(612e) Nanoparticle Transfer and Deposition Using An Integrated CFD Model of the Respiratory System

The transfer and deposition of nanoparticles in the respiratory system is of major interest for the development of targeted drug delivery formulations but also due to the increasing concerns over the potential toxicity of natural and engineered nanoparticles. Experimental and theoretical work have focused on different regions of the respiratory system, e.g., oropharyngeal, nasal, pulmonary, alveolar, where many aspects of the nanoparticle, NP, penetration are fairly well understood. However, several issues remain to be elucidated including the deposition of non-spherical NPs and nanofibers, dispersion and aggregation (e.g., of carbon nanotubes), changes in particle size and shape as well as aggregation state and finally the fate of deposited particles which is of major concern. Deposited particles can undergo disaggregation, can release beneficial drugs or harmful toxins, and, if sufficiently small, can penetrate into the bloodstream.

To further improve our understanding of NP penetration and deposition an integrated CFD model of the entire respiratory system, describing the flow of a dispersion of more particles has been developed through the nasal cavity and lungs. The flow through the pulmonary system is described down to the alveolar sac and individual alveoli level. The deposition of nanoparticles and nanofibers is approximated by a Lagrangian/Eulerian tracking scheme. Local deposition models of NPs are developed to provide a better insight into the deposition dynamics and the sticking efficiency of the NPs. These local deposition models utilize CFD solutions of the global geometry to supply inlet conditions for the local deposition problem geometry.

The nasal cavity consists of two nasal air paths converging to a single pathway at the back of the cavity which is then directed downwards to the trachea. The two nasal air paths are highly curved and convoluted in shape providing a total surface area of about 150 cm². The nasal walls are covered by a mucous layer which moves to the posterior clearing deposited particles. The flow and deposition of particles in the nasal cavity has recently been investigated by several groups (Liu et al., 2007; Shi et al., 2008; Wen et al., 2008). In this work, the nasal cavity geometry is reconstructed based on a series of medical images. A number of different computational grids are then constructed (from 0.3 10⁶ polyhedral to 1.6 10⁶ tetrahedral cells). Turbulent flow is described with a transitional k-ω model. The nasal deposition of large particles (i.e., 1-10μm) was found to be higher than the deposition of smaller particles. The particle deposition efficiency is described in terms of the impaction parameter, QD². Inlet particles are assumed to be either single- or multiple- sized. Comprehensive information on the axial and size distribution of deposited particles can be obtained. It was found that larger particles were mostly deposited in the anterior region of the nasal cavity while smaller particles were deposited less and more evenly throughout the nasal cavity.

The pulmonary system consists of a multitude of nonsymmetrical branches of progressively smaller diameter. There are a total of 23-24 branch generations leading to about 107 simple branches in the entire pulmonary system (Finlay, 2004). This limits the number of branch generations that can be completely simulated to around 5-6 (Longest and Vinchurkar, 2007; van Ertbruggen et al., 2005; Zhang et al., 2002). However, if a single pathline down to the alveolar sacs is considered, a successive simulation approach can be followed (Nowak et al., 2003). In the present work, a model of the pulmonary tract is developed based on 7 consecutive ?blocks? of the pulmonary system. Each block consists of 4 generations of symmetrical branches with one side rotated 90 degrees relative to the other and is discretized into 2 10⁵ tetrahedral cells. The inlet flow and particle motion conditions of each block are obtained from the outlet conditions of the previous block and the inlet conditions of the first block are obtained from the outlet conditions of the nasal cavity. Particle depositions in the pulmonary tract again favored the larger particles (i.e., 100nm-1μm), and only the smallest of particles (i.e., <100nm) could reach the lower respiratory tract and alveolar sacs at significant concentrations. Toxin (or drug) release from deposited particles and penetration through the underlying mucosal layer is described using a dual diffusion-layer model which accounted for the mucosal layer motion as well as the deposition location.

The alveolar sac model was integrated with the pulmonary model. Specifically, the outflow from the last block of the pulmonary model is taken as the inflow to an alveolar sac. Although each alveolar sac contains a number (i.e., 10-50) of alveoli, the description of flow to the alveolar sac and to the individual alveoli is simplified by considering a model of a single alveoli. The single alveoli model is comprised of a spherical volume which changes in size during inhalation due to inflow from the alveoli mouth. Nanoparticles also enter the alveoli and their deposition is controlled by Brownian motion and inertial forces.

The proposed integrated respiratory model describes the flow, penetration, and deposition of nanoparticles in the respiratory system accounting for the influence of the nasal cavity and the 23-24 generations of pulmonary branches including the alveolar sacs. Particle deposition is driven by Brownian motion for the smaller particles and by inertial forces for the larger particles. Sticking efficiencies for non-spherical NPs and nanofibers can be estimated from local deposition models. The present integrated model can approximately describe the transfer and deposition of nanoparticles and nanofibers throughout the respiratory system.

References

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Liu Y., E.A. Matida, J. Gu, and M.R. Johnson, 2007, ?Numerical simulation of aerosol deposition in a 3-D human nasal cavity using RANS, RANS/EIM, and LES?, Aerosol Sci., 38, 683-700.

Longest, P. and Vinchurkar, S., 2007, ?Validating CFD predictions of respiratory aerosol deposition: Effects of upstream transition and turbulence?, J. of Biomechanics, 40(20, 305-316

Nowak N., P.P. Kakade, and A.V. Annapragada, 2003, ?Computational Fluid Dynamics Simulation of Airflow and Aerosol Deposition in Human Lungs?, Annals of Biomed. Engineering, 31, 374-390.

Shi, H.W., C. Kleinstreuer and Z. Zhang, 2008, ?Dilute suspension flow with nanoparticle deposition in a representative nasal airway model?, Physics of Fluids 20, 013301.

van Ertbruggen, C., C. Hirsch, and M. Paiva, 2005, ?Anatomically based three-dimensional model of airways to simulate flow and particle transport using computational fluid dynamics?, J. Appl. Physiol. 98, 970-980.

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Zhang Z., C. Kleinstreuer, and S.K. Chong, 2002, ?Aerosol deposition efficiencies and upstream release positions for different inhalation modes in an upper bronchial airway model? Aerosol Sci. & Technol., 36, 828-844.