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Uncertainty Quantification in Irreversible Electroporation Simulations

One recent area of cancer research is irreversible electroporation (IRE). Irreversible electroporation is a minimally invasive procedure where needle electrodes are inserted into the body to ablate tumor cells with electricity. The aim of this paper is to investigate how uncertainty in tissue and tu...

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Detalles Bibliográficos
Autor principal: Labarbera, Nicholas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5590475/
https://www.ncbi.nlm.nih.gov/pubmed/28952520
http://dx.doi.org/10.3390/bioengineering4020041
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author Labarbera, Nicholas
author_facet Labarbera, Nicholas
author_sort Labarbera, Nicholas
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description One recent area of cancer research is irreversible electroporation (IRE). Irreversible electroporation is a minimally invasive procedure where needle electrodes are inserted into the body to ablate tumor cells with electricity. The aim of this paper is to investigate how uncertainty in tissue and tumor conductivity propagate into final ablation predictions used for treatment planning. Two dimensional simulations were performed for a circular tumor surrounded by healthy tissue, and electroporated from two monopolar electrodes. The conductivity values were treated as random variables whose distributions were taken from published literature on the average and standard deviation of liver tissue and liver tumors. Three different Monte Carlo setups were simulated each at three different voltages. Average and standard deviation data was reported for a multitude of electrical field properties experienced by the tumor. Plots showing the variability in the electrical field distribution throughout the tumor are also presented.
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spelling pubmed-55904752017-09-21 Uncertainty Quantification in Irreversible Electroporation Simulations Labarbera, Nicholas Bioengineering (Basel) Article One recent area of cancer research is irreversible electroporation (IRE). Irreversible electroporation is a minimally invasive procedure where needle electrodes are inserted into the body to ablate tumor cells with electricity. The aim of this paper is to investigate how uncertainty in tissue and tumor conductivity propagate into final ablation predictions used for treatment planning. Two dimensional simulations were performed for a circular tumor surrounded by healthy tissue, and electroporated from two monopolar electrodes. The conductivity values were treated as random variables whose distributions were taken from published literature on the average and standard deviation of liver tissue and liver tumors. Three different Monte Carlo setups were simulated each at three different voltages. Average and standard deviation data was reported for a multitude of electrical field properties experienced by the tumor. Plots showing the variability in the electrical field distribution throughout the tumor are also presented. MDPI 2017-05-06 /pmc/articles/PMC5590475/ /pubmed/28952520 http://dx.doi.org/10.3390/bioengineering4020041 Text en © 2017 by the author. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Labarbera, Nicholas
Uncertainty Quantification in Irreversible Electroporation Simulations
title Uncertainty Quantification in Irreversible Electroporation Simulations
title_full Uncertainty Quantification in Irreversible Electroporation Simulations
title_fullStr Uncertainty Quantification in Irreversible Electroporation Simulations
title_full_unstemmed Uncertainty Quantification in Irreversible Electroporation Simulations
title_short Uncertainty Quantification in Irreversible Electroporation Simulations
title_sort uncertainty quantification in irreversible electroporation simulations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5590475/
https://www.ncbi.nlm.nih.gov/pubmed/28952520
http://dx.doi.org/10.3390/bioengineering4020041
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