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Talami F, Lemieux L, Avanzini P, Ballerini A, Cantalupo G, Laufs H, Meletti S, Vaudano AE. The influence of wakefulness fluctuations on brain networks involved in centrotemporal spike occurrence. Clin Neurophysiol 2024; 164:47-56. [PMID: 38848666 DOI: 10.1016/j.clinph.2024.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 04/18/2024] [Accepted: 05/11/2024] [Indexed: 06/09/2024]
Abstract
OBJECTIVE Drowsiness has been implicated in the modulation of centro-temporal spikes (CTS) in Self-limited epilepsy with Centro-Temporal Spikes (SeLECTS). Here, we explore this relationship and whether fluctuations in wakefulness influence the brain networks involved in CTS generation. METHODS Functional MRI (fMRI) and electroencephalography (EEG) was simultaneously acquired in 25 SeLECTS. A multispectral EEG index quantified drowsiness ('EWI': EEG Wakefulness Index). EEG (Pearson Correlation, Cross Correlation, Trend Estimation, Granger Causality) and fMRI (PPI: psychophysiological interactions) analytic approaches were adopted to explore respectively: (a) the relationship between EWI and changes in CTS frequency and (b) the functional connectivity of the networks involved in CTS generation and wakefulness oscillations. EEG analyses were repeated on a sample of routine EEG from the same patient's cohort. RESULTS No correlation was found between EWI fluctuations and CTS density during the EEG-fMRI recordings, while they showed an anticorrelated trend when drowsiness was followed by proper sleep in routine EEG traces. According to PPI findings, EWI fluctuations modulate the connectivity between the brain networks engaged by CTS and the left frontal operculum. CONCLUSIONS While CTS frequency per se seems unrelated to drowsiness, wakefulness oscillations modulate the connectivity between CTS generators and key regions of the language circuitry, a cognitive function often impaired in SeLECTS. SIGNIFICANCE This work advances our understanding of (a) interaction between CTS occurrence and vigilance fluctuations and (b) possible mechanisms responsible for language disruption in SeLECTS.
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Affiliation(s)
- Francesca Talami
- Institute of Neuroscience, National Research Council of Italy, Parma, Italy; Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Louis Lemieux
- Department of Clinical and Experimental and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, Queen Square, London WC1N 3BG, United Kingdom
| | - Pietro Avanzini
- Institute of Neuroscience, National Research Council of Italy, Parma, Italy
| | - Alice Ballerini
- Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Gaetano Cantalupo
- Innovation Biomedicine Section, Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy; Child Neuropsychiatry Unit and Center for Research on Epilepsies in Pediatric age (CREP), University Hospital of Verona (full member of the European Reference Network EpiCARE), Verona, Italy
| | - Helmut Laufs
- University Medical Center Schleswig-Holstein, Christian-Albrechts-Universität zu Kiel, Germany
| | - Stefano Meletti
- Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurophysiology Unit and Epilepsy Centre, Neuroscience Department, AOU Modena, Italy.
| | - Anna Elisabetta Vaudano
- Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurophysiology Unit and Epilepsy Centre, Neuroscience Department, AOU Modena, Italy.
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Czarnetzki C, Spinelli L, Huppertz HJ, Schaller K, Momjian S, Lobrinus J, Vargas MI, Garibotto V, Vulliemoz S, Seeck M. Yield of non-invasive imaging in MRI-negative focal epilepsy. J Neurol 2024; 271:995-1003. [PMID: 37907727 PMCID: PMC10827933 DOI: 10.1007/s00415-023-11987-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 09/02/2023] [Accepted: 09/04/2023] [Indexed: 11/02/2023]
Abstract
OBJECTIVE The absence of MRI-lesion reduces considerably the probability of having an excellent outcome (International League Against Epilepsies [ILAE] class I-II) after epilepsy surgery. Surgical success in magnetic-resonance imaging (MRI)-negative cases relies therefore mainly on non-invasive techniques such as positron-emission tomography (PET), subtraction ictal/inter-ictal single-photon-emission-computed-tomography co-registered to MRI (SISCOM), electric source imaging (ESI) and morphometric MRI analysis (MAP). We were interested in identifying the optimal imaging technique or combination to achieve post-operative class I-II in patients with MRI-negative focal epilepsy. METHODS We identified 168 epileptic patients without MRI lesion. Thirty-three (19.6%) were diagnosed with unifocal epilepsy, underwent surgical resection and follow-up ⩾ 2 years. Sensitivity, specificity, predictive values, and diagnostic odds ratio (OR) were calculated for each technique individually and in combination (after co-registration). RESULTS 23/33 (70%) were free of disabling seizures (75.0% with temporal and 61.5% extratemporal lobe epilepsy). None of the individual modalities presented an OR > 1.5, except ESI if only patients with interictal epileptiform discharges (IEDs) were considered (OR 3.2). On a dual combination, SISCOM with ESI presented the highest outcome (OR = 6). MAP contributed to detecting indistinguishable focal cortical dysplasia in particular in extratemporal epilepsies with a sensitivity of 75%. Concordance of PET, ESI on interictal epileptic discharges, and SISCOM was associated with the highest chance for post-operative seizure control (OR = 11). CONCLUSION If MRI is negative, the chances to benefit from epilepsy surgery are almost as high as in lesional epilepsy, provided that multiple established non-invasive imaging tools are rigorously applied and co-registered together.
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Affiliation(s)
- Christian Czarnetzki
- EEG & Epilepsy Unit, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, University of Geneva, 4, Rue Gabrielle-Perret-Gentil, 1211, Geneva, Switzerland.
| | - Laurent Spinelli
- EEG & Epilepsy Unit, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, University of Geneva, 4, Rue Gabrielle-Perret-Gentil, 1211, Geneva, Switzerland
| | | | - Karl Schaller
- Department of Clinical Neurosciences, Neurosurgery Clinic, University Hospital of Geneva, Geneva, Switzerland
| | - Shahan Momjian
- Department of Clinical Neurosciences, Neurosurgery Clinic, University Hospital of Geneva, Geneva, Switzerland
| | - Johannes Lobrinus
- Department of Clinical Pathology, Faculty of Medicine, University Hospital of Geneva, Geneva, Switzerland
| | - Maria-Isabel Vargas
- Department of Radiology, Faculty of Medicine, University Hospital of Geneva, Geneva, Switzerland
| | - Valentina Garibotto
- Department of Radiology, Faculty of Medicine, University Hospital of Geneva, Geneva, Switzerland
| | - Serge Vulliemoz
- EEG & Epilepsy Unit, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, University of Geneva, 4, Rue Gabrielle-Perret-Gentil, 1211, Geneva, Switzerland
| | - Margitta Seeck
- EEG & Epilepsy Unit, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, University of Geneva, 4, Rue Gabrielle-Perret-Gentil, 1211, Geneva, Switzerland.
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Ikemoto S, Pana R, von Ellenrieder N, Gotman J. Electroencephalography-functional magnetic resonance imaging for clinical evaluation in focal epilepsy. Epilepsia Open 2024; 9:84-95. [PMID: 37724422 PMCID: PMC10839335 DOI: 10.1002/epi4.12829] [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: 04/13/2023] [Accepted: 08/27/2023] [Indexed: 09/20/2023] Open
Abstract
OBJECTIVE We aimed to evaluate the contribution of simultaneous recording of electroencephalography-functional magnetic resonance imaging (EEG-fMRI) in the diagnosis of epilepsy syndrome, localization of the epileptogenic zone (EZ), and decision-making regarding surgical treatment. METHODS We performed a retrospective study to evaluate patients with focal epilepsy who underwent EEG-fMRI. Two evaluators assessed epilepsy syndrome, presumed focus, and surgical candidacy and defined confidence levels. They assessed these clinical characteristics first without EEG-fMRI and then including EEG-fMRI to assess how the results of EEG-fMRI changed the evaluations. We also determined how the clinical evaluation was affected by the concordance level between the blood oxygen level-dependent (BOLD) response and the presumed focus location, and by the confidence level of the BOLD response itself based on the t-value of the primary and secondary clusters. RESULTS Fifty-one scans from 48 patients were included. The BOLD map affected 66.7% of the evaluations by altering evaluation items (epilepsy syndrome, presumed focus, or surgical candidacy) or their confidence levels. EEG-fMRI results increased the confidence levels of epilepsy syndrome, presumed focus, or surgical candidacy in 47.1% of patients but reduced clinical confidence in these features in 11.8%. More specifically, the confidence levels increased for epilepsy syndrome in 28.5%, identification of presumed focus in 33.9%, and determination of surgical candidacy in 29.4%. The BOLD signal confidence level, whether high or low, did not influence these clinical factors. SIGNIFICANCE Previous studies have emphasized the utility of EEG-fMRI for the localization of the epileptogenic zone. This study demonstrated the potential of EEG-fMRI to influence clinical confidence when determining epilepsy syndrome, the presumed epileptic focus, and surgical candidacy.
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Affiliation(s)
- Satoru Ikemoto
- Montreal Neurological Institute and HospitalMontrealQuebecCanada
- Department of PediatricsThe Jikei University School of MedicineMinato‐kuTokyoJapan
| | - Raluca Pana
- Montreal Neurological Institute and HospitalMontrealQuebecCanada
| | | | - Jean Gotman
- Montreal Neurological Institute and HospitalMontrealQuebecCanada
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Dangouloff-Ros V, Fillon L, Eisermann M, Losito E, Boisgontier J, Charpy S, Saitovitch A, Levy R, Roux CJ, Varlet P, Chiron C, Bourgeois M, Kaminska A, Blauwblomme T, Nabbout R, Boddaert N. Preoperative Detection of Subtle Focal Cortical Dysplasia in Children by Combined Arterial Spin Labeling, Voxel-Based Morphometry, Electroencephalography-Synchronized Functional MRI, Resting-State Regional Homogeneity, and 18F-fluorodeoxyglucose Positron Emission Tomography. Neurosurgery 2023; 92:820-826. [PMID: 36700754 DOI: 10.1227/neu.0000000000002310] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 09/29/2022] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Focal cortical dysplasia (FCD) causes drug-resistant epilepsy in children that can be cured surgically, but the lesions are often unseen by imaging. OBJECTIVE To assess the efficiency of arterial spin labeling (ASL), voxel-based-morphometry (VBM), fMRI electroencephalography (EEG), resting-state regional homogeneity (ReHo), 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET), and their combination in detecting pediatric FCD. METHODS We prospectively included 10 children for whom FCD was localized by surgical resection. They underwent 3T MR acquisition with concurrent EEG, including ASL perfusion, resting-state BOLD fMRI (allowing the processing of EEG-fMRI and ReHo), 3D T1-weighted images processed using VBM, and FDG PET-CT coregistered with MRI. Detection was assessed visually and by comparison with healthy controls (for ASL and VBM). RESULTS Eight children had normal MRI, and 2 had asymmetric sulci. Using MR techniques, FCD was accurately detected by ASL for 6/10, VBM for 5/10, EEG-fMRI for 5/8 (excluding 2 with uninterpretable results), and ReHo for 4/10 patients. The combination of ASL, VBM, and ReHo allowed correct FCD detection for 9/10 patients. FDG PET alone showed higher accuracy than the other techniques (7/9), and its combination with VBM allowed correct FCD detection for 8/9 patients. The detection efficiency was better for patients with asymmetric sulci (2/2 for all techniques), but advanced MR techniques and PET were useful for MR-negative patients (7/8). CONCLUSION A combination of multiple imaging techniques, including PET, ASL, and VBM analysis of T1-weighted images, is effective in detecting subtle FCD in children.
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Affiliation(s)
- Volodia Dangouloff-Ros
- Pediatric Radiology Department, AP-HP, Hôpital Universitaire Necker-Enfants Malades, Paris, France
- INSERM U1299, Université Paris Cité, Paris, France
- UMR 1163, Institut Imagine, Université Paris Cité, Paris, France
| | - Ludovic Fillon
- Pediatric Radiology Department, AP-HP, Hôpital Universitaire Necker-Enfants Malades, Paris, France
- INSERM U1299, Université Paris Cité, Paris, France
- UMR 1163, Institut Imagine, Université Paris Cité, Paris, France
| | - Monika Eisermann
- Department of Clinical Neurophysiology, Hôpital Universitaire Necker-Enfants Malades, AP-HP, Paris, France
- INSERM U 1163, Institut Imagine, Université Paris Cité, Paris, France
| | - Emma Losito
- INSERM U 1163, Institut Imagine, Université Paris Cité, Paris, France
- Pediatric Neurology Department, Reference Center for Rare Epilepsies, Hôpital Universitaire Necker-Enfants Malades, AP-HP, Paris, France
| | - Jennifer Boisgontier
- Pediatric Radiology Department, AP-HP, Hôpital Universitaire Necker-Enfants Malades, Paris, France
- INSERM U1299, Université Paris Cité, Paris, France
- UMR 1163, Institut Imagine, Université Paris Cité, Paris, France
| | - Sarah Charpy
- Pediatric Radiology Department, AP-HP, Hôpital Universitaire Necker-Enfants Malades, Paris, France
- INSERM U1299, Université Paris Cité, Paris, France
- UMR 1163, Institut Imagine, Université Paris Cité, Paris, France
| | - Ana Saitovitch
- Pediatric Radiology Department, AP-HP, Hôpital Universitaire Necker-Enfants Malades, Paris, France
- INSERM U1299, Université Paris Cité, Paris, France
- UMR 1163, Institut Imagine, Université Paris Cité, Paris, France
| | - Raphael Levy
- Pediatric Radiology Department, AP-HP, Hôpital Universitaire Necker-Enfants Malades, Paris, France
- INSERM U1299, Université Paris Cité, Paris, France
- UMR 1163, Institut Imagine, Université Paris Cité, Paris, France
| | - Charles-Joris Roux
- Pediatric Radiology Department, AP-HP, Hôpital Universitaire Necker-Enfants Malades, Paris, France
- INSERM U1299, Université Paris Cité, Paris, France
- UMR 1163, Institut Imagine, Université Paris Cité, Paris, France
| | - Pascale Varlet
- Neuropathology Department, GHU Paris, Université Paris Cité, Paris, France
| | - Catherine Chiron
- Pediatric Neurology Department, Reference Center for Rare Epilepsies, Hôpital Universitaire Necker-Enfants Malades, AP-HP, Paris, France
- Department of Nuclear Medicine, SHFJ-CEA, Orsay, France
- INSERM U1141, Paris, France
| | - Marie Bourgeois
- Pediatric Neurosurgery Department, AP-HP, Hôpital Universitaire Necker-Enfants Malades, Paris, France
| | - Anna Kaminska
- Department of Clinical Neurophysiology, Hôpital Universitaire Necker-Enfants Malades, AP-HP, Paris, France
- INSERM U 1163, Institut Imagine, Université Paris Cité, Paris, France
| | - Thomas Blauwblomme
- INSERM U 1163, Institut Imagine, Université Paris Cité, Paris, France
- Pediatric Neurosurgery Department, AP-HP, Hôpital Universitaire Necker-Enfants Malades, Paris, France
| | - Rima Nabbout
- INSERM U 1163, Institut Imagine, Université Paris Cité, Paris, France
- Pediatric Neurology Department, Reference Center for Rare Epilepsies, Hôpital Universitaire Necker-Enfants Malades, AP-HP, Paris, France
| | - Nathalie Boddaert
- Pediatric Radiology Department, AP-HP, Hôpital Universitaire Necker-Enfants Malades, Paris, France
- INSERM U1299, Université Paris Cité, Paris, France
- UMR 1163, Institut Imagine, Université Paris Cité, Paris, France
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Říha P, Doležalová I, Mareček R, Lamoš M, Bartoňová M, Kojan M, Mikl M, Gajdoš M, Vojtíšek L, Bartoň M, Strýček O, Pail M, Brázdil M, Rektor I. Multimodal combination of neuroimaging methods for localizing the epileptogenic zone in MR-negative epilepsy. Sci Rep 2022; 12:15158. [PMID: 36071087 PMCID: PMC9452535 DOI: 10.1038/s41598-022-19121-8] [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: 05/17/2022] [Accepted: 08/24/2022] [Indexed: 11/10/2022] Open
Abstract
The objective was to determine the optimal combination of multimodal imaging methods (IMs) for localizing the epileptogenic zone (EZ) in patients with MR-negative drug-resistant epilepsy. Data from 25 patients with MR-negative focal epilepsy (age 30 ± 10 years, 16M/9F) who underwent surgical resection of the EZ and from 110 healthy controls (age 31 ± 9 years; 56M/54F) were used to evaluate IMs based on 3T MRI, FDG-PET, HD-EEG, and SPECT. Patients with successful outcomes and/or positive histological findings were evaluated. From 38 IMs calculated per patient, 13 methods were selected by evaluating the mutual similarity of the methods and the accuracy of the EZ localization. The best results in postsurgical patients for EZ localization were found for ictal/ interictal SPECT (SISCOM), FDG-PET, arterial spin labeling (ASL), functional regional homogeneity (ReHo), gray matter volume (GMV), cortical thickness, HD electrical source imaging (ESI-HD), amplitude of low-frequency fluctuation (ALFF), diffusion tensor imaging, and kurtosis imaging. Combining IMs provides the method with the most accurate EZ identification in MR-negative epilepsy. The PET, SISCOM, and selected MRI-post-processing techniques are useful for EZ localization for surgical tailoring.
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Affiliation(s)
- Pavel Říha
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Irena Doležalová
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Radek Mareček
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Martin Lamoš
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Michaela Bartoňová
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Martin Kojan
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Michal Mikl
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Martin Gajdoš
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Lubomír Vojtíšek
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Marek Bartoň
- Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Ondřej Strýček
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Martin Pail
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Milan Brázdil
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Ivan Rektor
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic. .,Multimodal and Functional Neuroimaging Research Group, CEITEC-Central European Institute of Technology, Masaryk University, Brno, Czech Republic.
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Aslam S, Rajeshkannan R, Sandya CJ, Sarma M, Gopinath S, Pillai A. Statistical asymmetry analysis of volumetric MRI and FDG PET in temporal lobe epilepsy. Epilepsy Behav 2022; 134:108810. [PMID: 35802989 DOI: 10.1016/j.yebeh.2022.108810] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 06/01/2022] [Accepted: 06/20/2022] [Indexed: 11/16/2022]
Abstract
PURPOSE To analyze statistically derived threshold values of volumetric MRI and 18F fluorodeoxyglucose (FDG) PET asymmetry, independent of normative data, for non-invasive detection/exclusion of temporal lobe epilepsy (TLE). METHODS We retrospectively analyzed amygdalohippocampal volumetry and temporal FDG PET metabolism in 33 patients (age: 29.27 ± 8.56 years) who underwent surgery following Stereo-EEG implantation and had postsurgical seizure freedom lasting >12 months. The temporal lobe epilepsy group and the extratemporal lobe epilepsy (ETLE) group were compared. Percentage volume loss (PVL) was calculated from manually traced amygdalohippocampal volumetry whereas percentage metabolic loss (PML) was calculated from PET using amygdalohippocampal trace and temporal neocortical Brodmann areas (BA) template. RESULTS Receiver operating characteristic (ROC) curve analysis identified a cutoff hippocampal PVL of 4.21% as the minimum indicating probable hippocampal involvement in seizure onset, with sensitivity of 88.89% and the specificity of 100% (p < 0.001). Region of interest (ROI)-based PML values in PET imaging showed a significant correlation with the presence of TLE in the TLE group of patients and its absence in the ETLE group of patients. Region of interest curve analysis yielded PML cutoffs of 5.77% and 8.36%, respectively, for the hippocampus and BA 38 (temporopolar neocortex) to detect TLE with the sensitivity of 72.7% and specificity of 77.8%. CONCLUSION We describe statistical thresholds for asymmetry analysis of hippocampal volumetry and FDG PET to improve detection of TLE. These threshold parameters warrant further validation in prospective studies.
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Affiliation(s)
- Shameer Aslam
- Department of Neurology, Amrita Advanced Centre for Epilepsy, Amrita Institute of Medical Sciences & Research Center, Kochi, India
| | - Ramiah Rajeshkannan
- Department of Radiology, Amrita Advanced Centre for Epilepsy, Amrita Institute of Medical Sciences & Research Center, Kochi, India
| | - C J Sandya
- Department of Radiology, Amrita Advanced Centre for Epilepsy, Amrita Institute of Medical Sciences & Research Center, Kochi, India
| | - Manjit Sarma
- Department of Nuclear Medicine, Amrita Advanced Centre for Epilepsy, Amrita Institute of Medical Sciences & Research Center, Kochi, India
| | - Siby Gopinath
- Department of Neurology, Amrita Advanced Centre for Epilepsy, Amrita Institute of Medical Sciences & Research Center, Kochi, India
| | - Ashok Pillai
- Department of Neurosurgery, Amrita Advanced Centre for Epilepsy, Amrita Institute of Medical Sciences & Research Center, Kochi, India.
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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: 9] [Impact Index Per Article: 4.5] [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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8
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PET/MRI in the Presurgical Evaluation of Patients with Epilepsy: A Concordance Analysis. Biomedicines 2022; 10:biomedicines10050949. [PMID: 35625684 PMCID: PMC9138772 DOI: 10.3390/biomedicines10050949] [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: 03/07/2022] [Revised: 04/04/2022] [Accepted: 04/13/2022] [Indexed: 11/17/2022] Open
Abstract
The aim of our prospective study was to evaluate the clinical impact of hybrid [18F]-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging ([18F]-FDG PET/MRI) on the decision workflow of epileptic patients with discordant electroclinical and MRI data. A novel mathematical model was introduced for a clinical concordance calculation supporting the classification of our patients by subgroups of clinical decisions. Fifty-nine epileptic patients with discordant clinical and diagnostic results or MRI negativity were included in this study. The diagnostic value of the PET/MRI was compared to other modalities of presurgical evaluation (e.g., electroclinical data, PET, and MRI). The results of the population-level statistical analysis of the introduced data fusion technique and concordance analysis demonstrated that this model could be the basis for the development of a more accurate clinical decision support parameter in the future. Therefore, making the establishment of “invasive” (operable and implantable) and “not eligible for any further invasive procedures” groups could be much more exact. Our results confirmed the relevance of PET/MRI with the diagnostic algorithm of presurgical evaluation. The introduction of a concordance analysis could be of high importance in clinical and surgical decision-making in the management of epileptic patients. Our study corroborated previous findings regarding the advantages of hybrid PET/MRI technology over MRI and electroclinical data.
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9
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Abstract
PURPOSE OF REVIEW We review significant advances in epilepsy imaging in recent years. RECENT FINDINGS Structural MRI at 7T with optimization of acquisition and postacquisition image processing increases the diagnostic yield but artefactual findings remain a challenge. MRI analysis from multiple sites indicates different atrophy patterns and white matter diffusion abnormalities in temporal lobe and generalized epilepsies, with greater abnormalities close to the presumed seizure source. Structural and functional connectivity relate to seizure spread and generalization; longitudinal studies are needed to clarify the causal relationship of these associations. Diffusion MRI may help predict surgical outcome and network abnormalities extending beyond the epileptogenic zone. Three-dimensional multimodal imaging can increase the precision of epilepsy surgery, improve seizure outcome and reduce complications. Language and memory fMRI are useful predictors of postoperative deficits, and lead to risk minimization. FDG PET is useful for clinical studies and specific ligands probe the pathophysiology of neurochemical fluxes and receptor abnormalities. SUMMARY Improved structural MRI increases detection of abnormalities that may underlie epilepsy. Diffusion, structural and functional MRI indicate the widespread associations of epilepsy syndromes. These can assist stratification of surgical outcome and minimize risk. PET has continued utility clinically and for research into the pathophysiology of epilepsies.
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Affiliation(s)
- John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Karin Trimmel
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, UK
- Department of Neurology, Medical University of Vienna, Vienna, Austria
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10
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Cao M, Vogrin SJ, Peterson ADH, Woods W, Cook MJ, Plummer C. Dynamical Network Models From EEG and MEG for Epilepsy Surgery—A Quantitative Approach. Front Neurol 2022; 13:837893. [PMID: 35422755 PMCID: PMC9001937 DOI: 10.3389/fneur.2022.837893] [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: 12/17/2021] [Accepted: 03/01/2022] [Indexed: 11/16/2022] Open
Abstract
There is an urgent need for more informative quantitative techniques that non-invasively and objectively assess strategies for epilepsy surgery. Invasive intracranial electroencephalography (iEEG) remains the clinical gold standard to investigate the nature of the epileptogenic zone (EZ) before surgical resection. However, there are major limitations of iEEG, such as the limited spatial sampling and the degree of subjectivity inherent in the analysis and clinical interpretation of iEEG data. Recent advances in network analysis and dynamical network modeling provide a novel aspect toward a more objective assessment of the EZ. The advantage of such approaches is that they are data-driven and require less or no human input. Multiple studies have demonstrated success using these approaches when applied to iEEG data in characterizing the EZ and predicting surgical outcomes. However, the limitations of iEEG recordings equally apply to these studies—limited spatial sampling and the implicit assumption that iEEG electrodes, whether strip, grid, depth or stereo EEG (sEEG) arrays, are placed in the correct location. Therefore, it is of interest to clinicians and scientists to see whether the same analysis and modeling techniques can be applied to whole-brain, non-invasive neuroimaging data (from MRI-based techniques) and neurophysiological data (from MEG and scalp EEG recordings), thus removing the limitation of spatial sampling, while safely and objectively characterizing the EZ. This review aims to summarize current state of the art non-invasive methods that inform epilepsy surgery using network analysis and dynamical network models. We also present perspectives on future directions and clinical applications of these promising approaches.
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Affiliation(s)
- Miao Cao
- Center for MRI Research, Peking University, Beijing, China
- Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia
- Centre for Clinical Neurosciences and Neurological Research, St Vincent's Hospital Melbourne, Melbourne, VIC, Australia
| | - Simon J. Vogrin
- Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia
- Centre for Clinical Neurosciences and Neurological Research, St Vincent's Hospital Melbourne, Melbourne, VIC, Australia
- School of Health Sciences, Swinburne University of Technology, Melbourne, VIC, Australia
| | - Andre D. H. Peterson
- Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia
- Centre for Clinical Neurosciences and Neurological Research, St Vincent's Hospital Melbourne, Melbourne, VIC, Australia
| | - William Woods
- School of Health Sciences, Swinburne University of Technology, Melbourne, VIC, Australia
| | - Mark J. Cook
- Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia
- Centre for Clinical Neurosciences and Neurological Research, St Vincent's Hospital Melbourne, Melbourne, VIC, Australia
| | - Chris Plummer
- Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia
- Centre for Clinical Neurosciences and Neurological Research, St Vincent's Hospital Melbourne, Melbourne, VIC, Australia
- School of Health Sciences, Swinburne University of Technology, Melbourne, VIC, Australia
- *Correspondence: Chris Plummer
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11
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Comparison of Qualitative and Quantitative Analyses of MR-Arterial Spin Labeling Perfusion Data for the Assessment of Pediatric Patients with Focal Epilepsies. Diagnostics (Basel) 2022; 12:diagnostics12040811. [PMID: 35453858 PMCID: PMC9032819 DOI: 10.3390/diagnostics12040811] [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: 02/17/2022] [Revised: 03/17/2022] [Accepted: 03/23/2022] [Indexed: 12/07/2022] Open
Abstract
The role of MR Arterial-Spin-Labeling Cerebral Blood Flow maps (ASL-CBF) in the assessment of pediatric focal epilepsy is still debated. We aim to compare the Seizure Onset Zone (SOZ) detection rate of three methods of evaluation of ASL-CBF: 1) qualitative visual (qCBF), 2) z-score voxel-based quantitative analysis of index of asymmetry (AI-CBF), and 3) z-score voxel-based cluster analysis of the quantitative difference of patient’s CBF from the normative data of an age-matched healthy population (cCBF). Interictal ASL-CBF were acquired in 65 pediatric patients with focal epilepsy: 26 with focal brain lesions and 39 with a normal MRI. All hypoperfusion areas visible in at least 3 contiguous images of qCBF analysis were identified. In the quantitative evaluations, clusters with a significant z-score AI-CBF ≤ −1.64 and areas with a z-score cCBF ≤ −1.64 were considered potentially related to the SOZ. These areas were compared with the SOZ defined by the anatomo-electro-clinical data. In patients with a positive MRI, SOZ was correctly identified in 27% of patients using qCBF, 73% using AI-CBF, and 77% using cCBF. In negative MRI patients, SOZ was identified in 18% of patients using qCBF, in 46% using AI-CBF, and in 64% using cCBF (p < 0.001). Quantitative analyses of ASL-CBF maps increase the detection rate of SOZ compared to the qualitative method, principally in negative MRI patients.
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12
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Zhou H, Zhang W, Tan Z, Zhou Z, Li Y, Zhang S, Zhang L, Gan J, Wu H, Tang Y, Cheng Y, Ling X, Guo Q, Xu H. Localizing Epileptic Foci Before Surgery in Patients With MRI-Negative Refractory Epilepsy Using Statistical Parameter Mapping and Three-Dimensional Stereotactic Surface Projection Based on 18F-FDG PET. Front Bioeng Biotechnol 2022; 9:810890. [PMID: 35071215 PMCID: PMC8766976 DOI: 10.3389/fbioe.2021.810890] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 12/13/2021] [Indexed: 11/17/2022] Open
Abstract
Patients with refractory epilepsy are not only free of seizures after resecting epileptic foci, but also experience significantly improved quality of life. Fluorine-18-fluorodeoxyglucose positron-emission tomography (18F-FDG PET) is a promising avenue for detecting epileptic foci in patients with magnetic resonance imaging (MRI)-negative refractory epilepsy. However, the detection of epileptic foci by visual assessment based on 18F-FDG PET is often complicated by a variety of factors in clinical practice. Easy imaging methods based on 18F-FDG PET images, such as statistical parameter mapping (SPM) and three-dimensional stereotactic surface projection (3D-SSP), can objectively detect epileptic foci. In this study, the regions of surgical resection of patients with over 1 year follow-up and no seizures were defined as standard epileptic foci. We retrospectively analyzed the sensitivity of visual assessment, SPM and 3D-SSP based on 18F-FDG PET to detect epileptic foci in MRI-negative refractory epilepsy patients and obtained the sensitivities of visual assessment, SPM and 3D-SSP are 57, 70 and 60% respectively. Visual assessment combined with SPM or 3D-SSP can improve the sensitivity of detecting epileptic foci. The sensitivity was highest when the three methods were combined, but decreased consistency, in localizing epileptic foci. We conclude that SPM and 3D-SSP can be used as objective methods to detect epileptic foci before surgery in patients with MRI-negative refractory epilepsy. Visual assessment is the preferred method for PET image analysis in MRI-negative refractory epilepsy. When the visual assessment is inconsistent with the patient's electroclinical information, SPM or 3D-SSP was further selected to assess the epileptic foci. If the combination of the two methods still fails to accurately locate the epileptic foci, comprehensive evaluation can be performed by combining the three methods.
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Affiliation(s)
- Hailing Zhou
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Wei Zhang
- Epilepsy Center, Guangdong 999 Brain Hospital, Affiliated Brain Hospital of Jinan University, Guangzhou, China
| | - Zhiqiang Tan
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Ziqing Zhou
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Ying Li
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Shaojuan Zhang
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Lingling Zhang
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Jiefeng Gan
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Huanhua Wu
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Yongjin Tang
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Yong Cheng
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Xueying Ling
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Qiang Guo
- Epilepsy Center, Guangdong 999 Brain Hospital, Affiliated Brain Hospital of Jinan University, Guangzhou, China
| | - Hao Xu
- Department of Nuclear Medicine, PET/CT-MRI Center, Center of Cyclotron and PET Radiopharmaceuticals, The First Affiliated Hospital of Jinan University, Guangzhou, China
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13
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Kang L, Chen J, Huang J, Zhang T, Xu J. Identifying epilepsy based on machine-learning technique with diffusion kurtosis tensor. CNS Neurosci Ther 2021; 28:354-363. [PMID: 34939745 PMCID: PMC8841295 DOI: 10.1111/cns.13773] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Revised: 11/11/2021] [Accepted: 11/14/2021] [Indexed: 12/20/2022] Open
Abstract
Introduction Epilepsy is a serious hazard to human health. Minimally invasive surgery is an extremely effective treatment to refractory epilepsy currently if the location of epileptic foci is given. However, it is challenging to locate the epileptic foci since a multitude of patients are MRI‐negative. It is well known that DKI (diffusion kurtosis imaging) can analyze the pathological changes of local tissues and other regions of epileptic foci at the molecular level. In this article, we propose a new localization way for epileptic foci based on machine‐learning method with kurtosis tensor in DKI. Methods We recruited 59 children with hippocampus epilepsy and 70 age‐ and sex‐matched normal controls; their T1‐weighted images and DKI were collected simultaneously. Then, the hippocampus in DKI is segmented based on a mask as a local brain region, and DKE is utilized to estimate the kurtosis tensor of each subject's hippocampus. Finally, the kurtosis tensor is fed into SVM (support vector machine) to identify epilepsy. Results The classifier produced 95.24% accuracy for patient versus normal controls, which is higher than that obtained with FA (fractional anisotropy) and MK (mean kurtosis). Experimental results show that the kurtosis tensor is a kind of remarkable feature to identify epilepsy, which indicates that DKI images can act as an important biomarker for epilepsy from the view of clinical diagnosis. Conclusion Although the classification task for epileptic patients and normal controls discussed in this article did not directly achieve the location of epileptic foci and only identified epilepsy on certain brain region, the epileptic foci can be located with the results of identifying results on other brain regions.
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Affiliation(s)
- Li Kang
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China.,The Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China
| | - Jin Chen
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China.,The Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China
| | - Jianjun Huang
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China.,The Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China
| | - Tijiang Zhang
- The Affiliate Hospital of Zunyi Medical University, Zunyi, China
| | - Jiahui Xu
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China.,The Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China
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14
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Koupparis A, von Ellenrieder N, Khoo HM, Zazubovits N, Nguyen DK, Hall JA, Dudley RWR, Dubeau F, Gotman J. Association of EEG-fMRI Responses and Outcome After Epilepsy Surgery. Neurology 2021; 97:e1523-e1536. [PMID: 34400584 PMCID: PMC8575131 DOI: 10.1212/wnl.0000000000012660] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 08/04/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES To assess the utility of EEG-fMRI for epilepsy surgery, we evaluated surgical outcome in relation to the resection of the most significant EEG-fMRI response. METHODS Patients with postoperative neuroimaging and follow-up of at least 1 year were included. In EEG-fMRI responses, we defined as primary the cluster with the highest absolute t value located in the cortex and evaluated 3 levels of confidence for the results. The threshold for low confidence was t ≥ 3.1 (p < 0.005); the one for medium confidence corresponded to correction for multiple comparisons with a false discovery rate of 0.05; and a result reached high confidence when the primary cluster was much more significant than the next highest cluster. Concordance with the resection was determined by comparison to postoperative neuroimaging. RESULTS We evaluated 106 epilepsy surgeries in 84 patients. An increasing association between concordance and surgical outcome with higher levels of confidence was demonstrated. If the peak response was not resected, the surgical outcome was likely to be poor: for the high confidence level, no patient had a good outcome; for the medium and low levels, only 18% and 28% had a good outcome. The positive predictive value remained low for all confidence levels, indicating that removing the maximum cluster did not ensure seizure freedom. DISCUSSION Resection of the primary EEG-fMRI cluster, especially in high confidence cases, is necessary to obtain a good outcome but not sufficient. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that failure to resect the primary EEG-fMRI cluster is associated with poorer epilepsy surgery outcomes.
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Affiliation(s)
- Andreas Koupparis
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada.
| | - Nicolás von Ellenrieder
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
| | - Hui Ming Khoo
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
| | - Natalja Zazubovits
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
| | - Dang Khoa Nguyen
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
| | - Jeffery A Hall
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
| | - Roy W R Dudley
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
| | - Francois Dubeau
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
| | - Jean Gotman
- From the Montreal Neurological Institute and Hospital (A.K., N.v.E., N.Z., J.A.H., F.D. J.G.) and Montreal Children's Hospital (R.W.R.D.), McGill University, Quebec, Canada; Department of Neurosurgery (H.M.K.), Osaka University Graduate School of Medicine, Suita, Japan; and Division of Neurology (D.K.N.), Centre Hospitalier de l'Université de Montréal, 1000 Saint-Denis, Montreal, Quebec, Canada
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15
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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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Vaudano AE, Mirandola L, Talami F, Giovannini G, Monti G, Riguzzi P, Volpi L, Michelucci R, Bisulli F, Pasini E, Tinuper P, Di Vito L, Gessaroli G, Malagoli M, Pavesi G, Cardinale F, Tassi L, Lemieux L, Meletti S. fMRI-Based Effective Connectivity in Surgical Remediable Epilepsies: A Pilot Study. Brain Topogr 2021; 34:632-650. [PMID: 34152513 DOI: 10.1007/s10548-021-00857-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 06/13/2021] [Indexed: 11/24/2022]
Abstract
Simultaneous EEG-fMRI can contribute to identify the epileptogenic zone (EZ) in focal epilepsies. However, fMRI maps related to Interictal Epileptiform Discharges (IED) commonly show multiple regions of signal change rather than focal ones. Dynamic causal modeling (DCM) can estimate effective connectivity, i.e. the causal effects exerted by one brain region over another, based on fMRI data. Here, we employed DCM on fMRI data in 10 focal epilepsy patients with multiple IED-related regions of BOLD signal change, to test whether this approach can help the localization process of EZ. For each subject, a family of competing deterministic, plausible DCM models were constructed using IED as autonomous input at each node, one at time. The DCM findings were compared to the presurgical evaluation results and classified as: "Concordant" if the node identified by DCM matches the presumed focus, "Discordant" if the node is distant from the presumed focus, or "Inconclusive" (no statistically significant result). Furthermore, patients who subsequently underwent intracranial EEG recordings or surgery were considered as having an independent validation of DCM results. The effective connectivity focus identified using DCM was Concordant in 7 patients, Discordant in two cases and Inconclusive in one. In four of the 6 patients operated, the DCM findings were validated. Notably, the two Discordant and Invalidated results were found in patients with poor surgical outcome. Our findings provide preliminary evidence to support the applicability of DCM on fMRI data to investigate the epileptic networks in focal epilepsy and, particularly, to identify the EZ in complex cases.
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Affiliation(s)
- A E Vaudano
- Neurology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Via Giardini 1355, 41100, Modena, Italy. .,Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.
| | - L Mirandola
- Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - F Talami
- Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - G Giovannini
- Neurology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Via Giardini 1355, 41100, Modena, Italy.,Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - G Monti
- Neurology Unit, AUSL Modena, Ospedale Ramazzini, Carpi, MO, Italy
| | - P Riguzzi
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Unit of Neurology, Bellaria Hospital, Bologna, Italy
| | - L Volpi
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Unit of Neurology, Bellaria Hospital, Bologna, Italy
| | - R Michelucci
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Unit of Neurology, Bellaria Hospital, Bologna, Italy
| | - F Bisulli
- Department of Biomedical and NeuroMotor Sciences (DIBINEM), University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Epilepsy Center (Reference Center for Rare and Complex Epilepsies - EpiCARE), Bologna, Italy
| | - E Pasini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Unit of Neurology, Bellaria Hospital, Bologna, Italy
| | - P Tinuper
- Department of Biomedical and NeuroMotor Sciences (DIBINEM), University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Epilepsy Center (Reference Center for Rare and Complex Epilepsies - EpiCARE), Bologna, Italy
| | - L Di Vito
- Department of Biomedical and NeuroMotor Sciences (DIBINEM), University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Epilepsy Center (Reference Center for Rare and Complex Epilepsies - EpiCARE), Bologna, Italy
| | - G Gessaroli
- Neurology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Via Giardini 1355, 41100, Modena, Italy
| | - M Malagoli
- Neuroradiology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy
| | - G Pavesi
- Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.,Neurosurgery Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Modena, Italy
| | - F Cardinale
- "Claudio Munari" Epilepsy Surgery Center, Niguarda Hospital, Milan, Italy
| | - L Tassi
- "Claudio Munari" Epilepsy Surgery Center, Niguarda Hospital, Milan, Italy
| | - L Lemieux
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - S Meletti
- Neurology Unit, OCB Hospital, Azienda Ospedaliero-Universitaria of Modena, Via Giardini 1355, 41100, Modena, Italy.,Center for Neuroscience and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
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17
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Cohen N, Ebrahimi Y, Medvedovsky M, Gurevitch G, Aizenstein O, Hendler T, Fahoum F, Gazit T. Interictal Epileptiform Discharge Dynamics in Peri-sylvian Polymicrogyria Using EEG-fMRI. Front Neurol 2021; 12:658239. [PMID: 34149595 PMCID: PMC8212705 DOI: 10.3389/fneur.2021.658239] [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: 01/25/2021] [Accepted: 05/05/2021] [Indexed: 11/13/2022] Open
Abstract
Polymicrogyria (PMG) is a common malformation of cortical development associated with a higher susceptibility to epileptic seizures. Seizures secondary to PMG are characterized by difficult-to-localize cerebral sources due to the complex and widespread lesion structure. Tracing the dynamics of interictal epileptiform discharges (IEDs) in patients with epilepsy has been shown to reveal the location of epileptic activity sources, crucial for successful treatment in cases of focal drug-resistant epilepsy. In this case series IED dynamics were evaluated with simultaneous EEG-fMRI recordings in four patients with unilateral peri-sylvian polymicrogyria (PSPMG) by tracking BOLD activations over time: before, during and following IED appearance on scalp EEG. In all cases, focal BOLD activations within the lesion itself preceded the activity associated with the time of IED appearance on EEG, which showed stronger and more widespread activations. We therefore propose that early hemodynamic activity corresponding to IEDs may hold important localizing information potentially leading to the cerebral sources of epileptic activity. IEDs are suggested to develop within a small area in the PSPMG lesion with structural properties obscuring the appearance of their electric field on the scalp and only later engage widespread structures which allow the production of large currents which are recognized as IEDs on EEG.
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Affiliation(s)
- Noa Cohen
- Sagol Brain Institute, Wohl Institute for Advanced Imaging, Sourasky Medical Center, Tel Aviv, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Yoram Ebrahimi
- Sagol Brain Institute, Wohl Institute for Advanced Imaging, Sourasky Medical Center, Tel Aviv, Israel
| | - Mordekhay Medvedovsky
- Department of Neurology, Agnes Ginges Center of Neurogenetics, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Guy Gurevitch
- Sagol Brain Institute, Wohl Institute for Advanced Imaging, Sourasky Medical Center, Tel Aviv, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Orna Aizenstein
- Sagol Brain Institute, Wohl Institute for Advanced Imaging, Sourasky Medical Center, Tel Aviv, Israel.,Department of Diagnostic Imaging, Sourasky Medical Center, Tel Aviv, Israel
| | - Talma Hendler
- Sagol Brain Institute, Wohl Institute for Advanced Imaging, Sourasky Medical Center, Tel Aviv, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.,School of Psychological Science, Tel Aviv University, Tel Aviv, Israel.,Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Firas Fahoum
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.,Electroencephalography and Epilepsy Unit, Sourasky Medical Center, Tel Aviv, Israel
| | - Tomer Gazit
- Sagol Brain Institute, Wohl Institute for Advanced Imaging, Sourasky Medical Center, Tel Aviv, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
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18
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Sun K, Yu T, Yang D, Ren Z, Qiao L, Ni D, Wang X, Zhao Y, Chen X, Xiang J, Chen N, Gao R, Yang K, Lin Y, Kober T, Zhang G. Fluid and White Matter Suppression Imaging and Voxel-Based Morphometric Analysis in Conventional Magnetic Resonance Imaging-Negative Epilepsy. Front Neurol 2021; 12:651592. [PMID: 33995250 PMCID: PMC8116947 DOI: 10.3389/fneur.2021.651592] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 03/18/2021] [Indexed: 01/23/2023] Open
Abstract
Purpose: Delineation of subtle lesions in magnetic resonance imaging (MRI)-negative patients is of great importance in preoperative epilepsy evaluation. The aim of our study was to explore the diagnostic value of the novel fluid and white matter suppression (FLAWS) sequence in comparison with a voxel-based MRI postprocessing morphometric analysis program (MAP) in a consecutive cohort of non-lesional patients. Methods: Surgical candidates with a negative finding on an official neuroradiology report were enrolled. High-resolution FLAWS image and MAP maps generated based on high-resolution three-dimensional (3D) T1 image were visually inspected for each patient. The findings of FLAWS or MAP-positive (FLAWS/MAP+) regions were compared with the surgical resection cavity in correlation with surgical outcome and pathology. Results: Forty-five patients were enrolled; the pathological examination revealed focal cortical dysplasia (FCD) in 32 patients and other findings in 13 patients. The positive rate, sensitivity, and specificity were 48.9%, 0.43, and 0.87, respectively, for FLAWS and 64.4%, 0.57, and 0.8, respectively, for MAP. Concordance between surgical resection and FLAWS+ or MAP+ regions was significantly associated with a seizure-free outcome (FLAWS: p = 0.002; MAP: p = 0.0003). A positive finding in FLAWS and MAP together with abnormalities in the same gyrus (FLAWS–MAP gyral+) was detected in 31.1% of patients. FLAWS+ only and MAP+ only were found in 7 (15.5%) and 14 (31.1%) patients, respectively. Conclusions: FLAWS showed a promising value for identifying subtle epileptogenic lesions and can be used as a complement to current MAP in patients with MRI-negative epilepsy.
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Affiliation(s)
- Ke Sun
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Tao Yu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Dongju Yang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Zhiwei Ren
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Liang Qiao
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Duanyu Ni
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xueyuan Wang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yongxiang Zhao
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xin Chen
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jing Xiang
- Department of Neurology, MEG Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Nan Chen
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Runshi Gao
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Kun Yang
- Department of Evidence-Based Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yicong Lin
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Guojun Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
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19
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Otsubo H, Ogawa H, Pang E, Wong SM, Ibrahim GM, Widjaja E. A review of magnetoencephalography use in pediatric epilepsy: an update on best practice. Expert Rev Neurother 2021; 21:1225-1240. [PMID: 33780318 DOI: 10.1080/14737175.2021.1910024] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Introduction: Magnetoencephalography (MEG) is a noninvasive technique that is used for presurgical evaluation of children with drug-resistant epilepsy (DRE).Areas covered: The contributions of MEG for localizing the epileptogenic zone are discussed, in particular in extra-temporal lobe epilepsy and focal cortical dysplasia, which are common in children, as well as in difficult to localize epilepsy such as operculo-insular epilepsy. Further, the authors review current evidence on MEG for mapping eloquent cortex, its performance, application in clinical practice, and potential challenges.Expert opinion: MEG could change the clinical management of children with DRE by directing placement of intracranial electrodes thereby enhancing their yield. With improved identification of a circumscribed epileptogenic zone, MEG could render more patients as suitable candidates for epilepsy surgery and increase utilization of surgery.
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Affiliation(s)
- Hiroshi Otsubo
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada
| | - Hiroshi Ogawa
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada
| | - Elizabeth Pang
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada.,Neuroscience and Mental Health, Hospital for Sick Children, Toronto, Canada
| | - Simeon M Wong
- Neuroscience and Mental Health, Hospital for Sick Children, Toronto, Canada
| | - George M Ibrahim
- Division of Neurosurgery, Hospital for Sick Children, Toronto, Canada.,Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada
| | - Elysa Widjaja
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada.,Neuroscience and Mental Health, Hospital for Sick Children, Toronto, Canada.,Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada
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20
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Huang J, Xu J, Kang L, Zhang T. Identifying Epilepsy Based on Deep Learning Using DKI Images. Front Hum Neurosci 2020; 14:590815. [PMID: 33240068 PMCID: PMC7680804 DOI: 10.3389/fnhum.2020.590815] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 10/08/2020] [Indexed: 11/25/2022] Open
Abstract
Epilepsy is a serious hazard to human health. Minimally invasive surgery is currently an extremely effective treatment to refractory epilepsy. However, it is challenging to localize the lesion for most patients because they are MRI negative. The identification of epileptic foci in local brain region will be helpful to the localization of epileptic foci because we can infer whether there is a lesion from the results of the classification. For the sake of simplicity and the data we collected, only the hippocampus was segmented as a local brain region and classified in this paper. We recruited 59 children with hippocampus epilepsy and 70 age- and sex-matched normal controls, and diffusion kurtosis images (DKI) for all subjects were collected because DKI can understand the pathological changes of local tissues and other regions of epileptic foci at the molecular level. Then, a mask of hippocampus was made to segment the hippocampus of FA, MD, and MK images for all subjects, which are the parameter images of DKI and were used to perform the independent-sample t-test and the classification task. At last, a convolutional neural network (CNN) based on transfer learning technique was developed to extract features of FA, MD, MK, and the fusion of FA and MK, and support vector machine was employed to classify epilepsy and normal control. Finally, the classifier produced 90.8% accuracy for patient vs. normal controls. Experimental results showed that the features extraction based on CNN is very effective, and the high accuracy of classification means that FA and MK are two remarkable features to identify epilepsy, which indicates that DKI images can act as an important biomarker for epilepsy from the point of view of clinical diagnosis.
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Affiliation(s)
- Jianjun Huang
- College of Electrical and Information Engineering, Shenzhen University, Shenzhen, China
| | - Jiahui Xu
- College of Electrical and Information Engineering, Shenzhen University, Shenzhen, China
| | - Li Kang
- College of Electrical and Information Engineering, Shenzhen University, Shenzhen, China
| | - Tijiang Zhang
- Imaging Department, The Affiliated Hospital of Zunyi Medical University, Zunyi, China
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21
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Rossi Sebastiano D, Tassi L, Spreafico R, Panzica F. Reply to "Maximizing non-invasive investigations in the quest for identifying the epileptogenic zone". Clin Neurophysiol 2020; 131:2779-2780. [PMID: 33012639 DOI: 10.1016/j.clinph.2020.09.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 09/09/2020] [Accepted: 09/10/2020] [Indexed: 11/24/2022]
Affiliation(s)
| | - Laura Tassi
- "Claudio Munari" Epilepsy Surgery Centre, Niguarda Hospital, Milan, Italy
| | - Roberto Spreafico
- Epilepsy Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Ferruccio Panzica
- Clinical Engineering Service, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
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22
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Agrawal M, Chandra PS, Doddamani R, Kaur K, Samala R, Tripathi M. Maximizing non-invasive investigations in the quest for identifying the epileptogenic zone. Clin Neurophysiol 2020; 131:2777-2778. [PMID: 33011079 DOI: 10.1016/j.clinph.2020.08.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Accepted: 08/10/2020] [Indexed: 11/17/2022]
Affiliation(s)
- Mohit Agrawal
- Department of Neurosurgery, All India Institute of Medical Sciences, New Delhi, India
| | - P Sarat Chandra
- Department of Neurosurgery, All India Institute of Medical Sciences, New Delhi, India
| | - Ramesh Doddamani
- Department of Neurosurgery, All India Institute of Medical Sciences, New Delhi, India
| | - Kirandeep Kaur
- Department of Neurology, All India Institute of Medical Sciences, New Delhi, India
| | - Raghu Samala
- Department of Neurosurgery, All India Institute of Medical Sciences, New Delhi, India
| | - Manjari Tripathi
- Department of Neurology, All India Institute of Medical Sciences, New Delhi, India.
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