Towards whole-lung simulations of aerosol deposition: A model of the deep lung. (June 2020) - Koullapis, P.G.; Stylianou, F.S.; Sznitman, J.; Olsson, B.; Kassinos, S.C.
Abstract: In silico methods can be used to estimate regional deposition of inhaled aerosols in regions of the lung that are inaccessible by direct measurements. Knowledge of deposited dose is important for assessing the efficacy of inhaled pharmaceutical aerosols or the impact from exposure to environmental pollutants. Although patient-specific geometries of the upper airways are widely used nowadays, insufficient imaging resolution precludes the reconstruction of 3D models of the deeper lung generations. In the present study, the 3D model of the deep lung (DLM) we have previously developed is utilised to examine the effects of breathing profile, breathhold and gravity orientation on deposition in the deep airways. The objective is to assess whether a small number of DLMs could be utilised to provide deposition predictions in the entire peripheral lung, with the ultimate goal being the integration of DLM with imaging-derived models of the upper airways for whole-lung deposition predictions. It is found that deposition in the respiratory region during deep breathing increases remarkably compared to quiet breathing since particles avoid retention in the conducting generations. Significant increases in deposition are recorded when breathhold is employed, with approximately 70% rise in total deposition of 1–2  μ m particles. Our findings indicate that the breathing maneuver can be used to target different deposition sites in the deep lung: deep inhalation followed by breathhold should be employed to achieve higher deposition in the respiratory region, whereas quiet inhalation followed by breathhold is recommended when targeting the deep conducting airways. Small differences in deposition during quiet inhalation are observed when the DLM is placed in seven different orientations relative to gravity. These differences are further reduced when realistic angle distributions are utilised for each of the five lung lobes and angle-weighted deposition fractions are compared. Our findings suggest that a small number of DLMs along with the distribution of gravity angles of an upper airway model could be employed to provide deposition estimates in the deep lung. Highlights: A 3D Deep Lung model is presented covering the 15 most distal lung generations. CFD simulations were performed at quiet/deep breathing with/without breathhold. Gravity effect on deposition was assessed for realistic lobar gravity angles. We provide recommendations for inhalation maneuvers based on target deposition site. An efficient strategy is proposed for including gravity effects in whole lung models.