ParkinsonFranceV1, Main, Exploration, bibRecord, 000396

Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches

Identifieur interne : 000396 ( Main/Exploration ); précédent : 000395; suivant : 000397

Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches

Auteurs : Ralph G. Andrzejak ; Olivier David [France] ; Vadym Gnatkovsky [Italie] ; Fabrice Wendling [France] ; Fabrice Bartolomei [France] ; Stefano Francione [Italie] ; Philippe Kahane [France] ; Kaspar Schindler ; Marco Curtis [Italie]

Source :

RBID : Hal:hal-01260562

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

Url:

https://hal-univ-rennes1.archives-ouvertes.fr/hal-01260562

DOI: 10.1007/s10548-014-0380-8

Affiliations:

Links toward previous steps (curation, corpus...)

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Le document en format XML

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<placeName><settlement type="city">Rennes</settlement>
<region type="region" nuts="2">Région Bretagne</region>
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<orgName type="university">Université de Rennes 1</orgName>
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</author>
<author><name sortKey="Bartolomei, Fabrice" sort="Bartolomei, Fabrice" uniqKey="Bartolomei F" first="Fabrice" last="Bartolomei">Fabrice Bartolomei</name>
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  <orgName>Institut de Neurosciences des Systèmes</orgName>
  <orgName type="acronym">INS</orgName>
  <date type="start">2012</date>
  <desc>    <address>      <addrLine>Faculté de Médecine - Secteur Timone - 27 boulevard Jean Moulin 13385 Marseille Cedex 05</addrLine>
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  <orgName>Centre National de la Recherche Scientifique</orgName>
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  <date type="start">1939-10-19</date>
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<author><name sortKey="Francione, Stefano" sort="Francione, Stefano" uniqKey="Francione S" first="Stefano" last="Francione">Stefano Francione</name>
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<country>France</country>
<placeName><settlement type="city">Grenoble</settlement>
<region type="region" nuts="2">Auvergne-Rhône-Alpes</region>
<region type="old region" nuts="2">Rhône-Alpes</region>
</placeName>
<orgName type="university">Université Joseph Fourier</orgName>
<orgName type="institution" wicri:auto="newGroup">Université de Grenoble</orgName>
</affiliation>
</author>
<author><name sortKey="Schindler, Kaspar" sort="Schindler, Kaspar" uniqKey="Schindler K" first="Kaspar" last="Schindler">Kaspar Schindler</name>
</author>
<author><name sortKey="Curtis, Marco" sort="Curtis, Marco" uniqKey="Curtis M" first="Marco" last="Curtis">Marco Curtis</name>
<affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-35731" status="INCOMING">  <orgName>Department Experimental Neurophysiology</orgName>
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    </address>
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  <desc>    <address>      <country key="FR"></country>
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</hal:affiliation>
<country>Italie</country>
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<idno type="DOI">10.1007/s10548-014-0380-8</idno>
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<front><div type="abstract" xml:lang="en">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</div>
</front>
</TEI>
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<li>Italie</li>
</country>
<region><li>Auvergne-Rhône-Alpes</li>
<li>Provence-Alpes-Côte d'Azur</li>
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<li>Rennes</li>
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<orgName><li>Université Joseph Fourier</li>
<li>Université d'Aix-Marseille</li>
<li>Université de Grenoble</li>
<li>Université de Rennes 1</li>
<li>Université européenne de Bretagne</li>
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<tree><noCountry><name sortKey="Andrzejak, Ralph G" sort="Andrzejak, Ralph G" uniqKey="Andrzejak R" first="Ralph G." last="Andrzejak">Ralph G. Andrzejak</name>
<name sortKey="Schindler, Kaspar" sort="Schindler, Kaspar" uniqKey="Schindler K" first="Kaspar" last="Schindler">Kaspar Schindler</name>
</noCountry>
<country name="France"><region name="Auvergne-Rhône-Alpes"><name sortKey="David, Olivier" sort="David, Olivier" uniqKey="David O" first="Olivier" last="David">Olivier David</name>
</region>
<name sortKey="Bartolomei, Fabrice" sort="Bartolomei, Fabrice" uniqKey="Bartolomei F" first="Fabrice" last="Bartolomei">Fabrice Bartolomei</name>
<name sortKey="Kahane, Philippe" sort="Kahane, Philippe" uniqKey="Kahane P" first="Philippe" last="Kahane">Philippe Kahane</name>
<name sortKey="Wendling, Fabrice" sort="Wendling, Fabrice" uniqKey="Wendling F" first="Fabrice" last="Wendling">Fabrice Wendling</name>
</country>
<country name="Italie"><noRegion><name sortKey="Gnatkovsky, Vadym" sort="Gnatkovsky, Vadym" uniqKey="Gnatkovsky V" first="Vadym" last="Gnatkovsky">Vadym Gnatkovsky</name>
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<name sortKey="Curtis, Marco" sort="Curtis, Marco" uniqKey="Curtis M" first="Marco" last="Curtis">Marco Curtis</name>
<name sortKey="Francione, Stefano" sort="Francione, Stefano" uniqKey="Francione S" first="Stefano" last="Francione">Stefano Francione</name>
</country>
</tree>
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</record>

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	La maladie de Parkinson en France (serveur d'exploration)
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La maladie de Parkinson en France (serveur d'exploration)

Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches

Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches

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