Airflow and Particle Deposition in Acinar Models with Interalveolar Septal Walls and Different Alveolar Numbers

Design of a multilayer lung chip with multigenerational alveolar ducts to investigate the inhaled particle deposition

We present the development and application of a multilayer microfluidic lung chip designed to accurately replicate the human respiratory bronchi, providing an innovative platform for controlled particle deposition in the lung. By employing a quantitative control method of fluid velocity through the deformation of an elastic PDMS membrane, this platform mimics the passive breathing process in humans and allows for precise simulation of the respiration cycle. We utilized time-lapse photography of fluorescent particles in a water/glycerol solution to qualitatively observe fluid morphology in the channel, while a chip-aerosol exposure device combined with microscopy imaging was employed to visualise aerosol deposition. Both experimental and numerical simulation results showed that particle concentration decreased towards the distal generations of the lung, and that changes in breathing pattern significantly affected particle deposition trends. Furthermore, we found that increasing the residence time of particles in the channel facilitated deeper particle deposition, achievable by adjusting parameters such as breath-hold time, exhalation time, respiration cycle length, and tidal volume. The proposed microfluidic lung chip device has significant potential for future research in respiratory health and inhaled drug delivery, providing an efficient, cost-effective, and ethical alternative to traditional in vivo studies.

Pulmonary Oxygen Exchange in a Rhythmically Expanding–Contracting Alveolus–Capillary Model

Pulmonary gas exchanges are vital to human health, and disruptions to this process have been associated with many respiratory diseases. Previous gas exchange studies have predominately relied on whole-body testing and theoretical analysis with 1D or static models. However, pulmonary gas exchanges are inherently a dynamic process in 3D spaces with instantaneous interactions between air, blood, and tissue. This study aimed to develop a computational model for oxygen exchange that considered all factors mentioned above. Therefore, an integrated alveolus–membrane–capillary geometry was developed with prescribed rhythmic expansion/contraction. Airflow ventilation, blood perfusion, and oxygen diffusion were simulated using COMSOL. The temporal and spatial distribution of blood flow and oxygen within the capillaries were simulated under varying breathing depths and cardiac outputs. The results showed highly nonuniform blood flow distributions in the capillary network, while the rhythmic oscillation further increased this nonuniformity, leading to stagnant blood flow in the distal vessels. A static alveolus–capillary geometry underestimated perfusion by 11% for normal respirations, and the deviation grew with breathing depth. The rhythmic motion caused a phase lag in the blood flow. The blood PO2 reached equilibrium with the alveolar air after traveling 1/5–1/3 of the capillary network. The time to reach this equilibrium was significantly influenced by the air–blood barrier diffusivity, while it was only slightly affected by the perfusion rate. The computational platform in this study could be instrumental in obtaining refined knowledge of pulmonary O2 exchanges.

A comparison of CFPD, compartment, and uniform distribution models for radiation dosimetry of radionuclides in the lung

Radioactive aerosols that arise from natural sources and nuclear accidents can be a long-term hazard to human health. Despite the heterogeneous particle deposition in the respiratory tract, uniform aerosol doses have long been assumed in respiratory radiation dosimetry predictions, such as in the compartment and uniform distribution models. It is unclear how these deposition patterns affect internal radiation doses, which are critical in the health assessment of radioactive hazards. This work seeks to quantify the radio-dosimetry sensitivity to initial deposition patterns by comparing computational and compartment/uniform models. A new approach was developed to implement the compartment model into voxel phantoms (e.g. VIP-man) for radiation dosimetry. The calculated radiation fluence, energy deposition density and organ doses were compared to those obtained from coupling computational fluid-particle dynamics (CFPD) with Monte Carlo radiation transport and to those obtained from uniform source distribution approximation. The results show that the source particle distribution within the respiratory system substantially influences the radiation dosimetry distribution. The compartment and uniform models underestimated aerosol deposition in the crania ridge, leading to lower doses in the trachea and surrounding organs. For 0.5 MeV gammas, the CFPD-Monte Carlo N-particle (MCNP) model predicted a tracheal dose twice that of the compartment model and four times the uniform model. For 1 MeV betas, the CFPD-MCNP-predicted tracheal dose is 2.6 times that of the compartment model and 14 times the uniform model. Compared to the compartment/uniform models, the CFPD approach predicted a 50% lower beta dose in the lung but higher beta doses in the heart (six times), liver (four times) and stomach (2.5 times). It is suggested that including compartments for the lung periphery and tracheal carina ridge may improve the dosimetry accuracy of compartment models.

Radiation Dosimetry of Inhaled Radioactive Aerosols: CFPD and MCNP Transport Simulations of Radionuclides in the Lung

Despite extensive efforts in studying radioactive aerosols, including the transmission of radionuclides in different chemical matrices throughout the body, the internal organ-specific radiation dose due to inhaled radioactive aerosols has largely relied on experimental deposition data and simplified human phantoms. Computational fluid-particle dynamics (CFPD) has proven to be a reliable tool in characterizing aerosol transport in the upper airways, while Monte Carlo based radiation codes allow accurate simulation of radiation transport. The objective of this study is to numerically assess the radiation dosimetry due to particles decaying in the respiratory tract from environmental radioactive exposures by coupling CFPD with Monte Carlo N-Particle code, version 6 (MCNP6). A physiologically realistic mouth-lung model extending to the bifurcation generation G9 was used to simulate airflow and particle transport within the respiratory tract. Polydisperse aerosols with different distributions were considered, and deposition distribution of the inhaled aerosols on the internal airway walls was quantified. The deposition mapping of radioactive aerosols was then registered to the respiratory tract of an image-based whole-body adult male model (VIP-Man) to simulate radiation transport and energy deposition. Computer codes were developed for geometry visualization, spatial normalization, and source card definition in MCNP6. Spatial distributions of internal radiation dosimetry were compared for different radionuclides (¹³¹I, ^134,137Cs, ⁹⁰Sr-⁹⁰Y, ¹⁰³Ru and ^239,240Pu) in terms of the radiation fluence, energy deposition density, and dose per decay.

Nanoparticle Deposition in Rhythmically Moving Acinar Models with Interalveolar Septal Apertures

Pulmonary delivery of nanomedicines has been extensively studied in recent years because of their enhanced biocompatibility, sustained-release properties, and surface modification capability. The lung as a target also offers many advantages over other routers, such as large surface area, noninvasive, quick therapeutic onset, and avoiding first-pass metabolism. However, nanoparticles smaller than 0.26 µm typically escape phagocytosis and remain in the alveoli for a long time, leading to particle accumulation and invoking tissue responses. It is imperative to understand the behavior and fates of inhaled nanoparticles in the alveoli to reliably assess therapeutic outcomes of nanomedicines or health risk of environmental toxins. The objective of this study is to numerically investigate nanoparticle deposition in a duct-alveolar model with varying sizes of inter-alveolar septal apertures (pores). A discrete phase Lagrangian model was implemented to track nanoparticle trajectories under the influence of rhythmic wall expansion and contraction. Both temporal and spatial dosimetry in the alveoli were computed. Wall motions are essential for nanoparticles to penetrate the acinar region and deposit in the alveoli. The level of aerosol irreversibility (i.e., mixing of inhaled nanoparticles with residual air in the alveolar airspace) is determined by the particle diffusivity, which in turn, dictates the fraction of particles being exhaled out. When deposition in the upper airways was not considered, high alveolar deposition rates (74–95%) were predicted for all nanoparticles considered (1–1000 nm), which were released into the alveoli at the beginning of the inhalation. The pore size notably affects the deposition pattern of inhaled nanoparticles but exerts a low impact upon the total deposition fractions. This finding indicates that consistent pulmonary doses of nanomedicine are possible in emphysema patients if breathing maneuver with the same tidal volume can be performed.