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Cell death, perfusion and electrical parameters are critical in models of hepatic radiofrequency ablation
Purpose: A sensitivity analysis has been performed on a mathematical model of radiofrequency ablation (RFA) in the liver. The purpose of this is to identify the most important parameters in the model, defined as those that produce the largest changes in the prediction. This is important in understan...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Informa Healthcare
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4776731/ https://www.ncbi.nlm.nih.gov/pubmed/26000972 http://dx.doi.org/10.3109/02656736.2015.1032370 |
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author | Hall, Sheldon K. Ooi, Ean H. Payne, Stephen J. |
author_facet | Hall, Sheldon K. Ooi, Ean H. Payne, Stephen J. |
author_sort | Hall, Sheldon K. |
collection | PubMed |
description | Purpose: A sensitivity analysis has been performed on a mathematical model of radiofrequency ablation (RFA) in the liver. The purpose of this is to identify the most important parameters in the model, defined as those that produce the largest changes in the prediction. This is important in understanding the role of uncertainty and when comparing the model predictions to experimental data. Materials and methods: The Morris method was chosen to perform the sensitivity analysis because it is ideal for models with many parameters or that take a significant length of time to obtain solutions. A comprehensive literature review was performed to obtain ranges over which the model parameters are expected to vary, crucial input information. Results: The most important parameters in predicting the ablation zone size in our model of RFA are those representing the blood perfusion, electrical conductivity and the cell death model. The size of the 50 °C isotherm is sensitive to the electrical properties of tissue while the heat source is active, and to the thermal parameters during cooling. Conclusions: The parameter ranges chosen for the sensitivity analysis are believed to represent all that is currently known about their values in combination. The Morris method is able to compute global parameter sensitivities taking into account the interaction of all parameters, something that has not been done before. Research is needed to better understand the uncertainties in the cell death, electrical conductivity and perfusion models, but the other parameters are only of second order, providing a significant simplification. |
format | Online Article Text |
id | pubmed-4776731 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Informa Healthcare |
record_format | MEDLINE/PubMed |
spelling | pubmed-47767312016-03-16 Cell death, perfusion and electrical parameters are critical in models of hepatic radiofrequency ablation Hall, Sheldon K. Ooi, Ean H. Payne, Stephen J. Int J Hyperthermia Research Article Purpose: A sensitivity analysis has been performed on a mathematical model of radiofrequency ablation (RFA) in the liver. The purpose of this is to identify the most important parameters in the model, defined as those that produce the largest changes in the prediction. This is important in understanding the role of uncertainty and when comparing the model predictions to experimental data. Materials and methods: The Morris method was chosen to perform the sensitivity analysis because it is ideal for models with many parameters or that take a significant length of time to obtain solutions. A comprehensive literature review was performed to obtain ranges over which the model parameters are expected to vary, crucial input information. Results: The most important parameters in predicting the ablation zone size in our model of RFA are those representing the blood perfusion, electrical conductivity and the cell death model. The size of the 50 °C isotherm is sensitive to the electrical properties of tissue while the heat source is active, and to the thermal parameters during cooling. Conclusions: The parameter ranges chosen for the sensitivity analysis are believed to represent all that is currently known about their values in combination. The Morris method is able to compute global parameter sensitivities taking into account the interaction of all parameters, something that has not been done before. Research is needed to better understand the uncertainties in the cell death, electrical conductivity and perfusion models, but the other parameters are only of second order, providing a significant simplification. Informa Healthcare 2015-07-04 2015-05-22 /pmc/articles/PMC4776731/ /pubmed/26000972 http://dx.doi.org/10.3109/02656736.2015.1032370 Text en © 2015 The Author(s). Published by Taylor & Francis. http://creativecommons.org/Licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/Licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Hall, Sheldon K. Ooi, Ean H. Payne, Stephen J. Cell death, perfusion and electrical parameters are critical in models of hepatic radiofrequency ablation |
title | Cell death, perfusion and electrical parameters are critical in models of hepatic radiofrequency ablation |
title_full | Cell death, perfusion and electrical parameters are critical in models of hepatic radiofrequency ablation |
title_fullStr | Cell death, perfusion and electrical parameters are critical in models of hepatic radiofrequency ablation |
title_full_unstemmed | Cell death, perfusion and electrical parameters are critical in models of hepatic radiofrequency ablation |
title_short | Cell death, perfusion and electrical parameters are critical in models of hepatic radiofrequency ablation |
title_sort | cell death, perfusion and electrical parameters are critical in models of hepatic radiofrequency ablation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4776731/ https://www.ncbi.nlm.nih.gov/pubmed/26000972 http://dx.doi.org/10.3109/02656736.2015.1032370 |
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