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Computer-Assisted Planning for Stereoelectroencephalography (SEEG)
Stereoelectroencephalography (SEEG) is a diagnostic procedure in which multiple electrodes are stereotactically implanted within predefined areas of the brain to identify the seizure onset zone, which needs to be removed to achieve remission of focal epilepsy. Computer-assisted planning (CAP) has be...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6985077/ https://www.ncbi.nlm.nih.gov/pubmed/31432448 http://dx.doi.org/10.1007/s13311-019-00774-9 |
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author | Vakharia, Vejay N. Sparks, Rachel Miserocchi, Anna Vos, Sjoerd B. O’Keeffe, Aidan Rodionov, Roman McEvoy, Andrew W. Ourselin, Sebastien Duncan, John S. |
author_facet | Vakharia, Vejay N. Sparks, Rachel Miserocchi, Anna Vos, Sjoerd B. O’Keeffe, Aidan Rodionov, Roman McEvoy, Andrew W. Ourselin, Sebastien Duncan, John S. |
author_sort | Vakharia, Vejay N. |
collection | PubMed |
description | Stereoelectroencephalography (SEEG) is a diagnostic procedure in which multiple electrodes are stereotactically implanted within predefined areas of the brain to identify the seizure onset zone, which needs to be removed to achieve remission of focal epilepsy. Computer-assisted planning (CAP) has been shown to improve trajectory safety metrics and generate clinically feasible trajectories in a fraction of the time needed for manual planning. We report a prospective validation study of the use of EpiNav (UCL, London, UK) as a clinical decision support software for SEEG. Thirteen consecutive patients (125 electrodes) undergoing SEEG were prospectively recruited. EpiNav was used to generate 3D models of critical structures (including vasculature) and other important regions of interest. Manual planning utilizing the same 3D models was performed in advance of CAP. CAP was subsequently employed to automatically generate a plan for each patient. The treating neurosurgeon was able to modify CAP generated plans based on their preference. The plan with the lowest risk score metric was stereotactically implanted. In all cases (13/13), the final CAP generated plan returned a lower mean risk score and was stereotactically implanted. No complication or adverse event occurred. CAP trajectories were generated in 30% of the time with significantly lower risk scores compared to manually generated. EpiNav has successfully been integrated as a clinical decision support software (CDSS) into the clinical pathway for SEEG implantations at our institution. To our knowledge, this is the first prospective study of a complex CDSS in stereotactic neurosurgery and provides the highest level of evidence to date. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13311-019-00774-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6985077 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-69850772020-02-06 Computer-Assisted Planning for Stereoelectroencephalography (SEEG) Vakharia, Vejay N. Sparks, Rachel Miserocchi, Anna Vos, Sjoerd B. O’Keeffe, Aidan Rodionov, Roman McEvoy, Andrew W. Ourselin, Sebastien Duncan, John S. Neurotherapeutics Original Article Stereoelectroencephalography (SEEG) is a diagnostic procedure in which multiple electrodes are stereotactically implanted within predefined areas of the brain to identify the seizure onset zone, which needs to be removed to achieve remission of focal epilepsy. Computer-assisted planning (CAP) has been shown to improve trajectory safety metrics and generate clinically feasible trajectories in a fraction of the time needed for manual planning. We report a prospective validation study of the use of EpiNav (UCL, London, UK) as a clinical decision support software for SEEG. Thirteen consecutive patients (125 electrodes) undergoing SEEG were prospectively recruited. EpiNav was used to generate 3D models of critical structures (including vasculature) and other important regions of interest. Manual planning utilizing the same 3D models was performed in advance of CAP. CAP was subsequently employed to automatically generate a plan for each patient. The treating neurosurgeon was able to modify CAP generated plans based on their preference. The plan with the lowest risk score metric was stereotactically implanted. In all cases (13/13), the final CAP generated plan returned a lower mean risk score and was stereotactically implanted. No complication or adverse event occurred. CAP trajectories were generated in 30% of the time with significantly lower risk scores compared to manually generated. EpiNav has successfully been integrated as a clinical decision support software (CDSS) into the clinical pathway for SEEG implantations at our institution. To our knowledge, this is the first prospective study of a complex CDSS in stereotactic neurosurgery and provides the highest level of evidence to date. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13311-019-00774-9) contains supplementary material, which is available to authorized users. Springer International Publishing 2019-08-20 2019-10 /pmc/articles/PMC6985077/ /pubmed/31432448 http://dx.doi.org/10.1007/s13311-019-00774-9 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Article Vakharia, Vejay N. Sparks, Rachel Miserocchi, Anna Vos, Sjoerd B. O’Keeffe, Aidan Rodionov, Roman McEvoy, Andrew W. Ourselin, Sebastien Duncan, John S. Computer-Assisted Planning for Stereoelectroencephalography (SEEG) |
title | Computer-Assisted Planning for Stereoelectroencephalography (SEEG) |
title_full | Computer-Assisted Planning for Stereoelectroencephalography (SEEG) |
title_fullStr | Computer-Assisted Planning for Stereoelectroencephalography (SEEG) |
title_full_unstemmed | Computer-Assisted Planning for Stereoelectroencephalography (SEEG) |
title_short | Computer-Assisted Planning for Stereoelectroencephalography (SEEG) |
title_sort | computer-assisted planning for stereoelectroencephalography (seeg) |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6985077/ https://www.ncbi.nlm.nih.gov/pubmed/31432448 http://dx.doi.org/10.1007/s13311-019-00774-9 |
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