(470g) A Computational Multiphase Flow Model to Predict the Transport and Deposition of Inhaled Flu Virus-Laden Droplets in Human Respiratory Tracts for Early Infection Diagnosis

Keywords: Influenza Virus; Computational Fluid-Particle Dynamics (CFPD); Oxidative Stress; Noninvasive Early Diagnosis

Introduction

Influenza A virus (IAV) is highly transmissible as one of the leading causes of pulmonary infections such as pneumonia. 5 to 20% of the population in the United States contract influenza every year. Three circulating subtypes, i.e., type A/H1N1, type A/H3N2, and type B, can infect humans and cause massive global epidemics. IAVs pass among individuals through the air in droplets when someone sneezes or coughs. The airborne transmission of infectious substances expelled by the respiration system of an infected patient is commonly known to be the key contagion mechanism. Specifically, in the elderly (>65 years), in infants (0-4 years), and in people with chronic diseases, influenza is associated with especially high mortality. Influenza virus replicates in the epithelial cells throughout the respiratory tree, with the virus being recoverable from both the upper and lower respiratory tract of people naturally or experimentally infected. The epithelium of the trachea, bronchi and the pulmonary alveoli were primary sites of influenza viral replication. Moreover, lower airway infections can result in flooding of the alveolar compartment, development of acute respiratory distress syndrome and death from respiratory failure. Current approaches to diagnosis and surveillance rely heavily on clinical case definitions and a variety of laboratory assays, which are too slow. Therefore, early diagnosis of IAV infection is significant to improve treatment outcomes and decrease the use of antibiotics, especially for children. It can also aid the surveillance for the assessment of the current contamination situation and control the pandemic disease. The long-term goal is to develop a noninvasive and accurate early diagnostic methodology which will be able to detect the infection before the onset of symptomatic disease. The method should also be sensitive and specific, which can be used to identify the virus type, a primary infected region in the respiratory tracts, and the infection severity. Oxidative stress plays a key pathophysiological role. Influenza Infection may result in increased oxidative stress and induced increased excretion of VOC biomarkers in the breath such as alkanes and methylated alkanes. Enlightened by this fact, the research objective of this study is to virtually design and test the noninvasive diagnostic framework using a new multiscale computational model. The central hypothesis is that the exhaled VOC pattern variations can reflect the details of virus infection status in human pulmonary tracts. To virtually test the feasibility of the proposed diagnosis, the multiscale numerical model should be capable of capturing the transport and deposition dynamics of the inhaled virus-laden droplets, and the after-deposition dynamics (or within-host dynamics) of the virus to track the change of VOC biomarkers in human respiratory tracts. However, it is still a lack of effective tools to predict the human uptakes of the flu virus due to different exposure conditions, Significant knowledge gaps still exist regarding the quantitative relationships between exhaled VOC biomarkers and the influenza infections. Therefore, in this study, a computational multiphase flow model based on a Euler-Euler scheme is developed to predict the transport and deposition of inhaled flu virus-laden droplets in human respiratory tracts. The amount of pathogens inhaled and the regional deposition in upper airways and deeper airways are quantitatively predicted. Additionally, a compartment model is also developed for the within-host dynamics of the virus in epithelial cells.

The Multiscale Computational Model

A Computational Fluid-Particle Dynamics (CFPD) model is developed based on the Euler-Euler scheme to simulate the transport and deposition of flu virus-laden droplets transport in human respiratory systems. Realistic transient breathing conditions (Gupta et al., 2010) and indoor ventilation conditions will be applied (Ge et al., 2013). Physiochemical properties of virus-laden droplets were retrieved from realistic cough and sneeze aerosols (Gupta et al., 2010; Kwon et al., 2012; Thatiparti et al., 2017). Simulations will be performed in subject-specific human respiratory configurations from mouth to G6, which are reconstructed from CT/MRI data. Specifically, droplet diameter ranges from 0.4-30 µm, and droplet density is 1.388 kg/m³. Numerical solutions with appropriate boundary conditions were achieved by using a user-enhanced, commercial finite-volume based program, i.e., ANSYS Fluent and CFX 18.0 (ANSYS Inc., Canonsburg, PA). The shear stress transport (SST) transition model was employed to solve the laminar-to-turbulence airflow fields.

To bring the simulation process to the health endpoint, we will also establish a compartment model to describe the after-deposition dynamics in epithelial cells, i.e., within-host dynamics (Pawelek et al., 2012). It will include tracking the number changes of uninfected epithelial cells, infected epithelial cells, refractory cells, free virus, and IFN. Major mechanisms include infection, virus production, epithelial cell apoptosis, IFN-induced antiviral effect, as well as the concentrations of VOC biomarkers excreted.

Proposed Results Mainstream and secondary flow patterns and their influence on virus-laden transport will be visualized and discussed. Parametric analyses will be performed for the impacts of morphological variations and breathe patterns on virus local deposition in human respiratory tracts. The relationship between direct virus deposition and lower airway infection will be investigated based on the quantitative deposition data. The time courses of the flu virus and VOC biomarkers excreted due to the infection will also be tracked using the compartment model. Furthermore, inter-subject variability study will be performed numerically to evaluate the generality of the proposed diagnostic methodology.

Summary

Using the experimentally validated multiscale computational model, the lung aerosol dynamics simulation with realistic exposure conditions (coughing and indoor ventilation) provides us accurate and high-resolution data of virus transport and deposition in the human respiratory tract, which will be informative for the determination of the relationship between exposure, intakes and uptakes of the virus. The quantitative data pave the way for multiscale modeling include the within-host dynamics of the virus. The future multiscale model will provide a noninvasive and time-saving numerical tool guide the noninvasive diagnosis of the early detection of different influenza infection by providing information for virus transport, deposition, production, and elimination, as well as the VOC biomarker generation dynamics. It will also significantly contribute to: (1) optimize the indoor ventilation to control the transmission of the airborne infectious diseases mechanically; and (2) Evaluate the effectiveness of vaccines to cure pulmonary diseases.

Acknowledgements

The authors are grateful for the financial support by NIH (No. P20GM103648), and the use of ANSYS Software (ANSYS Inc., Canonsburg, PA) as part of the OSU-ANSYS Academic Partnership.

References

Ge, Q., Li, X., Inthavong, K., & Tu, J. (2013). Numerical study of the effects of human body heat on particle transport and inhalation in indoor environment. Building and Environment, 59, 1-9.

Gupta, J. K., Lin, C. H., & Chen, Q. (2010). Characterizing exhaled airflow from breathing and talking. Indoor air, 20(1), 31-39.

Kwon, S. B., Park, J., Jang, J., Cho, Y., Park, D. S., Kim, C., ... & Jang, A. (2012). Study on the initial velocity distribution of exhaled air from coughing and speaking. Chemosphere, 87(11), 1260-1264.

Pawelek, K. A., Huynh, G. T., Quinlivan, M., Cullinane, A., Rong, L., & Perelson, A. S. (2012). Modeling within-host dynamics of influenza virus infection including immune responses. PLoS Comput Biol, 8(6), e1002588.

Thatiparti, D. S., Ghia, U., & Mead, K. R. (2017). Computational fluid dynamics study on the influence of an alternate ventilation configuration on the possible flow path of infectious cough aerosols in a mock airborne infection isolation room. Science and Technology for the Built Environment, 23(2), 355-366.