title: Effect of static vs. dynamic imaging on particle transport in CT-based numerical models of human central airways.
abstract: Advances in quantitative computed tomography (CT) has provided methods to assess the detailed structure of the pulmonary airways and parenchyma, providing the means of applying computational fluid dynamics-based modeling to better understand subject-specific differences in structure-to-function relationships. Most of the previous numerical studies, seeking to predict patterns of inhaled particle deposition, have considered airway geometry and regional ventilation derived from static images. Because geometric alterations of the airway and parenchyma associated with regional ventilation may greatly affect particle transport, we have sought to investigate the effect of rigid vs. deforming airways, linear vs. nonlinear airway deformations, and step-wise static vs. dynamic imaging on particle deposition with varying numbers of intermediate lung volume increments. Airway geometry and regional ventilation at different time points were defined by four-dimensional (space and time) dynamic or static CT images. Laminar, transitional, and turbulent air flows were reproduced with a three-dimensional eddy-resolving computational fluid dynamics model. Finally, trajectories of particles were computed with the Lagrangian tracking algorithm. The results demonstrated that static-imaging-based models can contribute 7% uncertainty to overall particle distribution and deposition primarily due to regional flow rate (ventilation) differences as opposed to geometric alterations. The effect of rigid vs. deforming airways on serial distribution of particles over generations was significantly smaller than reported in a previous study that used the symmetric Weibel geometric model with smaller flow rate. Rigid vs. deforming airways were also shown to affect parallel particle distribution over lobes by 8% and the differences associated with use of static vs. dynamic imaging was 18%. These differences demonstrate that estimates derived from static vs. dynamic imaging can significantly affect the assessment of particle distribution heterogeneity. The effect of linear vs. nonlinear airway deformations was within the uncertainty due to mesh size.
authors.affiliation: IIHR-Hydroscience & Engineering, The University of Iowa, Iowa City, Iowa 52242.
authors.forename: Shinjiro
authors.initials: S
authors.lastname: Miyawaki
authors.affiliation: Department of Biomedical Engineering, The University of Iowa, Iowa City, Iowa 52242 ; Department of Medicine, The University of Iowa, Iowa City, Iowa 52242 ; Department of Radiology, The University of Iowa, Iowa City, Iowa 52242.
authors.forename: Eric A
authors.initials: EA
authors.lastname: Hoffman
authors.affiliation: IIHR-Hydroscience & Engineering, The University of Iowa, Iowa City, Iowa 52242 ; Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, Iowa 52242.
authors.forename: Ching-Long
authors.initials: CL
authors.lastname: Lin
keywords: 4DCT; computational fluid dynamics; image registration; parallel distribution; serial distribution