The author developed a computational framework for the study of the correlation between airway morphology and aerosol deposition based on a population of human subjects. The major improvement on the previous framework, which consists of a geometric airway model, a computational fluid dynamics (CFD) model, and a particle tracking algorithm, lies in automatic geometry construction and mesh generation of airways, which is essential for a population-based study. The new geometric model overcomes the shortcomings of both centerline (CL)-based cylindrical models, which are based on the skeleton and average branch diameters of airways called one-dimensional (1-D) trees, and computed tomography (CT)-based models. CL-based models are efficient in terms of pre- and post-processing, but fail to represent trifurcations and local morphology. In contrast, in spite of the accuracy of CT-based models, it is time-consuming to build these models manually, and non-trivial to match 1-D trees and three-dimensional (3-D) geometry. The new model, also known as a hybrid CL-CT-based model, is able to construct a physiologically-consistent laryngeal geometry, represent trifurcations, fit cylindrical branches to CT data, and create the optimal CFD mesh in an automatic fashion. The hybrid airway geometries constructed for 8 healthy and 16 severe asthmatic (SA) subjects agreed well with their CT-based counterparts. Furthermore, the prediction of aerosol deposition in a healthy subject by the hybrid model agreed well with that by the CT-based model. To demonstrate the potential application of the hybrid model to investigating the correlation between skeleton structure and aerosol deposition, the author applied the large eddy simulation (LES)-based CFD model that accounts for the turbulent laryngeal jet to three hybrid models of SA subjects. The correlation between diseased branch and aerosol deposition was significant in one of the three SA subjects. However, whether skeleton structure contributes to airway abnormality requires further investigation.
Dissertation
Automatic construction and meshing of multiscale image-based human airway models for simulations of aerosol delivery
University of Iowa
Doctor of Philosophy (PhD), University of Iowa
Autumn 2013
DOI: 10.17077/etd.2uawo9mb
Free to read and download, Open Access
Abstract
Details
- Title: Subtitle
- Automatic construction and meshing of multiscale image-based human airway models for simulations of aerosol delivery
- Creators
- Shinjiro Miyawaki - University of Iowa
- Contributors
- Ching-Long Lin (Advisor)Allen Bradley (Committee Member)James Buchholz (Committee Member)Eric Hoffman (Committee Member)Jia Lu (Committee Member)Jacob Odgaard (Committee Member)Merryn Tawhai (Committee Member)
- Resource Type
- Dissertation
- Degree Awarded
- Doctor of Philosophy (PhD), University of Iowa
- Degree in
- Civil and Environmental Engineering
- Date degree season
- Autumn 2013
- Publisher
- University of Iowa
- DOI
- 10.17077/etd.2uawo9mb
- Number of pages
- xv, 144 pages
- Copyright
- Copyright © 2013 Shinjiro Miyawaki
- Comment
This thesis has been optimized for improved web viewing. If you require the original version, contact the University Archives at the University of Iowa: https://www.lib.uiowa.edu/sc/contact/.
- Language
- English
- Description illustrations
- illustrations (some color)
- Description bibliographic
- Includes bibliographical references (pages 135-144).
- Academic Unit
- Civil and Environmental Engineering
- Record Identifier
- 9983777284602771
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