AUTHOR=Ilegbusi Olusegun J. , Khan Rafid Jahangir , Hoffman Bari 

TITLE=Computational modeling of cough-induced droplets and mucosal film dynamics in the upper airway for pulmonary disease classification

JOURNAL=Frontiers in Physiology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2025.1666826

DOI=10.3389/fphys.2025.1666826

ISSN=1664-042X

ABSTRACT=IntroductionCough-generated droplets are critical in the transmission and progression of respiratory diseases. This study investigates droplet formation and transport in the upper airway during a cough to improve understanding of their biomechanical behavior and explore their potential for non-invasive classification of airway diseases. MethodsA computational fluid dynamics model is employed to simulate a transient, droplet-laden cough in a CT-derived human upper airway, using an experimentally acquired cough profile. The method incorporates mucus film dynamics using the Eulerian Wall Film (EWF) model and droplet transport using the Discrete Phase Model (DPM). Three mucus thicknesses—healthy baseline (Type I), intermediate pathological thickening (Type II), and advanced pathological thickening (Type III)—and three viscosity levels for Type II: baseline viscosity (Type II-A), intermediate viscosity (Type II-B), and high viscosity (Type II-C) are considered. These cases represent a progressive increase in both mucus thickness and viscosity, encompassing a spectrum of respiratory conditions. ResultsThe results show that a 50% increase in mucus thickness (from 20 μm to 30 μm) results in 4.3-fold increase in exhaled droplet count and a 20% increase in mean droplet size. Conversely, a 50% increase in mucus viscosity reduces exhaled droplet count by 2.7-fold while increasing mean droplet size by 9%. Absorbed droplets, which remain within the airway, exhibit similar trends; however, as they are not measurable non-invasively, their diagnostic utility is limited. DiscussionThese findings highlight the role of mucus in droplet dynamics, with increased thickness and viscosity driving larger droplet sizes, with increased thickness and viscosity driving larger droplet sizes, and support the potential of exhaled droplet size distribution as a diagnostic biomarker for airway disease.