Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates

Autores
Princich, Juan Pablo; Wassermann, Demian; Latini, Facundo; Oddo, Silvia Andrea; Blenkmann, Alejandro Omar; Seifer, Gustavo; Kochen, Sara Silvia
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Depth intracranial electrodes (IEs) placement is one of the most used procedures to identify the epileptogenic zone (EZ) in surgical treatment of drug resistant epilepsy patients, about 20?30% of this population. IEs localization is therefore a critical issue defining the EZ and its relation with eloquent functional areas. That information is then used to target the resective surgery and has great potential to affect outcome. We designed a methodological procedure intended to avoid the need for highly specialized medical resources and reduce time to identify the anatomical location of IEs, during the first instances of intracranial EEG recordings. This workflow is based on established open source software; 3D Slicer and Freesurfer that uses MRI and Post-implant CT fusion for the localization of IEs and its relation with automatic labeled surrounding cortex. To test this hypothesis we assessed the time elapsed between the surgical implantation process and the final anatomical localization of IEs by means of our proposed method compared against traditional visual analysis of raw post-implant imaging in two groups of patients. All IEs were identified in the first 24 H (6?24 H) of implantation using our method in 4 patients of the first group. For the control group; all IEs were identified by experts with an overall time range of 36 h to 3 days using traditional visual analysis. It included (7 patients), 3 patients implanted with IEs and the same 4 patients from the first group. Time to localization was restrained in this group by the specialized personnel and the image quality available. To validate our method; we trained two inexperienced operators to assess the position of IEs contacts on four patients (5 IEs) using the proposed method. We quantified the discrepancies between operators and we also assessed the efficiency of our method to define the EZ comparing the findings against the results of traditional analysis.
Fil: Princich, Juan Pablo. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; Argentina
Fil: Wassermann, Demian. Harvard Medical School; Estados Unidos de América;
Fil: Latini, Facundo. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; Argentina
Fil: Oddo, Silvia Andrea. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; Argentina
Fil: Blenkmann, Alejandro Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurcs. ; Argentina
Fil: Seifer, Gustavo. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; Argentina
Fil: Kochen, Sara Silvia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurcs. ; Argentina
Materia
epilepsy
electrodes
seeg
MRI
localization
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/1246
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/1246
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidatesPrincich, Juan PabloWassermann, DemianLatini, FacundoOddo, Silvia AndreaBlenkmann, Alejandro OmarSeifer, GustavoKochen, Sara SilviaepilepsyelectrodesseegMRIlocalizationhttps://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3Depth intracranial electrodes (IEs) placement is one of the most used procedures to identify the epileptogenic zone (EZ) in surgical treatment of drug resistant epilepsy patients, about 20?30% of this population. IEs localization is therefore a critical issue defining the EZ and its relation with eloquent functional areas. That information is then used to target the resective surgery and has great potential to affect outcome. We designed a methodological procedure intended to avoid the need for highly specialized medical resources and reduce time to identify the anatomical location of IEs, during the first instances of intracranial EEG recordings. This workflow is based on established open source software; 3D Slicer and Freesurfer that uses MRI and Post-implant CT fusion for the localization of IEs and its relation with automatic labeled surrounding cortex. To test this hypothesis we assessed the time elapsed between the surgical implantation process and the final anatomical localization of IEs by means of our proposed method compared against traditional visual analysis of raw post-implant imaging in two groups of patients. All IEs were identified in the first 24 H (6?24 H) of implantation using our method in 4 patients of the first group. For the control group; all IEs were identified by experts with an overall time range of 36 h to 3 days using traditional visual analysis. It included (7 patients), 3 patients implanted with IEs and the same 4 patients from the first group. Time to localization was restrained in this group by the specialized personnel and the image quality available. To validate our method; we trained two inexperienced operators to assess the position of IEs contacts on four patients (5 IEs) using the proposed method. We quantified the discrepancies between operators and we also assessed the efficiency of our method to define the EZ comparing the findings against the results of traditional analysis.Fil: Princich, Juan Pablo. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; ArgentinaFil: Wassermann, Demian. Harvard Medical School; Estados Unidos de América;Fil: Latini, Facundo. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; ArgentinaFil: Oddo, Silvia Andrea. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; ArgentinaFil: Blenkmann, Alejandro Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurcs. ; ArgentinaFil: Seifer, Gustavo. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; ArgentinaFil: Kochen, Sara Silvia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurcs. ; ArgentinaFrontiers Res Found2013-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/1246Princich, Juan Pablo; Wassermann, Demian; Latini, Facundo; Oddo, Silvia Andrea; Blenkmann, Alejandro Omar; et al.; Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates; Frontiers Res Found; Frontiers In Human Neuroscience; 7; 12-2013; 260-2701662-5161enginfo:eu-repo/semantics/altIdentifier/doi/10.3389/fnins.2013.00260&utm_source=Email_to_authors_&utm_medium=Email&utm_content=T1_11.5e1_author&utm_campaign=Email_publication&journalName=Frontiers_in_Neurosciinfo:eu-repo/semantics/altIdentifier/url/http://www.frontiersin.org/Journal/Abstract.aspx?s=1304&name=brain_imaging_methods&ART_DOI=10.3389/fnins.2013.00260&utm_source=Email_to_authors_&utm_medium=Email&utm_content=T1_11.5e1_author&utm_campaign=Email_publication&journalName=Frontiers_in_Neurosciinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:55:34Zoai:ri.conicet.gov.ar:11336/1246instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:55:34.525CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates
title Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates
spellingShingle Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates
Princich, Juan Pablo
epilepsy
electrodes
seeg
MRI
localization
title_short Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates
title_full Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates
title_fullStr Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates
title_full_unstemmed Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates
title_sort Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates
dc.creator.none.fl_str_mv Princich, Juan Pablo
Wassermann, Demian
Latini, Facundo
Oddo, Silvia Andrea
Blenkmann, Alejandro Omar
Seifer, Gustavo
Kochen, Sara Silvia
author Princich, Juan Pablo
author_facet Princich, Juan Pablo
Wassermann, Demian
Latini, Facundo
Oddo, Silvia Andrea
Blenkmann, Alejandro Omar
Seifer, Gustavo
Kochen, Sara Silvia
author_role author
author2 Wassermann, Demian
Latini, Facundo
Oddo, Silvia Andrea
Blenkmann, Alejandro Omar
Seifer, Gustavo
Kochen, Sara Silvia
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv epilepsy
electrodes
seeg
MRI
localization
topic epilepsy
electrodes
seeg
MRI
localization
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.1
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Depth intracranial electrodes (IEs) placement is one of the most used procedures to identify the epileptogenic zone (EZ) in surgical treatment of drug resistant epilepsy patients, about 20?30% of this population. IEs localization is therefore a critical issue defining the EZ and its relation with eloquent functional areas. That information is then used to target the resective surgery and has great potential to affect outcome. We designed a methodological procedure intended to avoid the need for highly specialized medical resources and reduce time to identify the anatomical location of IEs, during the first instances of intracranial EEG recordings. This workflow is based on established open source software; 3D Slicer and Freesurfer that uses MRI and Post-implant CT fusion for the localization of IEs and its relation with automatic labeled surrounding cortex. To test this hypothesis we assessed the time elapsed between the surgical implantation process and the final anatomical localization of IEs by means of our proposed method compared against traditional visual analysis of raw post-implant imaging in two groups of patients. All IEs were identified in the first 24 H (6?24 H) of implantation using our method in 4 patients of the first group. For the control group; all IEs were identified by experts with an overall time range of 36 h to 3 days using traditional visual analysis. It included (7 patients), 3 patients implanted with IEs and the same 4 patients from the first group. Time to localization was restrained in this group by the specialized personnel and the image quality available. To validate our method; we trained two inexperienced operators to assess the position of IEs contacts on four patients (5 IEs) using the proposed method. We quantified the discrepancies between operators and we also assessed the efficiency of our method to define the EZ comparing the findings against the results of traditional analysis.
Fil: Princich, Juan Pablo. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; Argentina
Fil: Wassermann, Demian. Harvard Medical School; Estados Unidos de América;
Fil: Latini, Facundo. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; Argentina
Fil: Oddo, Silvia Andrea. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; Argentina
Fil: Blenkmann, Alejandro Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurcs. ; Argentina
Fil: Seifer, Gustavo. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; Argentina
Fil: Kochen, Sara Silvia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurcs. ; Argentina
description Depth intracranial electrodes (IEs) placement is one of the most used procedures to identify the epileptogenic zone (EZ) in surgical treatment of drug resistant epilepsy patients, about 20?30% of this population. IEs localization is therefore a critical issue defining the EZ and its relation with eloquent functional areas. That information is then used to target the resective surgery and has great potential to affect outcome. We designed a methodological procedure intended to avoid the need for highly specialized medical resources and reduce time to identify the anatomical location of IEs, during the first instances of intracranial EEG recordings. This workflow is based on established open source software; 3D Slicer and Freesurfer that uses MRI and Post-implant CT fusion for the localization of IEs and its relation with automatic labeled surrounding cortex. To test this hypothesis we assessed the time elapsed between the surgical implantation process and the final anatomical localization of IEs by means of our proposed method compared against traditional visual analysis of raw post-implant imaging in two groups of patients. All IEs were identified in the first 24 H (6?24 H) of implantation using our method in 4 patients of the first group. For the control group; all IEs were identified by experts with an overall time range of 36 h to 3 days using traditional visual analysis. It included (7 patients), 3 patients implanted with IEs and the same 4 patients from the first group. Time to localization was restrained in this group by the specialized personnel and the image quality available. To validate our method; we trained two inexperienced operators to assess the position of IEs contacts on four patients (5 IEs) using the proposed method. We quantified the discrepancies between operators and we also assessed the efficiency of our method to define the EZ comparing the findings against the results of traditional analysis.
publishDate 2013
dc.date.none.fl_str_mv 2013-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/1246
Princich, Juan Pablo; Wassermann, Demian; Latini, Facundo; Oddo, Silvia Andrea; Blenkmann, Alejandro Omar; et al.; Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates; Frontiers Res Found; Frontiers In Human Neuroscience; 7; 12-2013; 260-270
1662-5161
url http://hdl.handle.net/11336/1246
identifier_str_mv Princich, Juan Pablo; Wassermann, Demian; Latini, Facundo; Oddo, Silvia Andrea; Blenkmann, Alejandro Omar; et al.; Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates; Frontiers Res Found; Frontiers In Human Neuroscience; 7; 12-2013; 260-270
1662-5161
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3389/fnins.2013.00260&utm_source=Email_to_authors_&utm_medium=Email&utm_content=T1_11.5e1_author&utm_campaign=Email_publication&journalName=Frontiers_in_Neurosci
info:eu-repo/semantics/altIdentifier/url/http://www.frontiersin.org/Journal/Abstract.aspx?s=1304&name=brain_imaging_methods&ART_DOI=10.3389/fnins.2013.00260&utm_source=Email_to_authors_&utm_medium=Email&utm_content=T1_11.5e1_author&utm_campaign=Email_publication&journalName=Frontiers_in_Neurosci
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Frontiers Res Found
publisher.none.fl_str_mv Frontiers Res Found
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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