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Proceedings Paper

The relation of airway size to lung function
Author(s): J. Ken Leader; Bin Zheng; Frank C. Sciurba; Carl R. Fuhrman; Jessica M. Bon; Sang C. Park; Jiantao Pu; David Gur
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Paper Abstract

Chronic obstructive pulmonary disease may cause airway remodeling, and small airways are the mostly likely site of associated airway flow obstruction. Detecting and quantifying airways depicted on a typical computed tomography (CT) images is limited by spatial resolution. In this study, we examined the association between lung function and airway size. CT examinations and spirometry measurement of forced expiratory volume in one second as a percent predicted (FEV1%) from 240 subjects were used in this study. Airway sections depicted in axial CT section were automatically detected and quantified. Pearson correlation coefficients (PCC) were computed to compare lung function across three size categories: (1) all detected airways, (2) the smallest 50% of detected airways, and (3) the largest 50% of detected airways using the CORANOVA test. The mean number of all airways detected per subject was 117.4 (± 40.1) with mean size ranging from 20.2 to 50.0 mm2. The correlation between lung function (i.e., FEV1) and airway morphometry associated with airway remodeling and airflow obstruction (i.e., lumen perimeter and wall area as a percent of total airway area) was significantly stronger for smaller compared to larger airways (p < 0.05). The PCCs between FEV1 and all airways, the smallest 50%, and the largest 50% were 0.583, 0.617, 0.523, respectively, for lumen perimeter and -0.560, -0.584, and -0.514, respectively, for wall area percent. In conclusion, analyzing a set of smaller airways compared to larger airways may improve detection of an association between lung function and airway morphology change.

Paper Details

Date Published: 12 March 2008
PDF: 8 pages
Proc. SPIE 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images, 691623 (12 March 2008); doi: 10.1117/12.770886
Show Author Affiliations
J. Ken Leader, Univ. of Pittsburgh (United States)
Bin Zheng, Univ. of Pittsburgh (United States)
Frank C. Sciurba, Univ. of Pittsburgh (United States)
Carl R. Fuhrman, Univ. of Pittsburgh (United States)
Jessica M. Bon, Univ. of Pittsburgh (United States)
Sang C. Park, Univ. of Pittsburgh (United States)
Jiantao Pu, Univ. of Pittsburgh (United States)
David Gur, Univ. of Pittsburgh (United States)

Published in SPIE Proceedings Vol. 6916:
Medical Imaging 2008: Physiology, Function, and Structure from Medical Images
Xiaoping P. Hu; Anne V. Clough, Editor(s)

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