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Proceedings Paper

Quantitative computed tomography of lung parenchyma in patients with emphysema: analysis of higher-density lung regions
Author(s): Dror Lederman; Joseph K. Leader; Bin Zheng; Frank C. Sciurba; Jun Tan; David Gur
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Paper Abstract

Quantitative computed tomography (CT) has been widely used to detect and evaluate the presence (or absence) of emphysema applying the density masks at specific thresholds, e.g., -910 or -950 Hounsfield Unit (HU). However, it has also been observed that subjects with similar density-mask based emphysema scores could have varying lung function, possibly indicating differences of disease severity. To assess this possible discrepancy, we investigated whether density distribution of "viable" lung parenchyma regions with pixel values > -910 HU correlates with lung function. A dataset of 38 subjects, who underwent both pulmonary function testing and CT examinations in a COPD SCCOR study, was assembled. After the lung regions depicted on CT images were automatically segmented by a computerized scheme, we systematically divided the lung parenchyma into different density groups (bins) and computed a number of statistical features (i.e., mean, standard deviation (STD), skewness of the pixel value distributions) in these density bins. We then analyzed the correlations between each feature and lung function. The correlation between diffusion lung capacity (DLCO) and STD of pixel values in the bin of -910HU ≤ PV < -750HU was -0.43, as compared with a correlation of -0.49 obtained between the post-bronchodilator ratio (FEV1/FVC) measured by the forced expiratory volume in 1 second (FEV1) dividing the forced vital capacity (FVC) and the STD of pixel values in the bin of -1024HU ≤ PV < -910HU. The results showed an association between the distribution of pixel values in "viable" lung parenchyma and lung function, which indicates that similar to the conventional density mask method, the pixel value distribution features in "viable" lung parenchyma areas may also provide clinically useful information to improve assessments of lung disease severity as measured by lung functional tests.

Paper Details

Date Published: 16 March 2011
PDF: 6 pages
Proc. SPIE 7965, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging, 79651X (16 March 2011); doi: 10.1117/12.877542
Show Author Affiliations
Dror Lederman, Univ. of Pittsburgh (United States)
Joseph K. Leader, Univ. of Pittsburgh (United States)
Bin Zheng, Univ. of Pittsburgh (United States)
Frank C. Sciurba, Univ. of Pittsburgh (United States)
Jun Tan, Univ. of Pittsburgh (United States)
David Gur, Univ. of Pittsburgh (United States)


Published in SPIE Proceedings Vol. 7965:
Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging
John B. Weaver; Robert C. Molthen, Editor(s)

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