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Proceedings Paper

Parametric modeling for quantitative analysis of pulmonary structure to function relationships
Author(s): Clifton R. Haider; Brian J. Bartholmai; David R. Holmes; Jon J. Camp; Richard A. Robb
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Paper Abstract

While lung anatomy is well understood, pulmonary structure-to-function relationships such as the complex elastic deformation of the lung during respiration are less well documented. Current methods for studying lung anatomy include conventional chest radiography, high-resolution computed tomography (CT scan) and magnetic resonance imaging with polarized gases (MRI scan). Pulmonary physiology can be studied using spirometry or V/Q nuclear medicine tests (V/Q scan). V/Q scanning and MRI scans may demonstrate global and regional function. However, each of these individual imaging methods lacks the ability to provide high-resolution anatomic detail, associated pulmonary mechanics and functional variability of the entire respiratory cycle. Specifically, spirometry provides only a one-dimensional gross estimate of pulmonary function, and V/Q scans have poor spatial resolution, reducing its potential for regional assessment of structure-to-function relationships. We have developed a method which utilizes standard clinical CT scanning to provide data for computation of dynamic anatomic parametric models of the lung during respiration which correlates high-resolution anatomy to underlying physiology. The lungs are segmented from both inspiration and expiration three-dimensional (3D) data sets and transformed into a geometric description of the surface of the lung. Parametric mapping of lung surface deformation then provides a visual and quantitative description of the mechanical properties of the lung. Any alteration in lung mechanics is manifest by alterations in normal deformation of the lung wall. The method produces a high-resolution anatomic and functional composite picture from sparse temporal-spatial methods which quantitatively illustrates detailed anatomic structure to pulmonary function relationships impossible for translational methods to provide.

Paper Details

Date Published: 12 April 2005
PDF: 7 pages
Proc. SPIE 5744, Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display, (12 April 2005); doi: 10.1117/12.595244
Show Author Affiliations
Clifton R. Haider, Mayo Clinic College of Medicine (United States)
Brian J. Bartholmai, Mayo Clinic College of Medicine (United States)
David R. Holmes, Mayo Clinic College of Medicine (United States)
Jon J. Camp, Mayo Clinic College of Medicine (United States)
Richard A. Robb, Mayo Clinic College of Medicine (United States)


Published in SPIE Proceedings Vol. 5744:
Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display
Robert L. Galloway; Kevin R. Cleary, Editor(s)

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