Analysis of lung multiple indicator data with an effective diffusivity model of capillary exchange

Area of Science:

• Pulmonary physiology
• Microvascular exchange dynamics
• Quantitative modeling

Background:

• Lung microvascular exchange is crucial for gas and solute transport.
• Existing models like Crone, Sangren-Sheppard, and Rowlett-Harris have limitations in describing small molecule exchange.
• Multiple indicator dilution techniques provide data for model validation.

Purpose of the Study:

• To compare the effective diffusivity model with established models for lung microvascular exchange.
• To evaluate model performance in matching multiple-tracer data under varying physiological conditions.
• To assess the reliability and independence of model parameters.

Main Methods:

• Comparative analysis of four mathematical models: effective diffusivity, Crone integral, Sangren-Sheppard, and Rowlett-Harris.
• Model parameter adjustment to best fit multiple-tracer data from isolated dog lungs and awake sheep.
• Sensitivity analysis to determine parameter independence and reliability.

Main Results:

• The effective diffusivity model demonstrated superior data matching and captured the characteristic falling extraction pattern in the lung.
• Unlike other models, the effective diffusivity model parameter (D 1/2 S) was unaffected by reduced blood flow.
• Sensitivity analysis indicated more independent parameter determination for the effective diffusivity model compared to the Sangren-Sheppard model.

Conclusions:

• The effective diffusivity model is a more accurate descriptor of lung microvascular exchange of small molecules.
• Model parameters are more reliably and independently determined, offering better insights into capillary-tissue exchange.
• This model effectively captures the influence of flow and vasoactive agents like histamine on lung exchange processes.