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Personalized tDCS for Focal Epilepsy—A Narrative Review: A Data-Driven Workflow Based on Imaging and EEG Data

Conventional transcranial electric stimulation(tES) using standard anatomical positions for the electrodes and standard stimulation currents is frequently not sufficiently selective in targeting and reaching specific brain locations, leading to suboptimal application of electric fields. Recent advan...

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Autores principales: Beumer, Steven, Boon, Paul, Klooster, Debby C. W., van Ee, Raymond, Carrette, Evelien, Paulides, Maarten M., Mestrom, Rob M. C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139054/
https://www.ncbi.nlm.nih.gov/pubmed/35624997
http://dx.doi.org/10.3390/brainsci12050610
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author Beumer, Steven
Boon, Paul
Klooster, Debby C. W.
van Ee, Raymond
Carrette, Evelien
Paulides, Maarten M.
Mestrom, Rob M. C.
author_facet Beumer, Steven
Boon, Paul
Klooster, Debby C. W.
van Ee, Raymond
Carrette, Evelien
Paulides, Maarten M.
Mestrom, Rob M. C.
author_sort Beumer, Steven
collection PubMed
description Conventional transcranial electric stimulation(tES) using standard anatomical positions for the electrodes and standard stimulation currents is frequently not sufficiently selective in targeting and reaching specific brain locations, leading to suboptimal application of electric fields. Recent advancements in in vivo electric field characterization may enable clinical researchers to derive better relationships between the electric field strength and the clinical results. Subject-specific electric field simulations could lead to improved electrode placement and more efficient treatments. Through this narrative review, we present a processing workflow to personalize tES for focal epilepsy, for which there is a clear cortical target to stimulate. The workflow utilizes clinical imaging and electroencephalography data and enables us to relate the simulated fields to clinical outcomes. We review and analyze the relevant literature for the processing steps in the workflow, which are the following: tissue segmentation, source localization, and stimulation optimization. In addition, we identify shortcomings and ongoing trends with regard to, for example, segmentation quality and tissue conductivity measurements. The presented processing steps result in personalized tES based on metrics like focality and field strength, which allow for correlation with clinical outcomes.
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spelling pubmed-91390542022-05-28 Personalized tDCS for Focal Epilepsy—A Narrative Review: A Data-Driven Workflow Based on Imaging and EEG Data Beumer, Steven Boon, Paul Klooster, Debby C. W. van Ee, Raymond Carrette, Evelien Paulides, Maarten M. Mestrom, Rob M. C. Brain Sci Review Conventional transcranial electric stimulation(tES) using standard anatomical positions for the electrodes and standard stimulation currents is frequently not sufficiently selective in targeting and reaching specific brain locations, leading to suboptimal application of electric fields. Recent advancements in in vivo electric field characterization may enable clinical researchers to derive better relationships between the electric field strength and the clinical results. Subject-specific electric field simulations could lead to improved electrode placement and more efficient treatments. Through this narrative review, we present a processing workflow to personalize tES for focal epilepsy, for which there is a clear cortical target to stimulate. The workflow utilizes clinical imaging and electroencephalography data and enables us to relate the simulated fields to clinical outcomes. We review and analyze the relevant literature for the processing steps in the workflow, which are the following: tissue segmentation, source localization, and stimulation optimization. In addition, we identify shortcomings and ongoing trends with regard to, for example, segmentation quality and tissue conductivity measurements. The presented processing steps result in personalized tES based on metrics like focality and field strength, which allow for correlation with clinical outcomes. MDPI 2022-05-07 /pmc/articles/PMC9139054/ /pubmed/35624997 http://dx.doi.org/10.3390/brainsci12050610 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Beumer, Steven
Boon, Paul
Klooster, Debby C. W.
van Ee, Raymond
Carrette, Evelien
Paulides, Maarten M.
Mestrom, Rob M. C.
Personalized tDCS for Focal Epilepsy—A Narrative Review: A Data-Driven Workflow Based on Imaging and EEG Data
title Personalized tDCS for Focal Epilepsy—A Narrative Review: A Data-Driven Workflow Based on Imaging and EEG Data
title_full Personalized tDCS for Focal Epilepsy—A Narrative Review: A Data-Driven Workflow Based on Imaging and EEG Data
title_fullStr Personalized tDCS for Focal Epilepsy—A Narrative Review: A Data-Driven Workflow Based on Imaging and EEG Data
title_full_unstemmed Personalized tDCS for Focal Epilepsy—A Narrative Review: A Data-Driven Workflow Based on Imaging and EEG Data
title_short Personalized tDCS for Focal Epilepsy—A Narrative Review: A Data-Driven Workflow Based on Imaging and EEG Data
title_sort personalized tdcs for focal epilepsy—a narrative review: a data-driven workflow based on imaging and eeg data
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139054/
https://www.ncbi.nlm.nih.gov/pubmed/35624997
http://dx.doi.org/10.3390/brainsci12050610
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