The Role of Airway Epithelium in Replenishment of Evaporated Airway Surface Liquid From the Human Conducting Airways

Abstract

This article presents a multi-scale computational model describing the transport of water vapor and heat within the human conducting airways and its interaction with cellular fluid transport kinetics. This tight coupling between the cell and the evaporative flux allows the periciliary liquid (PCL) depth to be investigated within the context of a geometric framework of the human conducting airways with spatial and temporal variations. Within the in vivo airway, the epithelium is not the only source of fluid available for hydration of the PCL, and fluid may also be supplied from submucosal glands (SMGs) or via axial transport of the PCL. The model predicts that without fluid supplied by either SMGs or via PCL transport, significant dehydration would occur under normal breathing conditions. Previous studies have suggested that PCL transport from the periphery to the trachea would require absorption of the fluid by the epithelium; here we show that this can theoretically be sustained by the evaporative load under normal breathing conditions. SMGs could also provide a significant supply of fluid for airway hydration, a hypothesis which is corroborated by comparing the distribution of SMGs as a function of airway generation with the distribution of airway evaporative flux.

Appendix

Comparison with Experimental Data

The thermo-fluids model was validated through comparison with the experimental results of McFadden et al. 24 To account for a description of heat and moisture transfer in the nose or mouth the inspired temperatures used for simulations were those measured experimentally by McFadden et al. at the sub-glottis region. The inspired air was assumed to be at 95% RH for the simulations. Figure 7 shows model simulations compared with experimental data from McFadden et al. 24 for different ventilatory conditions $(\dot V=15, 30,60,$ and 100 L min⁻¹) when inspiring normal room air (26.7 °C, 8.8 mg L⁻¹). Experimental data are reproduced showing mean and standard error with error bars. A distance of 0 mm corresponds to the proximal end of the trachea.

FIGURE 7

Model simulations for inspiration of room temperature air with different ventilation rates compared with experimental data from McFadden et al. 24 End inspiration shown in blue, end expiration in red. Lumen gas temperature shown with dashed curves, and airway wall temperature shown with solid lines. Experimental data shown with error bars ± standard error. (a–d) Ventilation rates of $\dot V=15, 30,60,$ and 100 L min⁻¹, respectively

McFadden et al. 24 also considered the case where subjects inspired frigid air (−18.6 °C, 0.0 mg L⁻¹). which was produced using dry compressed air cooled to sub-freezing temperatures. Simulations for the four different ventilatory conditions $(\dot V=15, 30,60,$and 100 L min⁻¹) were also performed (Fig. 8). Inspiratory temperatures were again set to match those measured experimentally at the sub-glottis region and relative humidity was set at an assumed value of 60%.

The model simulations shown in Figs. 7 and 8 show a good correlation with the experimental data from McFadden et al. 24 The simulated temperatures in the center of the lumen match well during both inspiration and expiration at low ventilation rates. With colder inspiratory temperatures and higher ventilation rates (above 30 L min⁻¹) the model performs most poorly. This may in part be due to the upper bound on α being reached under high ventilation rates. However, at low ventilation rates Figs. 7 and 8 demonstrate the model’s ability to simulate different inspiratory conditions. While the model can predict airway temperature and humidity in anatomically accurate airway geometries, it is worth noting that within the literature there is a lack of data on airway humidity which would be necessary in order to provide further validation of the model’s performance. Within the model the equations describing the airway temperature and humidity are inexorably dependent. Therefore, an incorrect value in temperature will influence humidity, and vice versa. If the temperature distribution matches the experimental data with reasonable accuracy, it can be considered as an indirect validation of airway humidity.

FIGURE 8

Model simulations for inspiration of cold air with different ventilation rates compared with experimental data from McFadden et al. 24 End inspiration shown in blue, end expiration in red. Lumen gas temperature shown with dashed curves, and airway wall temperature shown with solid lines. Experimental data shown with error bars ± standard error. (a–d) Ventilation rates of $\dot V=15, 30,60,$ and 100 L min⁻¹, respectively

Convergence and Anatomical vs. Symmetric Geometry

Comparison of experimental measurements with the model are performed once the model has reached pseudo-steady-state. The lumen air temperature and absolute humidity converge relatively quickly after approximately 10 breaths, whereas convergence of the airway wall temperature takes approximately 45 breaths to reach pseudo-steady-state (Fig. 9a). For the cellular variables, such as PCL depth, pseudo-steady-state was reached after a considerably longer period—approximately 100 breaths.

FIGURE 9

(a) Convergence of airway wall temperature to pseudo-steady-state vs. breath number for inspiratory conditions of 32 °C, 80% RH and a ventilation rate of 6 L min⁻¹. (b) Comparison of the pseudo-steady-state solution using symmetric and anatomical geometry. Inspiratory conditions are 34 °C, 100% RH. Symmetric geometry solution shown with a solid curve and anatomical solution shown with error bars with limits representing the solution range. End inspiration shown in blue, end expiration in red

Inspiration of room-temperature air (34 °C, 100% RH at the tracheal entrance) was simulated in models with symmetric and anatomical geometry. Mid-airstream temperatures (T ₀) are shown in Fig. 9b for the end of inspiration (blue) and end of expiration (red). The symmetric model results are shown with a solid curve and the anatomical results shown with error bars representing the mean and solution range. For inspiration both geometries produce similar mean values for a given generation. However, for more distal generations the anatomical model displays an increasing range in the solution values due to the variability in the airway path length. However, the symmetric model did not produce vastly different values for temperature, or absolute or relative humidity from the anatomically based model.