The influence of moving walls on respiratory aerosol deposition modelling

Comment on “Regional particle size dependent deposition of inhaled aerosols in rats and mice” by Kuehl et al.

“…Kuehl et al (2012) do not report the density of the particles they used, however given that they were generated from a colloidal sulphur in a weak saline solution and apparently not explicitly dried using a diffusion dryer or similar, it is reasonable to assume that their particles have an effective bulk density of $1000 kgm À3 . This assumption is supported by our simulated deposition study (Mead-Hunter et al, 2013) which produced results which agreed well with Kuehl et al's (2012) results, using either 0.5-mm polydisperse or monodisperse particles with p ¼ 1000 kgm À3 . Therefore, in addition to the fact that one particle type was a (dry) solid and one a liquid colloid, a significant physical size difference exists between the particles used in the Raabe et al (1988) and Kuehl et al (2012) studies.…”

Dry Lung as a Physical Model in Studies of Aerosol Deposition

“…1b, the de-skinned lobe (1) was placed inside a bag (2) made from a soft, thin plastic. The bag was placed into a metalized grounded plastic box (3). In addition to the conductive tube connected to the inlet (5), three more inputs were introduced into the box: the outlet (6) on the opposite part of the bag, inlet (4), and outlet (7).…”

“…Though simulations of NAP deposition have been reported [3][4][5], the complexity of air dynamics within the lung structure is hard to account for in these simulations; therefore, experimental verification of these calculations on a reliable lung model is required, especially in cases, when aerosol is charged.…”

Imaging regional lung function: A critical tool for developing inhaled antimicrobial therapies

“…Although effective for fundamental studies of deposition, for computer simulation to accurately predict inhaled treatment deposition, detailed knowledge of airway geometry and pressure/flow inputs in both health and disease are required. As these data are not readily available, investigators must often resort to assumptions that can drastically influence results, reducing the ability of simulations to accurately reflect the real-world situation [30][31][32].…”

“…Often the geometry of the airway tree is measured from computed tomography (CT) images acquired during a breath-hold maneuver [33][34][35][36][37][38]. Mead-Hunter et al (2013) [30] studied the effect of the static airway geometry simplification on deposition distributions calculated from numerical modeling. Significant differences in the predicted deposition patterns were found between the simulations using a dynamic (moving) airway geometry compared with those simulated using a static airway tree.…”