Modeling techniques for inhaled particle deposition: the state of the art

W HOFMANN - Journal of Aerosol Medicine, 1996 - liebertpub.com
W HOFMANN
Journal of Aerosol Medicine, 1996liebertpub.com
Mathematical modeling of aerosol deposition in the human lung is based on idealized
assumptions regarding the morphometry of the lung, the fluid dynamics behavior of the
inspired air under defined breathing conditions, the transport of particles through the
branching airway system, the physical mechanisms acting upon inhaled particles, and the
deposition of particles within airways, airway bifurcations, and alveoli. Current models of
particle deposition in the human lung, ranging from experimentally based semi empirical to …
Abstract
Mathematical modeling of aerosol deposition in the human lung is based on idealized assumptions regarding the morphometry of the lung, the fluid dynamics behavior of the inspired air under defined breathing conditions, the transport of particles through the branching airway system, the physical mechanisms acting upon inhaled particles, and the deposition of particles within airways, airway bifurcations, and alveoli. Current models of particle deposition in the human lung, ranging from experimentally based semi empirical to rather sophisticated stochastic and numerical mathematical models, permit the prediction of particle deposition at different levels of complexity, ranging from total deposition in the whole lung to localized deposition patterns within single airway bifurcations. In this paper, the present state of the art in aerosol deposition modeling will be reviewed, focusing on the discussion of different conceptual ideas rather than on a complete listing of all published modeling efforts. The selection of specific contributions by various authors relevant to our present understanding of particle deposition in the human lung reflects the subjective view of the author. In addition, illustrations of salient features of different modeling approaches are based primarily on the author's own research.
Mary Ann Liebert