Numerical modeling of particle deposition in the conducting airways of asthmatic children

Optimal Treatment of Tumor in Upper Human Respiratory Tract Using Microaerosols

Lung cancer is a frequently diagnosed respiratory disease caused by particulate matter in the environment, especially among older individuals. For its effective treatment, a promising approach involves administering drug particles through the inhalation route. Multiple studies have investigated the flow behavior of inhaled particles in the respiratory airways of healthy patients. However, the existing literature lacks studies on the precise understanding of the transportation and deposition (TD) of inhaled particles through age-specific, unhealthy respiratory tracts containing a tumor, which can potentially optimize lung cancer treatment. This study aims to investigate the TD of inhaled drug particles within a tumorous, age-specific human respiratory tract. The computational model reports that drug particles within the size range of 5-10 μm are inclined to deposit more on the tumor located in the upper airways of a 70-year-old lung. Conversely, for individuals aged 50 and 60 years, an optimal particle size range for achieving the highest degree of particle deposition onto upper airway tumor falls within the 11-20 μm range. Flow disturbances are found to be at a maximum in the airway downstream of the tumor. Additionally, the impact of varying inhalation flow rates on particle TD is examined. The obtained patterns of airflow distribution and deposition efficiency on the tumor wall for different ages and tumor locations in the upper tracheobronchial airways would be beneficial for developing an efficient and targeted drug delivery system.

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 16^th generation of terminal bronchi.

METHODS

The realistic bronchi up to the 8^th generation are precisely and perfectly generated from computed tomography (CT) images, and an artificial model compensates for the 9^th-16^th 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 8^th generation; whilst the hot-spot of the deposited coarse particles was found in the 6^th 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.

A path forward in the development of new aerosol drug delivery devices for pediatrics

Inhaled medications are widely accepted as being the optimal route for treating pediatric respiratory diseases, a leading cause of hospitalization and death. Despite jet nebulizers being the preferred inhalation device for neonates and infants, current devices face performance issues with most of the drug never reaching the target lung location. Previous work has aimed to improve pulmonary drug deposition, yet nebulizer efficiency remains low. The development of an inhalant therapy that is efficacious and safe for pediatrics depends on a well-designed delivery system and formulation. To accomplish this, the field needs to rethink the current practice of basing pediatric treatments on adult studies. The rapidly evolving pediatric patient (i.e. neonates to eighteen) needs to be considered because they are different from adults with respect to airway anatomy, breathing patterns, and adherence. Previous research approaches to improve deposition efficiency have been limited due to the complexity of combining physics, which drives aerosol transport and deposition, and biology, especially within the area of pediatrics. To address these critical knowledge gaps, we need a better understanding of how patient age and disease state affect deposition of aerosolized drugs. The complexity of the multiscale respiratory system makes scientific investigation very challenging. The authors have simplified the complex problem into five components with these three areas as ones to address first: how the aerosol is (i) generated in a medical device, (ii) delivered to the patient, and (iii) deposited inside the lung. In this review, we discuss the technological advances and innovations made from experiments, simulations, and predictive models in each of these areas. In addition, we discuss the impact on patient treatment efficacy and recommend a clinical direction, with a focus on pediatrics. In each area, a series of research questions are posed and steps for future research to improve efficacy in aerosol drug delivery are outlined.

Association between ambient PM2.5 and outpatient visits of children's respiratory diseases in a megacity in Central China

Objective

To explore the relationship between ambient PM_2.5 level and outpatient visits of children with respiratory diseases in a megacity, Zhengzhou, in central China.

Methods

We collected daily outpatient visit data, air pollutant data, and meteorological data at the monitoring points of Zhengzhou from the time period 2018 to 2020 and used Spearman's rank correlation to analyze the correlation between children's respiratory outpatient visits and air pollutants and meteorological factors. Generalized additive models were used to analyze the association between PM_2.5 exposures and children's respiratory outpatient visits. A stratified analysis was further carried out for the seasons.

Results

From 2018 to 2020, the total number of outpatients with children's respiratory diseases was 79,1107, and the annual average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃-8h in Zhengzhou were respectively 59.48 μg/m³, 111.12 μg/m³, 11.10 μg/m³, 47.77 μg/m³, 0.90 mg/m³ and 108.81 μg/m³. The single-pollutant model showed that the risk of outpatient visits for children with respiratory disease increased by 0.341% (95%CI: 0.274-0.407%), 0.532% (95%CI: 0.455-0.609%) and 0.233% (95%CI: 0.177-0.289%) for every 10 μg/m³ increase in PM_2.5 with a 3-day lag, 1-day lag, and 1-day lag respectively for the whole year, heating period, and non-heating period. The multi-pollutant model showed that the risk of PM_2.5 on children's respiratory disease visits was robust. The excess risk of PM_2.5 on children's respiratory disease visits increased by 0.220% (95%CI: 0.147-0.294%) when SO₂ was adjusted. However, the PM_2.5 effects were stronger during the heating period than during the non-heating period.

Conclusion

The short-term exposure to PM_2.5 was significantly associated with outpatient visits for children's respiratory diseases. It is therefore necessary to strengthen the control of air pollution so as to protect children's health.

Algebraic approximation of the distributed model for the pressure drop in the respiratory airways

The complexity of the human respiratory system causes that one of the main methods of analyzing the dynamic pulmonary phenomena and interpreting experimental results are simulations of its computational models. Among the most compound elements of these models, apart from the bronchial tree structure, is the phenomenon of flow limitation in flexible bronchi, which causes them to collapse with increasing flow, thus their properties, such as resistance, compliance and inertance, are highly nonlinear and time-varying. Commonly, this phenomenon is ignored, or a distributed model for the airway pressure drop is applied, simulated with a modified numerical solver of this differential equation (ODE). The disadvantages of this solution are the problems with taking into account the inherent singularity of the model and the long computation time due to iterative nature of the ODE procedure. The aim of the work was to derive an algebraic approximation of this distributed model, suitable for implementation in continuous dynamic models, to validate it by comparing the results of simulations with the respiratory system model including approximate and original (ODE solver) numerical procedures, as well as to evaluate possible acceleration of calculations. All simulations, including spontaneous breathing, mechanical ventilation with the optimal ventilatory waveform and forced expiration, proved that algebraic approximation yielded results negligibly differing from the ODE solution, and shortened the computation time by an order. The proposed approach is an attractive alternative in the case of computer implementations of pulmonary models, where simulations of flows and pressures in the complex respiratory system are of primary importance.

Aerosol Particle Transport and Deposition in Upper and Lower Airways of Infant, Child and Adult Human Lungs

Understanding transportation and deposition (TD) of aerosol particles in the human respiratory system can help clinical treatment of lung diseases using medicines. The lung airway diameters and the breathing capacity of human lungs normally increase with age until the age of 30. Many studies have analyzed the particle TD in the human lung airways. However, the knowledge of the nanoparticle TD in airways of infants and children with varying inhalation flow rates is still limited in the literature. This study investigates nanoparticle (5 nm ≤ dp ≤ 500 nm) TD in the lungs of infants, children, and adults. The inhalation air flow rates corresponding to three ages are considered as Qin=3.22 L/min (infant), 8.09 L/min (Child), and Qin=14 L/min (adult). It is found that less particles are deposited in upper lung airways (G0–G3) than in lower airways (G12–G15) in the lungs of all the three age groups. The results suggest that the particle deposition efficiency in lung airways increases with the decrease of particle size due to the Brownian diffusion mechanism. About 3% of 500 nm particles are deposited in airways G12–G15 for the three age groups. As the particle size is decreased to 5 nm, the deposition rate in G12–G15 is increased to over 95%. The present findings can help medical therapy by individually simulating the distribution of drug-aerosol for the patient-specific lung.

The effect of the volumetric flow rate and endotracheal tube diameter on the pressure distribution in human airways

The comprehension of the fluid flow in the upper airways is of paramount importance when treating patients under clinical conditions that demand mechanical ventilation. Barotrauma and overdistension are related to undesirable pressures and might be responsible for morbidity and mortality. In the current work we use computational fluid dynamics to investigate the pressure field in the upper respiratory airways. We performed a set of simulations varying the volumetric flow rate of mechanical ventilators and we have shown that the pressure profile can be calculated by means of the volumetric flow rate in accordance with a mathematical expression given by P_av=aV˙², where P_av is the average pressure at selected sections of the upper airways and V˙ is the volumetric flow rate. Numerical findings provide evidence that the constant a varies with the location of the plane in the upper airways. We also show that some particular diameters of endotracheal tubes (ETT) must be used with care for a given range of volumetric flow rates. Overall, we document an important relationship among pressure, volumetric flow rate and selected internal diameters from ETT.

Computational fluid dynamics modelling of human upper airway: A review

BACKGROUND AND OBJECTIVE

Human upper airway (HUA) has been widely investigated by many researchers covering various aspects, such as the effects of geometrical parameters on the pressure, velocity and airflow characteristics. Clinically significant obstruction can develop anywhere throughout the upper airway, leading to asphyxia and death; this is where recognition and treatment are essential and lifesaving. The availability of advanced computer, either hardware or software, and rapid development in numerical method have encouraged researchers to simulate the airflow characteristics and properties of HUA by using various patient conditions at different ranges of geometry and operating conditions. Computational fluid dynamics (CFD) has emerged as an efficient alternative tool to understand the airflow of HUA and in preparing patients to undergo surgery. The main objective of this article is to review the literature that deals with the CFD approach and modeling in analyzing HUA.

METHODS

This review article discusses the experimental and computational methods in the study of HUA. The discussion includes computational fluid dynamics approach and steps involved in the modeling used to investigate the flow characteristics of HUA. From inception to May 2020, databases of PubMed, Embase, Scopus, the Cochrane Library, BioMed Central, and Web of Science have been utilized to conduct a thorough investigation of the literature. There had been no language restrictions in publication and study design of the database searches. A total of 117 articles relevant to the topic under investigation were thoroughly and critically reviewed to give a clear information about the subject. The article summarizes the review in the form of method of studying the HUA, CFD approach in HUA, and the application of CFD for predicting HUA obstacle, including the type of CFD commercial software are used in this research area.

RESULTS

This review found that the human upper airway was well studied through the application of computational fluid dynamics, which had considerably enhanced the understanding of flow in HUA. In addition, it assisted in making strategic and reasonable decision regarding the adoption of treatment methods in clinical settings. The literature suggests that most studies were related to HUA simulation that considerably focused on the aspects of fluid dynamics. However, there is a literature gap in obtaining information on the effects of fluid-structure interaction (FSI). The application of FSI in HUA is still limited in the literature; as such, this could be a potential area for future researchers. Furthermore, majority of researchers present the findings of their work through the mechanism of airflow, such as that of velocity, pressure, and shear stress. This includes the use of Navier-Stokes equation via CFD to help visualize the actual mechanism of the airflow. The above-mentioned technique expresses the turbulent kinetic energy (TKE) in its result to demonstrate the real mechanism of the airflow. Apart from that, key result such as wall shear stress (WSS) can be revealed via turbulent kinetic energy (TKE) and turbulent energy dissipation (TED), where it can be suggestive of wall injury and collapsibility tissue to the HUA.

Particle transport and deposition correlation with near-wall flow characteristic under inspiratory airflow in lung airways

Exposure of lung airways to detrimental suspended aerosols in the environment increases the vulnerability of the respiratory and cardiovascular systems. In addition, recent developments in therapeutic inhalation devices magnify the importance of particle transport. In this manuscript, particle transport and deposition patterns in the upper tracheobronchial (TB) tree were studied where the inertial forces are considerable for microparticles. Wall shear stress divergence (WSSdiv) is proposed as a wall-based parameter that can predict particle deposition patterns. WSSdiv is proportional to near-wall normal velocity and can quantify the strength of flow towards and away from the wall. Computational fluid dynamics (CFD) simulations were performed to quantify airflow velocity and WSS vectors for steady inhalation in one case-control and unsteady inhalation in six subject-specific airway trees. Turbulent flow simulation was performed for the steady case using large eddy simulation to study the effect of turbulence. Magnetic resonance velocimetry (MRV) measurements were used to validate the case-control CFD simulation. Inertial particle transport was modeled by solving the Maxey-Riley equation in a Lagrangian framework. Deposition percentage (DP) was quantified for the case-control model over five particle sizes. DP was found to be proportional to particle size in agreement with previous studies in the literature. A normalized deposition concentration (DC) was defined to characterize localized deposition. A relatively strong correlation (Pearson value > 0.7) was found between DC and positive WSSdiv for physiologically relevant Stokes (St) numbers. Additionally, a regional analysis was performed after dividing the lungs into smaller areas. A spatial integral of positive WSSdiv over each division was shown to maintain a very strong correlation (Pearson value > 0.9) with cumulative spatial DC or regional dosimetry. The conclusions were generalized to a larger population in which two healthy and four asthmatic patients were investigated. This study shows that WSSdiv could be used to predict the qualitative surface deposition and relative regional dosimetry without the need to solve a particle transport problem.