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Unnwongse K, Wolters CH, Wehner T, Krüger LT, Rampp S, Wellmer J. Introducing the Concept of Error Vectors to Improve Source Localization Results of Epileptic Discharges. J Clin Neurophysiol 2025:00004691-990000000-00225. [PMID: 40434071 DOI: 10.1097/wnp.0000000000001170] [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: 05/29/2025] Open
Abstract
PURPOSE To improve EEG source localization results of interictal epileptic discharges (IED) by applying postprocessing step to electrical source imaging (ESI). METHODS Localization error of ESI was evaluated in comparison to known sources of stimulation potentials (ESP) by recording simultaneous stereo-EEG/scalp EEG. Error vectors were defined as the offset of the ESI-dipole of ESP to the stereo-EEG contacts used for stimulation. The inverted error vector was applied to the ESI-dipole of IED (IED-dipole). RESULTS Seven IED clusters were evaluated. Corrected IED-dipoles were located closer to IED-onset contacts on stereo-EEG than uncorrected IED-dipoles (median [IQR]: 7.8 [2.5] versus 18.7 [10.7] mm, P = 0.02). Anatomically, for high skull conductivities, all corrected IED-dipoles were located in cortical structures or adjacent to epileptogenic lesion, whereas uncorrected IED-dipoles were located in white matter or CSF (P = 0.02). Physiologically, cortical extent of IED generators estimated from corrected IED-dipoles was 16.5 cm2 (IQR = 10.4 cm2) and 7.4 cm2 (range 5.8-9.2 cm2) in the group of anterior temporal IED and prefrontal IED, respectively; the former was concordant with the extent estimated by subdural electrodes. In addition, the relationship of stereo-EEG IED amplitude (a) drop with increasing distance (d) from corrected IED-dipole could be modeled as a negative power equation a(d)∝1/db (R2 = 0.87, P < 0.01), with b ranging from 0.79 to 2.3, median: 1.57, consistent with a simulation model of the sensitivity of intracerebral electrode. CONCLUSIONS Application of inverted error vector reduces localization error and shifts IED-dipole to an anatomically and physiologically plausible location.
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Affiliation(s)
- Kanjana Unnwongse
- Ruhr-Epileptology, Department of Neurology, University Hospital Knappschaftskrankenhaus, Ruhr-University Bochum, Bochum, Germany
| | - Carsten H Wolters
- Institute for Biomagnetism und Biosignalanalysis, University of Münster, Münster, Germany
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
| | - Tim Wehner
- Ruhr-Epileptology, Department of Neurology, University Hospital Knappschaftskrankenhaus, Ruhr-University Bochum, Bochum, Germany
| | - Lia Theophilo Krüger
- Ruhr-Epileptology, Department of Neurology, University Hospital Knappschaftskrankenhaus, Ruhr-University Bochum, Bochum, Germany
| | - Stefan Rampp
- Department of Neurosurgery and Department of Neuroradiology, University Hospital Erlangen, Erlangen, Germany; and
- Department of Neurosurgery, University Hospital Halle (Saale), Halle, Germany
| | - Jörg Wellmer
- Ruhr-Epileptology, Department of Neurology, University Hospital Knappschaftskrankenhaus, Ruhr-University Bochum, Bochum, Germany
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Sadeghzadeh P, Freibauer A, RamachandranNair R, Whitney R, Al Nassar M, Jain P, Donner E, Ochi A, Jones KC. Low-density scalp electrical source imaging of the ictal onset zone network using source coherence maps. Front Neurol 2024; 15:1483977. [PMID: 39748857 PMCID: PMC11693594 DOI: 10.3389/fneur.2024.1483977] [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] [Received: 08/21/2024] [Accepted: 12/06/2024] [Indexed: 01/04/2025] Open
Abstract
Introduction This study investigated low-density scalp electrical source imaging of the ictal onset zone and interictal spike ripple high-frequency oscillation networks using source coherence maps in the pediatric epilepsy surgical workup. Intracranial monitoring, the gold standard for determining epileptogenic zones, has limited spatial sampling. Source coherence analysis presents a promising new non-invasive technique. Methods This was a retrospective review of 12 patients who underwent focal resections. Source coherence maps were generated using standardized low-resolution electromagnetic tomography and concordance to resection margins was assessed, noting outcomes at 3 years post-surgery. Results Ictal source coherence maps were performed in 7/12 patients. Six of seven included the surgical resection. Five of seven cases were seizure free post-resection. Interictal spike ripple electrical source imaging and interictal spike ripple high-frequency oscillation networks using source coherence maps were performed for three cases, with two of three included in the resection and all three were seizure free. Discussion These findings may provide proof of principle supporting low-density scalp electrical source imaging of the ictal onset zone and spike ripple network using source coherence maps. This promising method is complementary to ictal and interictal electrical source imaging in the pediatric epilepsy surgical workup, guiding electrode placement for intracranial monitoring to identify the epileptogenic zone.
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Affiliation(s)
- Parnia Sadeghzadeh
- Division of Neurology, Department of Pediatrics, McMaster Children’s Hospital, Hamilton, ON, Canada
| | - Alexander Freibauer
- Division of Neurology, Department of Pediatrics, BC Children’s Hospital, Vancouver, BC, Canada
| | - Rajesh RamachandranNair
- Division of Neurology, Department of Pediatrics, McMaster Children’s Hospital, Hamilton, ON, Canada
| | - Robyn Whitney
- Division of Neurology, Department of Pediatrics, McMaster Children’s Hospital, Hamilton, ON, Canada
| | - Mutaz Al Nassar
- Division of Neuroimaging, Department of Diagnostic Imaging, McMaster Children’s Hospital, Hamilton, ON, Canada
| | - Puneet Jain
- Division of Neurology, Department of Pediatrics, The Hospital for Sick Children, Toronto, ON, Canada
| | - Elizabeth Donner
- Division of Neurology, Department of Pediatrics, The Hospital for Sick Children, Toronto, ON, Canada
| | - Ayako Ochi
- Division of Neurology, Department of Pediatrics, The Hospital for Sick Children, Toronto, ON, Canada
| | - Kevin C. Jones
- Division of Neurology, Department of Pediatrics, McMaster Children’s Hospital, Hamilton, ON, Canada
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Cheval M, Ferrand M, Colnat-Coubois S, Aron O, Tyvaert L, Koessler L, Maillard L. Patterns of ictal surface EEG in occipital seizures: A simultaneous scalp and intracerebral recording study. Clin Neurophysiol 2024; 168:83-94. [PMID: 39481134 DOI: 10.1016/j.clinph.2024.10.012] [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: 05/01/2024] [Revised: 10/16/2024] [Accepted: 10/18/2024] [Indexed: 11/02/2024]
Abstract
OBJECTIVE To describe the ictal scalp EEG patterns of occipital seizures (OS) and their spatiotemporal correlations with intracerebral occipital ictal discharges derived from simultaneous SEEG-EEG recordings. METHODS Patients with SEEG confirmed OS (14 OS from 8 patients) were selected from an epilepsy surgery center and were monitored 3-10 days using simultaneous scalp EEG and SEEG recordings. RESULTS On scalp EEG, the most common onset patterns were background activity suppression (28.6 %) and high amplitude slow wave corresponding to intracerebral DC-shift (28.6 %) and occurred with a median delay of 0 s after intra-cerebral onset. The initial discharge involved occipital electrodes in only 50 % of the seizures (7/14) with additional basal temporal (8/14) or parietal electrodes (5/14). The onset was ipsilateral to the intra-cerebral onset zone in 71.4 % of seizures and bilateral in the remaining (28.6 %). The most common propagation pattern was either unilateral (50 %) or bilateral (50 %) and a rhythmic slow activity (66.7 %). Different OS subtypes display distinct scalp EEG patterns. CONCLUSION Scalp EEG accurately determines intra-cerebral seizure onset time in OS and has good lateralizing value. However, initial scalp modification does not always involves occipital electrodes and the second modification is well lateralizing in only 50 % of seizures. SIGNIFICANCE This study describes will help clinicians to better identify OS during video EEG and better plan intra-cerebral explorations for epilepsy surgery.
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Affiliation(s)
- Margaux Cheval
- Reference Center for Rare Epilepsies, Neurology Department, University Hospital of Nancy, France; Epileptology Unit, Reference Center for Rare Epilepsies, Department of Neurology, AP-HP, Pitié-Salpêtrière Hospital, Paris, France.
| | - Mickaël Ferrand
- Reference Center for Rare Epilepsies, Neurology Department, University Hospital of Nancy, France; Clinical Neurosciences Research Project, Lorraine University, CNRS, UMR 7365, Nancy, France
| | | | - Olivier Aron
- Reference Center for Rare Epilepsies, Neurology Department, University Hospital of Nancy, France; Clinical Neurosciences Research Project, Lorraine University, CNRS, UMR 7365, Nancy, France
| | - Louise Tyvaert
- Reference Center for Rare Epilepsies, Neurology Department, University Hospital of Nancy, France; Clinical Neurosciences Research Project, Lorraine University, CNRS, UMR 7365, Nancy, France
| | - Laurent Koessler
- Clinical Neurosciences Research Project, Lorraine University, CNRS, UMR 7365, Nancy, France
| | - Louis Maillard
- Reference Center for Rare Epilepsies, Neurology Department, University Hospital of Nancy, France; Clinical Neurosciences Research Project, Lorraine University, CNRS, UMR 7365, Nancy, France
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Karimi-Rouzbahani H, Vogrin S, Cao M, Plummer C, McGonigal A. Multimodal and quantitative analysis of the epileptogenic zone network in the pre-surgical evaluation of drug-resistant focal epilepsy. Neurophysiol Clin 2024; 54:103021. [PMID: 39461243 DOI: 10.1016/j.neucli.2024.103021] [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: 07/11/2024] [Revised: 10/02/2024] [Accepted: 10/09/2024] [Indexed: 10/29/2024] Open
Abstract
Surgical resection for epilepsy often fails due to incomplete Epileptogenic Zone Network (EZN) localization from scalp electroencephalography (EEG), stereo-EEG (SEEG), and Magnetic Resonance Imaging (MRI). Subjective interpretation based on interictal, or ictal recordings limits conventional EZN localization. This study employs multimodal analysis using high-density-EEG (HDEEG), Magnetoencephalography (MEG), functional-MRI (fMRI), and SEEG to overcome these limitations in a patient with drug-resistant MRI-negative focal epilepsy. A 17-year-old with drug-resistant epilepsy underwent evaluation. HDEEG, MEG, fMRI, and SEEG were used, with a novel HDEEG-cap facilitating simultaneous EEG-MEG and EEG-fMRI recordings. Electrical and magnetic source imaging were performed, and fMRI data were analysed for homogenous regions. SEEG analysis involved spike detection, spike timing analysis, ictal fast activity quantification, and Granger-based connectivity analysis. Non-invasive sessions revealed consistent interictal source imaging results identifying the EZN in the right anterior cingulate cortex. EEG-fMRI highlighted broader activation in the right cingulate cortex. SEEG analysis localized spikes and fast activity in the right anterior and posterior cingulate gyri. Multi-modal analysis suggested the EZN in the right frontal lobe, primarily involving the anterior and mid-cingulate cortices. Multi-modal non-invasive analyses can optimise SEEG implantation and surgical decision-making. Invasive analyses corroborated non-invasive findings, emphasising the importance of individual-case quantitative analysis across modalities in complex epilepsy cases.
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Affiliation(s)
- Hamid Karimi-Rouzbahani
- Department of Neurosciences, Mater Misericordiae Hospital, Brisbane, Queensland, Australia; Mater Research Institute, Faculty of Medicine, University of Queensland, Australia; Queensland Brain Institute, University of Queensland, Australia.
| | - Simon Vogrin
- Department of Neurology, St Vincent's Hospital, Fitzroy, Australia; School of Health Sciences, Swinburne University of Technology, Hawthorn, Australia; Department of Medicine, University of Melbourne, Parkville, Australia
| | - Miao Cao
- Swinburne Neuroimaging Facility, Swinburne University of Technology, Hawthorn, Australia
| | - Chris Plummer
- Department of Neurology, St Vincent's Hospital, Fitzroy, Australia; School of Health Sciences, Swinburne University of Technology, Hawthorn, Australia
| | - Aileen McGonigal
- Department of Neurosciences, Mater Misericordiae Hospital, Brisbane, Queensland, Australia; Mater Research Institute, Faculty of Medicine, University of Queensland, Australia; Queensland Brain Institute, University of Queensland, Australia
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Avigdor T, Abdallah C, Afnan J, Cai Z, Rammal S, Grova C, Frauscher B. Consistency of electrical source imaging in presurgical evaluation of epilepsy across different vigilance states. Ann Clin Transl Neurol 2024; 11:389-403. [PMID: 38217279 PMCID: PMC10863930 DOI: 10.1002/acn3.51959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 10/24/2023] [Accepted: 11/18/2023] [Indexed: 01/15/2024] Open
Abstract
OBJECTIVE The use of electrical source imaging (ESI) in assessing the source of interictal epileptic discharges (IEDs) is gaining increasing popularity in presurgical work-up of patients with drug-resistant focal epilepsy. While vigilance affects the ability to locate IEDs and identify the epileptogenic zone, we know little about its impact on ESI. METHODS We studied overnight high-density electroencephalography recordings in focal drug-resistant epilepsy. IEDs were marked visually in each vigilance state, and examined in the sensor and source space. ESIs were calculated and compared between all vigilance states and the clinical ground truth. Two conditions were considered within each vigilance state, an unequalized and an equalized number of IEDs. RESULTS The number, amplitude, and duration of IEDs were affected by the vigilance state, with N3 sleep presenting the highest number, amplitude, and duration for both conditions (P < 0.001), while signal-to-noise ratio only differed in the unequalized condition (P < 0.001). The vigilance state did not affect channel involvement (P > 0.05). ESI maps showed no differences in distance, quality, extent, or maxima distances compared to the clinical ground truth for both conditions (P > 0.05). Only when an absolute reference (wakefulness) was used, the channel involvement (P < 0.05) and ESI source extent (P < 0.01) were impacted during rapid-eye-movement (REM) sleep. Clustering of amplitude-sensitive and -insensitive ESI maps pointed to amplitude rather than the spatial profile as the driver (P < 0.05). INTERPRETATION IED ESI results are stable across vigilance states, including REM sleep, if controlled for amplitude and IED number. ESI is thus stable and invariant to the vigilance state.
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Affiliation(s)
- Tamir Avigdor
- Analytical Neurophysiology LabMontreal Neurological Institute and Hospital, McGill UniversityMontrealQuebecCanada
- Multimodal Functional Imaging Lab, Biomedical Engineering DepartmentMcGill UniversityMontrealCanada
| | - Chifaou Abdallah
- Analytical Neurophysiology LabMontreal Neurological Institute and Hospital, McGill UniversityMontrealQuebecCanada
- Multimodal Functional Imaging Lab, Biomedical Engineering DepartmentMcGill UniversityMontrealCanada
| | - Jawata Afnan
- Multimodal Functional Imaging Lab, Biomedical Engineering DepartmentMcGill UniversityMontrealCanada
| | - Zhengchen Cai
- Montreal Neurological Institute and Hospital, McGill UniversityMontrealQuebecCanada
| | - Saba Rammal
- Analytical Neurophysiology LabMontreal Neurological Institute and Hospital, McGill UniversityMontrealQuebecCanada
| | - Christophe Grova
- Multimodal Functional Imaging Lab, Biomedical Engineering DepartmentMcGill UniversityMontrealCanada
- Multimodal Functional Imaging Lab, PERFORM Centre, Department of PhysicsConcordia UniversityMontrealQuebecCanada
| | - Birgit Frauscher
- Analytical Neurophysiology LabMontreal Neurological Institute and Hospital, McGill UniversityMontrealQuebecCanada
- Department of NeurologyDuke University Medical CenterDurhamNorth CarolinaUSA
- Department of Biomedical EngineeringDuke Pratt School of EngineeringDurhamNorth CarolinaUSA
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Rampp S, Müller-Voggel N, Hamer H, Doerfler A, Brandner S, Buchfelder M. Interictal Electrical Source Imaging. J Clin Neurophysiol 2024; 41:19-26. [PMID: 38181384 DOI: 10.1097/wnp.0000000000001012] [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: 01/07/2024] Open
Abstract
SUMMARY Interictal electrical source imaging (ESI) determines the neuronal generators of epileptic activity in EEG occurring outside of seizures. It uses computational models to take anatomic and neuronal characteristics of the individual patient into account. The presented article provides an overview of application and clinical value of interictal ESI in patients with pharmacoresistant focal epilepsies undergoing evaluation for surgery. Neurophysiological constraints of interictal data are discussed and technical considerations are summarized. Typical indications are covered as well as issues of integration into clinical routine. Finally, an outlook on novel markers of epilepsy for interictal source analysis is presented. Interictal ESI provides diagnostic performance on par with other established methods, such as MRI, PET, or SPECT. Although its accuracy benefits from high-density recordings, it provides valuable information already when applied to EEG with only a limited number of electrodes with complete coverage. Novel oscillatory markers and the integration of frequency coupling and connectivity may further improve accuracy and efficiency.
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Affiliation(s)
- Stefan Rampp
- Department of Neurosurgery, University Hospital Erlangen, Germany
- Department of Neurosurgery, University Hospital Halle (Saale), Germany
| | | | - Hajo Hamer
- Epilepsy Center, Department of Neurology, University Hospital Erlangen, Germany; and
| | - Arnd Doerfler
- Department of Neuroradiology, University Hospital Erlangen, Germany
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Heide E, van de Velden D, Garnica Agudelo D, Hewitt M, Riedel C, Focke NK. Feasibility of high-density electric source imaging in the presurgical workflow: Effect of number of spikes and automated spike detection. Epilepsia Open 2023; 8:785-796. [PMID: 36938790 PMCID: PMC10472417 DOI: 10.1002/epi4.12732] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 03/16/2023] [Indexed: 03/21/2023] Open
Abstract
OBJECTIVE Presurgical high-density electric source imaging (hdESI) of interictal epileptic discharges (IEDs) is only used by few epilepsy centers. One obstacle is the time-consuming workflow both for recording as well as for visual review. Therefore, we analyzed the effect of (a) an automated IED detection and (b) the number of IEDs on the accuracy of hdESI and time-effectiveness. METHODS In 22 patients with pharmacoresistant focal epilepsy receiving epilepsy surgery (Engel 1) we retrospectively detected IEDs both visually and semi-automatically using the EEG analysis software Persyst in 256-channel EEGs. The amount of IEDs, the Euclidean distance between hdESI maximum and resection zone, and the operator time were compared. Additionally, we evaluated the intra-individual effect of IED quantity on the distance between hdESI maximum of all IEDs and hdESI maximum when only a reduced amount of IEDs were included. RESULTS There was no significant difference in the number of IEDs between visually versus semi-automatically marked IEDs (74 ± 56 IEDs/patient vs 116 ± 115 IEDs/patient). The detection method of the IEDs had no significant effect on the mean distances between resection zone and hdESI maximum (visual: 26.07 ± 31.12 mm vs semi-automated: 33.6 ± 34.75 mm). However, the mean time needed to review the full datasets semi-automatically was shorter by 275 ± 46 min (305 ± 72 min vs 30 ± 26 min, P < 0.001). The distance between hdESI of the full versus reduced amount of IEDs of the same patient was smaller than 1 cm when at least a mean of 33 IEDs were analyzed. There was a significantly shorter intraindividual distance between resection zone and hdESI maximum when 30 IEDs were analyzed as compared to the analysis of only 10 IEDs (P < 0.001). SIGNIFICANCE Semi-automatized processing and limiting the amount of IEDs analyzed (~30-40 IEDs per cluster) appear to be time-saving clinical tools to increase the practicability of hdESI in the presurgical work-up.
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Affiliation(s)
- Ev‐Christin Heide
- Department of NeurologyUniversity Medical Center, Georg‐August UniversityGöttingenGermany
| | - Daniel van de Velden
- Department of NeurologyUniversity Medical Center, Georg‐August UniversityGöttingenGermany
| | - David Garnica Agudelo
- Department of NeurologyUniversity Medical Center, Georg‐August UniversityGöttingenGermany
| | - Manuel Hewitt
- Department of NeurologyUniversity Medical Center, Georg‐August UniversityGöttingenGermany
| | - Christian Riedel
- Institute for Diagnostic and Interventional NeuroradiologyUniversity Medical Center, Georg‐August UniversityGöttingenGermany
| | - Niels K. Focke
- Department of NeurologyUniversity Medical Center, Georg‐August UniversityGöttingenGermany
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Ferrand M, Baumann C, Aron O, Vignal JP, Jonas J, Tyvaert L, Colnat-Coulbois S, Koessler L, Maillard L. Intracerebral Correlates of Scalp EEG Ictal Discharges Based on Simultaneous Stereo-EEG Recordings. Neurology 2023; 100:e2045-e2059. [PMID: 36963841 PMCID: PMC10186237 DOI: 10.1212/wnl.0000000000207135] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 01/18/2023] [Indexed: 03/26/2023] Open
Abstract
BACKGROUND AND OBJECTIVES It remains unknown to what extent ictal scalp EEG can accurately predict the localization of the intracerebral seizure onset in presurgical evaluation of drug-resistant epilepsies. In this study, we aimed to define homogeneous ictal scalp EEG profiles (based on their first ictal abnormality) and assess their localizing value using simultaneously recorded scalp EEG and stereo-EEG. METHODS We retrospectively included consecutive patients with drug-resistant focal epilepsy who had simultaneous stereo-EEG and scalp EEG recordings of at least 1 seizure in the epileptology unit in Nancy, France. We analyzed 1 seizure per patient and used hierarchical cluster analysis to group similar seizure profiles on scalp EEG and then performed a descriptive analysis of their intracerebral correlates. RESULTS We enrolled 129 patients in this study. The hierarchical cluster analysis showed 6 profiles on scalp EEG first modification. None were specific to a single intracerebral localization. The "normal EEG" and "blurred EEG" clusters (early muscle artifacts) comprised only 5 patients each and corresponded to no preferential intracerebral localization. The "temporal discharge" cluster (n = 46) was characterized by theta or delta discharges on ipsilateral anterior temporal scalp electrodes and corresponded to a preferential mesial temporal intracerebral localization. The "posterior discharge" cluster (n = 42) was characterized by posterior ipsilateral or contralateral rhythmic alpha discharges or slow waves on scalp and corresponded to a preferential temporal localization. However, this profile was the statistically most frequent scalp EEG correlate of occipital and parietal seizures. The "diffuse suppression" cluster (n = 9) was characterized by a bilateral and diffuse background activity suppression on scalp and corresponded to mesial, and particularly insulo-opercular, localization. Finally, the "frontal discharge" cluster (n = 22) was characterized by bilateral frontal rhythmic fast activity or preictal spike on scalp and corresponded to preferential ventrodorsal frontal intracerebral localizations. DISCUSSION The hierarchical cluster analysis identified 6 seizure profiles regarding the first abnormality on scalp EEG. None of them were specific of a single intracerebral localization. Nevertheless, the strong relationships between the "temporal," "frontal," "diffuse suppression," and "posterior" profiles and intracerebral discharge localizations may contribute to hierarchize hypotheses derived from ictal scalp EEG analysis regarding intracerebral seizure onset.
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Affiliation(s)
- Mickaël Ferrand
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Cédric Baumann
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Olivier Aron
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Jean-Pierre Vignal
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Jacques Jonas
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Louise Tyvaert
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Sophie Colnat-Coulbois
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Laurent Koessler
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France
| | - Louis Maillard
- From the Department of Neurology (M.F., O.A., J.-P.V., J.J., L.T., L.M.), and University Hospital of Nancy, Lorraine University; Department of Epidemiology and Clinical Evaluation (C.B.), INSERM CIC-EC CIE6, Lorraine University, Vandoeuvre; Neurosciences of Systems and Cognition Project (O.A., J.J., L.T., L.K., L.M.), BioSiS Department (Department Biologie, Signaux et Systèmes en Cancérologie et Neurosciences), Research Center for Automatic Control of Nancy (CRAN), Lorraine University, CNRS, UMR 7039, Vandoeuvre; and Department of Neurosurgery (S.C.-C.), University Hospital of Nancy, Lorraine University, Nancy, France.
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9
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Santalucia R, Carapancea E, Vespa S, Germany Morrison E, Ghasemi Baroumand A, Vrielynck P, Fierain A, Joris V, Raftopoulos C, Duprez T, Ferrao Santos S, van Mierlo P, El Tahry R. Clinical added value of interictal automated electrical source imaging in the presurgical evaluation of MRI-negative epilepsy: A real-life experience in 29 consecutive patients. Epilepsy Behav 2023; 143:109229. [PMID: 37148703 DOI: 10.1016/j.yebeh.2023.109229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 04/09/2023] [Accepted: 04/20/2023] [Indexed: 05/08/2023]
Abstract
OBJECTIVE During the presurgical evaluation, manual electrical source imaging (ESI) provides clinically useful information in one-third of the patients but it is time-consuming and requires specific expertise. This prospective study aims to assess the clinical added value of a fully automated ESI analysis in a cohort of patients with MRI-negative epilepsy and describe its diagnostic performance, by evaluating sublobar concordance with stereo-electroencephalography (SEEG) results and surgical resection and outcome. METHODS All consecutive patients referred to the Center for Refractory Epilepsy (CRE) of St-Luc University Hospital (Brussels, Belgium) for presurgical evaluation between 15/01/2019 and 31/12/2020 meeting the inclusion criteria, were recruited to the study. Interictal ESI was realized on low-density long-term EEG monitoring (LD-ESI) and, whenever available, high-density EEG (HD-ESI), using a fully automated analysis (Epilog PreOp, Epilog NV, Ghent, Belgium). The multidisciplinary team (MDT) was asked to formulate hypotheses about the epileptogenic zone (EZ) location at sublobar level and make a decision on further management for each patient at two distinct moments: i) blinded to ESI and ii) after the presentation and clinical interpretation of ESI. Results leading to a change in clinical management were considered contributive. Patients were followed up to assess whether these changes lead to concordant results on stereo-EEG (SEEG) or successful epilepsy surgery. RESULTS Data from all included 29 patients were analyzed. ESI led to a change in the management plan in 12/29 patients (41%). In 9/12 (75%), modifications were related to a change in the plan of the invasive recording. In 8/9 patients, invasive recording was performed. In 6/8 (75%), the intracranial EEG recording confirmed the localization of the ESI at a sublobar level. So far, 5/12 patients, for whom the management plan was changed after ESI, were operated on and have at least one-year postoperative follow-up. In all cases, the EZ identified by ESI was included in the resection zone. Among these patients, 4/5 (80%) are seizure-free (ILAE 1) and one patient experienced a seizure reduction of more than 50% (ILAE 4). CONCLUSIONS In this single-center prospective study, we demonstrated the added value of automated ESI in the presurgical evaluation of MRI-negative cases, especially in helping to plan the implantation of depth electrodes for SEEG, provided that ESI results are integrated into the whole multimodal evaluation and clinically interpreted.
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Affiliation(s)
- Roberto Santalucia
- Cliniques Universitaires Saint-Luc, Paediatric Neurology Unit, Brussels, Belgium; Institute of Neurosciences (IoNS/NEUR), Université Catholique de Louvain (UCL), Brussels, Belgium; Centre Hospitalier Neurologique William Lennox (CHNWL), Clinical Neurophysiology, Ottignies, Belgium; Cliniques Universitaires Saint-Luc, Reference Center for Refractory Epilepsy (CRE), Brussels, Belgium.
| | - Evelina Carapancea
- Institute of Neurosciences (IoNS/NEUR), Université Catholique de Louvain (UCL), Brussels, Belgium
| | - Simone Vespa
- Institute of Neurosciences (IoNS/NEUR), Université Catholique de Louvain (UCL), Brussels, Belgium
| | - Enrique Germany Morrison
- Institute of Neurosciences (IoNS/NEUR), Université Catholique de Louvain (UCL), Brussels, Belgium
| | - Amir Ghasemi Baroumand
- Medical Image and Signal Processing, Ghent University, Ghent, Belgium; Epilog NV, Ghent, Belgium
| | - Pascal Vrielynck
- Centre Hospitalier Neurologique William Lennox (CHNWL), Clinical Neurophysiology, Ottignies, Belgium; Cliniques Universitaires Saint-Luc, Reference Center for Refractory Epilepsy (CRE), Brussels, Belgium
| | - Alexane Fierain
- Centre Hospitalier Neurologique William Lennox (CHNWL), Clinical Neurophysiology, Ottignies, Belgium; Cliniques Universitaires Saint-Luc, Reference Center for Refractory Epilepsy (CRE), Brussels, Belgium; Cliniques Universitaires Saint-Luc, Neurology Unit, Brussels, Belgium
| | - Vincent Joris
- Institute of Neurosciences (IoNS/NEUR), Université Catholique de Louvain (UCL), Brussels, Belgium; Cliniques Universitaires Saint-Luc, Reference Center for Refractory Epilepsy (CRE), Brussels, Belgium; Cliniques Universitaires Saint-Luc, Neurosurgery Unit, Brussels, Belgium
| | - Christian Raftopoulos
- Cliniques Universitaires Saint-Luc, Reference Center for Refractory Epilepsy (CRE), Brussels, Belgium; Cliniques Universitaires Saint-Luc, Neurosurgery Unit, Brussels, Belgium
| | - Thierry Duprez
- Cliniques Universitaires Saint-Luc, Reference Center for Refractory Epilepsy (CRE), Brussels, Belgium; Cliniques Universitaires Saint-Luc, Medical Imaging Department, Neuroradiology Unit, Belgium
| | - Susana Ferrao Santos
- Institute of Neurosciences (IoNS/NEUR), Université Catholique de Louvain (UCL), Brussels, Belgium; Cliniques Universitaires Saint-Luc, Reference Center for Refractory Epilepsy (CRE), Brussels, Belgium; Cliniques Universitaires Saint-Luc, Neurology Unit, Brussels, Belgium
| | - Pieter van Mierlo
- Medical Image and Signal Processing, Ghent University, Ghent, Belgium; Epilog NV, Ghent, Belgium
| | - Riëm El Tahry
- Institute of Neurosciences (IoNS/NEUR), Université Catholique de Louvain (UCL), Brussels, Belgium; Cliniques Universitaires Saint-Luc, Reference Center for Refractory Epilepsy (CRE), Brussels, Belgium; Cliniques Universitaires Saint-Luc, Neurology Unit, Brussels, Belgium; WELBIO Department, WEL Research Institute, Avenue Pasteur 6, 1300 Wavre, Belgium
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10
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Rampp S, Kaltenhäuser M, Müller-Voggel N, Doerfler A, Kasper BS, Hamer HM, Brandner S, Buchfelder M. MEG Node Degree for Focus Localization: Comparison with Invasive EEG. Biomedicines 2023; 11:biomedicines11020438. [PMID: 36830974 PMCID: PMC9953213 DOI: 10.3390/biomedicines11020438] [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] [Received: 01/10/2023] [Revised: 01/23/2023] [Accepted: 01/30/2023] [Indexed: 02/05/2023] Open
Abstract
Epilepsy surgery is a viable therapy option for patients with pharmacoresistant focal epilepsies. A prerequisite for postoperative seizure freedom is the localization of the epileptogenic zone, e.g., using electro- and magnetoencephalography (EEG/MEG). Evidence shows that resting state MEG contains subtle alterations, which may add information to the workup of epilepsy surgery. Here, we investigate node degree (ND), a graph-theoretical parameter of functional connectivity, in relation to the seizure onset zone (SOZ) determined by invasive EEG (iEEG) in a consecutive series of 50 adult patients. Resting state data were subjected to whole brain, all-to-all connectivity analysis using the imaginary part of coherence. Graphs were described using parcellated ND. SOZ localization was investigated on a lobar and sublobar level. On a lobar level, all frequency bands except alpha showed significantly higher maximal ND (mND) values inside the SOZ compared to outside (ratios 1.11-1.20, alpha 1.02). Area-under-the-curve (AUC) was 0.67-0.78 for all expected alpha (0.44, ns). On a sublobar level, mND inside the SOZ was higher for all frequency bands (1.13-1.38, AUC 0.58-0.78) except gamma (1.02). MEG ND is significantly related to SOZ in delta, theta and beta bands. ND may provide new localization tools for presurgical evaluation of epilepsy surgery.
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Affiliation(s)
- Stefan Rampp
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany
- Department of Neurosurgery, University Hospital Halle (Saale), 06120 Halle (Saale), Germany
- Correspondence: ; Tel.: +49-9131-85-46921; Fax: +49-9131-85-34476
| | - Martin Kaltenhäuser
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany
| | - Nadia Müller-Voggel
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany
| | - Arnd Doerfler
- Department of Neuroradiology, University Hospital Erlangen, 91054 Erlangen, Germany
| | - Burkhard S. Kasper
- Epilepsy Center, Department of Neurology, University Hospital Erlangen, 91054 Erlangen, Germany
| | - Hajo M. Hamer
- Epilepsy Center, Department of Neurology, University Hospital Erlangen, 91054 Erlangen, Germany
| | - Sebastian Brandner
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany
| | - Michael Buchfelder
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany
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11
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Thio BJ, Aberra AS, Dessert GE, Grill WM. Ideal current dipoles are appropriate source representations for simulating neurons for intracranial recordings. Clin Neurophysiol 2023; 145:26-35. [PMID: 36403433 PMCID: PMC9772254 DOI: 10.1016/j.clinph.2022.11.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 09/20/2022] [Accepted: 11/01/2022] [Indexed: 11/10/2022]
Abstract
OBJECTIVE To determine whether dipoles are an appropriate simplified representation of neural sources for stereo-EEG (sEEG). METHODS We compared the distributions of voltages generated by a dipole, biophysically realistic cortical neuron models, and extended regions of cortex to determine how well a dipole represented neural sources at different spatial scales and at electrode to neuron distances relevant for sEEG. We also quantified errors introduced by the dipole approximation of neural sources in sEEG source localization using standardized low-resolution electrotomography (sLORETA). RESULTS For pyramidal neurons, the coefficient of correlation between voltages generated by a dipole and neuron model were > 0.9 for distances > 1 mm. For small regions of cortex (∼0.1 cm2), the error in voltages between a dipole and region was < 100 µV for all distances. However, larger regions of active cortex (>5 cm2) yielded > 50 µV errors within 1.5 cm of an electrode when compared to single dipoles. Finally, source localization errors were < 5 mm when using dipoles to represent realistic neural sources. CONCLUSIONS Single dipoles are an appropriate source model to represent both single neurons and small regions of active cortex, while multiple dipoles are required to represent large regions of cortex. SIGNIFICANCE Dipoles are computationally tractable and valid source models for sEEG.
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Affiliation(s)
- Brandon J Thio
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
| | - Aman S Aberra
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
| | - Grace E Dessert
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
| | - Warren M Grill
- Department of Biomedical Engineering, Duke University, Durham, NC, United States; Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States; Department of Neurobiology, Duke University, Durham, NC, United States; Department of Neurosurgery, Duke University, Durham, NC, United States.
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12
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Spinelli L, Baroumand AG, Vulliemoz S, Momjian S, Strobbe G, van Mierlo P, Seeck M. Semiautomatic interictal electric source localization based on long-term electroencephalographic monitoring: A prospective study. Epilepsia 2022; 64:951-961. [PMID: 36346269 DOI: 10.1111/epi.17460] [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: 07/04/2022] [Revised: 11/07/2022] [Accepted: 11/07/2022] [Indexed: 11/09/2022]
Abstract
OBJECTIVE Electric source imaging (ESI) of interictal epileptiform discharges (IEDs) has shown significant yield in numerous studies; however, its implementation at most centers is labor- and cost-intensive. Semiautomatic ESI analysis (SAEA) has been proposed as an alternative and has previously shown benefit. Computer-assisted automatic spike cluster retrieval, averaging, and source localization are carried out for each cluster and are then reviewed by an expert neurophysiologist, to determine their relevance for the individual case. Here, we examine its yield in a prospective single center study. METHOD Between 2017 and 2022, 122 patients underwent SAEA. Inclusion criteria for the current study were unifocal epilepsy disorder, epilepsy surgery with curative purpose, and postoperative follow-up of 2 years or more. All patients (N=40) had continuous video-electroencephalographic (EEG) monitoring with 37 scalp electrodes, which underwent SAEA. Forty patients matched our inclusion criteria. RESULTS Twenty patients required intracranial monitoring; 13 were magnetic resonance imaging (MRI)-negative. Mean duration of analyzed EEG was 4.3 days (±3.1 days), containing a mean of 12 749 detected IEDs (±22 324). The sensitivity, specificity, and accuracy of SAEA for localizing the epileptogenic focus of the entire group were 74.3%, 80%, and 75%, respectively, leading to an odds ratio (OR) of 11.5 to become seizure-free if the source was included in the resection volume (p < .05). In patients with extratemporal lobe epilepsy, our results indicated an accuracy of 68% (OR=11.7). For MRI-negative patients (n = 13) and patients requiring intracranial EEG (n = 20), we found a similarly high accuracy of 84.6% (OR=19) and 75% (OR = 15.9), respectively. SIGNIFICANCE In this prospective study of SAEA of long-term video-EEG, spanning several days, we found excellent localizing information and a high yield, even in difficult patient groups. This compares favorably to high-density ESI, most likely due to marked improved signal-to-noise ratio of the averaged IEDs. We propose including ESI, or SAEA, in the workup of all patients who are referred for epilepsy surgery.
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Affiliation(s)
- Laurent Spinelli
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | - Amir G Baroumand
- Medical Image and Signal Processing, Ghent University, Ghent, Belgium.,Epilog, Ghent, Belgium
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | - Shahan Momjian
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
| | | | - Pieter van Mierlo
- Medical Image and Signal Processing, Ghent University, Ghent, Belgium.,Epilog, Ghent, Belgium
| | - Margitta Seeck
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
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13
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Jeong JW, Lee MH, Kuroda N, Sakakura K, O'Hara N, Juhasz C, Asano E. Multi-Scale Deep Learning of Clinically Acquired Multi-Modal MRI Improves the Localization of Seizure Onset Zone in Children With Drug-Resistant Epilepsy. IEEE J Biomed Health Inform 2022; 26:5529-5539. [PMID: 35925854 PMCID: PMC9710730 DOI: 10.1109/jbhi.2022.3196330] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
The present study investigates the effectiveness of a deep learning neural network for non-invasively localizing the seizure onset zone (SOZ) using multi-modal MRI data that are clinically acquired from children with drug-resistant epilepsy. A cortical parcellation was applied to localize the SOZ in cortical nodes of the epileptogenic hemisphere. At each node, the laminar surface analysis was followed to sample 1) the relative intensity of gray matter and white matter in multi-modal MRI and 2) the neighboring white matter connectivity using diffusion tractography edge strengths. A cross-validation was employed to train and test all layers of a multi-scale residual neural network (msResNet) that can classify SOZ node in an end-to-end fashion. A prediction probability of a given node belonging to the SOZ class was proposed as a non-invasive MRI marker of seizure onset likelihood. In an independent validation cohort, the proposed MRI marker provided a very large effect size of Cohen's d = 1.21 between SOZ and non-SOZ, and classified SOZ with a balanced accuracy of 0.75 in lesional and 0.67 in non-lesional MRI groups. The subsequent multi-variate logistic regression found the incorporation of the proposed MRI marker into interictal intracranial EEG (iEEG) markers further improves the differentiation between the epileptogenic focus (defined as SOZ resected during surgery) and non-epileptogenic sites (i.e., non-SOZ sites preserved during surgery) up to 15 % in non-lesional MRI group, suggesting that the proposed MRI marker could improve the localization of epileptogenic foci for successful pediatric epilepsy surgery.
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14
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Singh J, Ebersole JS, Brinkmann BH. From theory to practical fundamentals of electroencephalographic source imaging in localizing the epileptogenic zone. Epilepsia 2022; 63:2476-2490. [PMID: 35811476 PMCID: PMC9796417 DOI: 10.1111/epi.17361] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 07/07/2022] [Accepted: 07/07/2022] [Indexed: 01/01/2023]
Abstract
With continued advancement in computational technologies, the analysis of electroencephalography (EEG) has shifted from pure visual analysis to a noninvasive computational technique called EEG source imaging (ESI), which involves mathematical modeling of dipolar and distributed sources of a given scalp EEG pattern. ESI is a noninvasive phase I test for presurgical localization of the seizure onset zone in focal epilepsy. It is a relatively inexpensive modality, as it leverages scalp EEG and magnetic resonance imaging (MRI) data already collected typically during presurgical evaluation. With an adequate number of electrodes and combined with patient-specific MRI-based head models, ESI has proven to be a valuable and accurate clinical diagnostic tool for localizing the epileptogenic zone. Despite its advantages, however, ESI is routinely used at only a minority of epilepsy centers. This paper reviews the current evidence and practical fundamentals for using ESI of interictal and ictal epileptic activity during the presurgical evaluation of drug-resistant patients. We identify common errors in processing and interpreting ESI studies, describe the differences in approach needed for localizing interictal and ictal EEG discharges through practical examples, and describe best practices for optimizing the diagnostic information available from these studies.
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Affiliation(s)
- Jaysingh Singh
- Department of NeurologyThe Ohio State University Wexner Medical CenterColumbusOhioUSA
| | - John S. Ebersole
- Northeast Regional Epilepsy GroupAtlantic Health Neuroscience InstituteSummitNew JerseyUSA
| | - Benjamin H. Brinkmann
- Department of NeurologyMayo ClinicRochesterMinnesotaUSA,Department of Biomedical EngineeringMayo ClinicRochesterMinnesotaUSA
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15
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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: 28] [Impact Index Per Article: 9.3] [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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16
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Visual phenomena and anatomo-electro-clinical correlations in occipital lobe seizures. Rev Neurol (Paris) 2022; 178:644-648. [PMID: 35906139 DOI: 10.1016/j.neurol.2022.06.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 06/20/2022] [Accepted: 06/27/2022] [Indexed: 11/24/2022]
Abstract
BACKGROUND Occipital lobe seizure are underrepresented in epilepsy surgery cases series. This may reflect the fear for post-surgical functional deficits but also the doubt about the ability of anatomo-electro-clinical correlations to localize precisely the epileptogenic zone in occipital lobe seizure. METHODS In this expert opinion paper, we review first the general clinical characteristics of occipital lobe seizures, describe the repertoire of visual phenomena and oculo-motor signes in occipital seizures, describe inter-ictal and ictal EEG and finally the possible schemes of epileptogenic zone organization. RESULTS Visual and oculo-motor semiology points towards occipital onset seizures but is neither pathognomonic nor constant. Eyes version and unilateral ictal discharge have a strong lateralizing value but inter-ictal spikes as well as eyes version can be falsely lateralizing. CONCLUSION Although visual and oculo-motor phenomena are characteristic of occipital lobe seizures, they may be discrete, overlooked and should therefore be carefully assessed. There are no clear electro-clinical correlations of a sublobar organization of occipital seizures but the clinical pattern of propagation might help to differentiate complex occipito-temporal from occipito-parietal initial epileptogenic network.
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17
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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: 14] [Impact Index Per Article: 4.7] [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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18
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Billardello R, Ntolkeras G, Chericoni A, Madsen JR, Papadelis C, Pearl PL, Grant PE, Taffoni F, Tamilia E. Novel User-Friendly Application for MRI Segmentation of Brain Resection following Epilepsy Surgery. Diagnostics (Basel) 2022; 12:diagnostics12041017. [PMID: 35454065 PMCID: PMC9032020 DOI: 10.3390/diagnostics12041017] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 04/10/2022] [Accepted: 04/13/2022] [Indexed: 11/16/2022] Open
Abstract
Delineation of resected brain cavities on magnetic resonance images (MRIs) of epilepsy surgery patients is essential for neuroimaging/neurophysiology studies investigating biomarkers of the epileptogenic zone. The gold standard to delineate the resection on MRI remains manual slice-by-slice tracing by experts. Here, we proposed and validated a semiautomated MRI segmentation pipeline, generating an accurate model of the resection and its anatomical labeling, and developed a graphical user interface (GUI) for user-friendly usage. We retrieved pre- and postoperative MRIs from 35 patients who had focal epilepsy surgery, implemented a region-growing algorithm to delineate the resection on postoperative MRIs and tested its performance while varying different tuning parameters. Similarity between our output and hand-drawn gold standards was evaluated via dice similarity coefficient (DSC; range: 0-1). Additionally, the best segmentation pipeline was trained to provide an automated anatomical report of the resection (based on presurgical brain atlas). We found that the best-performing set of parameters presented DSC of 0.83 (0.72-0.85), high robustness to seed-selection variability and anatomical accuracy of 90% to the clinical postoperative MRI report. We presented a novel user-friendly open-source GUI that implements a semiautomated segmentation pipeline specifically optimized to generate resection models and their anatomical reports from epilepsy surgery patients, while minimizing user interaction.
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Affiliation(s)
- Roberto Billardello
- Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Newborn Medicine Division, Department of Pediatrics, Boston Children’s Hospital, Boston, MA 02115, USA; (G.N.); (A.C.); (P.E.G.)
- Advanced Robotics and Human-Centered Technologies-CREO Lab, Università Campus Bio-Medico di Roma, 00128 Rome, Italy;
- Correspondence: (R.B.); (E.T.)
| | - Georgios Ntolkeras
- Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Newborn Medicine Division, Department of Pediatrics, Boston Children’s Hospital, Boston, MA 02115, USA; (G.N.); (A.C.); (P.E.G.)
- Baystate Children’s Hospital, Springfield, MA 01199, USA
| | - Assia Chericoni
- Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Newborn Medicine Division, Department of Pediatrics, Boston Children’s Hospital, Boston, MA 02115, USA; (G.N.); (A.C.); (P.E.G.)
- Advanced Robotics and Human-Centered Technologies-CREO Lab, Università Campus Bio-Medico di Roma, 00128 Rome, Italy;
| | - Joseph R. Madsen
- Epilepsy Surgery Program, Department of Neurosurgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA;
| | - Christos Papadelis
- Jane and John Justin Neurosciences Center, Cook Children’s Health Care System, Fort Worth, TX 76104, USA;
| | - Phillip L. Pearl
- Division of Epilepsy and Clinical Neurophysiology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA;
| | - Patricia Ellen Grant
- Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Newborn Medicine Division, Department of Pediatrics, Boston Children’s Hospital, Boston, MA 02115, USA; (G.N.); (A.C.); (P.E.G.)
| | - Fabrizio Taffoni
- Advanced Robotics and Human-Centered Technologies-CREO Lab, Università Campus Bio-Medico di Roma, 00128 Rome, Italy;
| | - Eleonora Tamilia
- Fetal Neonatal Neuroimaging and Developmental Science Center (FNNDSC), Newborn Medicine Division, Department of Pediatrics, Boston Children’s Hospital, Boston, MA 02115, USA; (G.N.); (A.C.); (P.E.G.)
- Correspondence: (R.B.); (E.T.)
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19
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Carboni M, Brunet D, Seeber M, Michel CM, Vulliemoz S, Vorderwülbecke BJ. Linear distributed inverse solutions for interictal EEG source localisation. Clin Neurophysiol 2021; 133:58-67. [PMID: 34801964 DOI: 10.1016/j.clinph.2021.10.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 09/27/2021] [Accepted: 10/09/2021] [Indexed: 01/09/2023]
Abstract
OBJECTIVE To compare the spatial accuracy of 6 linear distributed inverse solutions for EEG source localisation of interictal epileptic discharges: Minimum Norm, Weighted Minimum Norm, Low-Resolution Electromagnetic Tomography (LORETA), Local Autoregressive Average (LAURA), Standardised LORETA, and Exact LORETA. METHODS Spatial accuracy was assessed clinically by retrospectively comparing the maximum source of averaged interictal discharges to the resected brain area in 30 patients with successful epilepsy surgery, based on 204-channel EEG. Additionally, localisation errors of the inverse solutions were assessed in computer simulations, with different levels of noise added to the signal in both sensor space and source space. RESULTS In the clinical evaluations, the source maximum was located inside the resected brain area in 50-57% of patients when using LORETA or LAURA, while all other inverse solutions performed significantly worse (17-30%; corrected p < 0.01). In the simulation studies, when noise levels exceeded 10%, LORETA and LAURA had substantially smaller localisation errors than the other inverse solutions. CONCLUSIONS LORETA and LAURA provided the highest spatial accuracy both in clinical and simulated data, alongside with a comparably high robustness towards noise. SIGNIFICANCE Among the different linear inverse solution algorithms tested, LORETA and LAURA might be preferred for interictal EEG source localisation.
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Affiliation(s)
- Margherita Carboni
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland
| | - Denis Brunet
- Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland
| | - Martin Seeber
- Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland
| | - Bernd J Vorderwülbecke
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; Epilepsy-Center Berlin-Brandenburg, Department of Neurology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
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20
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Ma K, Luan G, Wang X, Luo S, Qin L, Teng P, Guan Y, Zhao M, Wang J, Wang M, Gao JH. Magnetoencephalography STOUT Method Adapted to Radiofrequency Thermocoagulation for MR-Negative Insular Epilepsy: A Case Report. Front Neurol 2021; 12:683299. [PMID: 34721253 PMCID: PMC8548742 DOI: 10.3389/fneur.2021.683299] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 08/17/2021] [Indexed: 11/16/2022] Open
Abstract
Epilepsy is one of the most challenging neurologic diseases confronted by human society. Approximately 30–40% of the worldwide epilepsy patients are diagnosed with drug-resistant epilepsy and require pre-surgery evaluation. Magnetoencephalography (MEG) is a unique technology that provides optimal spatial-temporal resolution and has become a powerful non-invasive imaging modality that can localize the interictal spikes and guide the implantation of intracranial electrodes. Currently, the most widely used MEG source estimation method for clinical applications is equivalent current dipoles (ECD). However, ECD has difficulties in precisely locating deep sources such as insular lobe. In contrast to ECD, another MEG source estimation method named spatio-temporal unifying tomography (STOUT) with spatial sparsity has particular advantages in locating deep sources. In this case study, we recruited a 5 year-old female patient with insular lobe epilepsy and her seizure recurred in 1 year after receiving the radiofrequency thermocoagulation (RF-TC) therapy. The STOUT method was adopted to locate deep sources for identifying the epileptic foci in epilepsy evaluation. MEG STOUT method strongly supported a stereo-electroencephalographic (SEEG)-guided RF-TC operation, and the patient reported a satisfactory therapeutic effect. This case raises the possibility that STOUT method can be used particularly for the localization of deep sources, and successfully conducted RF-TC under the guidance of MEG STOUT results.
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Affiliation(s)
- Kaiqiang Ma
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Guoming Luan
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Epilepsy, Epilepsy Center, Sanbo Brain Hospital, Capital Medical University, Beijing, China.,Beijing Institute for Brain Disorders, Beijing, China
| | - Xiongfei Wang
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Epilepsy, Epilepsy Center, Sanbo Brain Hospital, Capital Medical University, Beijing, China.,Beijing Institute for Brain Disorders, Beijing, China
| | - Shen Luo
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Lang Qin
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Pengfei Teng
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Yuguang Guan
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Meng Zhao
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Jing Wang
- Department of Neurology, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Mengyang Wang
- Department of Neurology, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China.,McGovern Institute for Brain Research, Peking University, Beijing, China
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21
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Iachim E, Vespa S, Baroumand AG, Danthine V, Vrielynck P, de Tourtchaninoff M, Fierain A, Ribeiro Vaz JG, Raftopoulos C, Ferrao Santos S, van Mierlo P, El Tahry R. Automated electrical source imaging with scalp EEG to define the insular irritative zone: Comparison with simultaneous intracranial EEG. Clin Neurophysiol 2021; 132:2965-2978. [PMID: 34715421 DOI: 10.1016/j.clinph.2021.09.004] [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: 04/07/2021] [Revised: 08/13/2021] [Accepted: 09/16/2021] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To evaluate the accuracy of automatedinterictallow-density electrical source imaging (LD-ESI) to define the insular irritative zone (IZ) by comparing the simultaneous interictal ESI localization with the SEEG interictal activity. METHODS Long-term simultaneous scalp electroencephalography (EEG) and stereo-EEG (SEEG) with at least one depth electrode exploring the operculo-insular region(s) were analyzed. Automated interictal ESI was performed on the scalp EEG using standardized low-resolution brain electromagnetic tomography (sLORETA) and individual head models. A two-step analysis was performed: i) sublobar concordance betweencluster-based ESI localization and SEEG-based IZ; ii) time-locked ESI-/SEEG analysis. Diagnostic accuracy values were calculated using SEEG as reference standard. Subgroup analysis wascarried out, based onthe involvement of insular contacts in the seizure onset and patterns of insular interictal activity. RESULTS Thirty patients were included in the study. ESI showed an overall accuracy of 53% (C.I. 29-76%). Sensitivity and specificity were calculated as 53% (C.I. 29-76%), 55% (C.I. 23-83%) respectively. Higher accuracy was found in patients with frequent and dominant interictal insular spikes. CONCLUSIONS LD-ESI defines with good accuracy the insular implication in the IZ, which is not possible with classical interictalscalpEEG interpretation. SIGNIFICANCE Automated LD-ESI may be a valuable additional tool to characterize the epileptogenic zone in epilepsies with suspected insular involvement.
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Affiliation(s)
- Evelina Iachim
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania; Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Simone Vespa
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium.
| | - Amir G Baroumand
- Medical Image and Signal Processing Group (MEDISIP), Department of Electronics and Information Systems, Ghent University, Ghent, Belgium; Epilog NV, Ghent, Belgium
| | - Venethia Danthine
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium
| | - Pascal Vrielynck
- Epileptology and Clinical Neurophysiology, Centre Neurologique William Lennox, Ottignies, Belgium
| | - Marianne de Tourtchaninoff
- Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Alexane Fierain
- Epileptology and Clinical Neurophysiology, Centre Neurologique William Lennox, Ottignies, Belgium
| | - Jose Geraldo Ribeiro Vaz
- Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | | | - Susana Ferrao Santos
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium; Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Pieter van Mierlo
- Medical Image and Signal Processing Group (MEDISIP), Department of Electronics and Information Systems, Ghent University, Ghent, Belgium; Epilog NV, Ghent, Belgium
| | - Riëm El Tahry
- Institute of Neuroscience (IoNS), Université Catholique de Louvain, Brussels, Belgium; Centre for Refractory Epilepsy, Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
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22
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Vorderwülbecke BJ, Baroumand AG, Spinelli L, Seeck M, van Mierlo P, Vulliémoz S. Automated interictal source localisation based on high-density EEG. Seizure 2021; 92:244-251. [PMID: 34626920 DOI: 10.1016/j.seizure.2021.09.020] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 09/25/2021] [Accepted: 09/29/2021] [Indexed: 11/26/2022] Open
Abstract
PURPOSE To study the accuracy of automated interictal EEG source localisation based on high-density EEG, and to compare it to low-density EEG. METHODS Thirty patients operated for pharmacoresistant focal epilepsy were retrospectively examined. Twelve months after resective brain surgery, 18 were seizure-free or had 'auras' only, while 12 had persistence of disabling seizures. Presurgical 257-channel EEG lasting 3-20 h was down-sampled to 25, 40, and 204 channels for separate analyses. For each electrode setup, interictal spikes were detected, clustered, and averaged automatically before validation by an expert reviewer. An individual 6-layer finite difference head model and the standardised low-resolution electromagnetic tomography were used to localise the maximum source activity of the most prevalent spike. Sublobar concordance with the resected brain area was visually assessed and related to favourable vs. unfavourable postsurgical outcome. RESULTS Depending on the EEG setup, epileptic spikes were detected in 21-24 patients (70-80%). The median number of single spikes per average was 470 (range 17-15,066). Diagnostic sensitivity of EEG source localisation was 58-75%, specificity was 50-67%, and overall accuracy was 55-71%. There were no significant differences between low- and high-density EEG setups with 25 to 257 electrodes. CONCLUSION Automated high-density EEG source localisation provides meaningful information in the majority of cases. With hundreds of single spikes averaged, diagnostic accuracy is similar in high- and low-density EEG. Therefore, low-density EEG may be sufficient for interictal EEG source localisation if high numbers of spikes are available.
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Affiliation(s)
- Bernd J Vorderwülbecke
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; Epilepsy-Center Berlin-Brandenburg, Department of Neurology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
| | - Amir G Baroumand
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium; Epilog NV, Vlasgaardstraat 52, 9000 Ghent, Belgium
| | - Laurent Spinelli
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland
| | - Pieter van Mierlo
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium; Epilog NV, Vlasgaardstraat 52, 9000 Ghent, Belgium
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland
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23
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Demoulin G, Pruvost-Robieux E, Marchi A, Ramdani C, Badier JM, Bartolomei F, Gavaret M. Impact of skull-to-brain conductivity ratio for high resolution EEG source localization. Biomed Phys Eng Express 2021; 7. [PMID: 34298528 DOI: 10.1088/2057-1976/ac177f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 07/23/2021] [Indexed: 11/12/2022]
Abstract
Objective. To measure the impact of skull-to-brain conductivity ratios on interictal spikes source localizations, using high resolution EEG (HR EEG). In previous studies, two ratios were mainly employed: 1/80 and 1/40. Consequences of the employed ratios on source localization results are poorly studied.Methods. Twenty patients with drug-resistant epilepsy were studied using HR EEG (sixty-four scalp electrodes). For each patient, three-layers realistic head models based on individual MRI were elaborated using boundary element model. For each interictal spike, source localization was performed six times, using six skull-to-brain conductivity ratios (1/80, 1/50, 1/40, 1/30, 1/20 and 1/10), exploring all the spectrum of values reported in the literature. We then measured distances between the different sources obtained and between the sources and the anterior commissure (in order to estimate sources depth).Results. We measured a mean distance of 5.3 mm (sd: 3 mm) between the sources obtained with 1/40 versus 1/80 ratio. This distance increased when the discrepancy between the two evaluated ratios increased. We measured a mean distance of 14.2 mm (sd: 4.9 mm) between sources obtained with 1/10 ratio versus 1/80 ratio. Sources localized using 1/40 ratio were 4.3 mm closer to the anterior commissure than sources localized using 1/80 ratio.Significance. Skull-to-brain conductivity ratio is an often-neglected parameter in source localization studies. The different ratios mainly used in the litterature (1/80 and 1/40) lead to significant differences in source localizations. These variations mainly occur in source depth. A more accurate estimation of skull-to-brain conductivity is needed to increase source localization accuracy.Abbreviations. ECD: equivalent current dipole; EIT: electric impedance tomography, HR EEG: High resolution Electroencephalography, IIS: Inter ictal spikes, MEG: Magnetoencephalography, MRI: Magnetic resonance imaging, mS/m: milli-Siemens/m, S/m: Siemens/m, SD: Standard deviation.
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Affiliation(s)
- Grégoire Demoulin
- Neurophysiology Department, GHU Paris Psychiatrie et Neurosciences, Sainte Anne Hospital, 1 rue Cabanis, F-75014 Paris, France.,Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM UMR 1266, F-75014 Paris, France
| | - Estelle Pruvost-Robieux
- Neurophysiology Department, GHU Paris Psychiatrie et Neurosciences, Sainte Anne Hospital, 1 rue Cabanis, F-75014 Paris, France.,Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM UMR 1266, F-75014 Paris, France.,Université de Paris, F-75006 Paris, France
| | - Angela Marchi
- Neurophysiology Department, GHU Paris Psychiatrie et Neurosciences, Sainte Anne Hospital, 1 rue Cabanis, F-75014 Paris, France.,Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM UMR 1266, F-75014 Paris, France
| | - Céline Ramdani
- Institut de Recherche Biomédicale des Armées (IRBA), 91223 Brétigny-sur-Orge, France
| | - Jean-Michel Badier
- Aix Marseille Université, France.,INSERM, INS, Inst Neurosci Syst, Marseille, France.,APHM, Timone Hospital, Epileptology Department, Marseille, France
| | - Fabrice Bartolomei
- Aix Marseille Université, France.,INSERM, INS, Inst Neurosci Syst, Marseille, France.,APHM, Timone Hospital, Epileptology Department, Marseille, France
| | - Martine Gavaret
- Neurophysiology Department, GHU Paris Psychiatrie et Neurosciences, Sainte Anne Hospital, 1 rue Cabanis, F-75014 Paris, France.,Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM UMR 1266, F-75014 Paris, France.,Université de Paris, F-75006 Paris, France
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24
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Burkholder DB, Ritaccio AL, Shin C. Pre‐surgical Evaluation. EPILEPSY 2021:345-365. [DOI: 10.1002/9781119431893.ch19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2025]
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Fast oscillations >40 Hz localize the epileptogenic zone: An electrical source imaging study using high-density electroencephalography. Clin Neurophysiol 2020; 132:568-580. [PMID: 33450578 DOI: 10.1016/j.clinph.2020.11.031] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 10/04/2020] [Accepted: 11/06/2020] [Indexed: 01/25/2023]
Abstract
OBJECTIVE Fast Oscillations (FO) >40 Hz are a promising biomarker of the epileptogenic zone (EZ). Evidence using scalp electroencephalography (EEG) remains scarce. We assessed if electrical source imaging of FO using 256-channel high-density EEG (HD-EEG) is useful for EZ identification. METHODS We analyzed HD-EEG recordings of 10 focal drug-resistant epilepsy patients with seizure-free postsurgical outcome. We marked FO candidate events at the time of epileptic spikes and verified them by screening for an isolated peak in the time-frequency plot. We performed electrical source imaging of spikes and FO within the Maximum Entropy of the Mean framework. Source localization maps were validated against the surgical cavity. RESULTS We identified FO in five out of 10 patients who had a superficial or intermediate deep generator. The maximum of the FO maps was localized inside the cavity in all patients (100%). Analysis with a reduced electrode coverage using the 10-10 and 10-20 system showed a decreased localization accuracy of 60% and 40% respectively. CONCLUSIONS FO recorded with HD-EEG localize the EZ. HD-EEG is better suited to detect and localize FO than conventional EEG approaches. SIGNIFICANCE This study acts as proof-of-concept that FO localization using 256-channel HD-EEG is a viable marker of the EZ.
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Vorderwülbecke BJ, Carboni M, Tourbier S, Brunet D, Seeber M, Spinelli L, Seeck M, Vulliemoz S. High-density Electric Source Imaging of interictal epileptic discharges: How many electrodes and which time point? Clin Neurophysiol 2020; 131:2795-2803. [PMID: 33137569 DOI: 10.1016/j.clinph.2020.09.018] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 07/31/2020] [Accepted: 09/07/2020] [Indexed: 11/18/2022]
Abstract
OBJECTIVE To assess the value of caudal EEG electrodes over cheeks and neck for high-density electric source imaging (ESI) in presurgical epilepsy evaluation, and to identify the best time point during averaged interictal epileptic discharges (IEDs) for optimal ESI accuracy. METHODS We retrospectively examined presurgical 257-channel EEG recordings of 45 patients with pharmacoresistant focal epilepsy. By stepwise removal of cheek and neck electrodes, averaged IEDs were downsampled to 219, 204, and 156 EEG channels. Additionally, ESI at the IED's half-rise was compared to other time points. The respective sources of maximum activity were compared to the resected brain area and postsurgical outcome. RESULTS Caudal channels had disproportionately more artefacts. In 30 patients with favourable outcome, the 204-channel array yielded the most accurate results with ESI maxima < 10 mm from the resection in 67% and inside affected sublobes in 83%. Neither in temporal nor in extratemporal cases did the full 257-channel setup improve ESI accuracy. ESI was most accurate at 50% of the IED's rising phase. CONCLUSION Information from cheeks and neck electrodes did not improve high-density ESI accuracy, probably due to higher artefact load and suboptimal biophysical modelling. SIGNIFICANCE Very caudal EEG electrodes should be used for ESI with caution.
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Affiliation(s)
- Bernd J Vorderwülbecke
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; Department of Neurology, Epilepsy-Center Berlin-Brandenburg, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
| | - Margherita Carboni
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland.
| | - Sebastien Tourbier
- Connectomics Lab, Department of Radiology, Lausanne University Hospital, Rue du Bugnon 46, 1011 Lausanne, Switzerland.
| | - Denis Brunet
- Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland.
| | - Martin Seeber
- Functional Brain Mapping Lab, Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, 1202 Geneva, Switzerland.
| | - Laurent Spinelli
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland.
| | - Margitta Seeck
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland.
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland.
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Zheng L, Sheng J, Cen Z, Teng P, Wang J, Wang Q, Lee RR, Luan G, Huang M, Gao JH. Enhanced Fast-VESTAL for Magnetoencephalography Source Imaging: From Theory to Clinical Application in Epilepsy. IEEE Trans Biomed Eng 2020; 68:793-806. [PMID: 32790623 DOI: 10.1109/tbme.2020.3016468] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
A novel magnetoencephalography source imaging approach called Fast Vector-based Spatio-Temporal Analysis (Fast-VESTAL) has been successfully applied in creating source images from evoked and resting-state data from both healthy subjects and individuals with neurological and/or psychiatric disorders, but its reconstructed source images may show false-positive activations, especially under low signal-to-noise ratio conditions. Here, to effectively reduce false-positive artifacts, we introduced an enhanced Fast-VESTAL (eFast-VESTAL) approach that adopts generalized second-order cone programming. We compared the spatiotemporal characteristics of the eFast-VESTAL approach to those of the popular distributed source approaches (e.g., the minimum L2-norm/ mixed-norm methods) using computer simulations and auditory experiments. More importantly, we applied eFast-VESTAL to the presurgical evaluation of epilepsy. Our results demonstrated that eFast-VESTAL exhibited a lower dipole localization error and/or a higher correlation coefficient (CC) between the estimated source time series and ground truth under various conditions of source waveforms. Experimentally, eFast-VESTAL displayed more focal activation maps and a higher CC between the raw and predicted sensor data in response to auditory stimulation. Notably, eFast-VESTAL was the most accurate method for noninvasively detecting the epileptic zones determined using more invasive stereo-electroencephalography in the comparison.
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Khosropanah P, Ho ETW, Lim KS, Fong SL, Thuy Le MA, Narayanan V. EEG Source Imaging (ESI) utility in clinical practice. BIOMED ENG-BIOMED TE 2020; 65:/j/bmte.ahead-of-print/bmt-2019-0128/bmt-2019-0128.xml. [PMID: 32623371 DOI: 10.1515/bmt-2019-0128] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 02/21/2020] [Indexed: 11/15/2022]
Abstract
Epilepsy surgery is an important treatment modality for medically refractory focal epilepsy. The outcome of surgery usually depends on the localization accuracy of the epileptogenic zone (EZ) during pre-surgical evaluation. Good localization can be achieved with various electrophysiological and neuroimaging approaches. However, each approach has its own merits and limitations. Electroencephalography (EEG) Source Imaging (ESI) is an emerging model-based computational technique to localize cortical sources of electrical activity within the brain volume, three-dimensionally. ESI based pre-surgical evaluation gives an overall clinical yield of 73-91%, depending on choice of head model, inverse solution and EEG electrode density. It is a cost effective, non-invasive method which provides valuable additional information in presurgical evaluation due to its high localizing value specifically in MRI-negative cases, extra or basal temporal lobe epilepsy, multifocal lesions such as tuberous sclerosis or cases with multiple hypotheses. Unfortunately, less than 1% of surgical centers in developing countries use this method as a part of pre-surgical evaluation. This review promotes ESI as a useful clinical tool especially for patients with lesion-negative MRI to determine EZ cost-effectively with high accuracy under the optimized conditions.
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Affiliation(s)
- Pegah Khosropanah
- Division of Neurosurgery, Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Division of Neurology, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Eric Tatt-Wei Ho
- Center for Intelligent Signal & Imaging Research, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia
- Department of Electrical & Electronics Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia
| | - Kheng-Seang Lim
- Division of Neurology, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Si-Lei Fong
- Division of Neurology, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Minh-An Thuy Le
- Division of Neurology, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Department of Neurology, Faculty of Medicine, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Viet Nam
| | - Vairavan Narayanan
- Division of Neurosurgery, Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
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Aydin Ü, Pellegrino G, Ali OBK, Abdallah C, Dubeau F, Lina JM, Kobayashi E, Grova C. Magnetoencephalography resting state connectivity patterns as indicatives of surgical outcome in epilepsy patients. J Neural Eng 2020; 17:035007. [PMID: 32191632 DOI: 10.1088/1741-2552/ab8113] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVE Focal epilepsy is a disorder affecting several brain networks; however, epilepsy surgery usually targets a restricted region, the so-called epileptic focus. There is a growing interest in embedding resting state (RS) connectivity analysis into pre-surgical workup. APPROACH In this retrospective study, we analyzed Magnetoencephalography (MEG) long-range RS functional connectivity patterns in patients with drug-resistant focal epilepsy. MEG recorded prior to surgery from seven seizure-free (Engel Ia) and five non seizure-free (Engel III or IV) patients were analyzed (minimum 2-years post-surgical follow-up). MEG segments without any detectable epileptic activity were source localized using wavelet-based Maximum Entropy on the Mean method. Amplitude envelope correlation in the theta (4-8 Hz), alpha (8-13 Hz), and beta (13-26 Hz) bands were used for assessing connectivity. MAIN RESULTS For seizure-free patients, we found an isolated epileptic network characterized by weaker connections between the brain region where interictal epileptic discharges (IED) are generated and the rest of the cortex, when compared to connectivity between the corresponding contralateral homologous region and the rest of the cortex. Contrarily, non seizure-free patients exhibited a widespread RS epileptic network characterized by stronger connectivity between the IED generator and the rest of the cortex, in comparison to the contralateral region and the cortex. Differences between the two seizure outcome groups concerned mainly distant long-range connections and were found in the alpha-band. SIGNIFICANCE Importantly, these connectivity patterns suggest specific mechanisms describing the underlying organization of the epileptic network and were detectable at the individual patient level, supporting the prospect use of MEG connectivity patterns in epilepsy to predict post-surgical seizure outcome.
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Affiliation(s)
- Ümit Aydin
- Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University, Montreal, Québec, Canada. Authors to whom any correspondence should be addressed
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Vespa S, Baroumand AG, Ferrao Santos S, Vrielynck P, de Tourtchaninoff M, Feys O, Strobbe G, Raftopoulos C, van Mierlo P, El Tahry R. Ictal EEG source imaging and connectivity to localize the seizure onset zone in extratemporal lobe epilepsy. Seizure 2020; 78:18-30. [DOI: 10.1016/j.seizure.2020.03.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 02/27/2020] [Accepted: 03/01/2020] [Indexed: 12/16/2022] Open
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Rikir E, Maillard LG, Abdallah C, Gavaret M, Bartolomei F, Vignal JP, Colnat-Coulbois S, Koessler L. Respective Contribution of Ictal and Inter-ictal Electrical Source Imaging to Epileptogenic Zone Localization. Brain Topogr 2020; 33:384-402. [DOI: 10.1007/s10548-020-00768-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Accepted: 04/07/2020] [Indexed: 10/24/2022]
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Mégevand P, Seeck M. Electric source imaging for presurgical epilepsy evaluation: current status and future prospects. Expert Rev Med Devices 2020; 17:405-412. [DOI: 10.1080/17434440.2020.1748008] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Affiliation(s)
- Pierre Mégevand
- Epilepsy Unit, Neurology Division, Clinical Neuroscience Department, Geneva University Hospitals, Genève, Switzerland
- Basic Neuroscience Department, Faculty of Medicine, University of Geneva, Genève, Switzerland
| | - Margitta Seeck
- Epilepsy Unit, Neurology Division, Clinical Neuroscience Department, Geneva University Hospitals, Genève, Switzerland
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Electroencephalography in epilepsy: look for what could be beyond the visual inspection. Neurol Sci 2019; 40:2287-2291. [DOI: 10.1007/s10072-019-04026-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Accepted: 07/18/2019] [Indexed: 11/26/2022]
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Mégevand P, Hamid L, Dümpelmann M, Heers M. New horizons in clinical electric source imaging. ZEITSCHRIFT FUR EPILEPTOLOGIE 2019. [DOI: 10.1007/s10309-019-0258-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Tamilia E, AlHilani M, Tanaka N, Tsuboyama M, Peters JM, Grant PE, Madsen JR, Stufflebeam SM, Pearl PL, Papadelis C. Assessing the localization accuracy and clinical utility of electric and magnetic source imaging in children with epilepsy. Clin Neurophysiol 2019; 130:491-504. [PMID: 30771726 DOI: 10.1016/j.clinph.2019.01.009] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 12/07/2018] [Accepted: 01/08/2019] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To evaluate the accuracy and clinical utility of conventional 21-channel EEG (conv-EEG), 72-channel high-density EEG (HD-EEG) and 306-channel MEG in localizing interictal epileptiform discharges (IEDs). METHODS Twenty-four children who underwent epilepsy surgery were studied. IEDs on conv-EEG, HD-EEG, MEG and intracranial EEG (iEEG) were localized using equivalent current dipoles and dynamical statistical parametric mapping (dSPM). We compared the localization error (ELoc) with respect to the ground-truth Irritative Zone (IZ), defined by iEEG sources, between non-invasive modalities and the distance from resection (Dres) between good- (Engel 1) and poor-outcomes. For each patient, we estimated the resection percentage of IED sources and tested whether it predicted outcome. RESULTS MEG presented lower ELoc than HD-EEG and conv-EEG. For all modalities, Dres was shorter in good-outcome than poor-outcome patients, but only the resection percentage of the ground-truth IZ and MEG-IZ predicted surgical outcome. CONCLUSIONS MEG localizes the IZ more accurately than conv-EEG and HD-EEG. MSI may help the presurgical evaluation in terms of patient's outcome prediction. The promising clinical value of ESI for both conv-EEG and HD-EEG prompts the use of higher-density EEG-systems to possibly achieve MEG performance. SIGNIFICANCE Localizing the IZ non-invasively with MSI/ESI facilitates presurgical evaluation and surgical prognosis assessment.
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Affiliation(s)
- Eleonora Tamilia
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michel AlHilani
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Naoaki Tanaka
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Sapporo Neuroimaging Research Group, Sapporo, Japan
| | - Melissa Tsuboyama
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jurriaan M Peters
- 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 Developmental Science Center, 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, 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, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Fetal-Neonatal Neuroimaging Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
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Gavaret M. HR-EEG Source localization. Neurophysiol Clin 2018. [DOI: 10.1016/j.neucli.2018.06.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022] Open
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Feng R, Hu J, Wu J, Lang L, Ma C, Sun B, Gu X, Pan L. Accurate source imaging based on high resolution scalp electroencephalography and individualized finite difference head models in epilepsy pre-surgical workup. Seizure 2018; 59:126-131. [DOI: 10.1016/j.seizure.2018.05.009] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Revised: 05/12/2018] [Accepted: 05/15/2018] [Indexed: 10/16/2022] Open
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Sharma P, Scherg M, Pinborg LH, Fabricius M, Rubboli G, Pedersen B, Leffers AM, Uldall P, Jespersen B, Brennum J, Henriksen OM, Beniczky S. Ictal and interictal electric source imaging in pre-surgical evaluation: a prospective study. Eur J Neurol 2018; 25:1154-1160. [DOI: 10.1111/ene.13676] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2017] [Accepted: 05/03/2018] [Indexed: 12/01/2022]
Affiliation(s)
- P. Sharma
- Department of Clinical Neurophysiology; Danish Epilepsy Centre; Dianalund Denmark
- Department of Neurology; King George's Medical University; Lucknow India
| | - M. Scherg
- Research Department; BESA GmbH; Gräfelfing Germany
| | - L. H. Pinborg
- Department of Neurology; Copenhagen University Hospital Rigshospitalet; Copenhagen
- Neurobiology Research Unit; Copenhagen University Hospital Rigshospitalet; Copenhagen
| | - M. Fabricius
- Department of Clinical Neurophysiology; Copenhagen University Hospital Rigshospitalet; Copenhagen
| | - G. Rubboli
- Department of Neurology; Danish Epilepsy Centre; Dianalund
| | - B. Pedersen
- Department of Neurology; Danish Epilepsy Centre; Dianalund
| | - A.-M. Leffers
- Department of Diagnostic Radiology; Hvidovre Hospital; Hvidovre
| | - P. Uldall
- Department of Paediatrics, Child Neurology; Copenhagen University Hospital Rigshospitalet; Copenhagen
| | - B. Jespersen
- Department of Neurosurgery; Copenhagen University Hospital Rigshospitalet; Copenhagen
| | - J. Brennum
- Department of Neurosurgery; Copenhagen University Hospital Rigshospitalet; Copenhagen
| | - O. M. Henriksen
- Department of Clinical Physiology, Nuclear Medicine and PET; Copenhagen University Hospital Rigshospitalet; Copenhagen
| | - S. Beniczky
- Department of Clinical Neurophysiology; Danish Epilepsy Centre; Dianalund Denmark
- Department of Clinical Neurophysiology; Aarhus University Hospital; Aarhus Denmark
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Kasper BS, Rössler K, Hamer HM, Dörfler A, Blümcke I, Coras R, Roesch J, Mennecke A, Wellmer J, Sommer B, Lorber B, Lang JD, Graf W, Stefan H, Schwab S, Buchfelder M, Rampp S. Coregistrating magnetic source and magnetic resonance imaging for epilepsy surgery in focal cortical dysplasia. Neuroimage Clin 2018; 19:487-496. [PMID: 29984157 PMCID: PMC6029564 DOI: 10.1016/j.nicl.2018.04.034] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Revised: 04/18/2018] [Accepted: 04/28/2018] [Indexed: 11/29/2022]
Abstract
Background Epilepsy surgery for focal cortical dysplasia type II (FCD II) offers good chances for seizure freedom, but remains a challenge with respect to lesion detection, defining the epileptogenic zone and the optimal resection strategy. Integrating results from magnetic source imaging from magnetoencephalography (MEG) with magnetic resonance imaging (MRI) including MRI postprocessing may be useful for optimizing these goals. Methods We here present data from 21 adult FCD II patients, investigated during a 10 year period and evaluated including magnetic source imaging. 16 patients had epilepsy surgery, i.e. histopathologically verified FCD II, and a long follow up. We present our analysis of epileptogenic zones including MEG in relation to structural data according to MRI data and relate these results to surgical outcomes. Results FCD II in our cohort was characterized by high MEG yield and localization accuracy and MEG showed impact on surgical success-rates. MEG source localizations were detected in 95.2% of patients and were as close as 12.3 ± 8,1 mm to the MRI-lesion. After a mean follow up of >3 years, we saw >80% Engel I outcomes, with more favourable outcomes when the MEG source was completely resected (Fishers exact test 0,033). Conclusion We argue for a high value of conducting a combined MEG-MRI approach in the presurgical workup and the resection strategy in patients with FCD II related epilepsy.
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Affiliation(s)
- Burkhard S Kasper
- Epilepsy Center, Department of Neurology, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Karl Rössler
- Department of Neurosurgery, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Hajo M Hamer
- Epilepsy Center, Department of Neurology, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Arnd Dörfler
- Department of Neuroradiology, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Ingmar Blümcke
- Department of Neuropathology, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Roland Coras
- Department of Neuropathology, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Julie Roesch
- Department of Neuroradiology, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Angelika Mennecke
- Department of Neuroradiology, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Jörg Wellmer
- Ruhr-Epileptology, University Hospital Knappschaftskrankenhaus, Ruhr-University Bochum, In der Schornau 23-25, Germany.
| | - Björn Sommer
- Department of Neurosurgery, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Bogdan Lorber
- Department of Neurology, University Medical Centre Ljubljana, Zaloška cesta 2, 1000 Ljubljana, Slovenia.
| | - Johannes D Lang
- Epilepsy Center, Department of Neurology, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Wolfgang Graf
- Epilepsy Center, Department of Neurology, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Hermann Stefan
- Epilepsy Center, Department of Neurology, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Stefan Schwab
- Department of Neurology, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Michael Buchfelder
- Department of Neurosurgery, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Stefan Rampp
- Department of Neurosurgery, Friedrich Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
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