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Theoretical models for the quantification of lung injury using ventilation and perfusion distributions
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Brook, B. S., Murphy, C. M., Breen, D., Miles, A. W., Tilley, D. G. and Wilson, A. J. (2009) Theoretical models for the quantification of lung injury using ventilation and perfusion distributions. Computational and Mathematical Methods in Medicine, Vol.10 (No.2). pp. 139-154. doi:10.1080/17486700802201592 ISSN 1748-670X.
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Official URL: http://dx.doi.org/10.1080/17486700802201592
Abstract
This paper describes two approaches to modelling lung disease: one based on a multi-compartment statistical model with a log normal distribution of ventilation perfusion ratio ([image omitted]) values; and the other on a bifurcating tree which emulates the anatomical structure of the lung. In the statistical model, the distribution becomes bimodal, when the [image omitted] values of a randomly selected number of compartments are reduced by 85% to simulate lung disease. For the bifurcating tree model a difference in flow to the left and right branches coupled with a small random variation in flow ratio between generations results in a log normal distribution of flows in the terminal branches. Restricting flow through branches within the tree to simulate lung disease transforms this log normal distribution to a bi-modal one. These results are compatible with those obtained from experiments using the multiple inert gas elimination technique, where log normal distributions of [image omitted] ratio become bimodal in the presence of lung disease.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QH Natural history > QH301 Biology | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Physics | ||||
Journal or Publication Title: | Computational and Mathematical Methods in Medicine | ||||
Publisher: | Hindawi Publishing Corporation | ||||
ISSN: | 1748-670X | ||||
Official Date: | 2009 | ||||
Dates: |
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Volume: | Vol.10 | ||||
Number: | No.2 | ||||
Number of Pages: | 16 | ||||
Page Range: | pp. 139-154 | ||||
DOI: | 10.1080/17486700802201592 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Funder: | Engineering and Physical Sciences Research Council (EPSRC) | ||||
Grant number: | GR/L74323 (EPSRC), GR/L74835 (EPSRC) |
Data sourced from Thomson Reuters' Web of Knowledge
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