Electroencephalography derived connectivity informing epilepsy surgical planning: Towards clinical applications and future perspectives
Epilepsy is one of the most diffused neurological disorders, affecting 50 million people worldwide. Around 30% of patients have drug-resistant epilepsy (DRE), defined as failure of at least two tolerated antiseizure medications (ASMs) to achieve sustained seizure freedom. Brain surgery is an effecti...
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Elsevier
2024-01-01
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| Series: | NeuroImage: Clinical |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S221315822400144X |
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| author | Giulia Salvatici Giovanni Pellegrino Marco Perulli Alberto Danieli Paolo Bonanni Gian Marco Duma |
| author_facet | Giulia Salvatici Giovanni Pellegrino Marco Perulli Alberto Danieli Paolo Bonanni Gian Marco Duma |
| author_sort | Giulia Salvatici |
| collection | DOAJ |
| description | Epilepsy is one of the most diffused neurological disorders, affecting 50 million people worldwide. Around 30% of patients have drug-resistant epilepsy (DRE), defined as failure of at least two tolerated antiseizure medications (ASMs) to achieve sustained seizure freedom. Brain surgery is an effective therapeutic approach in this group, hinging on the accurate localization of the epileptic focus. The latter task is complex and requires multimodal investigation methods. Epilepsy is also a network disorder and represents one of the best application scenarios of methods leveraging brain functional organization at large scales. Connectivity analysis represents a promising tool for improving surgical assessment, enabling better identification of candidates who could benefit the most from epilepsy surgery. The scalp electroencephalography (EEG) is the most relevant tool to characterize epileptic activity. The EEG has benefited significantly from technological advancement across the last decades. Firstly, electrical source imaging (ESI) allows the reconstruction of electrical activity detected by EEG at the cortex level; secondly, functional connectivity (FC) allows the assessment of functional dependencies across brain areas. The EEG has therefore expanded potential applications in the localization and characterization of the epileptogenic network for surgical planning. As the translation of these methods in clinical practice is little discussed in the literature, we reviewed the investigations using EEG-derived FC. We showed that the FC-informed identification of the epileptic networks improves the localization precision in focal epilepsy. We discussed the heterogeneity in the results and methodology preventing prompt research-to-clinic translation. We finally provided practical suggestions for promoting the applicability of FC-based research in real clinical practice, looking for future research. |
| format | Article |
| id | doaj-art-c95aee3286a0498daa3c57ebd00ef3e0 |
| institution | DOAJ |
| issn | 2213-1582 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage: Clinical |
| spelling | doaj-art-c95aee3286a0498daa3c57ebd00ef3e02025-08-20T02:49:00ZengElsevierNeuroImage: Clinical2213-15822024-01-014410370310.1016/j.nicl.2024.103703Electroencephalography derived connectivity informing epilepsy surgical planning: Towards clinical applications and future perspectivesGiulia Salvatici0Giovanni Pellegrino1Marco Perulli2Alberto Danieli3Paolo Bonanni4Gian Marco Duma5Scientific Institute IRCCS E.Medea, Epilepsy and Clinical Neurophysiology Unit, Conegliano 31015, ItalyClinical Neurological Sciences Department, Schulich School of Medicine and Dentistry, Western University, London N6A5C1, Canada; Corresponding author.Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, ItalyScientific Institute IRCCS E.Medea, Epilepsy and Clinical Neurophysiology Unit, Conegliano 31015, ItalyScientific Institute IRCCS E.Medea, Epilepsy and Clinical Neurophysiology Unit, Conegliano 31015, ItalyScientific Institute IRCCS E.Medea, Epilepsy and Clinical Neurophysiology Unit, Conegliano 31015, ItalyEpilepsy is one of the most diffused neurological disorders, affecting 50 million people worldwide. Around 30% of patients have drug-resistant epilepsy (DRE), defined as failure of at least two tolerated antiseizure medications (ASMs) to achieve sustained seizure freedom. Brain surgery is an effective therapeutic approach in this group, hinging on the accurate localization of the epileptic focus. The latter task is complex and requires multimodal investigation methods. Epilepsy is also a network disorder and represents one of the best application scenarios of methods leveraging brain functional organization at large scales. Connectivity analysis represents a promising tool for improving surgical assessment, enabling better identification of candidates who could benefit the most from epilepsy surgery. The scalp electroencephalography (EEG) is the most relevant tool to characterize epileptic activity. The EEG has benefited significantly from technological advancement across the last decades. Firstly, electrical source imaging (ESI) allows the reconstruction of electrical activity detected by EEG at the cortex level; secondly, functional connectivity (FC) allows the assessment of functional dependencies across brain areas. The EEG has therefore expanded potential applications in the localization and characterization of the epileptogenic network for surgical planning. As the translation of these methods in clinical practice is little discussed in the literature, we reviewed the investigations using EEG-derived FC. We showed that the FC-informed identification of the epileptic networks improves the localization precision in focal epilepsy. We discussed the heterogeneity in the results and methodology preventing prompt research-to-clinic translation. We finally provided practical suggestions for promoting the applicability of FC-based research in real clinical practice, looking for future research.http://www.sciencedirect.com/science/article/pii/S221315822400144XEpilepsy surgeryDrug-resistant epilepsyEEGFunctional connectivityBrain dynamics |
| spellingShingle | Giulia Salvatici Giovanni Pellegrino Marco Perulli Alberto Danieli Paolo Bonanni Gian Marco Duma Electroencephalography derived connectivity informing epilepsy surgical planning: Towards clinical applications and future perspectives NeuroImage: Clinical Epilepsy surgery Drug-resistant epilepsy EEG Functional connectivity Brain dynamics |
| title | Electroencephalography derived connectivity informing epilepsy surgical planning: Towards clinical applications and future perspectives |
| title_full | Electroencephalography derived connectivity informing epilepsy surgical planning: Towards clinical applications and future perspectives |
| title_fullStr | Electroencephalography derived connectivity informing epilepsy surgical planning: Towards clinical applications and future perspectives |
| title_full_unstemmed | Electroencephalography derived connectivity informing epilepsy surgical planning: Towards clinical applications and future perspectives |
| title_short | Electroencephalography derived connectivity informing epilepsy surgical planning: Towards clinical applications and future perspectives |
| title_sort | electroencephalography derived connectivity informing epilepsy surgical planning towards clinical applications and future perspectives |
| topic | Epilepsy surgery Drug-resistant epilepsy EEG Functional connectivity Brain dynamics |
| url | http://www.sciencedirect.com/science/article/pii/S221315822400144X |
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