume conduction model accuracy. We recommend more empirical validations to be performed to identify those factors in volume conduction models that have the highest impact on the accuracy of simulated potentials. We share the dataset to allow researchers to further investigate the mismatch between measurements and FEM models and to contribute to improving volume conduction models.
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Affiliation(s)
- Maria Carla Piastra
- Clinical Neurophysiology, Faculty of Science and Technology, Technical Medical Centre, University of Twente, Enschede, Netherlands
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
| | - Robert Oostenveld
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
- NatMEG, Karolinska Institutet, Stockholm, Sweden
| | - Simon Homölle
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Biao Han
- School of Psychology, South China Normal University, Guangzhou, China
| | - Qi Chen
- School of Psychology, South China Normal University, Guangzhou, China
| | - Thom Oostendorp
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
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13
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Mellor S, Timms RC, O'Neill GC, Tierney TM, Spedden ME, Brookes MJ, Wagstyl K, Barnes GR. Combining OPM and lesion mapping data for epilepsy surgery planning: a simulation study. Sci Rep 2024; 14:2882. [PMID: 38311614 PMCID: PMC10838931 DOI: 10.1038/s41598-024-51857-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 01/10/2024] [Indexed: 02/06/2024] Open
Abstract
When planning for epilepsy surgery, multiple potential sites for resection may be identified through anatomical imaging. Magnetoencephalography (MEG) using optically pumped sensors (OP-MEG) is a non-invasive functional neuroimaging technique which could be used to help identify the epileptogenic zone from these candidate regions. Here we test the utility of a-priori information from anatomical imaging for differentiating potential lesion sites with OP-MEG. We investigate a number of scenarios: whether to use rigid or flexible sensor arrays, with or without a-priori source information and with or without source modelling errors. We simulated OP-MEG recordings for 1309 potential lesion sites identified from anatomical images in the Multi-centre Epilepsy Lesion Detection (MELD) project. To localise the simulated data, we used three source inversion schemes: unconstrained, prior source locations at centre of the candidate sites, and prior source locations within a volume around the lesion location. We found that prior knowledge of the candidate lesion zones made the inversion robust to errors in sensor gain, orientation and even location. When the reconstruction was too highly restricted and the source assumptions were inaccurate, the utility of this a-priori information was undermined. Overall, we found that constraining the reconstruction to the region including and around the participant's potential lesion sites provided the best compromise of robustness against modelling or measurement error.
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Affiliation(s)
- Stephanie Mellor
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK.
| | - Ryan C Timms
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - George C O'Neill
- Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Tim M Tierney
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Meaghan E Spedden
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
- UCL Great Ormond Street Institute for Child Health, University College London, 30 Guilford St, London, WC1N 1EH, UK
| | - Gareth R Barnes
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
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Hao G, Yan H, Wang X, Gao R, Xue Y, Zhang X, Ni D, Shu W, Qiao L, He L, Yu T. The role of magnetoencephalography in preoperative localization and postoperative outcome prediction in patients with posterior cortical epilepsy. CNS Neurosci Ther 2024; 30:e14602. [PMID: 38332652 PMCID: PMC10853654 DOI: 10.1111/cns.14602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 12/16/2023] [Accepted: 01/01/2024] [Indexed: 02/10/2024] Open
Abstract
OBJECTIVE We aimed to explore the value of magnetoencephalography in the presurgical evaluation of patients with posterior cortex epilepsy. METHODS A total of 39 patients with posterior cortex epilepsy (PCE) and intact magnetoencephalography (MEG) images were reviewed from August 2019 to July 2022. MEG dipole clusters were classified into single clusters, multiple clusters, and scatter dipoles based on tightness criteria. The association of the surgical outcome with MEG dipole classifications was evaluated using Fisher's exact tests. RESULTS Among the 39 cases, there were 24 cases of single clusters (61.5%), nine cases of multiple clusters (23.1%), and six cases of scattered dipoles (15.4%). Patients with single dipole clusters were more likely to become seizure-free. Among single dipole cluster cases (n = 24), complete MEG dipole resection yielded a more favorable surgical outcome than incomplete resection (83.3% vs. 16.7%, p = 0.007). Patients with concordant MRI and MEG findings achieved a significantly more favorable surgical outcome than discordant patients (66.7% vs. 33.3%, p = 0.044), especially in single dipole cluster patients (87.5% vs. 25.0%, p = 0.005). SIGNIFICANCE MEG can provide additional valuable information regarding surgical candidate selection, epileptogenic zone localization, electrode implantation schedule, and final surgical planning in patients with posterior cortex epilepsy.
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Affiliation(s)
- Guiliang Hao
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Hao Yan
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Xueyuan Wang
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Runshi Gao
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Yansong Xue
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Xiating Zhang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Duanyu Ni
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Wei Shu
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Liang Qiao
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Liu He
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Tao Yu
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
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15
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Geller AS, Teale P, Kronberg E, Ebersole JS. Magnetoencephalography for Epilepsy Presurgical Evaluation. Curr Neurol Neurosci Rep 2024; 24:35-46. [PMID: 38148387 DOI: 10.1007/s11910-023-01328-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/13/2023] [Indexed: 12/28/2023]
Abstract
PURPOSE OF THE REVIEW Magnetoencephalography (MEG) is a functional neuroimaging technique that records neurophysiology data with millisecond temporal resolution and localizes it with subcentimeter accuracy. Its capability to provide high resolution in both of these domains makes it a powerful tool both in basic neuroscience as well as clinical applications. In neurology, it has proven useful in its ability to record and localize epileptiform activity. Epilepsy workup typically begins with scalp electroencephalography (EEG), but in many situations, EEG-based localization of the epileptogenic zone is inadequate. The complementary sensitivity of MEG can be crucial in such cases, and MEG has been adopted at many centers as an important resource in building a surgical hypothesis. In this paper, we review recent work evaluating the extent of MEG influence of presurgical evaluations, novel analyses of MEG data employed in surgical workup, and new MEG instrumentation that will likely affect the field of clinical MEG. RECENT FINDINGS MEG consistently contributes to presurgical evaluation and these contributions often change the plan for epilepsy surgery. Extensive work has been done to develop new analytic methods for localizing the source of epileptiform activity with MEG. Systems using optically pumped magnetometry (OPM) have been successfully deployed to record and localize epileptiform activity. MEG remains an important noninvasive tool for epilepsy presurgical evaluation. Continued improvements in analytic methodology will likely increase the diagnostic yield of the test. Novel instrumentation with OPM may contribute to this as well, and may increase accessibility of MEG by decreasing cost.
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Affiliation(s)
- Aaron S Geller
- Department of Neurology, CU Anschutz Medical School, Aurora, CO, USA.
| | - Peter Teale
- Department of Neurology, CU Anschutz Medical School, Aurora, CO, USA
| | - Eugene Kronberg
- Department of Neurology, CU Anschutz Medical School, Aurora, CO, USA
| | - John S Ebersole
- Department of Neurology, Atlantic Neuroscience Institute, Summit, NJ, USA
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16
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Poghosyan V, Algethami H, Alshahrani A, Asiri S, Aldosari MM. Association Between Magnetoencephalography-Localized Epileptogenic Zone, Surgical Resection Volume, and Postsurgical Seizure Outcome. J Clin Neurophysiol 2024:00004691-990000000-00118. [PMID: 38194636 DOI: 10.1097/wnp.0000000000001069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2024] Open
Abstract
PURPOSE Surgical resection of magnetoencephalography (MEG) dipole clusters, reconstructed from interictal epileptiform discharges, is associated with favorable seizure outcomes. However, the relation of MEG cluster resection to the surgical resection volume is not known nor is it clear whether this association is direct and causal, or it may be mediated by the resection volume or other predictive factors. This study aims to clarify these open questions and assess the diagnostic accuracy of MEG in our center. METHODS We performed a retrospective cohort study of 68 patients with drug-resistant epilepsy who underwent MEG followed by resective epilepsy surgery and had at least 12 months of postsurgical follow-up. RESULTS Good seizure outcomes were associated with monofocal localization (χ2 = 6.94, P = 0.001; diagnostic odds ratio = 10.2) and complete resection of MEG clusters (χ2 = 22.1, P < 0.001; diagnostic odds ratio = 42.5). Resection volumes in patients with and without removal of MEG clusters were not significantly different (t = 0.18, P = 0.86; removed: M = 20,118 mm3, SD = 10,257; not removed: M = 19,566 mm3, SD = 10,703). Logistic regression showed that removal of MEG clusters predicts seizure-free outcome independent of the resection volume and other prognostic factors (P < 0.001). CONCLUSIONS Complete resection of MEG clusters leads to favorable seizure outcomes without affecting the volume of surgical resection and independent of other prognostic factors. MEG can localize the epileptogenic zone with high accuracy. MEG interictal epileptiform discharges mapping should be used whenever feasible to improve postsurgical seizure outcomes.
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Affiliation(s)
- Vahe Poghosyan
- Department of Neurophysiology, National Neuroscience Institute, King Fahad Medical City, Riyadh, K.S.A.; and
| | - Hanin Algethami
- Department of Neurology, National Neuroscience Institute, King Fahad Medical City, Riyadh, K.S.A
| | - Ashwaq Alshahrani
- Department of Neurology, National Neuroscience Institute, King Fahad Medical City, Riyadh, K.S.A
| | - Safiyyah Asiri
- Department of Neurology, National Neuroscience Institute, King Fahad Medical City, Riyadh, K.S.A
| | - Mubarak M Aldosari
- Department of Neurology, National Neuroscience Institute, King Fahad Medical City, Riyadh, K.S.A
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17
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Badier JM, Schwartz D, Bénar CG, Kanzari K, Daligault S, Romain R, Mitryukovskiy S, Fourcault W, Josselin V, Le Prado M, Jung J, Palacios-Laloy A, Romain C, Bartolomei F, Labyt E, Bonini F. Helium Optically Pumped Magnetometers Can Detect Epileptic Abnormalities as Well as SQUIDs as Shown by Intracerebral Recordings. eNeuro 2023; 10:ENEURO.0222-23.2023. [PMID: 37932045 PMCID: PMC10748329 DOI: 10.1523/eneuro.0222-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 09/22/2023] [Accepted: 09/26/2023] [Indexed: 11/08/2023] Open
Abstract
Magnetoencephalography based on superconducting quantum interference devices (SQUIDs) has been shown to improve the diagnosis and surgical treatment decision for presurgical evaluation of drug-resistant epilepsy. Still, its use remains limited because of several constraints such as cost, fixed helmet size, and the obligation of immobility. A new generation of sensors, optically pumped magnetometers (OPMs), could overcome these limitations. In this study, we validate the ability of helium-based OPM (4He-OPM) sensors to record epileptic brain activity thanks to simultaneous recordings with intracerebral EEG [stereotactic EEG (SEEG)]. We recorded simultaneous SQUIDs-SEEG and 4He-OPM-SEEG signals in one patient during two sessions. We show that epileptic activities on intracerebral EEG can be recorded by OPMs with a better signal-to noise ratio than classical SQUIDs. The OPM sensors open new venues for the widespread application of magnetoencephalography in the management of epilepsy and other neurologic diseases and fundamental neuroscience.
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Affiliation(s)
- Jean-Michel Badier
- Institut de Neurosciences des Systèmes, Institut National de la Santé et de la Recherche Médicale, Aix Marseille Université, Marseille 13005, France
| | - Denis Schwartz
- MEG Departement, CERMEP-Imagerie du Vivant, Lyon 69003, France
| | - Christian-George Bénar
- Institut de Neurosciences des Systèmes, Institut National de la Santé et de la Recherche Médicale, Aix Marseille Université, Marseille 13005, France
| | - Khoubeib Kanzari
- Institut de Neurosciences des Systèmes, Institut National de la Santé et de la Recherche Médicale, Aix Marseille Université, Marseille 13005, France
| | | | - Rudy Romain
- CEA-LETI, MINATEC, Université Grenoble Alpes, Grenoble 38054, France
- MAG4Health, Grenoble 38000, France
| | - Sergey Mitryukovskiy
- CEA-LETI, MINATEC, Université Grenoble Alpes, Grenoble 38054, France
- MAG4Health, Grenoble 38000, France
| | - William Fourcault
- CEA-LETI, MINATEC, Université Grenoble Alpes, Grenoble 38054, France
| | - Vincent Josselin
- CEA-LETI, MINATEC, Université Grenoble Alpes, Grenoble 38054, France
| | - Matthieu Le Prado
- CEA-LETI, MINATEC, Université Grenoble Alpes, Grenoble 38054, France
- MAG4Health, Grenoble 38000, France
| | - Julien Jung
- Centre de Recherche en Neurosciences de Lyon, Unité Mixte de Recherche S1028, Centre National de la Recherche Scientifique, Hospices Civils de Lyon, Institut National de la Santé et de la Recherche Médicale, Université Lyon 1, Lyon 69002, France
| | - Augustin Palacios-Laloy
- CEA-LETI, MINATEC, Université Grenoble Alpes, Grenoble 38054, France
- MAG4Health, Grenoble 38000, France
| | - Carron Romain
- Institut de Neurosciences des Systèmes, Institut National de la Santé et de la Recherche Médicale, Aix Marseille Université, Marseille 13005, France
- Department of Functional and Stereotactic Neurosurgery, Hôpital de la Timone, Assistance Publique-Hôpitaux de Marseille, Marseille 3005, France
| | - Fabrice Bartolomei
- Institut de Neurosciences des Systèmes, Institut National de la Santé et de la Recherche Médicale, Aix Marseille Université, Marseille 13005, France
- Department of Epileptology and Cerebral Rythmology, Hôpital de la Timone, Assistance Publique-Hôpitaux de Marseille, Marseille 3005, France
| | - Etienne Labyt
- CEA-LETI, MINATEC, Université Grenoble Alpes, Grenoble 38054, France
- MAG4Health, Grenoble 38000, France
| | - Francesca Bonini
- Institut de Neurosciences des Systèmes, Institut National de la Santé et de la Recherche Médicale, Aix Marseille Université, Marseille 13005, France
- MEG Departement, CERMEP-Imagerie du Vivant, Lyon 69003, France
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18
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Sindhu DM, Mundlamuri RC, Goutham B, Narayanan M, Raghavendra K, Asranna A, Vishwanathan LG, Kulanthaivelu K, Saini J, Mangalore S, Bharath RD, Sadashiva N, Mahadevan A, Jamuna R, Arivazhagan A, Rao MB, Sinha S. Role of magnetoencephalography in predicting the epileptogenic zone and post-operative seizure outcome - A retrospective study. Seizure 2023; 113:41-47. [PMID: 37976800 DOI: 10.1016/j.seizure.2023.11.004] [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: 08/05/2023] [Revised: 11/07/2023] [Accepted: 11/09/2023] [Indexed: 11/19/2023] Open
Abstract
PURPOSE Study assessed the role of MSI in predicting the post-operative seizure outcome. METHODS This retrospective study included patients who underwent MEG and epilepsy surgery and had a minimum 6 months of postoperative follow-up. Concordance of MEG cluster with post-surgical resection cavity was classified as follows Class I) Concordant and region-specific, Class II) Concordant and region non-specific, Class III) Concordant lateralization only and Class IV) Discordant lateralization. The relationship between MSI concordance and post-operative seizure outcome was assessed. RESULTS A total of 183 patients (M: F = 109:74) were included. The mean age at onset of seizures: 8.0 ± 6.4 years. The dipoles were frequent in 123(67.2 %). The primary cluster orientation was regular in 59 (32.2 %) and mixed in 124 (67.8 %) patients. Concordance between MEG and resection cavity: Class I - 124 (67.8 %), class II- 30 (16.4 %), class III- 23 (12.6 %), and class IV- 6 (3.3 %). The post-surgically mean duration of follow-up was 19.52 ± 11.27 months. At 6-month follow-up period, 144 (78.7 %) patients had complete seizure freedom out of which 106 (73.6 %) had class I concordance. Concordance of MEG with resection cavity was associated with a good outcome at 6 months (p = 0.001), 1 year (p = 0.001), 2 years (p = 0.0005) and 5 years (p = 0.04). MEG cluster characteristics had no association with seizure outcome except the strength of the cluster and outcome at 3 years (p = 0.02) follow-up. CONCLUSION The study supports that the complete resection of the MEG cluster had high chance of seizure-freedom and can be used as a complementary noninvasive presurgical evaluation tool.
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Affiliation(s)
| | | | - Bhargava Goutham
- MEG research Lab, NIMHANS, Hosur Road, Bangalore, India; Department of Neurology, NIMHANS, Hosur road, Bangalore, India
| | - Mariyappa Narayanan
- MEG research Lab, NIMHANS, Hosur Road, Bangalore, India; Department of Neurology, NIMHANS, Hosur road, Bangalore, India
| | | | - Ajay Asranna
- Department of Neurology, NIMHANS, Hosur road, Bangalore, India
| | | | - Karthik Kulanthaivelu
- Department of Neuroimaging and Interventional Radiology, NIMHANS, Hosur road, Bangalore, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, NIMHANS, Hosur road, Bangalore, India
| | - Sandhya Mangalore
- Department of Neuroimaging and Interventional Radiology, NIMHANS, Hosur road, Bangalore, India
| | - Rose Dawn Bharath
- Department of Neuroimaging and Interventional Radiology, NIMHANS, Hosur road, Bangalore, India
| | | | - Anita Mahadevan
- Department of Neuropathology, NIMHANS, Hosur road, Bangalore, India
| | - Rajeswaran Jamuna
- Department of Clinical Psychology, NIMHANS, Hosur road, Bangalore, India
| | | | | | - Sanjib Sinha
- MEG research Lab, NIMHANS, Hosur Road, Bangalore, India; Department of Neurology, NIMHANS, Hosur road, Bangalore, India.
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Zheng L, Liao P, Wu X, Cao M, Cui W, Lu L, Xu H, Zhu L, Lyu B, Wang X, Teng P, Wang J, Vogrin S, Plummer C, Luan G, Gao JH. An artificial intelligence-based pipeline for automated detection and localisation of epileptic sources from magnetoencephalography. J Neural Eng 2023; 20:046036. [PMID: 37615416 DOI: 10.1088/1741-2552/acef92] [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: 04/28/2023] [Accepted: 08/10/2023] [Indexed: 08/25/2023]
Abstract
Objective.Magnetoencephalography (MEG) is a powerful non-invasive diagnostic modality for presurgical epilepsy evaluation. However, the clinical utility of MEG mapping for localising epileptic foci is limited by its low efficiency, high labour requirements, and considerable interoperator variability. To address these obstacles, we proposed a novel artificial intelligence-based automated magnetic source imaging (AMSI) pipeline for automated detection and localisation of epileptic sources from MEG data.Approach.To expedite the analysis of clinical MEG data from patients with epilepsy and reduce human bias, we developed an autolabelling method, a deep-learning model based on convolutional neural networks and a hierarchical clustering method based on a perceptual hash algorithm, to enable the coregistration of MEG and magnetic resonance imaging, the detection and clustering of epileptic activity, and the localisation of epileptic sources in a highly automated manner. We tested the capability of the AMSI pipeline by assessing MEG data from 48 epilepsy patients.Main results.The AMSI pipeline was able to rapidly detect interictal epileptiform discharges with 93.31% ± 3.87% precision based on a 35-patient dataset (with sevenfold patientwise cross-validation) and robustly rendered accurate localisation of epileptic activity with a lobar concordance of 87.18% against interictal and ictal stereo-electroencephalography findings in a 13-patient dataset. We also showed that the AMSI pipeline accomplishes the necessary processes and delivers objective results within a much shorter time frame (∼12 min) than traditional manual processes (∼4 h).Significance.The AMSI pipeline promises to facilitate increased utilisation of MEG data in the clinical analysis of patients with epilepsy.
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Affiliation(s)
- Li Zheng
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
- Changping Laboratory, Beijing, People's Republic of China
| | - Pan Liao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
| | - Xiuwen Wu
- Changping Laboratory, Beijing, People's Republic of China
- Center for Biomedical Engineering, University of Science and Technology of China, Anhui, People's Republic of China
| | - Miao Cao
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
- Changping Laboratory, Beijing, People's Republic of China
| | - Wei Cui
- Center for Biomedical Engineering, University of Science and Technology of China, Anhui, People's Republic of China
| | - Lingxi Lu
- Center for the Cognitive Science of Language, Beijing Language and Culture University, Beijing, People's Republic of China
| | - Hui Xu
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
| | - Linlin Zhu
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
| | - Bingjiang Lyu
- Changping Laboratory, Beijing, People's Republic of China
| | - Xiongfei Wang
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, People's Republic of China
- Beijing Key Laboratory of Epilepsy, Capital Medical University, Beijing, People's Republic of China
| | - Pengfei Teng
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Jing Wang
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Simon Vogrin
- Department of Neuroimaging, Swinburne University of Technology, Melbourne, Australia
| | - Chris Plummer
- Department of Neuroimaging, Swinburne University of Technology, Melbourne, Australia
| | - Guoming Luan
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, People's Republic of China
- Beijing Key Laboratory of Epilepsy, Capital Medical University, Beijing, People's Republic of China
| | - Jia-Hong Gao
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
- Changping Laboratory, Beijing, People's Republic of China
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
- McGovern Institute for Brain Research, Peking University, Beijing, People's Republic of China
- National Biomedical Imaging Center, Peking University, Beijing, People's Republic of China
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20
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Sharma N, Mallela AN, Abou-Al-Shaar H, Aung T, Gonzalez-Martinez J. Trans-Interhemispheric Stereoelectroencephalography Depth Electrode Placement for Mesial Frontal Lobe Explorations in Medically Refractory Epilepsy: A Technical Note and Case Series. Oper Neurosurg (Hagerstown) 2023; 24:582-589. [PMID: 36786750 DOI: 10.1227/ons.0000000000000631] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 11/18/2022] [Indexed: 02/15/2023] Open
Abstract
BACKGROUND Stereoelectroencephalography (SEEG) is an established and safe methodology for extra-operative invasive monitoring in patients with medical refractory epilepsy. SEEG has several advantages such as the ability to record deep cortical structures, mapping the epileptogenic zone in a three-dimensional manner, and analyze bihemispheric regions without the need for bilateral craniotomies. In patients with bilateral hemispheric hypotheses, especially the mesial surface of frontal lobes, bilateral lead placement is compulsory to further define and localize the epileptogenic zone. In this particular cohort of patients, bilateral monitoring may be accomplished from a single entry point using trans-interhemispheric placement of the electrodes. The use of trans-interhemispheric monitoring offers several advantages including sparing the need for additional leads. OBJECTIVE To test the hypothesis that, given the lack of the falx as a limiting structure in the ventral and mesial frontal lobe regions, trans-interhemispheric SEEG placement is feasible and a potential benefit for the SEEG method. METHODS We report on 6 patients who underwent bilateral monitoring using trans-interhemispheric SEEG lead placement and discuss the operative technique. RESULTS Six patients underwent trans-interhemispheric monitoring, with a median of 3 leads per patient (19 total). Trajectory error was minimal (<0.3 mm), and operating room time was comparable with that in previous reports. All leads were placed without adverse events, mislocalization, electrode hemorrhages, or any other complications. All patients had successful localization of the epileptogenic zone. CONCLUSION Trans-interhemispheric SEEG to monitor the mesial wall of frontal lobe regions is technically feasible. No adverse events were observed, suggesting a favorable safety profile.
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Affiliation(s)
- Nikhil Sharma
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Arka N Mallela
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Hussam Abou-Al-Shaar
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Thandar Aung
- Department of Neurology and Epilepsy Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Jorge Gonzalez-Martinez
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
- Department of Neurology and Epilepsy Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
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21
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Vasilica AM, Litvak V, Cao C, Walker M, Vivekananda U. Detection of pathological high-frequency oscillations in refractory epilepsy patients undergoing simultaneous stereo-electroencephalography and magnetoencephalography. Seizure 2023; 107:81-90. [PMID: 36996757 DOI: 10.1016/j.seizure.2023.03.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 03/22/2023] [Indexed: 03/29/2023] Open
Abstract
BACKGROUND Stereo-electroencephalography (SEEG) and magnetoencephalography (MEG) have generally been used independently as part of the pre-surgical evaluation of drug-resistant epilepsy (DRE) patients. However, the possibility of simultaneously employing these recording techniques to determine whether MEG has the potential of offering the same information as SEEG less invasively, or whether it could offer a greater spatial indication of the epileptogenic zone (EZ) to aid surgical planning, has not been previously evaluated. METHODS Data from 24 paediatric and adult DRE patients, undergoing simultaneous SEEG and MEG as part of their pre-surgical evaluation, was analysed employing manual and automated high-frequency oscillations (HFOs) detection, and spectral and source localisation analyses. RESULTS Twelve patients (50%) were included in the analysis (4 males; mean age=25.08 years) and showed interictal SEEG and MEG HFOs. HFOs detection was concordant between the two recording modalities, but SEEG displayed higher ability of differentiating between deep and superficial epileptogenic sources. Automated HFO detector in MEG recordings was validated against the manual MEG detection method. Spectral analysis revealed that SEEG and MEG detect distinct epileptic events. The EZ was well correlated with the simultaneously recorded data in 50% patients, while 25% patients displayed poor correlation or discordance. CONCLUSION MEG recordings can detect HFOs, and simultaneous use of SEEG and MEG HFO identification facilitates EZ localisation during the presurgical planning stage for DRE patients. Further studies are necessary to validate these findings and support the translation of automated HFO detectors into routine clinical practice.
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Affiliation(s)
| | - Vladimir Litvak
- Wellcome Centre for Human Neuroimaging, UCL, Queen Square, London, WC1N 3AR, United Kingdom
| | - Chunyan Cao
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Matthew Walker
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Umesh Vivekananda
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
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22
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Wang Y, Li Y, Sun F, Xu Y, Xu F, Wang S, Wang X. Altered neuromagnetic activity in default mode network in childhood absence epilepsy. Front Neurosci 2023; 17:1133064. [PMID: 37008207 PMCID: PMC10060817 DOI: 10.3389/fnins.2023.1133064] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 02/27/2023] [Indexed: 03/18/2023] Open
Abstract
PurposeThe electrophysiological characterization of resting state oscillatory functional connectivity within the default mode network (DMN) during interictal periods in childhood absence epilepsy (CAE) remains unclear. Using magnetoencephalographic (MEG) recordings, this study investigated how the connectivity within the DMN was altered in CAE.MethodsUsing a cross-sectional design, we analyzed MEG data from 33 children newly diagnosed with CAE and 26 controls matched for age and sex. The spectral power and functional connectivity of the DMN were estimated using minimum norm estimation combined with the Welch technique and corrected amplitude envelope correlation.ResultsDefault mode network showed stronger activation in the delta band during the ictal period, however, the relative spectral power in other bands was significantly lower than that in the interictal period (pcorrected < 0.05 for DMN regions, except bilateral medial frontal cortex, left medial temporal lobe, left posterior cingulate cortex in the theta band, and the bilateral precuneus in the alpha band). It should be noted that the significant power peak in the alpha band was lost compared with the interictal data. Compared with controls, the interictal relative spectral power of DMN regions (except bilateral precuneus) in CAE patients was significantly increased in the delta band (pcorrected < 0.01), whereas the values of all DMN regions in the beta-gamma 2 band were significantly decreased (pcorrected < 0.01). In the higher frequency band (alpha-gamma1), especially in the beta and gamma1 band, the ictal node strength of DMN regions except the left precuneus was significantly higher than that in the interictal periods (pcorrected < 0.01), and the node strength of the right inferior parietal lobe increased most significantly in the beta band (Ictal: 3.8712 vs. Interictal: 0.7503, pcorrected < 0.01). Compared with the controls, the interictal node strength of DMN increased in all frequency bands, especially the right medial frontal cortex in the beta band (Controls: 0.1510 vs. Interictal: 3.527, pcorrected < 0.01). Comparing relative node strength between groups, the right precuneus in CAE children decreased significantly (β: Controls: 0.1009 vs. Interictal: 0.0475; γ 1: Controls:0.1149 vs. Interictal:0.0587, pcorrected < 0.01) such that it was no longer the central hub.ConclusionThese findings indicated DMN abnormalities in CAE patients, even in interictal periods without interictal epileptic discharges. Abnormal functional connectivity in CAE may reflect abnormal anatomo-functional architectural integration in DMN, as a result of cognitive mental impairment and unconsciousness during absence seizure. Future studies are needed to examine if the altered functional connectivity can be used as a biomarker for treatment responses, cognitive dysfunction, and prognosis in CAE patients.
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23
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Krishnan B, Tousseyn S, Wang ZI, Murakami H, Wu G, Burgess R, Iasemidis L, Najm I, Alexopoulos AV. Novel noninvasive identification of patient-specific epileptic networks in focal epilepsies: Linking single-photon emission computed tomography perfusion during seizures with resting-state magnetoencephalography dynamics. Hum Brain Mapp 2023; 44:1695-1710. [PMID: 36480260 PMCID: PMC9921232 DOI: 10.1002/hbm.26168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 08/31/2022] [Accepted: 11/18/2022] [Indexed: 12/13/2022] Open
Abstract
Single-photon emission computed tomography (SPECT) during seizures and magnetoencephalography (MEG) during the interictal state are noninvasive modalities employed in the localization of the epileptogenic zone in patients with drug-resistant focal epilepsy (DRFE). The present study aims to investigate whether there exists a preferentially high MEG functional connectivity (FC) among those regions of the brain that exhibit hyperperfusion or hypoperfusion during seizures. We studied MEG and SPECT data in 30 consecutive DRFE patients who had resective epilepsy surgery. We parcellated each ictal perfusion map into 200 regions of interest (ROIs) and generated ROI time series using source modeling of MEG data. FC between ROIs was quantified using coherence and phase-locking value. We defined a generalized linear model to relate the connectivity of each ROI, ictal perfusion z score, and distance between ROIs. We compared the coefficients relating perfusion z score to FC of each ROI and estimated the connectivity within and between resected and unresected ROIs. We found that perfusion z scores were strongly correlated with the FC of hyper-, and separately, hypoperfused ROIs across patients. High interictal connectivity was observed between hyperperfused brain regions inside and outside the resected area. High connectivity was also observed between regions of ictal hypoperfusion. Importantly, the ictally hypoperfused regions had a low interictal connectivity to regions that became hyperperfused during seizures. We conclude that brain regions exhibiting hyperperfusion during seizures highlight a preferentially connected interictal network, whereas regions of ictal hypoperfusion highlight a separate, discrete and interconnected, interictal network.
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Affiliation(s)
- Balu Krishnan
- Neurological InstituteEpilepsy Center, Cleveland ClinicClevelandOhioUSA
| | - Simon Tousseyn
- Academic Center for EpileptologyKempenhaeghe and Maastricht UMC+HeezeThe Netherlands
| | - Zhong Irene Wang
- Neurological InstituteEpilepsy Center, Cleveland ClinicClevelandOhioUSA
| | - Hiroatsu Murakami
- Neurological InstituteEpilepsy Center, Cleveland ClinicClevelandOhioUSA
| | - Guiyun Wu
- Neurological InstituteEpilepsy Center, Cleveland ClinicClevelandOhioUSA
| | - Richard Burgess
- Neurological InstituteEpilepsy Center, Cleveland ClinicClevelandOhioUSA
| | - Leonidas Iasemidis
- Department of Translational NeuroscienceBarrow Neurological InstituteScottsdaleArizonaUSA
- Department of NeurologyBarrow Neurological InstituteScottsdaleArizonaUSA
| | - Imad Najm
- Neurological InstituteEpilepsy Center, Cleveland ClinicClevelandOhioUSA
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24
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Laohathai C, Funke M. Epilepsy highlight: Ictal MEG in epilepsy surgery candidates - Results from largest cohort. Clin Neurophysiol 2023; 145:98-99. [PMID: 36435692 DOI: 10.1016/j.clinph.2022.11.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 11/08/2022] [Indexed: 11/17/2022]
Affiliation(s)
| | - Michael Funke
- Department of Pediatrics, University of Texas Health Science Center, McGovern Medical School, Houston, TX, USA
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25
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Katagiri M, Wang ZI, Hirfanoglu T, Aldosari MM, Aung T, Wang S, Kobayashi K, Bulacio J, Bingaman W, Najm IM, Alexopoulos AV, Burgess RC. Clinical significance of ictal magnetoencephalography in patients undergoing epilepsy surgery. Clin Neurophysiol 2023; 145:108-118. [PMID: 36443170 DOI: 10.1016/j.clinph.2022.10.005] [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: 04/28/2022] [Revised: 09/30/2022] [Accepted: 10/11/2022] [Indexed: 11/03/2022]
Abstract
OBJECTIVE The significance of ictal magnetoencephalography (MEG) is not well appreciated. We evaluated the relationships between ictal MEG, MRI, intracranial electroencephalography (ICEEG), surgery and postoperative seizure outcome. METHODS A total of 45 patients (46 cases) with ictal MEG who underwent epilepsy surgery was included. We examined the localization of each modality, surgical resection area and seizure freedom after surgery. RESULTS Twenty-one (45.7%) out of 46 cases were seizure-free at more than 6 months follow-up. Median duration of postoperative follow-up was 16.5 months. The patients in whom ictal, interictal single equivalent current dipole (SECD) and MRI lesion localization were completely included in the resection had a higher chance of being seizure-free significantly (p < 0.05). Concordance between ictal and interictal SECD localizations was significantly associated with seizure-freedom. Concordance between MRI lesion and ictal SECD, concordance between ictal ICEEG and ictal and interictal SECD, as well as concordance between ictal ICEEG and MRI lesion were significantly associated with seizure freedom. CONCLUSIONS Ictal MEG can contribute useful information for delineating the resection area in epilepsy surgery. SIGNIFICANCE Resection should include ictal, interictal SECDs and MRI lesion localization, when feasible. Concordant ictal and interictal SECDs on MEG can be a favorable predictor of seizure freedom.
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Affiliation(s)
- Masaya Katagiri
- Epilepsy Center, Cleveland Clinic, OH, USA; Department of Neurosurgery, Graduate School of Medicine, Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | | | - Tugba Hirfanoglu
- Epilepsy Center, Cleveland Clinic, OH, USA; Department of Pediatric Neurology, Gazi University School of Medicine, Ankara, Turkey
| | - Mubarak M Aldosari
- Epilepsy Center, Cleveland Clinic, OH, USA; Epilepsy Program, National Neurosciences Institute, King Fahad Medical City, Riyadh, Saudi Arabia
| | - Thandar Aung
- Epilepsy Center, Cleveland Clinic, OH, USA; Comprehensive Epilepsy Center, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Shan Wang
- Epilepsy Center, Cleveland Clinic, OH, USA; Epilepsy Center, Department of Neurology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Katsuya Kobayashi
- Epilepsy Center, Cleveland Clinic, OH, USA; Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan
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Mohanty D, Quach M. The Noninvasive Evaluation for Minimally Invasive Pediatric Epilepsy Surgery (MIPES): A Multimodal Exploration of the Localization-Based Hypothesis. JOURNAL OF PEDIATRIC EPILEPSY 2022. [DOI: 10.1055/s-0042-1760104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
AbstractMinimally invasive pediatric epilepsy surgery (MIPES) is a rising technique in the management of focal-onset drug-refractory epilepsy. Minimally invasive surgical techniques are based on small, focal interventions (such as parenchymal ablation or localized neuromodulation) leading to elimination of the seizure onset zone or interruption of the larger epileptic network. Precise localization of the seizure onset zone, demarcation of eloquent cortex, and mapping of the network leading to seizure propagation are required to achieve optimal outcomes. The toolbox for presurgical, noninvasive evaluation of focal epilepsy continues to expand rapidly, with a variety of options based on advanced imaging and electrophysiology. In this article, we will examine several of these diagnostic modalities from the standpoint of MIPES and discuss how each can contribute to the development of a localization-based hypothesis for potential surgical targets.
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Affiliation(s)
- Deepankar Mohanty
- Section of Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas
| | - Michael Quach
- Section of Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas
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27
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Maldjian JA, Lee R, Jordan J, Davenport EM, Proskovec AL, Wintermark M, Stufflebeam S, Anderson J, Mukherjee P, Nagarajan SS, Ferrari P, Gaetz W, Schwartz E, Roberts TPL. ACR White Paper on Magnetoencephalography and Magnetic Source Imaging: A Report from the ACR Commission on Neuroradiology. AJNR Am J Neuroradiol 2022; 43:E46-E53. [PMID: 36456085 DOI: 10.3174/ajnr.a7714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 10/04/2022] [Indexed: 12/04/2022]
Abstract
Magnetoencephalography, the extracranial detection of tiny magnetic fields emanating from intracranial electrical activity of neurons, and its source modeling relation, magnetic source imaging, represent a powerful functional neuroimaging technique, able to detect and localize both spontaneous and evoked activity of the brain in health and disease. Recent years have seen an increased utilization of this technique for both clinical practice and research, in the United States and worldwide. This report summarizes current thinking, presents recommendations for clinical implementation, and offers an outlook for emerging new clinical indications.
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Affiliation(s)
- J A Maldjian
- From the Advanced Neuroscience Imaging Research Laboratory (J.A.M., E.M.D., A.L.P.) .,MEG Center of Excellence (J.A.M., E.M.D., A.L.P.).,Department of Radiology (J.A.M., E.M.D., A.L.P.), University of Texas Southwestern Medical Center, Dallas, Texas
| | - R Lee
- Department of Neuroradiology (R.L.), University of California San Diego, San Diego, California
| | - J Jordan
- ACR Commission on Neuroradiology (J.J.), American College of Radiology, Reston, Virginia.,Stanford University School of Medicine (J.J.), Stanford, California
| | - E M Davenport
- From the Advanced Neuroscience Imaging Research Laboratory (J.A.M., E.M.D., A.L.P.).,MEG Center of Excellence (J.A.M., E.M.D., A.L.P.).,Department of Radiology (J.A.M., E.M.D., A.L.P.), University of Texas Southwestern Medical Center, Dallas, Texas
| | - A L Proskovec
- From the Advanced Neuroscience Imaging Research Laboratory (J.A.M., E.M.D., A.L.P.).,MEG Center of Excellence (J.A.M., E.M.D., A.L.P.).,Department of Radiology (J.A.M., E.M.D., A.L.P.), University of Texas Southwestern Medical Center, Dallas, Texas
| | - M Wintermark
- Department of Neuroradiology (M.W.), University of Texas MD Anderson Center, Houston, Texas
| | - S Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging (S.S.), Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts
| | - J Anderson
- Department of Radiology and Imaging Sciences (J.A.), University of Utah School of Medicine, Salt Lake City, Utah
| | - P Mukherjee
- Department of Radiology and Biomedical Imaging (P.M., S.S.N.), University of California, San Francisco, San Francisco, California
| | - S S Nagarajan
- Department of Radiology and Biomedical Imaging (P.M., S.S.N.), University of California, San Francisco, San Francisco, California
| | - P Ferrari
- Pediatric Neurosciences (P.F.), Helen DeVos Children's Hospital, Grand Rapids, Michigan.,Department of Pediatrics and Human Development (P.F.), College of Human Medicine, Michigan State University, Grand Rapids, Michigan
| | - W Gaetz
- Department of Radiology (W.G., E.S., T.P.L.R.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - E Schwartz
- Department of Radiology (W.G., E.S., T.P.L.R.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - T P L Roberts
- Department of Radiology (W.G., E.S., T.P.L.R.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
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Velmurugan J, Badier JM, Pizzo F, Medina Villalon S, Papageorgakis C, López-Madrona V, Jegou A, Carron R, Bartolomei F, Bénar CG. Virtual MEG sensors based on beamformer and independent component analysis can reconstruct epileptic activity as measured on simultaneous intracerebral recordings. Neuroimage 2022; 264:119681. [PMID: 36270623 DOI: 10.1016/j.neuroimage.2022.119681] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 09/30/2022] [Accepted: 10/10/2022] [Indexed: 11/09/2022] Open
Abstract
The prevailing gold standard for presurgical determination of epileptogenic brain networks is intracerebral EEG, a potent yet invasive approach. Magnetoencephalography (MEG) is a state-of-the art non-invasive method for investigating epileptiform discharges. However, it is not clear at what level the precision offered by MEG can reach that of SEEG. Here, we present a strategy for non-invasively retrieving the constituents of the interictal network, with high spatial and temporal precision. Our method is based on MEG and a combination of spatial filtering and independent component analysis (ICA). We validated this approach in twelve patients with drug-resistant focal epilepsy, thanks to the unprecedented ground truth provided by simultaneous recordings of MEG and SEEG. A minimum variance adaptive beamformer estimated the source time series and ICA was used to further decompose these time series into network constituents (MEG-ICs), each having a time series (virtual electrode) and a topography (spatial distribution of amplitudes in the brain). We show that MEG has a considerable sensitivity of 0.80 and 0.84 and a specificity of 0.93 and 0.91 for reconstructing deep and superficial sources, respectively, when compared to the ground truth (SEEG). For each epileptic MEG-IC (n = 131), we found at least one significantly correlating SEEG contact close to zero lag after correcting for multiple comparisons. All the patients except one had at least one epileptic component that was highly correlated (Spearman rho>0.3) with that of SEEG traces. MEG-ICs correlated well with SEEG traces. The strength of correlation coefficients did not depend on the depth of the SEEG contacts or the clinical outcome of the patient. A significant proportion of the MEG-ICs (n = 83/131) were localized in proximity with their maximally correlating SEEG, within a mean distance of 20±12.18mm. Our research is the first to validate the MEG-retrieved beamformer IC sources against SEEG-derived ground truth in a simultaneous MEG-SEEG framework. Observations from the present study suggest that non-invasive MEG source components may potentially provide additional information, comparable to SEEG in a number of instances.
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Affiliation(s)
- Jayabal Velmurugan
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France
| | - Jean-Michel Badier
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France
| | - Francesca Pizzo
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France; APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, F-13005, France
| | - Samuel Medina Villalon
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France; APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, F-13005, France
| | | | | | - Aude Jegou
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France
| | - Romain Carron
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France; APHM, Timone Hospital, Functional and Stereotactic Neurosurgery, Marseille, F-13005, France
| | - Fabrice Bartolomei
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France; APHM, Timone Hospital, Epileptology and Cerebral Rhythmology, Marseille, F-13005, France
| | - Christian-G Bénar
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, F-13005, France.
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Alkawadri R, Enatsu R, Hämäläinen M, Bagić A. Editorial: Magnetoencephalography: Methodological innovation paves the way for scientific discoveries and new clinical applications. Front Neurol 2022; 13:1056301. [PMID: 36504656 PMCID: PMC9731220 DOI: 10.3389/fneur.2022.1056301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 10/13/2022] [Indexed: 11/25/2022] Open
Affiliation(s)
- Rafeed Alkawadri
- University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), Department of Neurology, University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA, United States,*Correspondence: Rafeed Alkawadri ; https://www.humanbrainmapping.net/contactus
| | - Rei Enatsu
- Department of Neurosurgery, Sapporo Medical University, Sapporo, Japan
| | - Matti Hämäläinen
- Department of Radiology, Harvard Medical School, Boston, MA, United States,Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, Espoo, Finland
| | - Anto Bagić
- University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), Department of Neurology, University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA, United States
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Coan AC, Cavalcante CM, Burgess RC. Utility of Functional MRI and Magnetoencephalography in the Diagnosis of Infantile Spasms and Hypsarrhythmia. J Clin Neurophysiol 2022; 39:544-551. [PMID: 35323155 DOI: 10.1097/wnp.0000000000000501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
SUMMARY Neuroimaging and neurophysiology techniques can add a significant contribution to the comprehension of infantile spasms (IS) and hypsarrhythmia. Functional MRI and magnetoencephalography (MEG) are two noninvasive tools that can be used in young children with IS. In the past two decades, interesting data about IS have emerged from functional MRI and MEG studies. Regarding their clinical utility, MEG has supported the concept that epileptic spasms can have a focal origin. Moreover, MEG might contribute to the localization of the epileptogenic zone in children with IS under investigation for epilepsy surgery. Functional MRI data have contributed to improve the knowledge about the physiopathology of IS and hypsarrhythmia. It has demonstrated abnormal brainstem involvement during the high-amplitude slow waves of hypsarrhythmia and cortical involvement during the epileptiform discharges. Since the feasibility of these techniques has been demonstrated in infants, it is possible that, in the future, larger functional MRI and MEG studies might contribute to the treatment and the definition of the long-term prognosis of children with IS.
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Affiliation(s)
- Ana Carolina Coan
- Department of Neurology, Child Neurology Unit, University of Campinas (UNICAMP), Campinas, SP, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), at UNICAMP, Campinas, SP, Brazil; and
| | - Charlington M Cavalcante
- Department of Neurology, Child Neurology Unit, University of Campinas (UNICAMP), Campinas, SP, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), at UNICAMP, Campinas, SP, Brazil; and
| | - Richard C Burgess
- Epilepsy Center, Cleveland Clinic Foundation, Cleveland, Ohio, U.S.A
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Anand A, Magnotti JF, Smith DN, Gadot R, Najera RA, Hegazy MIR, Gavvala JR, Shofty B, Sheth SA. Predictive value of magnetoencephalography in guiding the intracranial implant strategy for intractable epilepsy. J Neurosurg 2022; 137:1237-1247. [PMID: 35303696 DOI: 10.3171/2022.1.jns212943] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Accepted: 01/31/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Magnetoencephalography (MEG) is a useful component of the presurgical evaluation of patients with epilepsy. Due to its high spatiotemporal resolution, MEG often provides additional information to the clinician when forming hypotheses about the epileptogenic zone (EZ). Because of the increasing utilization of stereo-electroencephalography (sEEG), MEG clusters are used to guide sEEG electrode targeting with increasing frequency. However, there are no predefined features of an MEG cluster that predict ictal activity. This study aims to determine which MEG cluster characteristics are predictive of the EZ. METHODS The authors retrospectively analyzed all patients who had an MEG study (2017-2021) and underwent subsequent sEEG evaluation. MEG dipoles and sEEG electrodes were reconstructed in the same coordinate space to calculate overlap among individual contacts on electrodes and MEG clusters. MEG cluster features-including number of dipoles, proximity, angle, density, magnitude, confidence parameters, and brain region-were used to predict ictal activity in sEEG. Logistic regression was used to identify important cluster features and to train a binary classifier to predict ictal activity. RESULTS Across 40 included patients, 196 electrodes (42.2%) sampled MEG clusters. Electrodes that sampled MEG clusters had higher rates of ictal and interictal activity than those that did not sample MEG clusters (ictal 68.4% vs 39.8%, p < 0.001; interictal 71.9% vs 44.6%, p < 0.001). Logistic regression revealed that the number of dipoles (odds ratio [OR] 1.09, 95% confidence interval [CI] 1.04-1.14, t = 3.43) and confidence volume (OR 0.02, 95% CI 0.00-0.86, t = -2.032) were predictive of ictal activity. This model was predictive of ictal activity with 77.3% accuracy (sensitivity = 80%, specificity = 74%, C-statistic = 0.81). Using only the number of dipoles had a predictive accuracy of 75%, whereas a threshold between 14 and 17 dipoles in a cluster detected ictal activity with 75.9%-85.2% sensitivity. CONCLUSIONS MEG clusters with approximately 14 or more dipoles are strong predictors of ictal activity and may be useful in the preoperative planning of sEEG implantation.
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Affiliation(s)
| | - John F Magnotti
- 2Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | | | | | | | | | - Jay R Gavvala
- 3Neurology, Baylor College of Medicine, Houston, Texas; and
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Chirkov V, Kryuchkova A, Koptelova A, Stroganova T, Kuznetsova A, Kleeva D, Ossadtchi A, Fedele T. Data-driven approach for the delineation of the irritative zone in epilepsy in MEG. PLoS One 2022; 17:e0275063. [PMID: 36282803 PMCID: PMC9595543 DOI: 10.1371/journal.pone.0275063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 09/09/2022] [Indexed: 11/06/2022] Open
Abstract
The reliable identification of the irritative zone (IZ) is a prerequisite for the correct clinical evaluation of medically refractory patients affected by epilepsy. Given the complexity of MEG data, visual analysis of epileptiform neurophysiological activity is highly time consuming and might leave clinically relevant information undetected. We recorded and analyzed the interictal activity from seven patients affected by epilepsy (Vectorview Neuromag), who successfully underwent epilepsy surgery (Engel > = II). We visually marked and localized characteristic epileptiform activity (VIS). We implemented a two-stage pipeline for the detection of interictal spikes and the delineation of the IZ. First, we detected candidate events from peaky ICA components, and then clustered events around spatio-temporal patterns identified by convolutional sparse coding. We used the average of clustered events to create IZ maps computed at the amplitude peak (PEAK), and at the 50% of the peak ascending slope (SLOPE). We validated our approach by computing the distance of the estimated IZ (VIS, SLOPE and PEAK) from the border of the surgically resected area (RA). We identified 25 spatiotemporal patterns mimicking the underlying interictal activity (3.6 clusters/patient). Each cluster was populated on average by 22.1 [15.0–31.0] spikes. The predicted IZ maps had an average distance from the resection margin of 8.4 ± 9.3 mm for visual analysis, 12.0 ± 16.5 mm for SLOPE and 22.7 ±. 16.4 mm for PEAK. The consideration of the source spread at the ascending slope provided an IZ closer to RA and resembled the analysis of an expert observer. We validated here the performance of a data-driven approach for the automated detection of interictal spikes and delineation of the IZ. This computational framework provides the basis for reproducible and bias-free analysis of MEG recordings in epilepsy.
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Affiliation(s)
- Valerii Chirkov
- Berlin School of Mind and Brain, Humboldt University, Berlin, Germany
| | - Anna Kryuchkova
- Center for Neurocognitive Research, MEG Center, MSUPE, Moscow, Russian Federation
| | - Alexandra Koptelova
- Center for Neurocognitive Research, MEG Center, MSUPE, Moscow, Russian Federation
| | - Tatiana Stroganova
- Center for Neurocognitive Research, MEG Center, MSUPE, Moscow, Russian Federation
| | - Alexandra Kuznetsova
- Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation
| | - Daria Kleeva
- Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation
| | - Alexei Ossadtchi
- Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation
| | - Tommaso Fedele
- Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation
- * E-mail:
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Seedat ZA, Rier L, Gascoyne LE, Cook H, Woolrich MW, Quinn AJ, Roberts TPL, Furlong PL, Armstrong C, St. Pier K, Mullinger KJ, Marsh ED, Brookes MJ, Gaetz W. Mapping Interictal activity in epilepsy using a hidden Markov model: A magnetoencephalography study. Hum Brain Mapp 2022; 44:66-81. [PMID: 36259549 PMCID: PMC9783449 DOI: 10.1002/hbm.26118] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 09/19/2022] [Accepted: 09/26/2022] [Indexed: 02/05/2023] Open
Abstract
Epilepsy is a highly heterogeneous neurological disorder with variable etiology, manifestation, and response to treatment. It is imperative that new models of epileptiform brain activity account for this variability, to identify individual needs and allow clinicians to curate personalized care. Here, we use a hidden Markov model (HMM) to create a unique statistical model of interictal brain activity for 10 pediatric patients. We use magnetoencephalography (MEG) data acquired as part of standard clinical care for patients at the Children's Hospital of Philadelphia. These data are routinely analyzed using excess kurtosis mapping (EKM); however, as cases become more complex (extreme multifocal and/or polymorphic activity), they become harder to interpret with EKM. We assessed the performance of the HMM against EKM for three patient groups, with increasingly complicated presentation. The difference in localization of epileptogenic foci for the two methods was 7 ± 2 mm (mean ± SD over all 10 patients); and 94% ± 13% of EKM temporal markers were matched by an HMM state visit. The HMM localizes epileptogenic areas (in agreement with EKM) and provides additional information about the relationship between those areas. A key advantage over current methods is that the HMM is a data-driven model, so the output is tuned to each individual. Finally, the model output is intuitive, allowing a user (clinician) to review the result and manually select the HMM epileptiform state, offering multiple advantages over previous methods and allowing for broader implementation of MEG epileptiform analysis in surgical decision-making for patients with intractable epilepsy.
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Affiliation(s)
- Zelekha A. Seedat
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK,Young EpilepsySt Pier's LaneLingfieldRH7 6PWUK
| | - Lukas Rier
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK
| | - Lauren E. Gascoyne
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK
| | - Harry Cook
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK
| | - Mark W. Woolrich
- Oxford Centre for Human Brain ActivityUniversity Department of Psychiatry, Warneford HospitalOxfordUK
| | - Andrew J. Quinn
- Oxford Centre for Human Brain ActivityUniversity Department of Psychiatry, Warneford HospitalOxfordUK
| | - Timothy P. L. Roberts
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | | | - Caren Armstrong
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA,Pediatric Epilepsy Program, Division of Child NeurologyCHOPPhiladelphiaPennsylvaniaUSA
| | | | - Karen J. Mullinger
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK,Centre for Human Brain Health, School of PsychologyUniversity of BirminghamBirminghamUK
| | - Eric D. Marsh
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA,Pediatric Epilepsy Program, Division of Child NeurologyCHOPPhiladelphiaPennsylvaniaUSA,Departments of Neurology and PaediatricsUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Matthew J. Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK
| | - William Gaetz
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
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Mozaffari K, Hofmann K, Boyd P, Chalif E, Pasupuleti A, Gaillard WD, Oluigbo C. The Impact of Magnetoencephalography-Directed Stereo-Electroencephalography Depth Electrode Implantation on Seizure Control Outcome in Children. Cureus 2022; 14:e29860. [PMID: 36348878 PMCID: PMC9630048 DOI: 10.7759/cureus.29860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/02/2022] [Indexed: 06/16/2023] Open
Abstract
Introduction The use of magnetoencephalography (MEG) in localizing epileptic foci and directing surgical treatment of medically refractory epilepsy is well established in clinical practice; however, it has not yet been incorporated into the routine planning of stereo-electroencephalography (EEG) (SEEG) depth electrode trajectories during invasive intracranial evaluation for epileptic foci localization. In this study, we assess the impact of MEG-directed SEEG on seizure outcomes in a pediatric cohort. Methods A retrospective analysis was performed on a single-institution cohort of pediatric patients with medically refractory epilepsy who underwent epilepsy surgery. The primary endpoint was the reduction in seizure burden as determined by dichotomized Engel scores (favorable outcome: Engel scores I and II; poor outcome: Engel scores III and IV). Results Thirty-seven patients met the inclusion criteria (24 males and 13 females). The median age at seizure onset was three years, the median age at surgery was 14.1 years, and the median follow-up length was 30.8 months. Concordance was noted in 7/10 (70%) patients who received MEG-directed SEEG. Good clinical outcomes were achieved in 70% of MEG-directed SEEG patients, compared to 59.4% in their counterparts; however, this difference was not statistically significant (p=0.72). We noted no statistically significant association between sex, disease laterality, or age at surgery and good clinical outcomes. Conclusions Patients who underwent MEG-directed SEEG had favorable clinical outcomes, which demonstrated the practicability of this technique for determining SEEG electrode placement. Although no significant difference in clinical outcomes was obtained between the two groups, this may have been due to low statistical power. Future prospective, multi-institutional investigations to assess the benefit of MEG-directed SEEG are warranted.
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Affiliation(s)
- Khashayar Mozaffari
- Department of Neurosurgery, George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Katherine Hofmann
- Department of Neurosurgery, Children's National Hospital, Washington, DC, USA
| | - Paul Boyd
- Department of Neurosurgery, Children's National Hospital, Washington, DC, USA
| | - Eric Chalif
- Department of Neurosurgery, George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Archana Pasupuleti
- Department of Neurology, Children's National Hospital, Washington, DC, USA
| | - William D Gaillard
- Department of Neurology, Children's National Hospital, Washington, DC, USA
| | - Chima Oluigbo
- Department of Neurosurgery, Children's National Hospital, Washington, DC, USA
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Ntolkeras G, Tamilia E, AlHilani M, Bolton J, Ellen Grant P, Prabhu SP, Madsen JR, Stufflebeam SM, Pearl PL, Papadelis C. Presurgical accuracy of dipole clustering in MRI-negative pediatric patients with epilepsy: Validation against intracranial EEG and resection. Clin Neurophysiol 2022; 141:126-138. [PMID: 33875376 PMCID: PMC8803140 DOI: 10.1016/j.clinph.2021.01.036] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 01/21/2021] [Accepted: 01/27/2021] [Indexed: 01/24/2023]
Abstract
OBJECTIVE To assess the utility of interictal magnetic and electric source imaging (MSI and ESI) using dipole clustering in magnetic resonance imaging (MRI)-negative patients with drug resistant epilepsy (DRE). METHODS We localized spikes in low-density (LD-EEG) and high-density (HD-EEG) electroencephalography as well as magnetoencephalography (MEG) recordings using dipoles from 11 pediatric patients. We computed each dipole's level of clustering and used it to discriminate between clustered and scattered dipoles. For each dipole, we computed the distance from seizure onset zone (SOZ) and irritative zone (IZ) defined by intracranial EEG. Finally, we assessed whether dipoles proximity to resection was predictive of outcome. RESULTS LD-EEG had lower clusterness compared to HD-EEG and MEG (p < 0.05). For all modalities, clustered dipoles showed higher proximity to SOZ and IZ than scattered (p < 0.001). Resection percentage was higher in optimal vs. suboptimal outcome patients (p < 0.001); their proximity to resection was correlated to outcome (p < 0.001). No difference in resection percentage was seen for scattered dipoles between groups. CONCLUSION MSI and ESI dipole clustering helps to localize the SOZ and IZ and facilitate the prognostic assessment of MRI-negative patients with DRE. SIGNIFICANCE Assessing the MSI and ESI clustering allows recognizing epileptogenic areas whose removal is associated with optimal outcome.
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Affiliation(s)
- Georgios Ntolkeras
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Eleonora Tamilia
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michel AlHilani
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; The Hillingdon Hospital NHS Foundation Trust, London, United Kingdom
| | - Jeffrey Bolton
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - P Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Division of Neuroradiology, Department of Radiology, Boston Children's Hospital, Harvard Medical School, MA, USA
| | - Sanjay P Prabhu
- Division of Neuroradiology, Department of Radiology, Boston Children's Hospital, Harvard Medical School, MA, USA
| | - Joseph R Madsen
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Steven M Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Phillip L Pearl
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Christos Papadelis
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA; School of Medicine, Texas Christian University and University of North Texas Health Science Center, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA.
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36
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Ricci L, Matarrese M, Peters JM, Tamilia E, Madsen JR, Pearl PL, Papadelis C. Virtual implantation using conventional scalp EEG delineates seizure onset and predicts surgical outcome in children with epilepsy. Clin Neurophysiol 2022; 139:49-57. [PMID: 35526353 PMCID: PMC10026594 DOI: 10.1016/j.clinph.2022.04.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 04/04/2022] [Accepted: 04/08/2022] [Indexed: 11/16/2022]
Abstract
OBJECTIVE Delineation of the seizure onset zone (SOZ) is required in children with drug resistant epilepsy (DRE) undergoing neurosurgery. Intracranial EEG (icEEG) serves as gold standard but has limitations. Here, we examine the utility of virtual implantation with electrical source imaging (ESI) on ictal scalp EEG for mapping the SOZ and predict surgical outcome. METHODS We retrospectively analyzed EEG data from 35 children with DRE who underwent surgery and dichotomized into seizure-free (SF) and non-seizure-free (NSF). We estimated virtual sensors (VSs) at brain locations that matched icEEG implantation and compared ictal patterns at VSs vs icEEG. We calculated the agreement between VSs SOZ and clinically defined SOZ and built receiver operating characteristic (ROC) curves to test whether it predicted outcome. RESULTS Twenty-one patients were SF after surgery. Moderate agreement between virtual and icEEG patterns was observed (kappa = 0.45, p < 0.001). Virtual SOZ agreement with clinically defined SOZ was higher in SF vs NSF patients (66.6% vs 41.6%, p = 0.01). Anatomical concordance of virtual SOZ with clinically defined SOZ predicted outcome (AUC = 0.73; 95% CI: 0.57-0.89; sensitivity = 66.7%; specificity = 78.6%; accuracy = 71.4%). CONCLUSIONS Virtual implantation on ictal scalp EEG can approximate the SOZ and predict outcome. SIGNIFICANCE SOZ mapping with VSs may contribute to tailoring icEEG implantation and predict outcome.
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Affiliation(s)
- Lorenzo Ricci
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, University Campus Bio-Medico of Rome, Rome, Italy
| | - Margherita Matarrese
- Unit of Non-Linear Physics and Mathematical Modelling, Engineering Department, University Campus Bio-Medico of Rome, Rome, Italy; Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA
| | - Jurriaan M Peters
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Eleonora Tamilia
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Joseph R Madsen
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Phillip L Pearl
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Christos Papadelis
- Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA; School of Medicine, Texas Christian University, Fort Worth, TX, USA.
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Abdallah C, Hedrich T, Koupparis A, Afnan J, Hall JA, Gotman J, Dubeau F, von Ellenrieder N, Frauscher B, Kobayashi E, Grova C. Clinical Yield of Electromagnetic Source Imaging and Hemodynamic Responses in Epilepsy: Validation With Intracerebral Data. Neurology 2022; 98:e2499-e2511. [PMID: 35473762 PMCID: PMC9231837 DOI: 10.1212/wnl.0000000000200337] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 02/21/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Accurate delineation of the seizure-onset zone (SOZ) in focal drug-resistant epilepsy often requires stereo-EEG (SEEG) recordings. Our aims were to propose a truly objective and quantitative comparison between EEG/magnetoencephalography (MEG) source imaging (EMSI), EEG/fMRI responses for similar spikes with primary irritative zone (PIZ) and SOZ defined by SEEG and to evaluate the value of EMSI and EEG/fMRI to predict postsurgical outcome. METHODS We identified patients with drug-resistant epilepsy who underwent EEG/MEG, EEG/fMRI, and subsequent SEEG at the Epilepsy Service from the Montreal Neurological Institute and Hospital. We quantified multimodal concordance within the SEEG channel space as spatial overlap with PIZ/SOZ and distances to the spike-onset, spike maximum amplitude and seizure core intracerebral channels by applying a new methodology consisting of converting EMSI results into SEEG electrical potentials (EMSIe-SEEG) and projecting the most significant fMRI response on the SEEG channels (fMRIp-SEEG). Spatial overlaps with PIZ/SOZ (AUCPIZ, AUCSOZ) were assessed by using the area under the receiver operating characteristic curve (AUC). Here, AUC represents the probability that a randomly picked active contact exhibited higher amplitude when located inside the spatial reference than outside. RESULTS Seventeen patients were included. Mean spatial overlaps with the PIZ and SOZ were 0.71 and 0.65 for EMSIe-SEEG and 0.57 and 0.62 for fMRIp-SEEG. Good EMSIe-SEEG spatial overlap with the PIZ was associated with smaller distance from the maximum EMSIe-SEEG contact to the spike maximum amplitude channel (median distance 14 mm). Conversely, good fMRIp-SEEG spatial overlap with the SOZ was associated with smaller distances from the maximum fMRIp-SEEG contact to the spike-onset and seizure core channels (median distances 10 and 5 mm, respectively). Surgical outcomes were correctly predicted by EEG/MEG in 12 of 15 (80%) patients and EEG/fMRI in 6 of 11(54%) patients. DISCUSSION With the use of a unique quantitative approach estimating EMSI and fMRI results in the reference SEEG channel space, EEG/MEG and EEG/fMRI accurately localized the SOZ and the PIZ. Precisely, EEG/MEG more accurately localized the PIZ, whereas EEG/fMRI was more sensitive to the SOZ. Both neuroimaging techniques provide complementary localization that can help guide SEEG implantation and select good candidates for surgery.
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Affiliation(s)
- Chifaou Abdallah
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada.
| | - Tanguy Hedrich
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Andreas Koupparis
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Jawata Afnan
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Jeffrey Alan Hall
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Jean Gotman
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Francois Dubeau
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Nicolas von Ellenrieder
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Birgit Frauscher
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Eliane Kobayashi
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
| | - Christophe Grova
- From the Multimodal Functional Imaging Lab (C.A., T.H., J.A., C.G.), Biomedical Engineering Department, Montreal Neurological Institute and Hospital (C.A., A.K., J.A., J.A.H., J.G., F.D., N.v.E., B.F., E.K., C.G.), Neurology and Neurosurgery Department, and Analytical Neurophysiology Lab (T.H., B.F.), McGill University; and Multimodal Functional Imaging Lab (C.G.), PERFORM Centre, Department of Physics, Concordia University, Montreal, Quebec, Canada
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Toledano R, Martínez-Alvarez R, Jiménez-Huete A, García-Morales I, Aledo-Serrano Á, Cabrera W, Rey G, Campo P, Gómez-Angulo JC, Blumcke I, Álvarez-Linera J, Del Pozo JM, Gil-Nagel A. Stereoelectroencephalography in the preoperative assessment of patients with refractory focal epilepsy: experience at an epilepsy centre. NEUROLOGÍA (ENGLISH EDITION) 2022; 37:334-345. [PMID: 35672120 DOI: 10.1016/j.nrleng.2019.05.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 05/20/2019] [Indexed: 10/21/2022] Open
Abstract
OBJECTIVE Stereoelectroencephalography (SEEG) is a technique for preoperative evaluation of patients with difficult-to-localise refractory focal epilepsy (DLRFE), enabling the study of deep cortical structures. The procedure, which is increasingly used in international epilepsy centres, has not been fully developed in Spain. We describe our experience with SEEG in the preoperative evaluation of DLRFE. MATERIAL AND METHODS In the last 8 years, 71 patients with DLRFE were evaluated with SEEG in our epilepsy centre. We prospectively analysed our results in terms of localisation of the epileptogenic zone (EZ), surgical outcomes, and complications associated with the procedure. RESULTS The median age of the sample was 30 years (range, 4-59 years); 27 patients (38%) were women. Forty-five patients (63.4%) showed no abnormalities on brain MR images. A total of 627 electrodes were implanted (median, 9 electrodes per patient; range, 1-17), and 50% of implantations were multilobar. The EZ was identified in 64 patients (90.1%), and was extratemporal or temporal plus in 66% of the cases. Follow-up was over one year in 55 of the 61 patients undergoing surgery: in the last year of follow-up, 58.2% were seizure-free (Engel Epilepsy Surgery Outcome Scale class I) and 76.4% had good outcomes (Engel I-II). Three patients (4.2%) presented brain haemorrhages. CONCLUSION SEEG enables localisation of the EZ in patients in whom this was previously impossible, offering better surgical outcomes than other invasive techniques while having a relatively low rate of complications.
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Affiliation(s)
- R Toledano
- Programa de Epilepsia, Servicio de Neurología, Hospital Ruber Internacional, Madrid, Spain; Programa de Epilepsia, Servicio de Neurología, Hospital Universitario Ramón y Cajal, Madrid, Spain.
| | - R Martínez-Alvarez
- Servicio de Neurocirugía Funcional y Radiocirugía, Hospital Ruber Internacional, Madrid, Spain
| | - A Jiménez-Huete
- Servicio de Neurología, Hospital Ruber Internacional, Madrid, Spain
| | - I García-Morales
- Programa de Epilepsia, Servicio de Neurología, Hospital Ruber Internacional, Madrid, Spain; Programa de Epilepsia, Servicio de Neurología, Hospital Clínico San Carlos, Madrid, Spain
| | - Á Aledo-Serrano
- Programa de Epilepsia, Servicio de Neurología, Hospital Ruber Internacional, Madrid, Spain
| | - W Cabrera
- Departamento de Anatomía y Embriología, Universidad Complutense de Madrid, Spain
| | - G Rey
- Servicio de Física Médica y Protección Radiológica, Hospital Ruber Internacional, Madrid, Spain
| | - P Campo
- Departamento de Psicología Básica, Universidad Autónoma de Madrid, Spain
| | - J C Gómez-Angulo
- Servicio de Neurocirugía, Hospital Universitario de Getafe, Spain; Servicio de Neurocirugía, Hospital Ruber Internacional, Madrid, Spain
| | - I Blumcke
- Institute of Neuropathology, University Hospital Erlangen, Erlangen, Alemania
| | - J Álvarez-Linera
- Servicio de Neuroradiología, Hospital Ruber Internacional, Madrid, Spain
| | - J M Del Pozo
- Servicio de Neurocirugía, Hospital Ruber Internacional, Madrid, Spain
| | - A Gil-Nagel
- Programa de Epilepsia, Servicio de Neurología, Hospital Ruber Internacional, Madrid, Spain
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Toledano R, Martínez-Álvarez R, Jiménez-Huete A, García-Morales I, Aledo-Serrano Á, Cabrera W, Rey G, Campo P, Gómez-Angulo JC, Blumcke I, Álvarez-Linera J, Del Pozo JM, Gil-Nagel A. Stereoelectroencephalography in the preoperative assessment of patients with refractory focal epilepsy: Experience at an epilepsy centre. Neurologia 2022; 37:334-345. [PMID: 31337558 DOI: 10.1016/j.nrl.2019.05.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Revised: 05/02/2019] [Accepted: 05/20/2019] [Indexed: 11/30/2022] Open
Abstract
OBJECTIVE Stereoelectroencephalography (SEEG) is a technique for preoperative evaluation of patients with difficult-to-localise refractory focal epilepsy (DLRFE), enabling the study of deep cortical structures. The procedure, which is increasingly used in international epilepsy centres, has not been fully developed in Spain. We describe our experience with SEEG in the preoperative evaluation of DLRFE. MATERIAL AND METHODS In the last 8 years, 71 patients with DLRFE were evaluated with SEEG in our epilepsy centre. We prospectively analysed our results in terms of localisation of the epileptogenic zone (EZ), surgical outcomes, and complications associated with the procedure. RESULTS The median age of the sample was 30 years (range, 4-59 years); 27 patients (38%) were women. Forty-five patients (63.4%) showed no abnormalities on brain MR images. A total of 627 electrodes were implanted (median, 9 electrodes per patient; range, 1-17), and 50% of implantations were multilobar. The EZ was identified in 64 patients (90.1%), and was extratemporal or temporal plus in 66% of the cases. Follow-up was over one year in 55 of the 61 patients undergoing surgery: in the last year of follow-up, 58.2% were seizure-free (Engel Epilepsy Surgery Outcome Scale class I) and 76.4% had good outcomes (Engel I-II). Three patients (4.2%) presented brain haemorrhages. CONCLUSION SEEG enables localisation of the EZ in patients in whom this was previously impossible, offering better surgical outcomes than other invasive techniques while having a relatively low rate of complications.
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Affiliation(s)
- R Toledano
- Programa de Epilepsia, Servicio de Neurología, Hospital Ruber Internacional, Madrid, España; Programa de Epilepsia, Servicio de Neurología, Hospital Universitario Ramón y Cajal, Madrid, España.
| | - R Martínez-Álvarez
- Servicio de Neurocirugía Funcional y Radiocirugía, Hospital Ruber Internacional, Madrid, España
| | - A Jiménez-Huete
- Servicio de Neurología, Hospital Ruber Internacional, Madrid, España
| | - I García-Morales
- Programa de Epilepsia, Servicio de Neurología, Hospital Ruber Internacional, Madrid, España; Programa de Epilepsia, Servicio de Neurología, Hospital Clínico San Carlos, Madrid, España
| | - Á Aledo-Serrano
- Programa de Epilepsia, Servicio de Neurología, Hospital Ruber Internacional, Madrid, España
| | - W Cabrera
- Departamento de Anatomía y Embriología, Universidad Complutense de Madrid, España
| | - G Rey
- Servicio de Física Médica y Protección Radiológica, Hospital Ruber Internacional, Madrid, España
| | - P Campo
- Departamento de Psicología Básica, Universidad Autónoma de Madrid, España
| | - J C Gómez-Angulo
- Servicio de Neurocirugía, Hospital Universitario de Getafe, España; Servicio de Neurocirugía, Hospital Ruber Internacional, Madrid, España
| | - I Blumcke
- Institute of Neuropathology, University Hospital Erlangen, Erlangen, Alemania
| | - J Álvarez-Linera
- Servicio de Neurorradiología, Hospital Ruber Internacional, Madrid, España
| | - J M Del Pozo
- Servicio de Neurocirugía, Hospital Ruber Internacional, Madrid, España
| | - A Gil-Nagel
- Programa de Epilepsia, Servicio de Neurología, Hospital Ruber Internacional, Madrid, España
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Poghosyan V, Rampp S, Wang ZI. Editorial: Magnetoencephalography (MEG) in Epilepsy and Neurosurgery. Front Hum Neurosci 2022; 16:873153. [PMID: 35360284 PMCID: PMC8963912 DOI: 10.3389/fnhum.2022.873153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 02/17/2022] [Indexed: 11/13/2022] Open
Affiliation(s)
- Vahe Poghosyan
- Department of Neurophysiology, National Neuroscience Institute, King Fahad Medical City, Riyadh, Saudi Arabia
- *Correspondence: Vahe Poghosyan
| | - Stefan Rampp
- Department of Neurosurgery, University Hospital Erlangen, Erlangen, Germany
- Department of Neurosurgery, University Hospital Halle (Saale), Halle (Saale), Germany
| | - Zhong Irene Wang
- Charles Shor Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
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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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Validating EEG, MEG and Combined MEG and EEG Beamforming for an Estimation of the Epileptogenic Zone in Focal Cortical Dysplasia. Brain Sci 2022; 12:brainsci12010114. [PMID: 35053857 PMCID: PMC8796031 DOI: 10.3390/brainsci12010114] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 01/04/2022] [Accepted: 01/06/2022] [Indexed: 02/04/2023] Open
Abstract
MEG and EEG source analysis is frequently used for the presurgical evaluation of pharmacoresistant epilepsy patients. The source localization of the epileptogenic zone depends, among other aspects, on the selected inverse and forward approaches and their respective parameter choices. In this validation study, we compare the standard dipole scanning method with two beamformer approaches for the inverse problem, and we investigate the influence of the covariance estimation method and the strength of regularization on the localization performance for EEG, MEG, and combined EEG and MEG. For forward modelling, we investigate the difference between calibrated six-compartment and standard three-compartment head modelling. In a retrospective study, two patients with focal epilepsy due to focal cortical dysplasia type IIb and seizure freedom following lesionectomy or radiofrequency-guided thermocoagulation (RFTC) used the distance of the localization of interictal epileptic spikes to the resection cavity resp. RFTC lesion as reference for good localization. We found that beamformer localization can be sensitive to the choice of the regularization parameter, which has to be individually optimized. Estimation of the covariance matrix with averaged spike data yielded more robust results across the modalities. MEG was the dominant modality and provided a good localization in one case, while it was EEG for the other. When combining the modalities, the good results of the dominant modality were mostly not spoiled by the weaker modality. For appropriate regularization parameter choices, the beamformer localized better than the standard dipole scan. Compared to the importance of an appropriate regularization, the sensitivity of the localization to the head modelling was smaller, due to similar skull conductivity modelling and the fixed source space without orientation constraint.
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Zillgitt A, Haykal MA, Elisevich K, Patra S, Sherburn F, Bowyer SM, Burdette DE. Magnetoencephalography-identified preictal spiking correlates to preictal spiking on stereotactic EEG. Epilepsy Behav Rep 2022; 19:100538. [PMID: 35573060 PMCID: PMC9095747 DOI: 10.1016/j.ebr.2022.100538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 03/20/2022] [Accepted: 03/21/2022] [Indexed: 11/01/2022] Open
Abstract
Ictal MEG can assist in sEEG implantation strategy and may improve surgical outcome. Preictal spiking is a seizure onset pattern that has been described with intracranial EEG, but preictal spiking can also be an ictal pattern on MEG. MEG-predominant or MEG-unique preictal spiking may represent neuronal hypersynchronization arising from a tangential source.
Magnetoencephalography (MEG) is a noninvasive diagnostic modality that directly measures neuronal signaling by recording the magnetic field created from dendritic, intracellular, electrical currents of the neuron at the surface of the head. In clinical practice, MEG is used in the epilepsy presurgical evaluation and most commonly is an “interictal” study that can provide source localization of spike-wave discharges. However, seizures may be recorded during MEG (“ictal MEG”) and mapping of these discharges may provide more accurate localization of the seizure onset zone. In addition, spike-negative EEG with unique MEG spike-waves may be present in up to 1/3 of MEG studies and unique MEG seizures (EEG-negative seizures) have been reported. This case report describes a patient with unique MEG seizures that exhibited MEG pre-ictal spiking in a tight cluster consistent with the independent interictal epileptiform activity. Stereotactic EEG demonstrated pre-ictal spiking concordant with the MEG pre-ictal spiking.
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Laohathai C, Ebersole JS, Mosher JC, Bagić AI, Sumida A, Von Allmen G, Funke ME. Practical Fundamentals of Clinical MEG Interpretation in Epilepsy. Front Neurol 2021; 12:722986. [PMID: 34721261 PMCID: PMC8551575 DOI: 10.3389/fneur.2021.722986] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 09/06/2021] [Indexed: 11/29/2022] Open
Abstract
Magnetoencephalography (MEG) is a neurophysiologic test that offers a functional localization of epileptic sources in patients considered for epilepsy surgery. The understanding of clinical MEG concepts, and the interpretation of these clinical studies, are very involving processes that demand both clinical and procedural expertise. One of the major obstacles in acquiring necessary proficiency is the scarcity of fundamental clinical literature. To fill this knowledge gap, this review aims to explain the basic practical concepts of clinical MEG relevant to epilepsy with an emphasis on single equivalent dipole (sECD), which is one the most clinically validated and ubiquitously used source localization method, and illustrate and explain the regional topology and source dynamics relevant for clinical interpretation of MEG-EEG.
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Affiliation(s)
- Christopher Laohathai
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School at UTHealth, Houston, TX, United States
- Department of Neurology, Saint Louis University, Saint Louis, MO, United States
| | - John S. Ebersole
- Northeast Regional Epilepsy Group, Atlantic Health Neuroscience Institute, Summit, NJ, United States
| | - John C. Mosher
- Department of Neurology, McGovern Medical School at UTHealth, Houston, TX, United States
| | - Anto I. Bagić
- University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), Department of Neurology, University of Pittsburgh Medical Center, Pittsburg, PA, United States
| | - Ai Sumida
- Department of Neurology, McGovern Medical School at UTHealth, Houston, TX, United States
| | - Gretchen Von Allmen
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School at UTHealth, Houston, TX, United States
| | - Michael E. Funke
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School at UTHealth, Houston, TX, United States
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Fitzgerald Z, Morita-Sherman M, Hogue O, Joseph B, Alvim MKM, Yasuda CL, Vegh D, Nair D, Burgess R, Bingaman W, Najm I, Kattan MW, Blumcke I, Worrell G, Brinkmann BH, Cendes F, Jehi L. Improving the prediction of epilepsy surgery outcomes using basic scalp EEG findings. Epilepsia 2021; 62:2439-2450. [PMID: 34338324 PMCID: PMC8488002 DOI: 10.1111/epi.17024] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 06/15/2021] [Accepted: 07/15/2021] [Indexed: 12/23/2022]
Abstract
OBJECTIVE This study aims to evaluate the role of scalp electroencephalography (EEG; ictal and interictal patterns) in predicting resective epilepsy surgery outcomes. We use the data to further develop a nomogram to predict seizure freedom. METHODS We retrospectively reviewed the scalp EEG findings and clinical data of patients who underwent surgical resection at three epilepsy centers. Using both EEG and clinical variables categorized into 13 isolated candidate predictors and 6 interaction terms, we built a multivariable Cox proportional hazards model to predict seizure freedom 2 years after surgery. Harrell's step-down procedure was used to sequentially eliminate the least-informative variables from the model until the change in the concordance index (c-index) with variable removal was less than 0.01. We created a separate model using only clinical variables. Discrimination of the two models was compared to evaluate the role of scalp EEG in seizure-freedom prediction. RESULTS Four hundred seventy patient records were analyzed. Following internal validation, the full Clinical + EEG model achieved an optimism-corrected c-index of 0.65, whereas the c-index of the model without EEG data was 0.59. The presence of focal to bilateral tonic-clonic seizures (FBTCS), high preoperative seizure frequency, absence of hippocampal sclerosis, and presence of nonlocalizable seizures predicted worse outcome. The presence of FBTCS had the largest impact for predicting outcome. The analysis of the models' interactions showed that in patients with unilateral interictal epileptiform discharges (IEDs), temporal lobe surgery cases had a better outcome. In cases with bilateral IEDs, abnormal magnetic resonance imaging (MRI) predicted worse outcomes, and in cases without IEDs, patients with extratemporal epilepsy and abnormal MRI had better outcomes. SIGNIFICANCE This study highlights the value of scalp EEG, particularly the significance of IEDs, in predicting surgical outcome. The nomogram delivers an individualized prediction of postoperative outcome, and provides a unique assessment of the relationship between the outcome and preoperative findings.
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Affiliation(s)
| | | | - Olivia Hogue
- Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Boney Joseph
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | - Deborah Vegh
- Epilepsy Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Dileep Nair
- Epilepsy Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Richard Burgess
- Epilepsy Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - William Bingaman
- Epilepsy Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Imad Najm
- Epilepsy Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Michael W. Kattan
- Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Ingmar Blumcke
- Institute of Neuropathology, University Hospitals Erlangen, Erlangen, Germany
| | - Gregory Worrell
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Fernando Cendes
- Department of Neurology, University of Campinas, Campinas, Brazil
| | - Lara Jehi
- Epilepsy Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA
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Papadelis C, Perry MS. Localizing the Epileptogenic Zone with Novel Biomarkers. Semin Pediatr Neurol 2021; 39:100919. [PMID: 34620466 PMCID: PMC8501232 DOI: 10.1016/j.spen.2021.100919] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 08/09/2021] [Accepted: 08/11/2021] [Indexed: 01/01/2023]
Abstract
Several noninvasive methods, such as high-density EEG or magnetoencephalography, are currently used to delineate the epileptogenic zone (EZ) during the presurgical evaluation of patients with drug resistant epilepsy (DRE). Yet, none of these methods can reliably identify the EZ by their own. In most cases a multimodal approach is needed. Challenging cases often require the implantation of intracranial electrodes, either through stereo-taxic EEG or electro-corticography. Recently, a growing body of literature introduces novel biomarkers of epilepsy that can be used for analyzing both invasive as well as noninvasive electrophysiological data. Some of these biomarkers are able to delineate the EZ with high precision, augment the presurgical evaluation, and predict the surgical outcome of patients with DRE undergoing surgery. However, the use of these epilepsy biomarkers in clinical practice is limited. Here, we summarize and discuss the latest technological advances in the presurgical neurophysiological evaluation of children with DRE with emphasis on electric and magnetic source imaging, high frequency oscillations, and functional connectivity.
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Affiliation(s)
- Christos Papadelis
- Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX; School of Medicine, Texas Christian University and University of North Texas Health Science Center, Fort Worth, TX; Department of Bioengineering, University of Texas at Arlington, Arlington, TX; Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA.
| | - M Scott Perry
- Jane and John Justin Neurosciences Center, Cook Children’s Health Care System, Fort Worth, TX, USA
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Individual localization value of resting-state fMRI in epilepsy presurgical evaluation: A combined study with stereo-EEG. Clin Neurophysiol 2021; 132:3197-3206. [PMID: 34538574 DOI: 10.1016/j.clinph.2021.07.028] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 06/30/2021] [Accepted: 07/21/2021] [Indexed: 02/08/2023]
Abstract
OBJECTIVE To examine the individual-patient-level localization value of resting-state functional MRI (rsfMRI) metrics for the seizure onset zone (SOZ) defined by stereo-electroencephalography (SEEG) in patients with medically intractable focal epilepsies. METHODS We retrospectively included 19 patients who underwent SEEG implantation for epilepsy presurgical evaluation. Voxel-wise whole-brain analysis was performed on 3.0 T rsfMRI to generate clusters for amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo) and degree centrality (DC), which were co-registered with the SEEG-defined SOZ to evaluate their spatial overlap. Subgroup and correlation analyses were conducted for various clinical characteristics. RESULTS ALFF demonstrated concordant clusters with SEEG-defined SOZ in 73.7% of patients, with 93.3% sensitivity and 77.8% PPV. The concordance rate showed no significant difference when subgrouped by lesional/non-lesional MRI, SOZ location, interictal epileptiform discharges on scalp EEG, pathology or seizure outcomes. No significant correlation was seen between ALFF concordance rate and epilepsy duration, seizure-onset age, seizure frequency or number of antiseizure medications. ReHo and DC did not achieve favorable concordance results (10.5% and 15.8%, respectively). All concordant clusters showed regional activation, representing increased neural activities. CONCLUSION ALFF had high concordance rate with SEEG-defined SOZ at individual-patient level. SIGNIFICANCE ALFF activation on rsfMRI can add localizing information for the noninvasive presurgical workup of intractable focal epilepsies.
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Jin L, Choi JY, Bulacio J, Alexopoulos AV, Burgess RC, Murakami H, Bingaman W, Najm I, Wang ZI. Multimodal Image Integration for Epilepsy Presurgical Evaluation: A Clinical Workflow. Front Neurol 2021; 12:709400. [PMID: 34421808 PMCID: PMC8372749 DOI: 10.3389/fneur.2021.709400] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 06/25/2021] [Indexed: 12/02/2022] Open
Abstract
Multimodal image integration (MMII) is a promising tool to help delineate the epileptogenic zone (EZ) in patients with medically intractable focal epilepsies undergoing presurgical evaluation. We report here the detailed methodology of MMII and an overview of the utility of MMII at the Cleveland Clinic Epilepsy Center from 2014 to 2018, exemplified by illustrative cases. The image integration was performed using the Curry platform (Compumedics Neuroscan™, Charlotte, NC, USA), including all available diagnostic modalities such as Magnetic resonance imaging (MRI), Positron Emission Tomography (PET), single-photon emission computed tomography (SPECT) and Magnetoencephalography (MEG), with additional capability of trajectory planning for intracranial EEG (ICEEG), particularly stereo-EEG (SEEG), as well as surgical resection planning. In the 5-year time span, 467 patients underwent MMII; of them, 98 patients (21%) had a history of prior neurosurgery and recurring seizures. Of the 467 patients, 425 patients underwent ICEEG implantation with further CT co-registration to identify the electrode locations. A total of 351 patients eventually underwent surgery after MMII, including 197 patients (56%) with non-lesional MRI and 223 patients (64%) with extra-temporal lobe epilepsy. Among 269 patients with 1-year post-operative follow up, 134 patients (50%) had remained completely seizure-free. The most common histopathological finding is focal cortical dysplasia. Our study illustrates the usefulness of MMII to enhance SEEG electrode trajectory planning, assist non-invasive/invasive data interpretation, plan resection strategy, and re-evaluate surgical failures. Information presented by MMII is essential to the understanding of the anatomo-functional-electro-clinical correlations in individual cases, which leads to the ultimate success of presurgical evaluation of patients with medically intractable focal epilepsies.
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Affiliation(s)
- Liri Jin
- Department of Neurology, Peking Union Medical College Hospital, Beijing, China.,Epilepsy Center, Cleveland Clinic, Cleveland, OH, United States
| | - Joon Yul Choi
- Epilepsy Center, Cleveland Clinic, Cleveland, OH, United States
| | - Juan Bulacio
- Epilepsy Center, Cleveland Clinic, Cleveland, OH, United States
| | | | | | | | - William Bingaman
- Department of Neurosurgery, Cleveland Clinic, Cleveland, OH, United States
| | - Imad Najm
- Epilepsy Center, Cleveland Clinic, Cleveland, OH, United States
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Xu N, Shan W, Qi J, Wu J, Wang Q. Presurgical Evaluation of Epilepsy Using Resting-State MEG Functional Connectivity. Front Hum Neurosci 2021; 15:649074. [PMID: 34276321 PMCID: PMC8283278 DOI: 10.3389/fnhum.2021.649074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Accepted: 06/07/2021] [Indexed: 11/21/2022] Open
Abstract
Epilepsy is caused by abnormal electrical discharges (clinically identified by electrophysiological recording) in a specific part of the brain [originating in only one part of the brain, namely, the epileptogenic zone (EZ)]. Epilepsy is now defined as an archetypical hyperexcited neural network disorder. It can be investigated through the network analysis of interictal discharges, ictal discharges, and resting-state functional connectivity. Currently, there is an increasing interest in embedding resting-state connectivity analysis into the preoperative evaluation of epilepsy. Among the various neuroimaging technologies employed to achieve brain functional networks, magnetoencephalography (MEG) with the excellent temporal resolution is an ideal tool for estimating the resting-state connectivity between brain regions, which can reveal network abnormalities in epilepsy. What value does MEG resting-state functional connectivity offer for epileptic presurgical evaluation? Regarding this topic, this paper introduced the origin of MEG and the workflow of constructing source-space functional connectivity based on MEG signals. Resting-state functional connectivity abnormalities correlate with epileptogenic networks, which are defined by the brain regions involved in the production and propagation of epileptic activities. This paper reviewed the evidence of altered epileptic connectivity based on low- or high-frequency oscillations (HFOs) and the evidence of the advantage of using simultaneous MEG and intracranial electroencephalography (iEEG) recordings. More importantly, this review highlighted that MEG-based resting-state functional connectivity has the potential to predict postsurgical outcomes. In conclusion, resting-state MEG functional connectivity has made a substantial progress toward serving as a candidate biomarker included in epileptic presurgical evaluations.
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Affiliation(s)
- Na Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wei Shan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jing Qi
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jianping Wu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Qun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
- Beijing Institute of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neuromodulation, Beijing, China
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Watkins MW, Shah EG, Funke ME, Garcia-Tarodo S, Shah MN, Tandon N, Maestu F, Laohathai C, Sandberg DI, Lankford J, Thompson S, Mosher J, Von Allmen G. Indications for Inpatient Magnetoencephalography in Children - An Institution's Experience. Front Hum Neurosci 2021; 15:667777. [PMID: 34149382 PMCID: PMC8213217 DOI: 10.3389/fnhum.2021.667777] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Accepted: 04/14/2021] [Indexed: 11/13/2022] Open
Abstract
Magnetoencephalography (MEG) is recognized as a valuable non-invasive clinical method for localization of the epileptogenic zone and critical functional areas, as part of a pre-surgical evaluation for patients with pharmaco-resistant epilepsy. MEG is also useful in localizing functional areas as part of pre-surgical planning for tumor resection. MEG is usually performed in an outpatient setting, as one part of an evaluation that can include a variety of other testing modalities including 3-Tesla MRI and inpatient video-electroencephalography monitoring. In some clinical circumstances, however, completion of the MEG as an inpatient can provide crucial ictal or interictal localization data during an ongoing inpatient evaluation, in order to expedite medical or surgical planning. Despite well-established clinical indications for performing MEG in general, there are no current reports that discuss indications or considerations for completion of MEG on an inpatient basis. We conducted a retrospective institutional review of all pediatric MEGs performed between January 2012 and December 2020, and identified 34 cases where MEG was completed as an inpatient. We then reviewed all relevant medical records to determine clinical history, all associated diagnostic procedures, and subsequent treatment plans including epilepsy surgery and post-surgical outcomes. In doing so, we were able to identify five indications for completing the MEG on an inpatient basis: (1) super-refractory status epilepticus (SRSE), (2) intractable epilepsy with frequent electroclinical seizures, and/or frequent or repeated episodes of status epilepticus, (3) intractable epilepsy with infrequent epileptiform discharges on EEG or outpatient MEG, or other special circumstances necessitating inpatient monitoring for successful and safe MEG data acquisition, (4) MEG mapping of eloquent cortex or interictal spike localization in the setting of tumor resection or other urgent neurosurgical intervention, and (5) international or long-distance patients, where outpatient MEG is not possible or practical. MEG contributed to surgical decision-making in the majority of our cases (32 of 34). Our clinical experience suggests that MEG should be considered on an inpatient basis in certain clinical circumstances, where MEG data can provide essential information regarding the localization of epileptogenic activity or eloquent cortex, and be used to develop a treatment plan for surgical management of children with complicated or intractable epilepsy.
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Affiliation(s)
- Michael W Watkins
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School, Houston, TX, United States
| | - Ekta G Shah
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School, Houston, TX, United States
| | - Michael E Funke
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School, Houston, TX, United States.,Department of Neurology, McGovern Medical School, Houston, TX, United States
| | - Stephanie Garcia-Tarodo
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School, Houston, TX, United States.,Pediatric Neurology Unit, Children's Hospital, Geneva University Hospitals, Geneva, Switzerland
| | - Manish N Shah
- Department of Neurosurgery, McGovern Medical School, Houston, TX, United States.,Division of Pediatric Neurosurgery, Department of Pediatric Surgery, McGovern Medical School, Houston, TX, United States
| | - Nitin Tandon
- Department of Neurosurgery, McGovern Medical School, Houston, TX, United States
| | - Fernando Maestu
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School, Houston, TX, United States.,Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politecnica de Madrid, Madrid, Spain.,Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain
| | - Christopher Laohathai
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School, Houston, TX, United States
| | - David I Sandberg
- Department of Neurosurgery, McGovern Medical School, Houston, TX, United States.,Division of Pediatric Neurosurgery, Department of Pediatric Surgery, McGovern Medical School, Houston, TX, United States
| | - Jeremy Lankford
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School, Houston, TX, United States
| | - Stephen Thompson
- Department of Neurology, McGovern Medical School, Houston, TX, United States
| | - John Mosher
- Department of Neurology, McGovern Medical School, Houston, TX, United States
| | - Gretchen Von Allmen
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School, Houston, TX, United States.,Department of Neurology, McGovern Medical School, Houston, TX, United States
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