Imaging the extent and location of spatiotemporally distributed epileptiform sources from MEG measurements

Non-invasive MEG/EEG source imaging provides valuable information about the epileptogenic brain areas which can be used to aid presurgical planning in focal epilepsy patients suffering from drug-resistant seizures. However, the source extent estimation for electrophysiological source imaging remains...

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Autores principales:	Xiyuan Jiang, Shuai Ye, Abbas Sohrabpour, Anto Bagić, Bin He
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2022
Materias:	Epilepsy Magnetoencephalography (MEG) Electrophysiological source imaging (ESI) Source extent imaging Computer applications to medicine. Medical informatics R858-859.7 Neurology. Diseases of the nervous system RC346-429
Acceso en línea:	https://doaj.org/article/ca156ceaa2a14b3b9db809ad6580dae0
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id	oai:doaj.org-article:ca156ceaa2a14b3b9db809ad6580dae0
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spelling	oai:doaj.org-article:ca156ceaa2a14b3b9db809ad6580dae02021-12-04T04:34:02ZImaging the extent and location of spatiotemporally distributed epileptiform sources from MEG measurements2213-158210.1016/j.nicl.2021.102903https://doaj.org/article/ca156ceaa2a14b3b9db809ad6580dae02022-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2213158221003478https://doaj.org/toc/2213-1582Non-invasive MEG/EEG source imaging provides valuable information about the epileptogenic brain areas which can be used to aid presurgical planning in focal epilepsy patients suffering from drug-resistant seizures. However, the source extent estimation for electrophysiological source imaging remains to be a challenge and is usually largely dependent on subjective choice. Our recently developed algorithm, fast spatiotemporal iteratively reweighted edge sparsity minimization (FAST-IRES) strategy, has been shown to objectively estimate extended sources from EEG recording, while it has not been applied to MEG recordings. In this work, through extensive numerical experiments and real data analysis in a group of focal drug-resistant epilepsy patients’ interictal spikes, we demonstrated the ability of FAST-IRES algorithm to image the location and extent of underlying epilepsy sources from MEG measurements. Our results indicate the merits of FAST-IRES in imaging the location and extent of epilepsy sources for pre-surgical evaluation from MEG measurements.Xiyuan JiangShuai YeAbbas SohrabpourAnto BagićBin HeElsevierarticleEpilepsyMagnetoencephalography (MEG)Electrophysiological source imaging (ESI)Source extent imagingComputer applications to medicine. Medical informaticsR858-859.7Neurology. Diseases of the nervous systemRC346-429ENNeuroImage: Clinical, Vol 33, Iss , Pp 102903- (2022)
institution	DOAJ
collection	DOAJ
language	EN
topic	Epilepsy Magnetoencephalography (MEG) Electrophysiological source imaging (ESI) Source extent imaging Computer applications to medicine. Medical informatics R858-859.7 Neurology. Diseases of the nervous system RC346-429
spellingShingle	Epilepsy Magnetoencephalography (MEG) Electrophysiological source imaging (ESI) Source extent imaging Computer applications to medicine. Medical informatics R858-859.7 Neurology. Diseases of the nervous system RC346-429 Xiyuan Jiang Shuai Ye Abbas Sohrabpour Anto Bagić Bin He Imaging the extent and location of spatiotemporally distributed epileptiform sources from MEG measurements
description	Non-invasive MEG/EEG source imaging provides valuable information about the epileptogenic brain areas which can be used to aid presurgical planning in focal epilepsy patients suffering from drug-resistant seizures. However, the source extent estimation for electrophysiological source imaging remains to be a challenge and is usually largely dependent on subjective choice. Our recently developed algorithm, fast spatiotemporal iteratively reweighted edge sparsity minimization (FAST-IRES) strategy, has been shown to objectively estimate extended sources from EEG recording, while it has not been applied to MEG recordings. In this work, through extensive numerical experiments and real data analysis in a group of focal drug-resistant epilepsy patients’ interictal spikes, we demonstrated the ability of FAST-IRES algorithm to image the location and extent of underlying epilepsy sources from MEG measurements. Our results indicate the merits of FAST-IRES in imaging the location and extent of epilepsy sources for pre-surgical evaluation from MEG measurements.
format	article
author	Xiyuan Jiang Shuai Ye Abbas Sohrabpour Anto Bagić Bin He
author_facet	Xiyuan Jiang Shuai Ye Abbas Sohrabpour Anto Bagić Bin He
author_sort	Xiyuan Jiang
title	Imaging the extent and location of spatiotemporally distributed epileptiform sources from MEG measurements
title_short	Imaging the extent and location of spatiotemporally distributed epileptiform sources from MEG measurements
title_full	Imaging the extent and location of spatiotemporally distributed epileptiform sources from MEG measurements
title_fullStr	Imaging the extent and location of spatiotemporally distributed epileptiform sources from MEG measurements
title_full_unstemmed	Imaging the extent and location of spatiotemporally distributed epileptiform sources from MEG measurements
title_sort	imaging the extent and location of spatiotemporally distributed epileptiform sources from meg measurements
publisher	Elsevier
publishDate	2022
url	https://doaj.org/article/ca156ceaa2a14b3b9db809ad6580dae0
work_keys_str_mv	AT xiyuanjiang imagingtheextentandlocationofspatiotemporallydistributedepileptiformsourcesfrommegmeasurements AT shuaiye imagingtheextentandlocationofspatiotemporallydistributedepileptiformsourcesfrommegmeasurements AT abbassohrabpour imagingtheextentandlocationofspatiotemporallydistributedepileptiformsourcesfrommegmeasurements AT antobagic imagingtheextentandlocationofspatiotemporallydistributedepileptiformsourcesfrommegmeasurements AT binhe imagingtheextentandlocationofspatiotemporallydistributedepileptiformsourcesfrommegmeasurements
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Imaging the extent and location of spatiotemporally distributed epileptiform sources from MEG measurements

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