Regional deposition effects are important in the pulmonary delivery of drugs intended for the topical treatment of respiratory ailments. They also play a critical role in the systemic delivery of drugs with limited lung bioavailability. In recent years, significant improvements in the quality of pulmonary imaging have taken place, however the resolution of current imaging modalities remains inadequate for quantifying regional deposition. Computational Fluid-Particle Dynamics (CFPD) can fill this gap by providing detailed information about regional deposition in the extrathoracic and conducting airways. It is therefore not surprising that the last 15years have seen an exponential growth in the application of CFPD methods in this area. Survey of the recent literature however, reveals a wide variability in the range of modelling approaches used and in the assumptions made about important physical processes taking place during aerosol inhalation. The purpose of this work is to provide a concise critical review of the computational approaches used to date, and to present a benchmark case for validation of future studies in the upper airways. In the spirit of providing the wider community with a reference for quality assurance of CFPD studies, in vitro deposition measurements have been conducted in a human-based model of the upper airways, and several groups within MP1404 SimInhale have computed the same case using a variety of simulation and discretization approaches. Here, we report the results of this collaborative effort and provide a critical discussion of the performance of the various simulation methods. The benchmark case, in vitro deposition data and in silico results will be published online and made available to the wider community. Particle image velocimetry measurements of the flow, as well as additional numerical results from the community, will be appended to the online database as they become available in the future.

Numerous models of human lungs with various levels of idealization have been reported in the literature; consequently, results acquired using these models are difficult to compare to in vivo measurements. We have developed a set of model components based on realistic geometries, which permits the analysis of the effects of subsequent model simplification. A realistic digital upper airway geometry except for the lack of an oral cavity has been created which proved suitable both for computational fluid dynamics (CFD) simulations and for the fabrication of physical models. Subsequently, an oral cavity was added to the tracheobronchial geometry. The airway geometry including the oral cavity was adjusted to enable fabrication of a semi-realistic model. Five physical models were created based on these three digital geometries. Two optically transparent models, one with and one without the oral cavity, were constructed for flow velocity measurements, two realistic segmented models, one with and one without the oral cavity, were constructed for particle deposition measurements, and a semi-realistic model with glass cylindrical airways was developed for optical measurements of flow velocity and in situ particle size measurements. One-dimensional phase doppler anemometry measurements were made and compared to the CFD calculations for this model and good agreement was obtained.

Researchers have been studying aerosol transport in human lungs for some decades. The overall lung deposition can be predicted with sufficient precision nowadays. However, the prediction of local deposition remains an unsolved problem. Numerical modeling of aerosol transport can provide detailed data with such precision and spatial resolution which were unavailable in the past. Yet, the necessary validation of numerical results represents a difficult task, as the experimental data in a sufficient spatial resolution are hardly available. This article introduces a method based on positron emission tomography, which allows acquisition of detailed experimental data on local aerosol deposition in a realistic model of human lungs. The method utilizes the Condensation Monodisperse Aerosol Generator modified for a safe production of radioactive aerosol particles and a special measuring rig. The scanning of the model is performed on a positron emission tomography–computed tomography scanner. The evaluation of aerosol deposition is based on a volume radioactivity analysis in a specialized, yet publicly available software. The reliability of the method was tested and its first results are discussed in the article. The measurements performed using the presented method can serve for validation of numerical simulations, since the presented lung model digital geometry is available.

An Eulerian internally mixed aerosol model is used for predictions of deposition inside a realistic cast of the human upper airways. The model, formulated in the multi-species and compressible framework, is solved using the sectional discretization of the droplet size distribution function to accurately capture size-dependent aerosol dynamics such as droplet drift, gravitational settling and diffusion. These three mechanisms are implemented in a consistent way in the model, guaranteeing that the total droplet mass as given by the droplet size distribution is always equal to the total droplet mass due to the mass concentration fields. To validate the model, we simulate monodisperse glycerol aerosol deposition inside the lung cast, for which experimental data is available. Provided that an adequate computational mesh is used and an adequate boundary treatment for the inertial deposition velocity, excellent agreement is found with the experimental data. Finally, we study the size-dependent deposition inside the lung cast for a polydisperse aerosol with droplet sizes ranging from the nanometer scale to beyond the micrometer scale. The typical ‘V-shape’ deposition curve is recovered. The aim of this paper is to 1) provide an overview of the Eulerian aerosol dynamics model and method, to 2) validate this method in a relevant complex lung geometry and to 3) explore the capabilities of the method by simulating polydisperse aerosol deposition