Distributions of VA/Q in dog lungs obtained with the 50 compartment and the log normal approach.


From the lung wash-out ratios of six inert gases that were intravenously administered to 26 anaesthetized normal dogs, 120 distributions of ventilation--perfusion ratios (VA/Q) were determined, using two different techniques: the 50 compartment approach developed by Wagner et al. (1974a) and a least squares curve fitting method, comparing observed and calculated inert gas data corresponding to a single log normal distribution. The latter is defined by three parameters, the (geometric) mean VA/Q, the standard deviation of log VA/Q and a shunt fraction. A unimodal log normal fit was almost always obtained, but in 14 cases the 50 compartment approach yielded a bimodal distribution, which gave a better fit to the data in 7 cases. In most other cases the log normal distribution fitted better; the mean VA/Q's were about equal, but the standard deviations obtained from the log normal fit were often much less. It appears that, whereas in the log normal approach distributions of any sharpness can be fitted, the computer technique used in the 50 compartment approach, involving a smoothing algorithm, shortens and broadens any sharp and narrow peak in them. The effect of different smoothing factors in the 50 compartment approach was investigated. The PaO2 predicted from either distribution was about the same and somewhat less than the actual PaO2, so that one model is not superior to the other in describing oxygen transfer in the lung.


Citations per Year

69 Citations

Semantic Scholar estimates that this publication has 69 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@article{Hendriks1979DistributionsOV, title={Distributions of VA/Q in dog lungs obtained with the 50 compartment and the log normal approach.}, author={F. F. A. Hendriks and B C van Zomeren and Keith Kroll and Matthew E. Wise and P H Quanier}, journal={Respiration physiology}, year={1979}, volume={38 3}, pages={267-82} }