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A numerical study of gas transport in human lung models
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Paper Abstract

Stable Xenon (Xe) gas has been used as an imaging agent for decades in its radioactive form, is chemically inert, and has been used as a ventilation tracer in its non radioactive form during computerized tomography (CT) imaging. Magnetic resonance imaging (MRI) using hyperpolarized Helium (He) gas and Xe has also emerged as a powerful tool to study regional lung structure and function. However, the present state of knowledge regarding intra-bronchial Xe and He transport properties is incomplete. As the use of these gases rapidly advances, it has become critically important to understand the nature of their transport properties and to, in the process, better understand the role of gas density in general in determining regional distribution of respiratory gases. In this paper, we applied the custom developed characteristic-Galerkin finite element method, which solves the three-dimensional (3D) incompressible variable-density Navier-Stokes equations, to study the transport of Xe and He in the CT-based human lung geometries, especially emulating the washin and washout processes. The realistic lung geometries are segmented and reconstructed from CT images as part of an effort to build a normative atlas (NIH HL-064368) documenting airway geometry over 4 decades of age in healthy and disease-state adult humans. The simulation results show that the gas transport process depends on the gas density and the body posture. The implications of these results on the difference between washin and washout time constants are discussed.

Paper Details

Date Published: 14 April 2005
PDF: 9 pages
Proc. SPIE 5746, Medical Imaging 2005: Physiology, Function, and Structure from Medical Images, (14 April 2005); doi: 10.1117/12.601169
Show Author Affiliations
Ching-Long Lin, The Univ. of Iowa (United States)
Eric A. Hoffman, The Univ. of Iowa College of Medicine (United States)

Published in SPIE Proceedings Vol. 5746:
Medical Imaging 2005: Physiology, Function, and Structure from Medical Images
Amir A. Amini; Armando Manduca, Editor(s)

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