Our lungs contain a branching network of airways. Lung stability and normal breathing is maintained by a natural substance called surfactant. The lungs of most premature babies are underdeveloped and lack surfactant, making breathing very difficult for the newborn. These babies often receive a treatment that involves instilling a surfactant solution into their windpipe. Airflow from a ventilator is then used to direct the solution into the lung airways. The success of this treatment heavily depends on the uniformity of distribution of surfactant in airways. However, evidence from x-ray imaging shows non-uniform surfactant distribution, leading to a poor response to the treatment. Improving this treatment and its effectiveness has proved difficult due to inaccessibility of airways. This project will address this unresolved issue by using a combined experimental and simulation approach. We will design realistic models of human lung airways, use them to study surfactant delivery to the lungs, and determine delivery conditions that lead to a uniform surfactant distribution, thereby making the treatment more effective. In addition to providing training opportunities to students and promoting diversity through outreach programs, our project will also make a transformative impact through developing new tools and elucidating fluid flow in lung airways.
The overarching goal of this project is to understand fluid dynamics of surfactant delivery and distribution in conducting zone airways. Using a set of design rules, we generate 3D computational models of airway tree and fabricate them using additive manufacturing. We will then use complementary experimental and computational studies to quantitatively elucidate how fluid type (Newtonian and non-Newtonian surfactants), airflow type (constant vs cyclic), and gravitational orientation of the airway tree affect surfactant deposition and distribution in airways. We will achieve this goal through two specific aims: (i) Quantitatively study surfactant distribution in lung airway tree under constant airflow; and (ii) Cyclic airflow and pre-existing surfactant film effects on surfactant distribution. This work will make a transformative impact on fundamental understanding of fluid dynamics of multi-phase flow in lung airways and lead to design of strategies to enhance surfactant replacement therapy.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
