Abstract
A detailed picture of how an aerosol is transported and deposited in the self-affine bronchial tree structure of patients is fundamental to design and optimize orally inhaled drug products. This work describes a Monte Carlo-based statistical deposition model able to simulate aerosol transport and deposition in a 3D human bronchial tree. The model enables working with complex and realistic inhalation maneuvers including breath-holding and exhalation. It can run on fully stochastically generated bronchial trees as well as on those whose proximal airways are extracted from patient chest scans. However, at present, a mechanical breathing model is not explicitly included in our trees; their ventilation can be controlled by means of heuristic airflow splitting rules at bifurcations and by an alveolation index controlling the distal lung volume. Our formulation allows us to introduce different types of pathologies on the trees, both those altering their morphology (e.g., bronchiectasis and chronic obstructive pulmonary disease) and those impairing their function (e.g., interstitial lung diseases and emphysema). In this initial activity we describe deposition and ventilation models as well as the stochastic tree construction algorithm, and we validate them against total, regional, lobar, and sub-lobar deposition for healthy subjects.