
Proceedings Paper
Principal component analysis of the CT density histogram to generate parametric response maps of COPDFormat | Member Price | Non-Member Price |
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Paper Abstract
Pulmonary x-ray computed tomography (CT) may be used to characterize emphysema and airways disease in patients with chronic obstructive pulmonary disease (COPD). One analysis approach – parametric response mapping (PMR) utilizes registered inspiratory and expiratory CT image volumes and CT-density-histogram thresholds, but there is no consensus regarding the threshold values used, or their clinical meaning. Principal-component-analysis (PCA) of the CT density histogram can be exploited to quantify emphysema using data-driven CT-density-histogram thresholds. Thus, the objective of this proof-of-concept demonstration was to develop a PRM approach using PCA-derived thresholds in COPD patients and ex-smokers without airflow limitation. Methods: Fifteen COPD ex-smokers and 5 normal ex-smokers were evaluated. Thoracic CT images were also acquired at full inspiration and full expiration and these images were non-rigidly co-registered. PCA was performed for the CT density histograms, from which the components with the highest eigenvalues greater than one were summed. Since the values of the principal component curve correlate directly with the variability in the sample, the maximum and minimum points on the curve were used as threshold values for the PCA-adjusted PRM technique. Results: A significant correlation was determined between conventional and PCA-adjusted PRM with 3He MRI apparent diffusion coefficient (p<0.001), with CT RA950 (p<0.0001), as well as with 3He MRI ventilation defect percent, a measurement of both small airways disease (p=0.049 and p=0.06, respectively) and emphysema (p=0.02). Conclusions: PRM generated using PCA thresholds of the CT density histogram showed significant correlations with CT and 3He MRI measurements of emphysema, but not airways disease.
Paper Details
Date Published: 17 March 2015
PDF: 8 pages
Proc. SPIE 9417, Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging, 941716 (17 March 2015); doi: 10.1117/12.2076396
Published in SPIE Proceedings Vol. 9417:
Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Robert C. Molthen, Editor(s)
PDF: 8 pages
Proc. SPIE 9417, Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging, 941716 (17 March 2015); doi: 10.1117/12.2076396
Show Author Affiliations
Nanxi Zha, Western Univ. (Canada)
Dante P. I. Capaldi, The Univ. of Western Ontario (Canada)
Damien Pike, The Univ. of Western Ontario (Canada)
Dante P. I. Capaldi, The Univ. of Western Ontario (Canada)
Damien Pike, The Univ. of Western Ontario (Canada)
David G. McCormack M.D., The Univ. of Western Ontario (Canada)
Ian A. Cunningham, The Univ. of Western Ontario (Canada)
Grace Parraga, The Univ. of Western Ontario (Canada)
Ian A. Cunningham, The Univ. of Western Ontario (Canada)
Grace Parraga, The Univ. of Western Ontario (Canada)
Published in SPIE Proceedings Vol. 9417:
Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Robert C. Molthen, Editor(s)
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