Abstract

In patients with cystic fibrosis (CF), the lung regions most affected by infection are presumed to be poorly ventilated and, hence, difficult to treat with inhaled therapeutic aerosols. Current dosimetric models do not adequately describe regional particle deposition in CF. We have developed a multiple-path particle deposition model and compared model predictions with the observed pattern of coarse particle (5 microm, mass median aerodynamic diameter) deposition in ten CF patients and eight healthy volunteers. Our model divides the lung into quadrants, separated at lobar bronchi, representing apical and basal lung regions. The volume and ventilation of quadrants were experimentally determined from a xenon equilibrium and multi-breath washout, respectively. Regional ventilation in the healthy lung was assumed to be determined largely by regional compliance. In CF patients, the deviations in regional ventilation from that observed in the healthy subjects were assumed to be due to regional resistance. A "custom" lung morphology was calculated for each subject based on their lung volume (functional residual capacity plus one-half tidal volume) and ventilation to each quadrant. Input parameters for particle deposition calculations were "custom" lung morphology, breathing pattern, and inhaled particle size. Relative to healthy subjects, the CF patients had reduced ventilation to the apices and increased ventilation to the bases of the lung. In healthy subjects, the general pattern of particle deposition followed ventilation. However, in the CF patients, the model predicted increased particle deposition in the large airways of the apices (an obstructed and poorly ventilated region) and to a lesser extent in the basal lung (relatively healthier and better-ventilated region), whereas particle deposition in the parenchyma was only increased in the basal lung and was decreased or absent in the apical lung. Our modeling strategy improves estimates of regional aerosol deposition and may be useful for predicting breathing conditions and particle size for optimal drug delivery in a given CF patient.

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