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Hernandez H, Baez S, Medel V, Moguilner S, Cuadros J, Santamaria-Garcia H, Tagliazucchi E, Valdes-Sosa PA, Lopera F, OchoaGómez JF, González-Hernández A, Bonilla-Santos J, Gonzalez-Montealegre RA, Aktürk T, Yıldırım E, Anghinah R, Legaz A, Fittipaldi S, Yener GG, Escudero J, Babiloni C, Lopez S, Whelan R, Lucas AAF, García AM, Huepe D, Caterina GD, Soto-Añari M, Birba A, Sainz-Ballesteros A, Coronel C, Herrera E, Abasolo D, Kilborn K, Rubido N, Clark R, Herzog R, Yerlikaya D, Güntekin B, Parra MA, Prado P, Ibanez A. Brain health in diverse settings: How age, demographics and cognition shape brain function. Neuroimage 2024; 295:120636. [PMID: 38777219 DOI: 10.1016/j.neuroimage.2024.120636] [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: 02/08/2024] [Revised: 04/17/2024] [Accepted: 05/04/2024] [Indexed: 05/25/2024] Open
Abstract
Diversity in brain health is influenced by individual differences in demographics and cognition. However, most studies on brain health and diseases have typically controlled for these factors rather than explored their potential to predict brain signals. Here, we assessed the role of individual differences in demographics (age, sex, and education; n = 1298) and cognition (n = 725) as predictors of different metrics usually used in case-control studies. These included power spectrum and aperiodic (1/f slope, knee, offset) metrics, as well as complexity (fractal dimension estimation, permutation entropy, Wiener entropy, spectral structure variability) and connectivity (graph-theoretic mutual information, conditional mutual information, organizational information) from the source space resting-state EEG activity in a diverse sample from the global south and north populations. Brain-phenotype models were computed using EEG metrics reflecting local activity (power spectrum and aperiodic components) and brain dynamics and interactions (complexity and graph-theoretic measures). Electrophysiological brain dynamics were modulated by individual differences despite the varied methods of data acquisition and assessments across multiple centers, indicating that results were unlikely to be accounted for by methodological discrepancies. Variations in brain signals were mainly influenced by age and cognition, while education and sex exhibited less importance. Power spectrum activity and graph-theoretic measures were the most sensitive in capturing individual differences. Older age, poorer cognition, and being male were associated with reduced alpha power, whereas older age and less education were associated with reduced network integration and segregation. Findings suggest that basic individual differences impact core metrics of brain function that are used in standard case-control studies. Considering individual variability and diversity in global settings would contribute to a more tailored understanding of brain function.
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Affiliation(s)
- Hernan Hernandez
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile
| | - Sandra Baez
- Universidad de los Andes, Bogota, Colombia; Global Brain Health Institute (GBHI), University of California, San Francisco, US Trinity College Dublin, Dublin, Ireland
| | - Vicente Medel
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile
| | - Sebastian Moguilner
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; Harvard Medical School, Boston, MA, USA
| | - Jhosmary Cuadros
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; Advanced Center for Electrical and Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso 2390123, Chile; Grupo de Bioingeniería, Decanato de Investigación, Universidad Nacional Experimental del Táchira, San Cristóbal 5001, Venezuela
| | - Hernando Santamaria-Garcia
- Pontificia Universidad Javeriana (PhD Program in Neuroscience) Bogotá, San Ignacio, Colombia; Center of Memory and Cognition Intellectus, Hospital Universitario San Ignacio Bogotá, San Ignacio, Colombia
| | - Enzo Tagliazucchi
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; University of Buenos Aires, Argentina
| | - Pedro A Valdes-Sosa
- The Clinical Hospital of Chengdu Brain Sciences, University of Electronic Sciences Technology of China, Chengdu, China; Cuban Neuroscience Center, La Habana, Cuba
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia, University of Antioquia, Medellín, Colombia
| | | | | | | | | | - Tuba Aktürk
- Department of Neurosciences, Health Sciences Institute, Dokuz Eylül University, Izmir, Turkey
| | - Ebru Yıldırım
- Department of Neurosciences, Health Sciences Institute, Dokuz Eylül University, Izmir, Turkey
| | - Renato Anghinah
- Reference Center of Behavioural Disturbances and Dementia, School of Medicine, University of Sao Paulo, Sao Paulo, Brazil; Traumatic Brain Injury Cognitive Rehabilitation Out-Patient Center, University of Sao Paulo, Sao Paulo, Brazil
| | - Agustina Legaz
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina; Facultad de Psicología, Universidad Nacional de Córdoba, Córdoba, Argentina
| | - Sol Fittipaldi
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; Global Brain Health Institute (GBHI), University of California, San Francisco, US Trinity College Dublin, Dublin, Ireland; School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Görsev G Yener
- Faculty of Medicine, Izmir University of Economics, 35330, Izmir, Turkey; Brain Dynamics Multidisciplinary Research Center, Dokuz Eylul University, Izmir, Turkey; Izmir Biomedicine and Genome Center, Izmir, Turkey
| | - Javier Escudero
- School of Engineering, Institute for Imaging, Data and Communications, University of Edinburgh, Scotland, UK
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "V. Erspamer", Sapienza University of Rome, Rome, Italy; Hospital San Raffaele Cassino, Cassino, (FR), Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology "V. Erspamer", Sapienza University of Rome, Rome, Italy
| | - Robert Whelan
- Global Brain Health Institute (GBHI), University of California, San Francisco, US Trinity College Dublin, Dublin, Ireland; Department of Legal Medicine, Psychiatry and Pathology at the Complutense University of Madrid, Madrid, Spain
| | - Alberto A Fernández Lucas
- Department of Legal Medicine, Psychiatry and Pathology at the Complutense University of Madrid, Madrid, Spain
| | - Adolfo M García
- Global Brain Health Institute (GBHI), University of California, San Francisco, US Trinity College Dublin, Dublin, Ireland; Cognitive Neuroscience Center, Universidad de San Andréss, Buenos Aires, Argentina; Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile
| | - David Huepe
- Center for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibáñez
| | - Gaetano Di Caterina
- Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK
| | | | - Agustina Birba
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile
| | | | - Carlos Coronel
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; Global Brain Health Institute (GBHI), University of California, San Francisco, US Trinity College Dublin, Dublin, Ireland; Centro Interdisciplinario de Neurociencia de Valparaíso (CINV), Universidad de Valparaíso, Valparaíso, Chile
| | - Eduar Herrera
- Departamento de Estudios Psicológicos, Universidad ICESI, Cali, Colombia
| | - Daniel Abasolo
- Centre for Biomedical Engineering, School of Mechanical Engineering Sciences, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, UK
| | - Kerry Kilborn
- School of Psychology, University of Glasgow, Glasgow, Scotland, UK
| | - Nicolás Rubido
- Institute for Complex Systems and Mathematical Biology, University of Aberdeen, Aberdeen, AB24 3UE, UK
| | - Ruaridh Clark
- Centre for Signal and Image Processing, Department of Electronic and Electrical Engineering, University of Strathclyde, UK
| | - Ruben Herzog
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, Paris 75013, France
| | - Deniz Yerlikaya
- Department of Neurosciences, Health Sciences Institute, Dokuz Eylül University, Izmir, Turkey
| | - Bahar Güntekin
- Health Sciences and Technology Research Institute (SABITA), Istanbul Medipol University, Istanbul, Turkey; Department of Biophysics, School of Medicine, Istanbul Medipol University, Turkey
| | - Mario A Parra
- Department of Psychological Sciences and Health, University of Strathclyde, United Kingdom and Associate Researcher of the Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Pavel Prado
- Escuela de Fonoaudiología, Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián, Santiago, Chile
| | - Agustin Ibanez
- Latin American Brain Health Institute, Universidad Adolfo Ibañez, Santiago de Chile, Chile; Global Brain Health Institute, University of California San Francisco, San Francisco, CA, USA; Cognitive Neuroscience Center, Universidad de San Andrés and Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina; Trinity College Dublin, The University of Dublin, Dublin, Ireland.
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Bi J, Gao Y, Peng Z, Ma Y. Classification of motor imagery using chaotic entropy based on sub-band EEG source localization. J Neural Eng 2024; 21:036016. [PMID: 38722315 DOI: 10.1088/1741-2552/ad4914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Accepted: 05/09/2024] [Indexed: 05/18/2024]
Abstract
Objective.Electroencephalography (EEG) has been widely used in motor imagery (MI) research by virtue of its high temporal resolution and low cost, but its low spatial resolution is still a major criticism. The EEG source localization (ESL) algorithm effectively improves the spatial resolution of the signal by inverting the scalp EEG to extrapolate the cortical source signal, thus enhancing the classification accuracy.Approach.To address the problem of poor spatial resolution of EEG signals, this paper proposed a sub-band source chaotic entropy feature extraction method based on sub-band ESL. Firstly, the preprocessed EEG signals were filtered into 8 sub-bands. Each sub-band signal was source localized respectively to reveal the activation patterns of specific frequency bands of the EEG signals and the activities of specific brain regions in the MI task. Then, approximate entropy, fuzzy entropy and permutation entropy were extracted from the source signal as features to quantify the complexity and randomness of the signal. Finally, the classification of different MI tasks was achieved using support vector machine.Main result.The proposed method was validated on two MI public datasets (brain-computer interface (BCI) competition III IVa, BCI competition IV 2a) and the results showed that the classification accuracies were higher than the existing methods.Significance.The spatial resolution of the signal was improved by sub-band EEG localization in the paper, which provided a new idea for EEG MI research.
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Affiliation(s)
- Jicheng Bi
- College of Automation, Hangzhou Dianzi University, Hangzhou, People's Republic of China
| | - Yunyuan Gao
- College of Automation, Hangzhou Dianzi University, Hangzhou, People's Republic of China
| | - Zheng Peng
- College of Automation, Hangzhou Dianzi University, Hangzhou, People's Republic of China
| | - Yuliang Ma
- College of Automation, Hangzhou Dianzi University, Hangzhou, People's Republic of China
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Trinka E, Koepp M, Kalss G, Kobulashvili T. Evidence based noninvasive presurgical evaluation for patients with drug resistant epilepsies. Curr Opin Neurol 2024; 37:141-151. [PMID: 38334495 DOI: 10.1097/wco.0000000000001253] [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: 02/10/2024]
Abstract
PURPOSE OF REVIEW To review the current practices and evidence for the diagnostic accuracy and the benefits of presurgical evaluation. RECENT FINDINGS Preoperative evaluation of patients with drug-resistant focal epilepsies and subsequent epilepsy surgery leads to a significant proportion of seizure-free patients. Even those who are not completely seizure free postoperatively often experience improved quality of life with better social integration. Systematic reviews and meta-analysis on the diagnostic accuracy are available for Video-electroencephalographic (EEG) monitoring, magnetic resonance imaging (MRI), electric and magnetic source imaging, and functional MRI for lateralization of language and memory. There are currently no evidence-based international guidelines for presurgical evaluation and epilepsy surgery. SUMMARY Presurgical evaluation is a complex multidisciplinary and multiprofessional clinical pathway. We rely on limited consensus-based recommendations regarding the required staffing or methodological expertise in epilepsy centers.
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Affiliation(s)
- Eugen Trinka
- Department of Neurology, Neurocritical Care, and Neurorehabilitation, Christian-Doppler University Hospital, Paracelsus Medical University, Centre for Cognitive Neuroscience, Member of EpiCARE
- Neuroscience Institute, Christian-Doppler University Hospital, Paracelsus Medical University, Centre for Cognitive Neuroscience, Salzburg
- Institute of Public Health, Medical Decision-Making and HTA, UMIT - Private University for Health Sciences, Medical Informatics and Technology, Hall in Tyrol, Austria
- Karl Landsteiner Institute for Neurorehabilitation and Space Neurology, Salzburg Austria
| | - Matthias Koepp
- UCL Queen Square Institute of Neurology
- National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Gudrun Kalss
- Department of Neurology, Neurocritical Care, and Neurorehabilitation, Christian-Doppler University Hospital, Paracelsus Medical University, Centre for Cognitive Neuroscience, Member of EpiCARE
- Neuroscience Institute, Christian-Doppler University Hospital, Paracelsus Medical University, Centre for Cognitive Neuroscience, Salzburg
| | - Teia Kobulashvili
- Department of Neurology, Neurocritical Care, and Neurorehabilitation, Christian-Doppler University Hospital, Paracelsus Medical University, Centre for Cognitive Neuroscience, Member of EpiCARE
- Neuroscience Institute, Christian-Doppler University Hospital, Paracelsus Medical University, Centre for Cognitive Neuroscience, Salzburg
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Schulze-Bonhage A, Nitsche MA, Rotter S, Focke NK, Rao VR. Neurostimulation targeting the epileptic focus: Current understanding and perspectives for treatment. Seizure 2024; 117:183-192. [PMID: 38452614 DOI: 10.1016/j.seizure.2024.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 02/29/2024] [Accepted: 03/02/2024] [Indexed: 03/09/2024] Open
Abstract
For the one third of people with epilepsy whose seizures are not controlled with medications, targeting the seizure focus with neurostimulation can be an effective therapeutic strategy. In this focused review, we summarize a discussion of targeted neurostimulation modalities during a workshop held in Frankfurt, Germany in September 2023. Topics covered include: available devices for seizure focus stimulation; alternating current (AC) and direct current (DC) stimulation to reduce focal cortical excitability; modeling approaches to simulate DC stimulation; reconciling the efficacy of focal stimulation with the network theory of epilepsy; and the emerging concept of 'neurostimulation zones,' which are defined as cortical regions where focal stimulation is most effective for reducing seizures and which may or may not directly involve the seizure onset zone. By combining experimental data, modeling results, and clinical outcome analysis, rational selection of target regions and stimulation parameters is increasingly feasible, paving the way for a broader use of neurostimulation for epilepsy in the future.
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Affiliation(s)
- Andreas Schulze-Bonhage
- Epilepsy Center, University Medical Center, University of Freiburg, Germany; European Reference Network EpiCare, Belgium; NeuroModul Basic, University of Freiburg, Freiburg, Germany.
| | - Michael A Nitsche
- Dept. Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany; Bielefeld University, University Hospital OWL, Protestant Hospital of Bethel Foundation, University Clinic of Psychiatry and Psychotherapy, Germany; German Center for Mental Health (DZPG), Germany
| | - Stefan Rotter
- Bernstein Center Freiburg & Faculty of Biology, University of Freiburg, Germany
| | - Niels K Focke
- Epilepsy Center, Clinic for Neurology, University Medical Center Göttingen, Germany
| | - Vikram R Rao
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, USA
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Antal DC, Altenmüller DM, Dümpelmann M, Scheiwe C, Reinacher PC, Crihan ET, Ignat BE, Cuciureanu ID, Demerath T, Urbach H, Schulze-Bonhage A, Heers M. Semiautomated electric source imaging determines epileptogenicity of encephaloceles in temporal lobe epilepsy. Epilepsia 2024; 65:651-663. [PMID: 38258618 DOI: 10.1111/epi.17879] [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: 09/22/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 01/24/2024]
Abstract
OBJECTIVE We aimed to assess the ability of semiautomated electric source imaging (ESI) from long-term video-electroencephalographic (EEG) monitoring (LTM) to determine the epileptogenicity of temporopolar encephaloceles (TEs) in patients with temporal lobe epilepsy. METHODS We conducted a retrospective study involving 32 temporal lobe epilepsy patients with TEs as potentially epileptogenic lesions in structural magnetic resonance imaging scans. Findings were validated through invasive intracerebral stereo-EEG in six of 32 patients and postsurgical outcome after tailored resection of the TE in 17 of 32 patients. LTM (mean duration = 6 days) was performed using the 10/20 system with additional T1/T2 for all patients and sphenoidal electrodes in 23 of 32 patients. Semiautomated detection and clustering of interictal epileptiform discharges (IEDs) were carried out to create IED types. ESI was performed on the averages of the two most frequent IED types per patient, utilizing individual head models, and two independent inverse methods (sLORETA [standardized low-resolution brain electromagnetic tomography], MUSIC [multiple signal classification]). ESI maxima concordance and propagation in spatial relation to TEs were quantified for sources with good signal quality (signal-to-noise ratio > 2, explained signal > 60%). RESULTS ESI maxima correctly colocalized with a TE in 20 of 32 patients (62.5%) either at the onset or half-rising flank of at least one IED type per patient. ESI maxima showed propagation from the temporal pole to other temporal or extratemporal regions in 14 of 32 patients (44%), confirming propagation originating in the area of the TE. The findings from both inverse methods validated each other in 14 of 20 patients (70%), and sphenoidal electrodes exhibited the highest signal amplitudes in 17 of 23 patients (74%). The concordance of ESI with the TE predicted a seizure-free postsurgical outcome (Engel I vs. >I) with a diagnostic odds ratio of 2.1. SIGNIFICANCE Semiautomated ESI from LTM often successfully identifies the epileptogenicity of TEs and the IED onset zone within the area of the TEs. Additionally, it shows potential predictive power for postsurgical outcomes in these patients.
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Affiliation(s)
- Dorin-Cristian Antal
- Faculty of Medicine, Epilepsy Center, Medical Center-University of Freiburg, Freiburg, Germany
- Neurology Clinic, Rehabilitation Clinical Hospital, Iași, Romania
- I Neurology Clinic, "Prof. Dr. N. Oblu" Emergency Clinical Hospital, Iasi, Romania
- University of Medicine and Pharmacy "Grigore T. Popa", Iasi, Romania
| | | | - Matthias Dümpelmann
- Faculty of Medicine, Epilepsy Center, Medical Center-University of Freiburg, Freiburg, Germany
| | - Christian Scheiwe
- Department of Neurosurgery, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Peter C Reinacher
- Department of Stereotactic and Functional Neurosurgery, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Fraunhofer Institute for Laser Technology, Aachen, Germany
| | | | - Bogdan-Emilian Ignat
- Neurology Clinic, Rehabilitation Clinical Hospital, Iași, Romania
- University of Medicine and Pharmacy "Grigore T. Popa", Iasi, Romania
| | - Iulian-Dan Cuciureanu
- I Neurology Clinic, "Prof. Dr. N. Oblu" Emergency Clinical Hospital, Iasi, Romania
- University of Medicine and Pharmacy "Grigore T. Popa", Iasi, Romania
| | - Theo Demerath
- Department of Neuroradiology, University Hospital Freiburg, Freiburg, Germany
| | - Horst Urbach
- Department of Neuroradiology, University Hospital Freiburg, Freiburg, Germany
| | - Andreas Schulze-Bonhage
- Faculty of Medicine, Epilepsy Center, Medical Center-University of Freiburg, Freiburg, Germany
| | - Marcel Heers
- Faculty of Medicine, Epilepsy Center, Medical Center-University of Freiburg, Freiburg, Germany
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Czarnetzki C, Spinelli L, Huppertz HJ, Schaller K, Momjian S, Lobrinus J, Vargas MI, Garibotto V, Vulliemoz S, Seeck M. Yield of non-invasive imaging in MRI-negative focal epilepsy. J Neurol 2024; 271:995-1003. [PMID: 37907727 PMCID: PMC10827933 DOI: 10.1007/s00415-023-11987-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 09/02/2023] [Accepted: 09/04/2023] [Indexed: 11/02/2023]
Abstract
OBJECTIVE The absence of MRI-lesion reduces considerably the probability of having an excellent outcome (International League Against Epilepsies [ILAE] class I-II) after epilepsy surgery. Surgical success in magnetic-resonance imaging (MRI)-negative cases relies therefore mainly on non-invasive techniques such as positron-emission tomography (PET), subtraction ictal/inter-ictal single-photon-emission-computed-tomography co-registered to MRI (SISCOM), electric source imaging (ESI) and morphometric MRI analysis (MAP). We were interested in identifying the optimal imaging technique or combination to achieve post-operative class I-II in patients with MRI-negative focal epilepsy. METHODS We identified 168 epileptic patients without MRI lesion. Thirty-three (19.6%) were diagnosed with unifocal epilepsy, underwent surgical resection and follow-up ⩾ 2 years. Sensitivity, specificity, predictive values, and diagnostic odds ratio (OR) were calculated for each technique individually and in combination (after co-registration). RESULTS 23/33 (70%) were free of disabling seizures (75.0% with temporal and 61.5% extratemporal lobe epilepsy). None of the individual modalities presented an OR > 1.5, except ESI if only patients with interictal epileptiform discharges (IEDs) were considered (OR 3.2). On a dual combination, SISCOM with ESI presented the highest outcome (OR = 6). MAP contributed to detecting indistinguishable focal cortical dysplasia in particular in extratemporal epilepsies with a sensitivity of 75%. Concordance of PET, ESI on interictal epileptic discharges, and SISCOM was associated with the highest chance for post-operative seizure control (OR = 11). CONCLUSION If MRI is negative, the chances to benefit from epilepsy surgery are almost as high as in lesional epilepsy, provided that multiple established non-invasive imaging tools are rigorously applied and co-registered together.
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Affiliation(s)
- Christian Czarnetzki
- EEG & Epilepsy Unit, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, University of Geneva, 4, Rue Gabrielle-Perret-Gentil, 1211, Geneva, Switzerland.
| | - Laurent Spinelli
- EEG & Epilepsy Unit, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, University of Geneva, 4, Rue Gabrielle-Perret-Gentil, 1211, Geneva, Switzerland
| | | | - Karl Schaller
- Department of Clinical Neurosciences, Neurosurgery Clinic, University Hospital of Geneva, Geneva, Switzerland
| | - Shahan Momjian
- Department of Clinical Neurosciences, Neurosurgery Clinic, University Hospital of Geneva, Geneva, Switzerland
| | - Johannes Lobrinus
- Department of Clinical Pathology, Faculty of Medicine, University Hospital of Geneva, Geneva, Switzerland
| | - Maria-Isabel Vargas
- Department of Radiology, Faculty of Medicine, University Hospital of Geneva, Geneva, Switzerland
| | - Valentina Garibotto
- Department of Radiology, Faculty of Medicine, University Hospital of Geneva, Geneva, Switzerland
| | - Serge Vulliemoz
- EEG & Epilepsy Unit, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, University of Geneva, 4, Rue Gabrielle-Perret-Gentil, 1211, Geneva, Switzerland
| | - Margitta Seeck
- EEG & Epilepsy Unit, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, University of Geneva, 4, Rue Gabrielle-Perret-Gentil, 1211, Geneva, Switzerland.
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Vogrin SJ, Plummer C. EEG Source Imaging-Clinical Considerations for EEG Acquisition and Signal Processing for Improved Temporo-Spatial Resolution. J Clin Neurophysiol 2024; 41:8-18. [PMID: 38181383 DOI: 10.1097/wnp.0000000000001023] [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 EEG source imaging (ESI) has gained traction in recent years as a useful clinical tool for the noninvasive surgical work-up of patients with drug-resistant focal epilepsy. Despite its proven benefits for the temporo-spatial modeling of spike and seizure sources, ESI remains widely underused in clinical practice. This partly relates to a lack of clarity around an optimal approach to the acquisition and processing of scalp EEG data for the purpose of ESI. Here, we describe some of the practical considerations for the clinical application of ESI. We focus on patient preparation, the impact of electrode number and distribution across the scalp, the benefit of averaging raw data for signal analysis, and the relevance of modeling different phases of the interictal discharge as it evolves from take-off to peak. We emphasize the importance of recording high signal-to-noise ratio data for reliable source analysis. We argue that the accuracy of modeling cortical sources can be improved using higher electrode counts that include an inferior temporal array, by averaging interictal waveforms rather than limiting ESI to single spike analysis, and by careful interrogation of earlier phase components of these waveforms. No amount of postacquisition signal processing or source modeling sophistication, however, can make up for suboptimally recorded scalp EEG data in a poorly prepared patient.
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Affiliation(s)
- Simon J Vogrin
- Centre for Mental Health and Brain Sciences, Swinburne University of Technology, Melbourne, Victoria, Australia
- Department of Neurosciences, St Vincent's Hospital, Melbourne, Victoria, Australia; and
- Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia
| | - Chris Plummer
- Centre for Mental Health and Brain Sciences, Swinburne University of Technology, Melbourne, Victoria, Australia
- Department of Neurosciences, St Vincent's Hospital, Melbourne, Victoria, Australia; and
- Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia
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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: 1.0] [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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9
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Chikara RK, Jahromi S, Tamilia E, Madsen JR, Stufflebeam SM, Pearl PL, Papadelis C. Electromagnetic source imaging predicts surgical outcome in children with focal cortical dysplasia. Clin Neurophysiol 2023; 153:88-101. [PMID: 37473485 PMCID: PMC10528204 DOI: 10.1016/j.clinph.2023.06.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 05/25/2023] [Accepted: 06/15/2023] [Indexed: 07/22/2023]
Abstract
OBJECTIVE To evaluate the diagnostic accuracy of electromagnetic source imaging (EMSI) in localizing spikes and predict surgical outcome in children with drug resistant epilepsy (DRE) due to focal cortical dysplasia (FCD). METHODS We retrospectively analyzed magnetoencephalography (MEG) and high-density (HD-EEG) data from 23 children with FCD-associated DRE who underwent intracranial EEG and surgery. We localized spikes using equivalent current dipole (ECD) fitting, dipole clustering, and dynamical statistical parametric mapping (dSPM) on EMSI, electric source imaging (ESI), and magnetic source imaging (MSI). We calculated the distance from the seizure onset zone (DSOZ) and resection (DRES). We estimated receiver operating characteristic (ROC) curves with Youden's index (J) to predict outcome. RESULTS EMSI presented shorter DSOZ (15.18 ± 9.06 mm) and DRES (8.56 ± 6.24 mm) compared to ESI (DSOZ: 25.04 ± 16.20 mm, p < 0.009; DRES: 18.88 ± 17.30 mm, p < 0.03) and MSI (DSOZ: 23.37 ± 8.98 mm, p < 0.03; DRES: 15.51 ± 10.11 mm, p < 0.02) for clustering in patients with good outcome. Clustering showed shorter DSOZ and DRES compared to ECD fitting and dSPM (p < 0.05). EMSI had higher performance as outcome predictor (J = 70.63%) compared to ESI (J = 41.27%) and MSI (J = 33.33%) for clustering. CONCLUSIONS EMSI provides superior localization and improved predictive performance than individual modalities. SIGNIFICANCE EMSI can help the surgical planning and facilitate the localization of epileptogenic foci.
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Affiliation(s)
- Rupesh Kumar Chikara
- Jane and John Justin Institute for Mind Health, Neuroscience Research, Cook Children's Health Care System, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA
| | - Saeed Jahromi
- Jane and John Justin Institute for Mind Health, Neuroscience Research, Cook Children's Health Care System, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA
| | - Eleonora Tamilia
- Fetal-Neonatal Neuroimaging and 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, Boston, MA, USA
| | - Steve M Stufflebeam
- Athinoula 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
- Jane and John Justin Institute for Mind Health, Neuroscience Research, Cook Children's Health Care System, Fort Worth, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA; School of Medicine, Texas Christian University, Fort Worth, TX, USA.
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10
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Miron G, Baag T, Götz K, Holtkamp M, Vorderwülbecke BJ. Integration of interictal EEG source localization in presurgical epilepsy evaluation - A single-center prospective study. Epilepsia Open 2023; 8:877-887. [PMID: 37170682 PMCID: PMC10472400 DOI: 10.1002/epi4.12754] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 04/27/2023] [Indexed: 05/13/2023] Open
Abstract
OBJECTIVE To investigate cost in working hours for initial integration of interictal EEG source localization (ESL) into clinical practice of a tertiary epilepsy center, and to examine concordance of results obtained with three different ESL pipelines. METHODS This prospective study covered the first year of using ESL in the Epilepsy-Center Berlin-Brandenburg. Patients aged ≥14 years with drug-resistant focal epilepsy referred for noninvasive presurgical evaluation were included. Interictal ESL was based on low-density EEG and individual head models. Source maxima were obtained from two freely available software packages and one commercial provider. One physician and computer scientist documented their working hours for setting up and processing ESL. Additionally, a survey was conducted among epilepsy centers in Germany to assess the current role of ESL in presurgical evaluation. RESULTS Of 40 patients included, 22 (55%) had enough interictal spikes for ESL. The physician's working times decreased from median 4.7 hours [interquartile range 3.9-6.4] in the first third of cases to 2.0 hours [1.9-2.4] in the remaining two thirds; P < 0.01. In addition, computer scientist and physician spent a total of 35.5 and 33.0 working hours on setting up the digital infrastructure, and on training and testing. Sublobar agreement between all three pipelines was 20%, mean measurement of agreement (kappa) 0.13. Finally, the survey revealed that 53% of epilepsy centers in Germany currently use ESL for presurgical evaluation. SIGNIFICANCE This study provides information regarding expected effort and costs for integration of ESL into an epilepsy surgery program. Low result agreement across different ESL pipelines calls for further standardization.
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Affiliation(s)
- Gadi Miron
- Epilepsy‐Center Berlin‐BrandenburgInstitute for Diagnostics of EpilepsyBerlinGermany
- Department of Neurology, Epilepsy‐Center Berlin‐BrandenburgCharité – Universitätsmedizin BerlinBerlinGermany
| | - Thomas Baag
- Epilepsy‐Center Berlin‐BrandenburgInstitute for Diagnostics of EpilepsyBerlinGermany
| | - Kara Götz
- Epilepsy‐Center Berlin‐BrandenburgInstitute for Diagnostics of EpilepsyBerlinGermany
- Department of Neurology, Epilepsy‐Center Berlin‐BrandenburgCharité – Universitätsmedizin BerlinBerlinGermany
| | - Martin Holtkamp
- Epilepsy‐Center Berlin‐BrandenburgInstitute for Diagnostics of EpilepsyBerlinGermany
- Department of Neurology, Epilepsy‐Center Berlin‐BrandenburgCharité – Universitätsmedizin BerlinBerlinGermany
| | - Bernd J. Vorderwülbecke
- Epilepsy‐Center Berlin‐BrandenburgInstitute for Diagnostics of EpilepsyBerlinGermany
- Department of Neurology, Epilepsy‐Center Berlin‐BrandenburgCharité – Universitätsmedizin BerlinBerlinGermany
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11
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Zheng L, Liao P, Wu X, Cao M, Cui W, Lu L, Xu H, Zhu L, Lyu B, Wang X, Teng P, Wang J, Vogrin S, Plummer C, Luan G, Gao JH. An artificial intelligence-based pipeline for automated detection and localisation of epileptic sources from magnetoencephalography. J Neural Eng 2023; 20:046036. [PMID: 37615416 DOI: 10.1088/1741-2552/acef92] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 08/10/2023] [Indexed: 08/25/2023]
Abstract
Objective.Magnetoencephalography (MEG) is a powerful non-invasive diagnostic modality for presurgical epilepsy evaluation. However, the clinical utility of MEG mapping for localising epileptic foci is limited by its low efficiency, high labour requirements, and considerable interoperator variability. To address these obstacles, we proposed a novel artificial intelligence-based automated magnetic source imaging (AMSI) pipeline for automated detection and localisation of epileptic sources from MEG data.Approach.To expedite the analysis of clinical MEG data from patients with epilepsy and reduce human bias, we developed an autolabelling method, a deep-learning model based on convolutional neural networks and a hierarchical clustering method based on a perceptual hash algorithm, to enable the coregistration of MEG and magnetic resonance imaging, the detection and clustering of epileptic activity, and the localisation of epileptic sources in a highly automated manner. We tested the capability of the AMSI pipeline by assessing MEG data from 48 epilepsy patients.Main results.The AMSI pipeline was able to rapidly detect interictal epileptiform discharges with 93.31% ± 3.87% precision based on a 35-patient dataset (with sevenfold patientwise cross-validation) and robustly rendered accurate localisation of epileptic activity with a lobar concordance of 87.18% against interictal and ictal stereo-electroencephalography findings in a 13-patient dataset. We also showed that the AMSI pipeline accomplishes the necessary processes and delivers objective results within a much shorter time frame (∼12 min) than traditional manual processes (∼4 h).Significance.The AMSI pipeline promises to facilitate increased utilisation of MEG data in the clinical analysis of patients with epilepsy.
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Affiliation(s)
- Li Zheng
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
- Changping Laboratory, Beijing, People's Republic of China
| | - Pan Liao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
| | - Xiuwen Wu
- Changping Laboratory, Beijing, People's Republic of China
- Center for Biomedical Engineering, University of Science and Technology of China, Anhui, People's Republic of China
| | - Miao Cao
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
- Changping Laboratory, Beijing, People's Republic of China
| | - Wei Cui
- Center for Biomedical Engineering, University of Science and Technology of China, Anhui, People's Republic of China
| | - Lingxi Lu
- Center for the Cognitive Science of Language, Beijing Language and Culture University, Beijing, People's Republic of China
| | - Hui Xu
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
| | - Linlin Zhu
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
| | - Bingjiang Lyu
- Changping Laboratory, Beijing, People's Republic of China
| | - Xiongfei Wang
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, People's Republic of China
- Beijing Key Laboratory of Epilepsy, Capital Medical University, Beijing, People's Republic of China
| | - Pengfei Teng
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Jing Wang
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Simon Vogrin
- Department of Neuroimaging, Swinburne University of Technology, Melbourne, Australia
| | - Chris Plummer
- Department of Neuroimaging, Swinburne University of Technology, Melbourne, Australia
| | - Guoming Luan
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, People's Republic of China
- Beijing Key Laboratory of Epilepsy, Capital Medical University, Beijing, People's Republic of China
| | - Jia-Hong Gao
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
- Changping Laboratory, Beijing, People's Republic of China
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
- McGovern Institute for Brain Research, Peking University, Beijing, People's Republic of China
- National Biomedical Imaging Center, Peking University, Beijing, People's Republic of China
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12
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Pascarella A, Mikulan E, Sciacchitano F, Sarasso S, Rubino A, Sartori I, Cardinale F, Zauli F, Avanzini P, Nobili L, Pigorini A, Sorrentino A. An in-vivo validation of ESI methods with focal sources. Neuroimage 2023:120219. [PMID: 37307867 DOI: 10.1016/j.neuroimage.2023.120219] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 05/05/2023] [Accepted: 06/02/2023] [Indexed: 06/14/2023] Open
Abstract
Electrophysiological source imaging (ESI) aims at reconstructing the precise origin of brain activity from measurements of the electric field on the scalp. Across laboratories/research centers/hospitals, ESI is performed with different methods, partly due to the ill-posedness of the underlying mathematical problem. However, it is difficult to find systematic comparisons involving a wide variety of methods. Further, existing comparisons rarely take into account the variability of the results with respect to the input parameters. Finally, comparisons are typically performed using either synthetic data, or in-vivo data where the ground-truth is only roughly known. We use an in-vivo high-density EEG dataset recorded during intracranial single pulse electrical stimulation, in which the true sources are substantially dipolar and their locations are precisely known. We compare ten different ESI methods, using their implementation in the MNE-Python package: MNE, dSPM, LORETA, sLORETA, eLORETA, LCMV beamformers, irMxNE, Gamma Map, SESAME and dipole fitting. We perform comparisons under multiple choices of input parameters, to assess the accuracy of the best reconstruction, as well as the impact of such parameters on the localization performance. Best reconstructions often fall within 1 cm from the true source, with most accurate methods hitting an average localization error of 1.2 cm and outperforming least accurate ones erring by 2.5 cm. As expected, dipolar and sparsity-promoting methods tend to outperform distributed methods. For several distributed methods, the best regularization parameter turned out to be the one in principle associated with low SNR, despite the high SNR of the available dataset. Depth weighting played no role for two out of the six methods implementing it. Sensitivity to input parameters varied widely between methods. While one would expect high variability being associated with low localization error at the best solution, this is not always the case, with some methods producing highly variable results and high localization error, and other methods producing stable results with low localization error. In particular, recent dipolar and sparsity-promoting methods provide significantly better results than older distributed methods. As we repeated the tests with "conventional" (32 channels) and dense (64, 128, 256 channels) EEG recordings, we observed little impact of the number of channels on localization accuracy; however, for distributed methods denser montages provide smaller spatial dispersion. Overall findings confirm that EEG is a reliable technique for localization of point sources and therefore reinforce the importance that ESI may have in the clinical context, especially when applied to identify the surgical target in potential candidates for epilepsy surgery.
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Affiliation(s)
| | - Ezequiel Mikulan
- Department of Biomedical and Clinical Sciences "L. Sacco",Università degli Studi di Milano, Milan, Italy
| | | | - Simone Sarasso
- Department of Biomedical and Clinical Sciences "L. Sacco",Università degli Studi di Milano, Milan, Italy
| | - Annalisa Rubino
- Department of Neurosciences, Center for Epilepsy Surgery "C. Munari", Hospital Niguarda, Milan, Italy
| | - Ivana Sartori
- Department of Neurosciences, Center for Epilepsy Surgery "C. Munari", Hospital Niguarda, Milan, Italy
| | - Francesco Cardinale
- Department of Neurosciences, Center for Epilepsy Surgery "C. Munari", Hospital Niguarda, Milan, Italy
| | - Flavia Zauli
- Department of Biomedical and Clinical Sciences "L. Sacco",Università degli Studi di Milano, Milan, Italy
| | | | - Lino Nobili
- Child Neuropsychiatry Unit, IRCCS "G. Gaslini" Institute, Genoa, Italy; DINOGMI, Università degli Studi di Genova, Genoa, Italy
| | - Andrea Pigorini
- Department of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, Milan, Italy
| | - Alberto Sorrentino
- Department of Mathematics, Università degli Studi di Genova, Genoa, Italy.
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13
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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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14
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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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15
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Gallotto S, Seeck M. EEG biomarker candidates for the identification of epilepsy. Clin Neurophysiol Pract 2022; 8:32-41. [PMID: 36632368 PMCID: PMC9826889 DOI: 10.1016/j.cnp.2022.11.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 10/14/2022] [Accepted: 11/30/2022] [Indexed: 12/23/2022] Open
Abstract
Electroencephalography (EEG) is one of the main pillars used for the diagnosis and study of epilepsy, readily employed after a possible first seizure has occurred. The most established biomarker of epilepsy, in case seizures are not recorded, are interictal epileptiform discharges (IEDs). In clinical practice, however, IEDs are not always present and the EEG may appear completely normal despite an underlying epileptic disorder, often leading to difficulties in the diagnosis of the disease. Thus, finding other biomarkers that reliably predict whether an individual suffers from epilepsy even in the absence of evident epileptic activity would be extremely helpful, since they could allow shortening the period of diagnostic uncertainty and consequently decreasing the risk of seizure. To date only a few EEG features other than IEDs seem to be promising candidates able to distinguish between epilepsy, i.e. > 60 % risk of recurrent seizures, or other (pathological) conditions. The aim of this narrative review is to provide an overview of the EEG-based biomarker candidates for epilepsy and the techniques employed for their identification.
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16
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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: 2.5] [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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17
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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: 8] [Impact Index Per Article: 4.0] [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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18
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Mattioli P, Cleeren E, Hadady L, Cossu A, Cloppenborg T, Arnaldi D, Beniczky S. Electric Source Imaging in Presurgical Evaluation of Epilepsy: An Inter-Analyser Agreement Study. Diagnostics (Basel) 2022; 12:diagnostics12102303. [PMID: 36291992 PMCID: PMC9601236 DOI: 10.3390/diagnostics12102303] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 09/13/2022] [Accepted: 09/21/2022] [Indexed: 11/16/2022] Open
Abstract
Electric source imaging (ESI) estimates the cortical generator of the electroencephalography (EEG) signals recorded with scalp electrodes. ESI has gained increasing interest for the presurgical evaluation of patients with drug-resistant focal epilepsy. In spite of a standardised analysis pipeline, several aspects tailored to the individual patient involve subjective decisions of the expert performing the analysis, such as the selection of the analysed signals (interictal epileptiform discharges and seizures, identification of the onset epoch and time-point of the analysis). Our goal was to investigate the inter-analyser agreement of ESI in presurgical evaluations of epilepsy, using the same software and analysis pipeline. Six experts, of whom five had no previous experience in ESI, independently performed interictal and ictal ESI of 25 consecutive patients (17 temporal, 8 extratemporal) who underwent presurgical evaluation. The overall agreement among experts for the ESI methods was substantial (AC1 = 0.65; 95% CI: 0.59–0.71), and there was no significant difference between the methods. Our results suggest that using a standardised analysis pipeline, newly trained experts reach similar ESI solutions, calling for more standardisation in this emerging clinical application in neuroimaging.
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Affiliation(s)
- Pietro Mattioli
- Department of Neuroscience (DINOGMI), University of Genoa, 16132 Genoa, Italy
- Danish Epilepsy Center, 4293 Dianalund, Denmark
| | - Evy Cleeren
- Danish Epilepsy Center, 4293 Dianalund, Denmark
- Department of Neurology, University Hospital Leuven, 3000 Leuven, Belgium
| | - Levente Hadady
- Danish Epilepsy Center, 4293 Dianalund, Denmark
- Department of Neurology, Albert Szent-Györgyi Medical School, University of Szeged, 6720 Szeged, Hungary
| | - Alberto Cossu
- Danish Epilepsy Center, 4293 Dianalund, Denmark
- Child Neuropsychiatry, Department of Surgical Sciences, Dentistry, Gynecology and Pediatrics, University of Verona, 37126 Verona, Italy
| | - Thomas Cloppenborg
- Department of Epileptology, Krankenhaus Mara, Medical School, Bielefeld University, 33615 Bielefeld, Germany
| | - Dario Arnaldi
- Department of Neuroscience (DINOGMI), University of Genoa, 16132 Genoa, Italy
- IRCCS San Martino Hospital, 16132 Genoa, Italy
| | - Sándor Beniczky
- Danish Epilepsy Center, 4293 Dianalund, Denmark
- Department of Neurology, Albert Szent-Györgyi Medical School, University of Szeged, 6720 Szeged, Hungary
- Department of Clinical Neurophysiology, Aarhus University Hospital, 8200 Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, 8000 Aarhus, Denmark
- Correspondence: ; Tel.: +45-26-981536
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19
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Paulo DL, Ball TJ, Englot DJ. Emerging Technologies for Epilepsy Surgery. Neurol Clin 2022; 40:849-867. [DOI: 10.1016/j.ncl.2022.03.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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20
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Heers M, Böttcher S, Kalina A, Katletz S, Altenmüller DM, Baroumand AG, Strobbe G, van Mierlo P, von Oertzen TJ, Marusic P, Schulze-Bonhage A, Beniczky S, Dümpelmann M. Detection of interictal epileptiform discharges in an extended scalp EEG array and high-density EEG - A prospective multicenter study. Epilepsia 2022; 63:1619-1629. [PMID: 35357698 DOI: 10.1111/epi.17246] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 03/29/2022] [Accepted: 03/29/2022] [Indexed: 12/01/2022]
Abstract
OBJECTIVES High counts of averaged interictal epileptiform discharges (IEDs) are key components of accurate interictal electric source imaging (ESI) in patients with focal epilepsy. Automated detections may be time-efficient, but they need to identify the correct IED types. Thus, we compared semiautomated and automated detection of IED types in long-term video EEG monitoring (LTM) using an extended scalp EEG array and short-term high-density EEG (hdEEG) with visual detection of IED types and the seizure onset zone (SOZ). METHODS We prospectively recruited consecutive patients from four epilepsy centers who underwent both LTM with 40 electrodes scalp EEG and short-term hdEEG with 256 electrodes. Only patients with a single circumscribed SOZ in LTM were included. In LTM and hdEEG, IED types were identified visually, semiautomatically and automatically. Concordances of semiautomated and automated detections in LTM and hdEEG as well as visual detections in hdEEG were compared against visually detected IED types and the SOZ in LTM. RESULTS Fifty-two out of 62 patients with LTM and hdEEG were included. The most frequent IED types per patient, detected semiautomatically and automatically in LTM and visually in hdEEG, were significantly concordant with the most frequently visually identified IED type in LTM and the SOZ. Semiautomated and automated detections of IED types in hdEEG were significantly concordant with visually identified IED types in LTM only when IED types with more than 50 detected single IEDs were selected. The threshold of 50 detected IED in hdEEG was reached in half of the patients. For all IED types per patient, agreement between visual and semiautomated detections in LTM was high. SIGNIFICANCE Semiautomated and automated detections of IED types in LTM show significant agreement with visually detected IED types and the SOZ. In short-term hdEEG, semiautomated detections of IED types are concordant with visually detected IED types and the SOZ in LTM if high IED counts were detected.
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Affiliation(s)
- Marcel Heers
- Epilepsy Center, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Germany.,Member of European Reference Network EpiCARE
| | - Sebastian Böttcher
- Epilepsy Center, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Germany.,Member of European Reference Network EpiCARE
| | - Adam Kalina
- Member of European Reference Network EpiCARE.,Department of Neurology, Charles University, Second Faculty of Medicine, Motol University Hospital, Prague, Czech Republic
| | - Stefan Katletz
- Member of European Reference Network EpiCARE.,Department of Neurology 1, Kepler Universitätsklinikum, Johannes Kepler University Linz, Linz, Austria
| | - Dirk-Matthias Altenmüller
- Epilepsy Center, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Germany.,Member of European Reference Network EpiCARE
| | - Amir G Baroumand
- Epilog, Vlasgaardstraat 52, Ghent, Belgium.,Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | | | - Pieter van Mierlo
- Epilog, Vlasgaardstraat 52, Ghent, Belgium.,Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Tim J von Oertzen
- Member of European Reference Network EpiCARE.,Department of Neurology 1, Kepler Universitätsklinikum, Johannes Kepler University Linz, Linz, Austria
| | - Petr Marusic
- Member of European Reference Network EpiCARE.,Department of Neurology, Charles University, Second Faculty of Medicine, Motol University Hospital, Prague, Czech Republic
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Germany.,Member of European Reference Network EpiCARE
| | - Sándor Beniczky
- Member of European Reference Network EpiCARE.,Department of Clinical Neurophysiology, Danish Epilepsy Center, Dianalund, Denmark.,Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
| | - Matthias Dümpelmann
- Epilepsy Center, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Germany.,Member of European Reference Network EpiCARE
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21
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Gschwind M, Zima B, Nedeltchev K, van Mierlo P, Rüegg S. Tracking Multifocal Epilepsy With Automated Electric Source Imaging in a Patient With Triple-X Syndrome. J Clin Neurol 2022; 18:96-98. [PMID: 35021284 PMCID: PMC8762506 DOI: 10.3988/jcn.2022.18.1.96] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 09/03/2021] [Accepted: 09/03/2021] [Indexed: 11/29/2022] Open
Affiliation(s)
- Markus Gschwind
- Department of Neurology, Aarau Cantonal Hospital, Aarau, Switzerland.,Department of Neurology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland.
| | - Barbora Zima
- Department of Neurology, Aarau Cantonal Hospital, Aarau, Switzerland
| | | | - Pieter van Mierlo
- Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - Stephan Rüegg
- Department of Neurology, University Hospital Basel and University of Basel, Basel, Switzerland
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22
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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: 2.0] [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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23
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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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24
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Scherg M, Schulz R, Berg P, Cho JH, Bornfleth H, Kural MA, Woermann FG, Bien CG, Beniczky S. Relative Source Power: A novel method for localizing epileptiform EEG discharges. Clin Neurophysiol 2021; 133:9-19. [PMID: 34788717 DOI: 10.1016/j.clinph.2021.10.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 10/13/2021] [Accepted: 10/21/2021] [Indexed: 11/15/2022]
Abstract
OBJECTIVE To validate relative source power (RSP) imaging of extratemporal interictal epileptiform discharges (IEDs). METHODS The accuracy of RSP was validated in a cohort of patients with extratemporal focal epilepsy and a confined epileptogenic lesion (<19 cm3) using distance to the lesion, concordance with resected area and postoperative outcome. Performance was compared with three conventional methods: voltage maps, equivalent current dipole and a distributed source model. RESULTS Thirty-three of 41 consecutive patients (80%) had IED averages suitable for analysis. While the peak negativity in voltage maps localized above the epileptogenic lesion only in 18 cases, RSP-maps matched in 29 cases (88%, p < 0.0026). Source localization showed a median distance of 9.8 mm from the lesion. Source-regions with 20 mm radius included 98% of all source-to-lesion distances. In the 21 surgical cases, outcome showed a sensitivity of 82.35% and specificity of 50% without significant differences between the three source imaging methods. CONCLUSIONS RSP-maps provide a rapid, intuitive and more accurate source estimation than voltage maps. At sublobar level, RSP localizes with an accuracy similar to conventional methods and results of previous studies. SIGNIFICANCE The definition of a source region with 20 mm radius helps in guiding further exploration in extratemporal focal epilepsy.
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Affiliation(s)
| | - Reinhard Schulz
- Department of Epileptology (Krankenhaus Mara), Bielefeld University, Medical School, Bielefeld, Germany
| | | | | | | | - Mustafa A Kural
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
| | - Friedrich G Woermann
- Department of Epileptology (Krankenhaus Mara), Bielefeld University, Medical School, Bielefeld, Germany
| | - Christian G Bien
- Department of Epileptology (Krankenhaus Mara), Bielefeld University, Medical School, Bielefeld, Germany
| | - Sándor Beniczky
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Neurophysiology, Danish Epilepsy Centre, Dianalund, Denmark
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25
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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: 10] [Impact Index Per Article: 3.3] [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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26
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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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Saute RL, Peixoto-Santos JE, Velasco TR, Leite JP. Improving surgical outcome with electric source imaging and high field magnetic resonance imaging. Seizure 2021; 90:145-154. [PMID: 33608134 DOI: 10.1016/j.seizure.2021.02.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 01/26/2021] [Accepted: 02/04/2021] [Indexed: 12/14/2022] Open
Abstract
While most patients with focal epilepsy present with clear structural abnormalities on standard, 1.5 or 3 T MRI, some patients are MRI-negative. For those, quantitative MRI techniques, such as volumetry, voxel-based morphometry, and relaxation time measurements can aid in finding the epileptogenic focus. High-field MRI, just recently approved for clinical use by the FDA, increases the resolution and, in several publications, was shown to improve the detection of focal cortical dysplasias and mild cortical malformations. For those cases without any tissue abnormality in neuroimaging, even at 7 T, scalp EEG alone is insufficient to delimitate the epileptogenic zone. They may benefit from the use of high-density EEG, in which the increased number of electrodes helps improve spatial sampling. The spatial resolution of even low-density EEG can benefit from electric source imaging techniques, which map the source of the recorded abnormal activity, such as interictal epileptiform discharges, focal slowing, and ictal rhythm. These EEG techniques help localize the irritative, functional deficit, and seizure-onset zone, to better estimate the epileptogenic zone. Combining those technologies allows several drug-resistant cases to be submitted to surgery, increasing the odds of seizure freedom and providing a must needed hope for patients with epilepsy.
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Affiliation(s)
- Ricardo Lutzky Saute
- Department of Neurosciences and Behavioral Sciences, Ribeirao Preto Medical School, University of Sao Paulo, Brazil
| | - Jose Eduardo Peixoto-Santos
- Discipline of Neuroscience, Department of Neurology and Neurosurgery, Paulista School of Medicine, Unifesp, Brazil
| | - Tonicarlo R Velasco
- Department of Neurosciences and Behavioral Sciences, Ribeirao Preto Medical School, University of Sao Paulo, Brazil
| | - Joao Pereira Leite
- Department of Neurosciences and Behavioral Sciences, Ribeirao Preto Medical School, University of Sao Paulo, Brazil.
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Ricci L, Tamilia E, Alhilani M, Alter A, Scott Perry Μ, Madsen JR, Peters JM, Pearl PL, Papadelis C. Source imaging of seizure onset predicts surgical outcome in pediatric epilepsy. Clin Neurophysiol 2021; 132:1622-1635. [PMID: 34034087 PMCID: PMC8202024 DOI: 10.1016/j.clinph.2021.03.043] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 02/08/2021] [Accepted: 03/04/2021] [Indexed: 12/20/2022]
Abstract
Objective: To assess whether ictal electric source imaging (ESI) on low-density scalp EEG can approximate the seizure onset zone (SOZ) location and predict surgical outcome in children with refractory epilepsy undergoing surgery. Methods: We examined 35 children with refractory epilepsy. We dichotomized surgical outcome into seizure- and non-seizure-free. We identified ictal onsets recorded with scalp and intracranial EEG and localized them using equivalent current dipoles and standardized low-resolution magnetic tomography (sLORETA). We estimated the localization accuracy of scalp EEG as distance of scalp dipoles from intracranial dipoles. We also calculated the distances of scalp dipoles from resection, as well as their resection percentage and compared between seizure-free and non-seizure-free patients. We built receiver operating characteristic curves to test whether resection percentage predicted outcome. Results: Resection distance was lower in seizure-free patients for both dipoles (p = 0.006) and sLORETA (p = 0.04). Resection percentage predicted outcome with a sensitivity of 57.1% (95% CI, 34–78.2%), a specificity of 85.7% (95% CI, 57.2–98.2%) and an accuracy of 68.6% (95% CI, 50.7–83.5%) (p = 0.01). Conclusion: Ictal ESI performed on low-density scalp EEG can delineate the SOZ and predict outcome. Significance: Such an application may increase the number of children who are referred for epilepsy surgery and improve their outcome.
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Affiliation(s)
- Lorenzo Ricci
- Laboratory of Children's Brain Dynamics, Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, University Campus Bio-Medico of Rome, Rome, Italy
| | - 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
| | - 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; The Hillingdon Hospital NHS Foundation Trust, London, UK
| | - Aliza Alter
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Μ Scott Perry
- Jane and John Justin Neurosciences Center, Cook Children's Health Care System, Fort Worth, TX, USA
| | - Joseph R Madsen
- Division of Epilepsy Surgery, Department of Neurosurgery, 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
| | - 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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29
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Baroumand AG, Arbune AA, Strobbe G, Keereman V, Pinborg LH, Fabricius M, Rubboli G, Gøbel Madsen C, Jespersen B, Brennum J, Mølby Henriksen O, Mierlo PV, Beniczky S. Automated ictal EEG source imaging: A retrospective, blinded clinical validation study. Clin Neurophysiol 2021; 141:119-125. [PMID: 33972159 DOI: 10.1016/j.clinph.2021.03.040] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 02/23/2021] [Accepted: 03/02/2021] [Indexed: 11/03/2022]
Abstract
OBJECTIVE EEG source imaging (ESI) is a validated tool in the multimodal workup of patients with drug resistant focal epilepsy. However, it requires special expertise and it is underutilized. To circumvent this, automated analysis pipelines have been developed and validated for the interictal discharges. In this study, we present the clinical validation of an automated ESI for ictal EEG signals. METHODS We have developed an automated analysis pipeline of ictal EEG activity, based on spectral analysis in source space, using an individual head model of six tissues. The analysis was done blinded to all other data. As reference standard, we used the concordance with the resected area and one-year postoperative outcome. RESULTS We analyzed 50 consecutive patients undergoing epilepsy surgery (34 temporal and 16 extra-temporal). Thirty patients (60%) became seizure-free. The accuracy of the automated ESI was 74% (95% confidence interval: 59.66-85.37%). CONCLUSIONS Automated ictal ESI has a high accuracy for localizing the seizure onset zone. SIGNIFICANCE Automating the ESI of the ictal EEG signals will facilitate implementation of this tool in the presurgical evaluation.
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Affiliation(s)
- Amir G Baroumand
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Campus UZ Corneel Heymanslaan 10, 9000 Ghent, Belgium; Epilog NV, Vlasgaardstraat 52, 9000 Ghent, Belgium
| | - Anca A Arbune
- Department of Clinical Neurophysiology, Danish Epilepsy Centre, Visby Allé 5, 4293 Dianalund, Denmark; Neurology Clinic, Fundeni Clinical Institute, Soseaua Fundeni no. 258, Sector 2, 022328 Bucharest, Romania
| | | | - Vincent Keereman
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Campus UZ Corneel Heymanslaan 10, 9000 Ghent, Belgium; Epilog NV, Vlasgaardstraat 52, 9000 Ghent, Belgium
| | - Lars H Pinborg
- Department of Neurology, Copenhagen University Hospital Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen Ø, Denmark; Neurobiology Research Unit, Copenhagen University Hospital Rigshospitalet, 9 Blegdamsvej, DK-2100 Copenhagen Ø, Denmark
| | - Martin Fabricius
- Department of Clinical Neurophysiology, Copenhagen University Hospital Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen Ø, Denmark
| | - Guido Rubboli
- Department of Neurology, Danish Epilepsy Centre, Kolonivej 1, 4293 Dianalund, Denmark; Institute of Clinical Medicine, University of Copenhagen, Denmark
| | - Camilla Gøbel Madsen
- Department of Diagnostic Radiology, Centre for Functional and Diagnostic Imaging and Research, Hvidovre Hospital, Kettegaard Alle 30, 2650 Hvidovre, Denmark
| | - Bo Jespersen
- Department of Neurosurgery, Copenhagen University Hospital Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen Ø, Denmark
| | - Jannick Brennum
- Department of Neurosurgery, Copenhagen University Hospital Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen Ø, Denmark
| | - Otto Mølby Henriksen
- Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Blegdamsvej 9, 2100 Copenhagen Ø, Denmark
| | - Pieter van Mierlo
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Campus UZ Corneel Heymanslaan 10, 9000 Ghent, Belgium; Epilog NV, Vlasgaardstraat 52, 9000 Ghent, Belgium
| | - Sándor Beniczky
- Department of Clinical Neurophysiology, Danish Epilepsy Centre, Visby Allé 5, 4293 Dianalund, Denmark; Department of Clinical Neurophysiology, Aarhus University Hospital, Palle Juul-Jensens Blvd., 8200 Aarhus, Denmark.
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Abstract
PURPOSE OF REVIEW Epilepsy surgery is the therapy of choice for 30-40% of people with focal drug-resistant epilepsy. Currently only ∼60% of well selected patients become postsurgically seizure-free underlining the need for better tools to identify the epileptogenic zone. This article reviews the latest neurophysiological advances for EZ localization with emphasis on ictal EZ identification, interictal EZ markers, and noninvasive neurophysiological mapping procedures. RECENT FINDINGS We will review methods for computerized EZ assessment, summarize computational network approaches for outcome prediction and individualized surgical planning. We will discuss electrical stimulation as an option to reduce the time needed for presurgical work-up. We will summarize recent research regarding high-frequency oscillations, connectivity measures, and combinations of multiple markers using machine learning. This latter was shown to outperform single markers. The role of NREM sleep for best identification of the EZ interictally will be discussed. We will summarize recent large-scale studies using electrical or magnetic source imaging for clinical decision-making. SUMMARY New approaches based on technical advancements paired with artificial intelligence are on the horizon for better EZ identification. They are ultimately expected to result in a more efficient, less invasive, and less time-demanding presurgical investigation.
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Liu F, Wang L, Lou Y, Li RC, Purdon PL. Probabilistic Structure Learning for EEG/MEG Source Imaging With Hierarchical Graph Priors. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:321-334. [PMID: 32956052 DOI: 10.1109/tmi.2020.3025608] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Brain source imaging is an important method for noninvasively characterizing brain activity using Electroencephalogram (EEG) or Magnetoencephalography (MEG) recordings. Traditional EEG/MEG Source Imaging (ESI) methods usually assume the source activities at different time points are unrelated, and do not utilize the temporal structure in the source activation, making the ESI analysis sensitive to noise. Some methods may encourage very similar activation patterns across the entire time course and may be incapable of accounting the variation along the time course. To effectively deal with noise while maintaining flexibility and continuity among brain activation patterns, we propose a novel probabilistic ESI model based on a hierarchical graph prior. Under our method, a spanning tree constraint ensures that activity patterns have spatiotemporal continuity. An efficient algorithm based on an alternating convex search is presented to solve the resulting problem of the proposed model with guaranteed convergence. Comprehensive numerical studies using synthetic data on a realistic brain model are conducted under different levels of signal-to-noise ratio (SNR) from both sensor and source spaces. We also examine the EEG/MEG datasets in two real applications, in which our ESI reconstructions are neurologically plausible. All the results demonstrate significant improvements of the proposed method over benchmark methods in terms of source localization performance, especially at high noise levels.
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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: 3.3] [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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Ye S, Yang L, Lu Y, Kucewicz MT, Brinkmann B, Nelson C, Sohrabpour A, Worrell GA, He B. Contribution of Ictal Source Imaging for Localizing Seizure Onset Zone in Patients With Focal Epilepsy. Neurology 2020; 96:e366-e375. [PMID: 33097598 DOI: 10.1212/wnl.0000000000011109] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Accepted: 09/01/2020] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To determine whether seizure onset zone (SOZ) can be localized accurately prior to surgical planning in patients with focal epilepsy, we performed noninvasive EEG recordings and source localization analyses on 39 patients. METHODS In 39 patients with focal epilepsy, we recorded and extracted 138 seizures and 1,325 interictal epileptic discharges using high-density EEG. We investigated a novel approach for directly imaging sources of seizures and interictal spikes from high-density EEG recordings, and rigorously validated it for noninvasive localization of SOZ determined from intracranial EEG findings and surgical resection volume. Conventional source imaging analyses were also performed for comparison. RESULTS Ictal source imaging showed a concordance rate of 95% when compared to intracranial EEG or resection results. The average distance from estimation to seizure onset (intracranial) electrodes is 1.35 cm in patients with concordant results, and 0.74 cm to surgical resection boundary in patients with successful surgery. About 41% of the patients were found to have multiple types of interictal activities; coincidentally, a lower concordance rate and a significantly worse performance in localizing SOZ were observed in these patients. CONCLUSION Noninvasive ictal source imaging with high-density EEG recording can provide highly concordant results with clinical decisions obtained by invasive monitoring or confirmed by resective surgery. By means of direct seizure imaging using high-density scalp EEG recordings, the added value of ictal source imaging is particularly high in patients with complex interictal activity patterns, who may represent the most challenging cases with poor prognosis.
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Affiliation(s)
- Shuai Ye
- From the Department of Biomedical Engineering (S.Y., A.S., B.H.), Carnegie Mellon University, Pittsburgh, PA; Department of Biomedical Engineering (L.Y., Y.L.), University of Minnesota, Minneapolis; Mayo Clinic (M.T.K., B.B., C.N., G.A.W.), Rochester, MN
| | - Lin Yang
- From the Department of Biomedical Engineering (S.Y., A.S., B.H.), Carnegie Mellon University, Pittsburgh, PA; Department of Biomedical Engineering (L.Y., Y.L.), University of Minnesota, Minneapolis; Mayo Clinic (M.T.K., B.B., C.N., G.A.W.), Rochester, MN
| | - Yunfeng Lu
- From the Department of Biomedical Engineering (S.Y., A.S., B.H.), Carnegie Mellon University, Pittsburgh, PA; Department of Biomedical Engineering (L.Y., Y.L.), University of Minnesota, Minneapolis; Mayo Clinic (M.T.K., B.B., C.N., G.A.W.), Rochester, MN
| | - Michal T Kucewicz
- From the Department of Biomedical Engineering (S.Y., A.S., B.H.), Carnegie Mellon University, Pittsburgh, PA; Department of Biomedical Engineering (L.Y., Y.L.), University of Minnesota, Minneapolis; Mayo Clinic (M.T.K., B.B., C.N., G.A.W.), Rochester, MN
| | - Benjamin Brinkmann
- From the Department of Biomedical Engineering (S.Y., A.S., B.H.), Carnegie Mellon University, Pittsburgh, PA; Department of Biomedical Engineering (L.Y., Y.L.), University of Minnesota, Minneapolis; Mayo Clinic (M.T.K., B.B., C.N., G.A.W.), Rochester, MN
| | - Cindy Nelson
- From the Department of Biomedical Engineering (S.Y., A.S., B.H.), Carnegie Mellon University, Pittsburgh, PA; Department of Biomedical Engineering (L.Y., Y.L.), University of Minnesota, Minneapolis; Mayo Clinic (M.T.K., B.B., C.N., G.A.W.), Rochester, MN
| | - Abbas Sohrabpour
- From the Department of Biomedical Engineering (S.Y., A.S., B.H.), Carnegie Mellon University, Pittsburgh, PA; Department of Biomedical Engineering (L.Y., Y.L.), University of Minnesota, Minneapolis; Mayo Clinic (M.T.K., B.B., C.N., G.A.W.), Rochester, MN
| | - Gregory A Worrell
- From the Department of Biomedical Engineering (S.Y., A.S., B.H.), Carnegie Mellon University, Pittsburgh, PA; Department of Biomedical Engineering (L.Y., Y.L.), University of Minnesota, Minneapolis; Mayo Clinic (M.T.K., B.B., C.N., G.A.W.), Rochester, MN
| | - Bin He
- From the Department of Biomedical Engineering (S.Y., A.S., B.H.), Carnegie Mellon University, Pittsburgh, PA; Department of Biomedical Engineering (L.Y., Y.L.), University of Minnesota, Minneapolis; Mayo Clinic (M.T.K., B.B., C.N., G.A.W.), Rochester, MN.
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Luria G, Duran D, Visani E, Rossi Sebastiano D, Sorrentino A, Tassi L, Granvillano A, Franceschetti S, Panzica F. Towards the Automatic Localization of the Irritative Zone Through Magnetic Source Imaging. Brain Topogr 2020; 33:651-663. [PMID: 32770321 PMCID: PMC7429532 DOI: 10.1007/s10548-020-00789-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Accepted: 07/24/2020] [Indexed: 10/29/2022]
Abstract
The present work aims at validating a Bayesian multi-dipole modeling algorithm (SESAME) in the clinical scenario consisting of localizing the generators of single interictal epileptiform discharges from resting state magnetoencephalographic recordings. We use the results of Equivalent Current Dipole fitting, performed by an expert user, as a benchmark, and compare the results of SESAME with those of two widely used source localization methods, RAP-MUSIC and wMNE. In addition, we investigate the relation between post-surgical outcome and concordance of the surgical plan with the cerebral lobes singled out by the methods. Unlike dipole fitting, the tested algorithms do not rely on any subjective channel selection and thus contribute towards making source localization more unbiased and automatic. We show that the two dipolar methods, SESAME and RAP-MUSIC, generally agree with dipole fitting in terms of identified cerebral lobes and that the results of the former are closer to the fitted equivalent current dipoles than those of the latter. In addition, for all the tested methods and particularly for SESAME, concordance with surgical plan is a good predictor of seizure freedom while discordance is not a good predictor of poor post-surgical outcome. The results suggest that the dipolar methods, especially SESAME, represent a reliable and more objective alternative to manual dipole fitting for clinical applications in the field of epilepsy surgery.
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Affiliation(s)
- Gianvittorio Luria
- Department of Neurophysiology and Diagnostic Epileptology, IRCCS Foundation Carlo Besta Neurological Institute, Milan, Italy.
- Department of Mathematics, University of Genoa, Genoa, Italy.
| | - Dunja Duran
- Department of Neurophysiology and Diagnostic Epileptology, IRCCS Foundation Carlo Besta Neurological Institute, Milan, Italy
| | - Elisa Visani
- Department of Neurophysiology and Diagnostic Epileptology, IRCCS Foundation Carlo Besta Neurological Institute, Milan, Italy
| | - Davide Rossi Sebastiano
- Department of Neurophysiology and Diagnostic Epileptology, IRCCS Foundation Carlo Besta Neurological Institute, Milan, Italy
| | - Alberto Sorrentino
- Department of Mathematics, University of Genoa, Genoa, Italy
- CNR - SPIN, Genoa, Italy
| | - Laura Tassi
- Epilepsy Surgery Center, Ospedale Niguarda, Milan, Italy
| | - Alice Granvillano
- Department of Neurophysiology and Diagnostic Epileptology, IRCCS Foundation Carlo Besta Neurological Institute, Milan, Italy
| | - Silvana Franceschetti
- Department of Neurophysiology and Diagnostic Epileptology, IRCCS Foundation Carlo Besta Neurological Institute, Milan, Italy
| | - Ferruccio Panzica
- Department of Neurophysiology and Diagnostic Epileptology, IRCCS Foundation Carlo Besta Neurological Institute, Milan, Italy
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35
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van Mierlo P, Vorderwülbecke BJ, Staljanssens W, Seeck M, Vulliémoz S. Ictal EEG source localization in focal epilepsy: Review and future perspectives. Clin Neurophysiol 2020; 131:2600-2616. [PMID: 32927216 DOI: 10.1016/j.clinph.2020.08.001] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 07/12/2020] [Accepted: 08/04/2020] [Indexed: 11/25/2022]
Abstract
Electroencephalographic (EEG) source imaging localizes the generators of neural activity in the brain. During presurgical epilepsy evaluation, EEG source imaging of interictal epileptiform discharges is an established tool to estimate the irritative zone. However, the origin of interictal activity can be partly or fully discordant with the origin of seizures. Therefore, source imaging based on ictal EEG data to determine the seizure onset zone can provide precious clinical information. In this descriptive review, we address the importance of localizing the seizure onset zone based on noninvasive EEG recordings as a complementary analysis that might reduce the burden of the presurgical evaluation. We identify three major challenges (low signal-to-noise ratio of the ictal EEG data, spread of ictal activity in the brain, and validation of the developed methods) and discuss practical solutions. We provide an extensive overview of the existing clinical studies to illustrate the potential clinical utility of EEG-based localization of the seizure onset zone. Finally, we conclude with future perspectives and the needs for translating ictal EEG source imaging into clinical practice.
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Affiliation(s)
- Pieter van Mierlo
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
| | - Bernd J Vorderwülbecke
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland; Department of Neurology, Epilepsy-Center Berlin-Brandenburg, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
| | - Willeke Staljanssens
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Margitta Seeck
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland.
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine Geneva, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland.
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36
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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: 2.8] [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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37
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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: 1.0] [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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Diagnostic added value of electrical source imaging in presurgical evaluation of patients with epilepsy: A prospective study. Clin Neurophysiol 2020; 131:324-329. [DOI: 10.1016/j.clinph.2019.07.031] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Revised: 07/02/2019] [Accepted: 07/28/2019] [Indexed: 11/21/2022]
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Baumgartner C, Koren JP, Britto-Arias M, Zoche L, Pirker S. Presurgical epilepsy evaluation and epilepsy surgery. F1000Res 2019; 8. [PMID: 31700611 PMCID: PMC6820825 DOI: 10.12688/f1000research.17714.1] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/14/2019] [Indexed: 12/21/2022] Open
Abstract
With a prevalence of 0.8 to 1.2%, epilepsy represents one of the most frequent chronic neurological disorders; 30 to 40% of patients suffer from drug-resistant epilepsy (that is, seizures cannot be controlled adequately with antiepileptic drugs). Epilepsy surgery represents a valuable treatment option for 10 to 50% of these patients. Epilepsy surgery aims to control seizures by resection of the epileptogenic tissue while avoiding neuropsychological and other neurological deficits by sparing essential brain areas. The most common histopathological findings in epilepsy surgery specimens are hippocampal sclerosis in adults and focal cortical dysplasia in children. Whereas presurgical evaluations and surgeries in patients with mesial temporal sclerosis and benign tumors recently decreased in most centers, non-lesional patients, patients requiring intracranial recordings, and neocortical resections increased. Recent developments in neurophysiological techniques (high-density electroencephalography [EEG], magnetoencephalography, electrical and magnetic source imaging, EEG-functional magnetic resonance imaging [EEG-fMRI], and recording of pathological high-frequency oscillations), structural magnetic resonance imaging (MRI) (ultra-high-field imaging at 7 Tesla, novel imaging acquisition protocols, and advanced image analysis [post-processing] techniques), functional imaging (positron emission tomography and single-photon emission computed tomography co-registered to MRI), and fMRI significantly improved non-invasive presurgical evaluation and have opened the option of epilepsy surgery to patients previously not considered surgical candidates. Technical improvements of resective surgery techniques facilitate successful and safe operations in highly delicate brain areas like the perisylvian area in operculoinsular epilepsy. Novel less-invasive surgical techniques include stereotactic radiosurgery, MR-guided laser interstitial thermal therapy, and stereotactic intracerebral EEG-guided radiofrequency thermocoagulation.
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Affiliation(s)
- Christoph Baumgartner
- Department of Neurology, General Hospital Hietzing with Neurological Center Rosenhügel, Vienna, Austria.,Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, Vienna, Austria.,Medical Faculty, Sigmund Freud University, Vienna, Austria
| | - Johannes P Koren
- Department of Neurology, General Hospital Hietzing with Neurological Center Rosenhügel, Vienna, Austria.,Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, Vienna, Austria
| | - Martha Britto-Arias
- Department of Neurology, General Hospital Hietzing with Neurological Center Rosenhügel, Vienna, Austria.,Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, Vienna, Austria
| | - Lea Zoche
- Department of Neurology, General Hospital Hietzing with Neurological Center Rosenhügel, Vienna, Austria.,Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, Vienna, Austria
| | - Susanne Pirker
- Department of Neurology, General Hospital Hietzing with Neurological Center Rosenhügel, Vienna, Austria.,Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, Vienna, Austria
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Carboni M, Rubega M, Iannotti GR, De Stefano P, Toscano G, Tourbier S, Pittau F, Hagmann P, Momjian S, Schaller K, Seeck M, Michel CM, van Mierlo P, Vulliemoz S. The network integration of epileptic activity in relation to surgical outcome. Clin Neurophysiol 2019; 130:2193-2202. [PMID: 31669753 DOI: 10.1016/j.clinph.2019.09.006] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 08/21/2019] [Accepted: 09/12/2019] [Indexed: 11/24/2022]
Abstract
OBJECTIVE Epilepsy is a network disease with epileptic activity and cognitive impairment involving large-scale brain networks. A complex network is involved in the seizure and in the interictal epileptiform discharges (IEDs). Directed connectivity analysis, describing the information transfer between brain regions, and graph analysis are applied to high-density EEG to characterise networks. METHODS We analysed 19 patients with focal epilepsy who had high-density EEG containing IED and underwent surgery. We estimated cortical activity during IED using electric source analysis in 72 atlas-based cortical regions of the individual brain MRI. We applied directed connectivity analysis (information Partial Directed Coherence) and graph analysis on these sources and compared patients with good vs poor post-operative outcome at global, hemispheric and lobar level. RESULTS We found lower network integration reflected by global, hemispheric, lobar efficiency during the IED (p < 0.05) in patients with good post-surgical outcome, compared to patients with poor outcome. Prediction was better than using the IED field or the localisation obtained by electric source imaging. CONCLUSIONS Abnormal network patterns in epilepsy are related to seizure outcome after surgery. SIGNIFICANCE Our finding may help understand networks related to a more "isolated" epileptic activity, limiting the extent of the epileptic network in patients with subsequent good post-operative outcome.
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Affiliation(s)
- M Carboni
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland.
| | - M Rubega
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - G R Iannotti
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland; Department of Neurosurgery, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - P De Stefano
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - G Toscano
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Unit of Sleep Medicine and Epilepsy, C. Mondino National Neurological Institute, Pavia, Italy
| | - S Tourbier
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - F Pittau
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - P Hagmann
- Connectomics Lab, Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
| | - S Momjian
- Department of Neurosurgery, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - K Schaller
- Department of Neurosurgery, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - M Seeck
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - C M Michel
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - P van Mierlo
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland; Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium
| | - S Vulliemoz
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland.
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Coito A, Biethahn S, Tepperberg J, Carboni M, Roelcke U, Seeck M, van Mierlo P, Gschwind M, Vulliemoz S. Interictal epileptogenic zone localization in patients with focal epilepsy using electric source imaging and directed functional connectivity from low-density EEG. Epilepsia Open 2019; 4:281-292. [PMID: 31168495 PMCID: PMC6546067 DOI: 10.1002/epi4.12318] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Revised: 02/25/2019] [Accepted: 03/15/2019] [Indexed: 01/23/2023] Open
Abstract
OBJECTIVE Electrical source imaging (ESI) is used increasingly to estimate the epileptogenic zone (EZ) in patients with epilepsy. Directed functional connectivity (DFC) coupled to ESI helps to better characterize epileptic networks, but studies on interictal activity have relied on high-density recordings. We investigated the accuracy of ESI and DFC for localizing the EZ, based on low-density clinical electroencephalography (EEG). METHODS We selected patients with the following: (a) focal epilepsy, (b) interictal spikes on standard EEG, (c) either a focal structural lesion concordant with the electroclinical semiology or good postoperative outcome. In 34 patients (20 temporal lobe epilepsy [TLE], 14 extra-TLE [ETLE]), we marked interictal spikes and estimated the cortical activity during each spike in 82 cortical regions using a patient-specific head model and distributed linear inverse solution. DFC between brain regions was computed using Granger-causal modeling followed by network topologic measures. The concordance with the presumed EZ at the sublobar level was computed using the epileptogenic lesion or the resected area in postoperative seizure-free patients. RESULTS ESI, summed outflow, and efficiency were concordant with the presumed EZ in 76% of the patients, whereas the clustering coefficient and betweenness centrality were concordant in 70% of patients. There was no significant difference between ESI and connectivity measures. In all measures, patients with TLE had a significantly higher (P < 0.05) concordance with the presumed EZ than patients with with ETLE. The brain volume accepted for concordance was significantly larger in TLE. SIGNIFICANCE ESI and DFC derived from low-density EEG can reliably estimate the EZ from interictal spikes. Connectivity measures were not superior to ESI for EZ localization during interictal spikes, but the current validation of the localization of connectivity measure is promising for other applications.
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Affiliation(s)
- Ana Coito
- Department of NeurologyCantonal Hospital AarauAarauSwitzerland
| | - Silke Biethahn
- Department of NeurologyCantonal Hospital AarauAarauSwitzerland
| | | | | | - Ulrich Roelcke
- Department of Neurology and Brain Tumor CenterCantonal Hospital AarauAarauSwitzerland
| | - Margitta Seeck
- Department of NeurologyUniversity Hospital GenevaGenevaSwitzerland
| | - Pieter van Mierlo
- Department of Electronics and Information SystemsGhent UniversityGhentBelgium
| | - Markus Gschwind
- Department of NeurologyCantonal Hospital AarauAarauSwitzerland
| | - Serge Vulliemoz
- Department of NeurologyUniversity Hospital GenevaGenevaSwitzerland
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Michel CM, Brunet D. EEG Source Imaging: A Practical Review of the Analysis Steps. Front Neurol 2019; 10:325. [PMID: 31019487 PMCID: PMC6458265 DOI: 10.3389/fneur.2019.00325] [Citation(s) in RCA: 281] [Impact Index Per Article: 56.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Accepted: 03/15/2019] [Indexed: 11/13/2022] Open
Abstract
The electroencephalogram (EEG) is one of the oldest technologies to measure neuronal activity of the human brain. It has its undisputed value in clinical diagnosis, particularly (but not exclusively) in the identification of epilepsy and sleep disorders and in the evaluation of dysfunctions in sensory transmission pathways. With the advancement of digital technologies, the analysis of EEG has moved from pure visual inspection of amplitude and frequency modulations over time to a comprehensive exploration of the temporal and spatial characteristics of the recorded signals. Today, EEG is accepted as a powerful tool to capture brain function with the unique advantage of measuring neuronal processes in the time frame in which these processes occur, namely in the sub-second range. However, it is generally stated that EEG suffers from a poor spatial resolution that makes it difficult to infer to the location of the brain areas generating the neuronal activity measured on the scalp. This statement has challenged a whole community of biomedical engineers to offer solutions to localize more precisely and more reliably the generators of the EEG activity. High-density EEG systems combined with precise information of the head anatomy and sophisticated source localization algorithms now exist that convert the EEG to a true neuroimaging modality. With these tools in hand and with the fact that EEG still remains versatile, inexpensive and portable, electrical neuroimaging has become a widely used technology to study the functions of the pathological and healthy human brain. However, several steps are needed to pass from the recording of the EEG to 3-dimensional images of neuronal activity. This review explains these different steps and illustrates them in a comprehensive analysis pipeline integrated in a stand-alone freely available academic software: Cartool. The information about how the different steps are performed in Cartool is only meant as a suggestion. Other EEG source imaging software may apply similar or different approaches to the different steps.
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Affiliation(s)
- Christoph M. Michel
- Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
- Center for Biomedical Imaging Lausanne-Geneva (CIBM), Geneva, Switzerland
| | - Denis Brunet
- Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
- Center for Biomedical Imaging Lausanne-Geneva (CIBM), Geneva, Switzerland
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