Computational fluid-particle dynamics modeling of ultrafine to coarse particles deposition in the human respiratory system, down to the terminal bronchiole.

BACKGROUND AND OBJECTIVES: Suspended respirable airborne particles are associated with human health risks and especially particles within the range of ultrafine (< 0.1 µm) or fine (< 2.5 µm) have a high possibility of penetrating the lung region, which is concerned to be closely related to the bronchial or alveoli tissue dosimetry. Nature complex structure of the respiratory system requires much effort to explore and comprehend the flow and the inhaled particle dynamics for precise health risk assessment. Therefore, this study applied the computational fluid-particle dynamics (CFPD) method to elucidate the deposition characteristics of ultrafine-to-coarse particles in the human respiratory tract from nostrils to the 16th generation of terminal bronchi. METHODS: The realistic bronchi up to the 8th generation are precisely and perfectly generated from computed tomography (CT) images, and an artificial model compensates for the 9th-16th bronchioles. Herein, the steady airflow is simulated at constant breathing flow rates of 7.5, 15, and 30 L/min, reproducing human resting-intense activity. Then, trajectories of the particle size ranging from 0.002 - 10 µm are tracked using a discrete phase model. RESULTS: Here, we report reliable results of airflow patterns and particle deposition efficiency in the human respiratory system validated against experimental data. The individual-related focal point of ultrafine and fine particles deposition rates was actualized at the 8th generation; whilst the hot-spot of the deposited coarse particles was found in the 6th generation. Lobar deposition characterizes the dominance of coarse particles deposited in the right lower lobe, whereas the left upper-lower and right lower lobes simultaneously occupy high deposition rates for ultrafine particles. Finally, the results indicate a higher deposition in the right lung compared to its counterpart. CONCLUSIONS: From the results, the developed realistic human respiratory system down to the terminal bronchiole in this study, in coupling with the CFPD method, delivers the accurate prediction of a wide range of particles in terms of particle dosimetry and visualization of site-specific in the consecutive respiratory system. In addition, the series of CFPD analyses and their results are to offer in-depth information on particle behavior in human bronchioles, which may benefit health risk assessment or drug delivery studies.

In-silico decongested trial effects on the impaired breathing function of a bulldog suffering from severe brachycephalic obstructive airway syndrome.

BACKGROUND AND OBJECTIVE: Brachycephalic obstructive airway syndrome (BOAS) susceptible dogs (e.g., French bulldog), suffer health complications related to deficient breathing primarily due to anatomical airway geometry. Surgical interventions are known to provide acceptable functional and cosmetic results; however, the long-term post-surgery outcome is not well known. In silico analysis provides an objective measure to quantify the respiratory function in postoperative dogs which is critical for successful long-term outcomes. A virtual surgery to open the airway can explore the ability for improved breathing in an obstructed airway of a patient dog, thus supporting surgeons in pre-surgery planning using computational fluid dynamics. METHODS: In this study five surgical interventions were generated with a gradual increment of decongested levels in a bulldog based on computed tomography images. The effects of the decongested airways on the breathing function of a patient bulldog, i.e., airflow characteristics, pressure drop, wall shear stress, and air-conditioning capacity, were quantified by benchmarking against a clinically healthy bulldog using computational fluid dynamics (CFD) method. RESULTS: Our findings demonstrated a promising decrease in excessive airstream velocity, pressure drop, and wall shear stress in virtual surgical scenarios, while constantly preserving adequate air-conditioning efficiency. A linear fit curve was proposed to correlate the reduction in the pressure drop and decongested level. CONCLUSIONS: The in silico analysis is a viable tool providing visual and quantitative insight into new unexplored surgical techniques.

Computational fluid dynamics comparison of impaired breathing function in French bulldogs with nostril stenosis and an examination of the efficacy of rhinoplasty.

BACKGROUND: Brachycephalic obstructive airway syndrome (BOAS) in dogs indicates a particular set of upper airway abnormalities found in brachycephalic dogs (e.g., French bulldogs). Stenotic nares is one of the primary BOAS-related abnormalities restricting the functional breathing of affected dogs. For severe stenosis, rhinoplasty is required to increase the accessibility of the external nostril to air; however, the specific improvement from surgery in terms of respiratory physiology and uptake of inhaled air has not been fully elucidated METHOD: This study employed Computational Fluid Dynamics (CFD) simulations to evaluate the effects of different stenotic intensities on airflow patterns in a total of eight French bulldog upper airways. A bulldog with severe stenosis after surgery was included to examine the efficacy of the surgical intervention. RESULTS: The results showed homogeneous airflow distributions in healthy and mild stenosis cases and significantly accelerated airstreams at the constricted positions in moderate and severe stenosis bulldogs. The airflow resistance was over 20-fold greater in severe stenosis cases than the healthy cases. After surgery, a decrease in airflow velocity was observed in the surgical region, and the percentage of reduced airflow resistance was approximately 4%. CONCLUSIONS: This study suggests impaired breathing function in brachycephalic dogs with moderate and severe stenosis. The results also serve as a reference for veterinarians in surgical planning and monitoring bulldogs' recuperation after surgery.

Numerical modeling of nanoparticle deposition in realistic monkey airway and human airway models: a comparative study.

BACKGROUND: One of the most promising approaches to understand inhalation toxicology and to assess the potential risks of inhaled particles is to examine the disposition of the hazardous airborne particles in the monkey airway. This study presents a comparative, numerical investigation of nanoparticle deposition in the monkey and human airway models. MATERIALS AND METHODS: Computational fluid dynamics (CFD) method was applied to analyze the steady flow rates under light and moderate metabolic conditions. The nanoparticles, ranging from 5 to 100 nm in diameter, were used to predict the total and regional deposition fraction in both the models. RESULTS: The Brownian and turbulent motion significantly impacted the transportation and deposition of nanoparticles as evidenced by the large fluctuations of particle acceleration. A higher deposition efficiency was observed in the monkey model at the particle size of 25 nm or less. Nonetheless, on applying the geometric factors for combined diffusion term parameters, the total deposition fraction of both models converged into a single curve. The site-specific deposition of the particles of size 5 nm in the vestibule, valve, and nasal turbinate regions of the monkey model was observed to be greater compared to the human model. A study of the deposition curves of the particle diameter ranging from 2 nm to 10 µm showed that the highest deposition rates were associated with particles of size 2 nm and 10 µm. CONCLUSIONS: The results of this study can contribute to the research involving extrapolation of inhalation toxicology studies, from monkeys to humans.

CFD analysis of the flow structure in a monkey upper airway validated by PIV experiments.

Inhalation exposure to airborne contaminants has adverse effects on humans; however, related research is typically conducted using in vivo/in vitro tests on animals. Extrapolating the test results is complicated by anatomical and physiological differences between animals and humans and a lack of understanding of the transport mechanism inside their respective respiratory tracts. This study determined the detailed air-flow structure in the upper airway of a monkey. A steady computational fluid dynamics simulation, which was validated by previous particle image velocimetry measurements, was adopted for flow rates of 4 L/min and 10 L/min to analyze the flow structure from the nasal/oral cavities to the trachea region in a monkey airway model. The low Reynolds number type k-ε model provided a reasonably accurate prediction of the airflow in a monkey upper airway. Furthermore, it was confirmed that large velocity gradients were generated in the nasal vestibule and larynx regions, as well as increased turbulent air kinetic energy and wall sheer stress.

Flow visualization through particle image velocimetry in realistic model of rhesus monkey's upper airway.

Studies concerning inhalation toxicology and respiratory drug-delivery systems require biological testing involving experiments performed on animals. Particle image velocimetry (PIV) is an effective in vitro technique that reveals detailed inhalation flow patterns, thereby assisting analyses of inhalation exposure to various substances. A realistic model of a rhesus-monkey upper airway was developed to investigate flow patterns in its oral and nasal cavities through PIV experiments performed under steady-state constant inhalation conditions at various flow rates-4, 10, and 20 L/min. Flow rate of the fluid passing through the inlet into the trachea was measured to obtain characteristic flow mechanisms, and flow phenomena in the model were confirmed via characterized flow fields. It was observed that increase in flow rate leads to constant velocity profiles in upper and lower trachea regions. It is expected that the results of this study would contribute to future validation of studies aimed at developing in silico models, especially those involving computational fluid dynamic (CFD) analysis.