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research-article

Assessing Airflow Sensitivity to Healthy and Diseased Lung Conditions in a Computational Fluid Dynamics Model Validated In Vitro

[+] Author and Article Information
Bora Sul

Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, Maryland
bsul@bhsai.org

Zachary Oppito

Mechanical Engineering Department, Rochester Institute of Technology, Rochester, New York
zto3889@rit.edu

Shehan Jayasekera

Mechanical Engineering Department, Rochester Institute of Technology, Rochester, New York
shehan.droid@gmail.com

Brian Vanger

Mechanical Engineering Department, Rochester Institute of Technology, Rochester, New York
bsv6329@rit.edu

Amy Zeller

Mechanical Engineering Department, Rochester Institute of Technology, Rochester, New York
amz8073@rit.edu

Michael Morris

Department of Medicine, San Antonio Military Medical Center, JBSA Fort Sam Houston, Texas
michael.j.morris34.civ@mail.mil

Kai Ruppert

Radiolology Department, University of Pennsylvania, Philadelphia, Pennsylvania
kai.ruppert@gmail.com

Talissa Altes

Department of Radiology, University of Missouri, Columbia, Missouri
altest@health.missouri.edu

Vineet Rakesh

Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, Maryland
vineetrakesh@gmail.com

Steven Day

Mechanical Engineering Department, Rochester Institute of Technology, Rochester, New York
swdeme@rit.edu

Risa J. Robinson

Mechanical Engineering Department, Rochester Institute of Technology, Rochester, New York
rjreme@rit.edu

Jaques Reifman

Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, Maryland
jaques.reifman.civ@mail.mil

Anders Wallqvist

Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, Maryland
sven.a.wallqvist.civ@mail.mil

1Corresponding author.

ASME doi:10.1115/1.4038896 History: Received December 21, 2016; Revised October 18, 2017

Abstract

Computational models are useful for understanding respiratory physiology. Crucial to such models are the boundary conditions specifying the flow conditions at truncated airway branches (terminal flow rates). However, most studies make assumptions about these values, which are difficult to obtain in vivo. We developed a computational fluid dynamics (CFD) model of airflows for steady expiration to investigate how terminal flows affect airflow patterns in respiratory airways. First, we measured in vitro airflow patterns in a physical airway model, using particle image velocimetry. The measured and computed airflow patterns agreed well, validating our CFD model. Next, we used the lobar flow fractions from a healthy or chronic obstructive pulmonary disease (COPD) subject as constraints to derive different terminal flow rates (i.e., three healthy, one COPD), and computed the corresponding airflow patterns in the same geometry. To assess airflow sensitivity to the boundary conditions, we used the correlation coefficient of the shape similarity (R) and the root mean square of the velocity magnitude difference (Drms) between two velocity contours. Airflow patterns in the central airways were similar across healthy conditions (minimum R, 0.80) despite variations in terminal flow rates, but markedly different for COPD (minimum R, 0.26; maximum Drms, 10 times that of healthy cases). In contrast, those in the upper airway were similar for all cases. Our findings quantify how variability in terminal and lobar flows contribute to airflow patterns in respiratory airways. They highlight the importance of using lobar flow fractions to examine physiologically relevant airflow characteristics.

Copyright (c) 2017 by ASME
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