Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches
In patients diagnosed with pharmaco-resistant epilepsy, cerebral areas responsible for seizure generation can be defined by performing implantation of intracranial electrodes. The identification of the epileptogenic zone (EZ) is based on visual inspection of the intracranial electroencephalogram (IE...
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description | In patients diagnosed with pharmaco-resistant epilepsy, cerebral areas responsible for seizure generation can be defined by performing implantation of intracranial electrodes. The identification of the epileptogenic zone (EZ) is based on visual inspection of the intracranial electroencephalogram (IEEG) performed by highly qualified neurophysiologists. New computer-based quantitative EEG analyses have been developed in collaboration with the signal analysis community to expedite EZ detection. The aim of the present report is to compare different signal analysis approaches developed in four different European laboratories working in close collaboration with four European Epilepsy Centers. Computer-based signal analysis methods were retrospectively applied to IEEG recordings performed in four patients undergoing pre-surgical exploration of pharmaco-resistant epilepsy. The four methods elaborated by the different teams to identify the EZ are based either on frequency analysis, on nonlinear signal analysis, on connectivity measures or on statistical parametric mapping of epileptogenicity indices. All methods converge on the identification of EZ in patients that present with fast activity at seizure onset. When traditional visual inspection was not successful in detecting EZ on IEEG, the different signal analysis methods produced highly discordant results. Quantitative analysis of IEEG recordings complement clinical evaluation by contributing to the study of epileptogenic networks during seizures. We demonstrate that the degree of sensitivity of different computer-based methods to detect the EZ in respect to visual EEG inspection depends on the specific seizure pattern. |
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We demonstrate that the degree of sensitivity of different computer-based methods to detect the EZ in respect to visual EEG inspection depends on the specific seizure pattern.</description><identifier>ISSN: 0896-0267</identifier><identifier>EISSN: 1573-6792</identifier><identifier>DOI: 10.1007/s10548-014-0380-8</identifier><identifier>PMID: 24929558</identifier><identifier>CODEN: BRTOEZ</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Adult ; Bioengineering ; Biomedical and Life Sciences ; Biomedicine ; Brain - pathology ; Brain - physiopathology ; Brain Mapping ; Brain Waves - physiology ; Brief Communication ; Electroencephalography ; Epilepsy - pathology ; Female ; Humans ; Life Sciences ; Male ; Neurology ; Neurosciences ; Psychiatry ; Signal Processing, Computer-Assisted ; Young Adult</subject><ispartof>Brain topography, 2015-11, Vol.28 (6), p.832-837</ispartof><rights>Springer Science+Business Media New York 2014</rights><rights>Springer Science+Business Media New York 2015</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c585t-50fc35d77f184b3c4adce6f23fe92fb1f0230c297cc3ac1c19f4b8274757c93d3</citedby><cites>FETCH-LOGICAL-c585t-50fc35d77f184b3c4adce6f23fe92fb1f0230c297cc3ac1c19f4b8274757c93d3</cites><orcidid>0000-0003-2428-9665 ; 0000-0003-0776-0216 ; 0000-0002-1678-0297</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10548-014-0380-8$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10548-014-0380-8$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24929558$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://univ-rennes.hal.science/hal-01260562$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Andrzejak, Ralph G.</creatorcontrib><creatorcontrib>David, Olivier</creatorcontrib><creatorcontrib>Gnatkovsky, Vadym</creatorcontrib><creatorcontrib>Wendling, Fabrice</creatorcontrib><creatorcontrib>Bartolomei, Fabrice</creatorcontrib><creatorcontrib>Francione, Stefano</creatorcontrib><creatorcontrib>Kahane, Philippe</creatorcontrib><creatorcontrib>Schindler, Kaspar</creatorcontrib><creatorcontrib>de Curtis, Marco</creatorcontrib><title>Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches</title><title>Brain topography</title><addtitle>Brain Topogr</addtitle><addtitle>Brain Topogr</addtitle><description>In patients diagnosed with pharmaco-resistant epilepsy, cerebral areas responsible for seizure generation can be defined by performing implantation of intracranial electrodes. The identification of the epileptogenic zone (EZ) is based on visual inspection of the intracranial electroencephalogram (IEEG) performed by highly qualified neurophysiologists. New computer-based quantitative EEG analyses have been developed in collaboration with the signal analysis community to expedite EZ detection. The aim of the present report is to compare different signal analysis approaches developed in four different European laboratories working in close collaboration with four European Epilepsy Centers. Computer-based signal analysis methods were retrospectively applied to IEEG recordings performed in four patients undergoing pre-surgical exploration of pharmaco-resistant epilepsy. The four methods elaborated by the different teams to identify the EZ are based either on frequency analysis, on nonlinear signal analysis, on connectivity measures or on statistical parametric mapping of epileptogenicity indices. All methods converge on the identification of EZ in patients that present with fast activity at seizure onset. When traditional visual inspection was not successful in detecting EZ on IEEG, the different signal analysis methods produced highly discordant results. Quantitative analysis of IEEG recordings complement clinical evaluation by contributing to the study of epileptogenic networks during seizures. We demonstrate that the degree of sensitivity of different computer-based methods to detect the EZ in respect to visual EEG inspection depends on the specific seizure pattern.</description><subject>Adult</subject><subject>Bioengineering</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Brain - pathology</subject><subject>Brain - physiopathology</subject><subject>Brain Mapping</subject><subject>Brain Waves - physiology</subject><subject>Brief Communication</subject><subject>Electroencephalography</subject><subject>Epilepsy - pathology</subject><subject>Female</subject><subject>Humans</subject><subject>Life Sciences</subject><subject>Male</subject><subject>Neurology</subject><subject>Neurosciences</subject><subject>Psychiatry</subject><subject>Signal Processing, Computer-Assisted</subject><subject>Young Adult</subject><issn>0896-0267</issn><issn>1573-6792</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNp1kc2OFCEUhYnROG3rA7gxJG50UXqBoijcdSbtzCSd-De6cENoCnqYVEMNVI0ZH8Jnlk6NHWPiBnK53z33kIPQcwJvCIB4mwnwuq2A1BWwFqr2AVoQLljVCEkfogW0sqmANuIEPcn5GgCYFOIxOqG1pJLzdoF-baLRvf-pRx8Djg6vB9_bYYw7G7zB32OwuDQ-JlvlKe18gfFFGJM2SQdfivX6DH-2JqbOh11-hy_jD506rPG3ItsdZT9NOox-LPWtxV_8LpTRVTnuss94NQwpanNl81P0yOk-22f39xJ9fb--PD2vNh_OLk5Xm8rwlo8VB2cY74RwpK23zNS6M7ZxlDkrqdsSB5SBoVIYw7QhhkhXb1sqasGFkaxjS_R61r3SvRqS3-t0p6L26ny1UYc3ILQB3tBbUthXM1tM3kw2j2rvs7F9r4ONU1ZEUCKJaMrOJXr5D3odp1S-OVNEAKN1ochMmRRzTtYdHRBQh2DVHGwxUatDsKotMy_ulaft3nbHiT9JFoDOQC6tsLPpr9X_Vf0NU2CuWQ</recordid><startdate>20151101</startdate><enddate>20151101</enddate><creator>Andrzejak, Ralph G.</creator><creator>David, Olivier</creator><creator>Gnatkovsky, Vadym</creator><creator>Wendling, Fabrice</creator><creator>Bartolomei, Fabrice</creator><creator>Francione, Stefano</creator><creator>Kahane, Philippe</creator><creator>Schindler, Kaspar</creator><creator>de Curtis, Marco</creator><general>Springer US</general><general>Springer Nature B.V</general><general>Springer Verlag</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88G</scope><scope>8AO</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M7P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope><scope>1XC</scope><orcidid>https://orcid.org/0000-0003-2428-9665</orcidid><orcidid>https://orcid.org/0000-0003-0776-0216</orcidid><orcidid>https://orcid.org/0000-0002-1678-0297</orcidid></search><sort><creationdate>20151101</creationdate><title>Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches</title><author>Andrzejak, Ralph G. ; David, Olivier ; Gnatkovsky, Vadym ; Wendling, Fabrice ; Bartolomei, Fabrice ; Francione, Stefano ; Kahane, Philippe ; Schindler, Kaspar ; de Curtis, Marco</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c585t-50fc35d77f184b3c4adce6f23fe92fb1f0230c297cc3ac1c19f4b8274757c93d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Adult</topic><topic>Bioengineering</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Brain - pathology</topic><topic>Brain - physiopathology</topic><topic>Brain Mapping</topic><topic>Brain Waves - physiology</topic><topic>Brief Communication</topic><topic>Electroencephalography</topic><topic>Epilepsy - pathology</topic><topic>Female</topic><topic>Humans</topic><topic>Life Sciences</topic><topic>Male</topic><topic>Neurology</topic><topic>Neurosciences</topic><topic>Psychiatry</topic><topic>Signal Processing, Computer-Assisted</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Andrzejak, Ralph G.</creatorcontrib><creatorcontrib>David, Olivier</creatorcontrib><creatorcontrib>Gnatkovsky, Vadym</creatorcontrib><creatorcontrib>Wendling, Fabrice</creatorcontrib><creatorcontrib>Bartolomei, Fabrice</creatorcontrib><creatorcontrib>Francione, Stefano</creatorcontrib><creatorcontrib>Kahane, Philippe</creatorcontrib><creatorcontrib>Schindler, Kaspar</creatorcontrib><creatorcontrib>de Curtis, Marco</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest Psychology</collection><collection>Biological Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Brain topography</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Andrzejak, Ralph G.</au><au>David, Olivier</au><au>Gnatkovsky, Vadym</au><au>Wendling, Fabrice</au><au>Bartolomei, Fabrice</au><au>Francione, Stefano</au><au>Kahane, Philippe</au><au>Schindler, Kaspar</au><au>de Curtis, Marco</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches</atitle><jtitle>Brain topography</jtitle><stitle>Brain Topogr</stitle><addtitle>Brain Topogr</addtitle><date>2015-11-01</date><risdate>2015</risdate><volume>28</volume><issue>6</issue><spage>832</spage><epage>837</epage><pages>832-837</pages><issn>0896-0267</issn><eissn>1573-6792</eissn><coden>BRTOEZ</coden><abstract>In patients diagnosed with pharmaco-resistant epilepsy, cerebral areas responsible for seizure generation can be defined by performing implantation of intracranial electrodes. The identification of the epileptogenic zone (EZ) is based on visual inspection of the intracranial electroencephalogram (IEEG) performed by highly qualified neurophysiologists. New computer-based quantitative EEG analyses have been developed in collaboration with the signal analysis community to expedite EZ detection. The aim of the present report is to compare different signal analysis approaches developed in four different European laboratories working in close collaboration with four European Epilepsy Centers. Computer-based signal analysis methods were retrospectively applied to IEEG recordings performed in four patients undergoing pre-surgical exploration of pharmaco-resistant epilepsy. The four methods elaborated by the different teams to identify the EZ are based either on frequency analysis, on nonlinear signal analysis, on connectivity measures or on statistical parametric mapping of epileptogenicity indices. All methods converge on the identification of EZ in patients that present with fast activity at seizure onset. When traditional visual inspection was not successful in detecting EZ on IEEG, the different signal analysis methods produced highly discordant results. Quantitative analysis of IEEG recordings complement clinical evaluation by contributing to the study of epileptogenic networks during seizures. We demonstrate that the degree of sensitivity of different computer-based methods to detect the EZ in respect to visual EEG inspection depends on the specific seizure pattern.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>24929558</pmid><doi>10.1007/s10548-014-0380-8</doi><tpages>6</tpages><orcidid>https://orcid.org/0000-0003-2428-9665</orcidid><orcidid>https://orcid.org/0000-0003-0776-0216</orcidid><orcidid>https://orcid.org/0000-0002-1678-0297</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adult Bioengineering Biomedical and Life Sciences Biomedicine Brain - pathology Brain - physiopathology Brain Mapping Brain Waves - physiology Brief Communication Electroencephalography Epilepsy - pathology Female Humans Life Sciences Male Neurology Neurosciences Psychiatry Signal Processing, Computer-Assisted Young Adult |
title | Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches |
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