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Modelling structural determinants of ventilation heterogeneity: A perturbative approach
We have developed a computational model of gas mixing and ventilation in the human lung represented as a bifurcating network. We have simulated multiple-breath washout (MBW), a clinical test for measuring ventilation heterogeneity (VH) in patients with obstructive lung conditions. By applying airway...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6264152/ https://www.ncbi.nlm.nih.gov/pubmed/30496317 http://dx.doi.org/10.1371/journal.pone.0208049 |
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author | Whitfield, Carl A. Horsley, Alex Jensen, Oliver E. |
author_facet | Whitfield, Carl A. Horsley, Alex Jensen, Oliver E. |
author_sort | Whitfield, Carl A. |
collection | PubMed |
description | We have developed a computational model of gas mixing and ventilation in the human lung represented as a bifurcating network. We have simulated multiple-breath washout (MBW), a clinical test for measuring ventilation heterogeneity (VH) in patients with obstructive lung conditions. By applying airway constrictions inter-regionally, we have predicted the response of MBW indices to obstructions and found that they detect a narrow range of severe constrictions that reduce airway radius to 10%–30% of healthy values. These results help to explain the success of the MBW test to distinguish obstructive lung conditions from healthy controls. Further, we have used a perturbative approach to account for intra-regional airway heterogeneity that avoids modelling each airway individually. We have found, for random airway heterogeneity, that the variance in MBW indices is greater when indices are already elevated due to constrictions. By quantifying this effect, we have shown that variability in lung structure and mechanical properties alone can lead to clinically significant variability in MBW indices (specifically the Lung Clearance Index—LCI, and the gradient of phase-III slopes—S(cond)), but only in cases simulating obstructive lung conditions. This method is a computationally efficient way to probe the lung’s sensitivity to structural changes, and to quantify uncertainty in predictions due to random variations in lung mechanical and structural properties. |
format | Online Article Text |
id | pubmed-6264152 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-62641522018-12-19 Modelling structural determinants of ventilation heterogeneity: A perturbative approach Whitfield, Carl A. Horsley, Alex Jensen, Oliver E. PLoS One Research Article We have developed a computational model of gas mixing and ventilation in the human lung represented as a bifurcating network. We have simulated multiple-breath washout (MBW), a clinical test for measuring ventilation heterogeneity (VH) in patients with obstructive lung conditions. By applying airway constrictions inter-regionally, we have predicted the response of MBW indices to obstructions and found that they detect a narrow range of severe constrictions that reduce airway radius to 10%–30% of healthy values. These results help to explain the success of the MBW test to distinguish obstructive lung conditions from healthy controls. Further, we have used a perturbative approach to account for intra-regional airway heterogeneity that avoids modelling each airway individually. We have found, for random airway heterogeneity, that the variance in MBW indices is greater when indices are already elevated due to constrictions. By quantifying this effect, we have shown that variability in lung structure and mechanical properties alone can lead to clinically significant variability in MBW indices (specifically the Lung Clearance Index—LCI, and the gradient of phase-III slopes—S(cond)), but only in cases simulating obstructive lung conditions. This method is a computationally efficient way to probe the lung’s sensitivity to structural changes, and to quantify uncertainty in predictions due to random variations in lung mechanical and structural properties. Public Library of Science 2018-11-29 /pmc/articles/PMC6264152/ /pubmed/30496317 http://dx.doi.org/10.1371/journal.pone.0208049 Text en © 2018 Whitfield et al 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 author and source are credited. |
spellingShingle | Research Article Whitfield, Carl A. Horsley, Alex Jensen, Oliver E. Modelling structural determinants of ventilation heterogeneity: A perturbative approach |
title | Modelling structural determinants of ventilation heterogeneity: A perturbative approach |
title_full | Modelling structural determinants of ventilation heterogeneity: A perturbative approach |
title_fullStr | Modelling structural determinants of ventilation heterogeneity: A perturbative approach |
title_full_unstemmed | Modelling structural determinants of ventilation heterogeneity: A perturbative approach |
title_short | Modelling structural determinants of ventilation heterogeneity: A perturbative approach |
title_sort | modelling structural determinants of ventilation heterogeneity: a perturbative approach |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6264152/ https://www.ncbi.nlm.nih.gov/pubmed/30496317 http://dx.doi.org/10.1371/journal.pone.0208049 |
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