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.
|Number of pages||16|
|Journal||Computational and Mathematical Methods in Medicine|
|Publication status||Published - Jun 2009|
- log normal
- lung disease
Brook, B. S., Murphy, C. M., Breen, D., Miles, A. W., Tilley, D. G., & Wilson, A. J. (2009). Theoretical models for the quantification of lung injury using ventilation and perfusion distributions. Computational and Mathematical Methods in Medicine, 10(2), 139-154. https://doi.org/10.1080/17486700802201592