An extended soluble gas exchange model for estimating pulmonary perfusion--I: Derivation and implementation

A tidal breathing model of the forced inspired inert gas sinewave technique

We have shown previously that it is possible to assess the cardio-respiratory function using sinusoidally oscillating inert gas forcing signals of nitrous oxide and argon (Hahn et al., 1993). This method uses an extension of a mathematical model of respiratory gas exchange introduced by Zwart et al. (1976), which assumed continuous ventilation. We investigate the effects of this assumption by developing a mathematical model using a single alveolar compartment and incorporating tidal ventilation, which must be solved using numerical methods. We compare simulated results from the tidal model with those from the continuous model, as the governing ventilatory and cardiac parameters are varied. The mathematical model is designed to be the basis of an on-line, non-invasive, cardio-respiratory measurement method, and will only be useful if the associated parameter recovery techniques are both reliable and robust. We demonstrate, in the presence of simulated measurement errors, that: (a) accurate recovery of the ventilatory parameters end-tidal volume, VA, and airways series dead-space, VD, are possible using the tidal breathing model; and (b) that a robust technique for recovery of pulmonary blood flow, QP, can be obtained using the more familiar continuous ventilation model.

On-line determination of pulmonary blood flow using respiratory inert gas analysis

An inert gas analysis method has been developed to perform on-line real time determination of pulmonary blood flow using a nonrebreathing approach. This technique is based on a mathematical model describing mass balance of two inert gases which are breathed using an open gas circuit. The measurements using this method are noninvasive, easy to peform, and do not disturb normal physiological processes. As well, since data are collected on a breath-by-breath basis, it is possible to estimate other respiratory, cardiopulmonary, and metabolic parameters simultaneously in a breath-by-breath manner. Special consideration was given to developing effective data processing algorithms to minimize the influence of measurement noise and respiratory variations. Experimental studies to compare this method with other accepted techniques were conducted to validate the present technique.

An extended soluble gas exchange model for estimating pulmonary perfusion--II: Simulation results

The assumptions made in deriving models of soluble gas exchange used for continuous estimation of pulmonary perfusion are critically examined. Comparisons are made between estimation algorithms based on simple and more complex models. The more complex model includes a general treatment of tidal breathing, an inhomogeneous lung comprising multiple distensible compartments, and nonlinearities due to multiple-gas effects. The results show that sensitivity of perfusion estimates to errors inherent in simple linear models. These errors can invalidate the estimates under realistic physiological conditions. Concentration and multiple-gas effects, for example, can cause substantial estimation errors. Large ventilations relative to lung volume can also lead to errors. These simulations can be used to delimit the conditions under which the estimates can be considered reliable. A further set of simulations is used to assess the sensitivity of perfusion estimates to errors in the assumed values of unknown or approximately known model parameters. Inadequate specification of the compartmental structure of the lung (distributions of ventilation/perfusion and ventilation/volume) can cause large estimate errors. Precise estimates of lung tissue volume do not appear to be necessary. These results are important for the practical application of soluble gas methods for pulmonary perfusion determination. In both sets of simulations, it is shown that parameter estimate accuracy must be confirmed independently of goodness-of-fit criteria. Close agreement between predicted and observed end-tidal concentrations does not ensure accurate perfusion estimates.