Ventilation-perfusion distribution in normal subjects

Kenneth C. Beck, Bruce D. Johnson, Thomas P. Olson, Theodore A. Wilson

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Functional values of LogSD of the ventilation distribution (δV̇) have been reported previously, but functional values of LogSD of the perfusion distribution (δq̇) and the coefficient of correlation between ventilation and perfusion (π) have not been measured in humans. Here, we report values for δV̇, δq̇, and δ obtained from wash-in data for three gases, helium and two soluble gases, acetylene and dimethyl ether. Normal subjects inspired gas containing the test gases, and the concentrations of the gases at end-expiration during the first 10 breaths were measured with the subjects at rest and at increasing levels of exercise. The regional distribution of ventilation and perfusion was described by a bivariate log-normal distribution with parameters δV̇, δq̇, and δ, and these parameters were evaluated by matching the values of expired gas concentrations calculated for this distribution to the measured values. Values of cardiac output and LogSD ventilation/perfusion (V̇A/Q̇) were obtained. At rest, δq̇is high (1.08 ± 0.12). With the onset of ventilation, δq̇decreases to 0.85 ± 0.09 but remains higher than δV̇(0.43 ± 0.09) at all exercise levels. Rho increases to 0.87 ± 0.07, and the value of LogSDV̇A/Q̇for light and moderate exercise is primarily the result of the difference between the magnitudes of δq̇ and δV̇. With known values for the parameters, the bivariate distribution describes the comprehensive distribution of ventilation and perfusion that underlies the distribution of the V̇A/Q̇ratio.

Original languageEnglish (US)
Pages (from-to)872-877
Number of pages6
JournalJournal of applied physiology
Issue number6
StatePublished - Sep 15 2012


  • Cardiac output
  • Gas exchange
  • Gas mixing

ASJC Scopus subject areas

  • Physiology
  • Physiology (medical)


Dive into the research topics of 'Ventilation-perfusion distribution in normal subjects'. Together they form a unique fingerprint.

Cite this