Theoretical models for the quantification of lung injury using ventilation and perfusion distributions

B S Brook, C M Murphy, D Breen, Anthony W Miles, Derek G Tilley, A J Wilson

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)139-154
Number of pages16
JournalComputational and Mathematical Methods in Medicine
Volume10
Issue number2
DOIs
Publication statusPublished - Jun 2009

Keywords

  • log normal
  • tree
  • lung disease
  • modelling

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