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Wagstyl K, Kobow K, Casillas-Espinosa PM, Cole AJ, Jiménez-Jiménez D, Nariai H, Baulac S, O'Brien T, Henshall DC, Akman O, Sankar R, Galanopoulou AS, Auvin S. WONOEP 2022: Neurotechnology for the diagnosis of epilepsy. Epilepsia 2024; 65:2238-2247. [PMID: 38829313 DOI: 10.1111/epi.18028] [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: 03/11/2024] [Revised: 05/10/2024] [Accepted: 05/13/2024] [Indexed: 06/05/2024]
Abstract
Epilepsy's myriad causes and clinical presentations ensure that accurate diagnoses and targeted treatments remain a challenge. Advanced neurotechnologies are needed to better characterize individual patients across multiple modalities and analytical techniques. At the XVIth Workshop on Neurobiology of Epilepsy: Early Onset Epilepsies: Neurobiology and Novel Therapeutic Strategies (WONOEP 2022), the session on "advanced tools" highlighted a range of approaches, from molecular phenotyping of genetic epilepsy models and resected tissue samples to imaging-guided localization of epileptogenic tissue for surgical resection of focal malformations. These tools integrate cutting edge research, clinical data acquisition, and advanced computational methods to leverage the rich information contained within increasingly large datasets. A number of common challenges and opportunities emerged, including the need for multidisciplinary collaboration, multimodal integration, potential ethical challenges, and the multistage path to clinical translation. Despite these challenges, advanced epilepsy neurotechnologies offer the potential to improve our understanding of the underlying causes of epilepsy and our capacity to provide patient-specific treatment.
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Affiliation(s)
- Konrad Wagstyl
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
- Developmental Neurosciences, UCL Great Ormond Street for Child Health, UCL, London, UK
| | - Katja Kobow
- Institute of Neuropathology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Pablo M Casillas-Espinosa
- Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Parkville, Victoria, Australia
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Department of Neurology, Alfred Hospital, Melbourne, Victoria, Australia
| | - Andrew J Cole
- MGH Epilepsy Service, Division of Clinical Neurophysiology, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Diego Jiménez-Jiménez
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Hiroki Nariai
- Division of Pediatric Neurology, Department of Pediatrics, UCLA Medical Center, Los Angeles, California, USA
| | - Stéphanie Baulac
- Institut du Cerveau-Paris Brain Institute-ICM, INSERM, CNRS, Sorbonne Université, Paris, France
| | - Terence O'Brien
- Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Parkville, Victoria, Australia
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Department of Neurology, Alfred Hospital, Melbourne, Victoria, Australia
| | - David C Henshall
- FutureNeuro SFI Research Centre, RCSI University of Medicine and Health Sciences, Dublin, Ireland
- Department of Physiology and Medical Physics, RCSI University of Medicine and Health Sciences, Dublin, Ireland
| | - Ozlem Akman
- Department of Physiology, Faculty of Medicine, Demiroglu Bilim University, Istanbul, Turkey
| | - Raman Sankar
- Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, California, USA
- UCLA Children's Discovery and Innovation Institute, California, Los Angeles, USA
| | - Aristea S Galanopoulou
- Saul R. Korey Department of Neurology, Isabelle Rapin Division of Child Neurology, Laboratory of Developmental Epilepsy, Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Stéphane Auvin
- Université Paris-Cité, INSERM NeuroDiderot, Paris, France
- Pediatric Neurology Department, APHP, Robert Debré University Hospital, CRMR Epilepsies Rares, EpiCARE member, Paris, France
- Institut Universitaire de France, Paris, France
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Marawar R. Get Out the Door: Ambulatory EEG Trumps Routine EEG in the Detection of Interictal Epileptiform Abnormalities After a First Unprovoked Seizure. Epilepsy Curr 2024; 24:34-36. [PMID: 38327531 PMCID: PMC10846511 DOI: 10.1177/15357597231217647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024] Open
Abstract
Diagnostic Accuracy of Ambulatory EEG vs Routine EEG in Patients With First Single Unprovoked Seizure Hernandez-Ronquillo L, Thorpe L, Feng C, Hunter G, Dash D, Hussein T, Dolinsky C, Waterhouse K, Roy P, Jette N. Neurol Clin Pract . 2023;13(3). doi:10.1212/CPJ.0000000000200160 Background and Objective: To evaluate the diagnostic accuracy of the ambulatory EEG (aEEG) at detecting interictal epileptiform discharges (IEDs)/seizures compared with routine EEG (rEEG) and repetitive/second rEEG in patients with a first single unprovoked seizure (FSUS). We also evaluated the association between IED/seizures on aEEG and seizure recurrence within 1 year of follow-up. Methods: We prospectively evaluated 100 consecutive patients with FSUS at the provincial Single Seizure Clinic. They underwent 3 sequential EEG modalities: first rEEG, second rEEG, and aEEG. Clinical epilepsy diagnosis was ascertained based on the 2014 International League Against Epilepsy definition by a neurologist/epileptologist at the clinic. An EEG-certified epileptologist/neurologist interpreted all 3 EEGs. All patients were followed up for 52 weeks until they had either second unprovoked seizure or maintained single seizure status. Accuracy measures (sensitivity, specificity, negative and positive predictive values, and likelihood ratios), receiver operating characteristic (ROC) analysis, and area under the curve (AUC) were used to evaluate the diagnostic accuracy of each EEG modality. Life tables and the Cox proportional hazard model were used to estimate the probability and association of seizure recurrence. Results: Ambulatory EEG captured IED/seizures with a sensitivity of 72%, compared with 11% for the first rEEG and 22% for the second rEEG. The diagnostic performance of the aEEG was statistically better (AUC: 0.85) compared with the first rEEG (AUC: 0.56) and second rEEG (AUC: 0.60). There were no statistically significant differences between the 3 EEG modalities regarding specificity and positive predictive value. Finally, IED/seizure on the aEEG was associated with more than 3 times the hazard of seizure recurrence. Discussion: The overall diagnostic accuracy of aEEG at capturing IED/seizures in people presenting with FSUS was higher than the first and second rEEGs. We also found that IED/seizures on the aEEG were associated with an increased risk of seizure recurrence. Classification of Evidence: This study provides Class I evidence supporting that, in adults with First Single Unprovoked Seizure (FSUS), 24-h ambulatory EEG has increased sensitivity when compared with routine and repeated EEG.
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