An individualised 3D computational flow and particle model to predict the deposition of inhaled medicines - A case study using a nebuliser.

BACKGROUND AND OBJECTIVE: Drug inhalation is generally accepted as the preferred administration method for treating respiratory diseases. To achieve effective inhaled drug delivery for an individual, it is necessary to use an interdisciplinary approach that can cope with inter-individual differences. The paper aims to present an individualised pulmonary drug deposition model based on Computational Fluid and Particle Dynamics simulations within a time frame acceptable for clinical use. METHODS: We propose a model that can analyse the inhaled drug delivery efficiency based on the patient's airway geometry as well as breathing pattern, which has the potential to also serve as a tool for a sub-regional diagnosis of respiratory diseases. The particle properties and size distribution are taken for the case of drug inhalation by using nebulisers, as they are independent of the patient's breathing pattern. Finally, the inhaled drug doses that reach the deep airways of different lobe regions of the patient are studied. RESULTS: The numerical accuracy of the proposed model is verified by comparison with experimental results. The difference in total drug deposition fractions between the simulation and experimental results is smaller than 4.44% and 1.43% for flow rates of 60 l/min and 15 l/min, respectively. A case study involving a COVID-19 patient is conducted to illustrate the potential clinical use of the model. The study analyses the drug deposition fractions in relation to the breathing pattern, aerosol size distribution, and different lobe regions. CONCLUSIONS: The entire process of the proposed model can be completed within 48 h, allowing an evaluation of the deposition of the inhaled drug in an individual patient's lung within a time frame acceptable for clinical use. Achieving a 48-hour time window for a single evaluation of patient-specific drug delivery enables the physician to monitor the patient's changing conditions and potentially adjust the drug administration accordingly. Furthermore, we show that the proposed methodology also offers a possibility to be extended to a detection approach for some respiratory diseases.

Anatomy matters: The role of the subject-specific respiratory tract on aerosol deposition - A CFD study.

The COVID-19 pandemic is one of the greatest challenges to humanity nowadays. COVID-19 virus can replicate in the host's larynx region, which is in contrast to other viruses that replicate in lungs only, i.e. SARS. This is conjectured to support a fast spread of COVID-19. However, there is sparse research in this field about quantitative comparison of virus load in the larynx for varying susceptible individuals. In this regard the lung geometry itself could influence the risk of reproducing more pathogens and consequently exhaling more virus. Disadvantageously, there are only sparse lung geometries available. To still be able to investigate realistic geometrical deviations we employ three different digital replicas of human airways up to the 7 th level of bifurcation, representing two realistic lungs (male and female) as well as a more simplified experimental model. Our aim is to investigate the influence of breathing scenarios on aerosol deposition in anatomically different, realistic human airways. In this context, we employ three levels of cardiovascular activity as well as reported experimental particle size distributions by means of Computational Fluid Dynamics (CFD) with special focus on the larynx region to enable new insights into the local virus loads in human respiratory tracts. In addition, the influence of more realistic boundary conditions is investigated by performing transient simulations of a complete respiratory cycle in the upper lung regions of the considered respiratory models, focusing in particular on deposition in the oral cavity, the laryngeal region, and trachea, while simplifying the tracheobronchial tree. The aerosol deposition is modeled via OpenFOAM\protect \relax \special {t4ht=®} by employing an Euler-Lagrangian frame including steady and unsteady Reynolds Averaged Navier-Stokes (RANS) resolved turbulent flow using the k- ω -SST and k- ω -SST DES turbulence models. We observed that the respiratory geometry altered the local deposition patterns, especially in the laryngeal region. Despite the larynx region, the effects of varying flow rate for the airway geometries considered were found to be similar in the majority of respiratory tract regions. For all particle size distributions considered, localized particle accumulation occurred in the larynx of all considered lung models, which were more pronounced for larger particle size distributions. Moreover, it was found, that employing transient simulations instead of steady-state analysis, the overall particle deposition pattern is maintained, however with a stronger intensity in the transient cases.

Risk Assessment of Infection by Airborne Droplets and Aerosols at Different Levels of Cardiovascular Activity.

Since end of 2019 the COVID-19 pandemic, caused by the SARS-CoV-2 virus, is threatening humanity. Despite the fact that various scientists across the globe try to shed a light on this new respiratory disease, it is not yet fully understood. Unlike many studies on the geographical spread of the pandemic, including the study of external transmission routes, this work focuses on droplet and aerosol transport and their deposition inside the human airways. For this purpose, a digital replica of the human airways is used and particle transport under various levels of cardiovascular activity in enclosed spaces is studied by means of computational fluid dynamics. The influence of the room size, where the activity takes place, and the aerosol concentration is studied. The contribution aims to assess the risk of various levels of exercising while inhaling infectious pathogens to gain further insights in the deposition behavior of aerosols in the human airways. The size distribution of the expiratory droplets or aerosols plays a crucial role for the disease onset and progression. As the size of the expiratory droplets and aerosols differs for various exhaling scenarios, reported experimental particle size distributions are taken into account when setting up the environmental conditions. To model the aerosol deposition we employ OpenFOAM  by using an Euler-Lagrangian frame including Reynolds-Averaged Navier-Stokes resolved turbulent flow. Within this study, the effects of different exercise levels and thus breathing rates as well as particle size distributions and room sizes are investigated to enable new insights into the local particle deposition in the human airway and virus loads. A general observation can be made that exercising at higher levels of activity is increasing the risk to develop a severe cause of the COVID-19 disease due to the increased aerosolized volume that reaches into the lower airways, thus the knowledge of the inhaled particle dynamics in the human airways at various exercising levels provides valuable information for infection control strategies.

Can CFD establish a connection to a milder COVID-19 disease in younger people? Aerosol deposition in lungs of different age groups based on Lagrangian particle tracking in turbulent flow.

To respond to the ongoing pandemic of SARS-CoV-2, this contribution deals with recently highlighted COVID-19 transmission through respiratory droplets in form of aerosols. Unlike other recent studies that focused on airborne transmission routes, this work addresses aerosol transport and deposition in a human respiratory tract. The contribution therefore conducts a computational study of aerosol deposition in digital replicas of human airways, which include the oral cavity, larynx and tracheobronchial airways down to the 12th generation of branching. Breathing through the oral cavity allows the air with aerosols to directly impact the larynx and tracheobronchial airways and can be viewed as one of the worst cases in terms of inhalation rate and aerosol load. The implemented computational model is based on Lagrangian particle tracking in Reynolds-Averaged Navier-Stokes resolved turbulent flow. Within this framework, the effects of different flow rates, particle diameters and lung sizes are investigated to enable new insights into local particle deposition behavior and therefore virus loads among selected age groups. We identify a signicant increase of aerosol deposition in the upper airways and thus a strong reduction of virus load in the lower airways for younger individuals. Based on our findings, we propose a possible relation between the younger age related fluid mechanical protection of the lower lung regions due to the airway size and a reduced risk of developing a severe respiratory illness originating from COVID-19 airborne transmission.

Settling characteristics of nonspherical porous sludge flocs with nonhomogeneous mass distribution.

The paper reports on the development of an advanced Lagrangian particle tracking model of sludge flocs that takes into account its nonspherical shape, the internal porosity and permeability, as well as the nonhomogenous mass distribution. The floc shapes, sizes and free settling velocities are determined based on the experimental measurement of settling sludge flocs originating from a wastewater treatment plant. Based on the floc shape characterization, a prolate axisymmetric ellipsoid is selected as the modelled sludge particle. In order to determine the main particle characteristics, e.g. the internal porosity, the density and the flow permeability, a Lagrangian particle tracking model is developed based on Brenner's drag model for a prolate axisymmetric ellipsoid and a buoyancy force model for a porous particle. The model is implemented for numerical simulations of the free settling process. The obtained floc characteristics are presented in the form of a two-part polynomial fitting curve, which can be used to model floc characteristics. The values of settling velocities of flocs computed by the model show very good agreement with experimental results. Futhermore, as the internal structure of a floc is seldom uniform, the nonhomogeneous mass distribution is considered, influencing the rotational and translational motions of the settling flocs. The nonhomogeneous mass distribution is introduced into the floc settling model. The parametric analyses of different barycentre offsets and shear rates are performed, and their influences on the free settling velocity are evaluated. The presented modelling approach can also be applied to flocculent settling of alum and other flocs in drinking water treatment plants. The developed Lagrangian model is suitable for use as a point source within the framework of Eulerian flow computations, and is solved as a two-phase flow model with a suitable Computational Fluid Dynamics code.