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Proceedings Paper

Three-dimensional segmentation of pulmonary artery volume from thoracic computed tomography imaging
Author(s): Tamas J. Lindenmaier; Khadija Sheikh; Emma Bluemke; Igor Gyacskov; Marco Mura; Christopher Licskai; Lisa Mielniczuk; Aaron Fenster; Ian A. Cunningham; Grace Parraga
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Paper Abstract

Chronic obstructive pulmonary disease (COPD), is a major contributor to hospitalization and healthcare costs in North America. While the hallmark of COPD is airflow limitation, it is also associated with abnormalities of the cardiovascular system. Enlargement of the pulmonary artery (PA) is a morphological marker of pulmonary hypertension, and was previously shown to predict acute exacerbations using a one-dimensional diameter measurement of the main PA. We hypothesized that a three-dimensional (3D) quantification of PA size would be more sensitive than 1D methods and encompass morphological changes along the entire central pulmonary artery. Hence, we developed a 3D measurement of the main (MPA), left (LPA) and right (RPA) pulmonary arteries as well as total PA volume (TPAV) from thoracic CT images. This approach incorporates segmentation of pulmonary vessels in cross-section for the MPA, LPA and RPA to provide an estimate of their volumes. Three observers performed five repeated measurements for 15 ex-smokers with ≥10 pack-years, and randomly identified from a larger dataset of 199 patients. There was a strong agreement (r2=0.76) for PA volume and PA diameter measurements, which was used as a gold standard. Observer measurements were strongly correlated and coefficients of variation for observer 1 (MPA:2%, LPA:3%, RPA:2%, TPA:2%) were not significantly different from observer 2 and 3 results. In conclusion, we generated manual 3D pulmonary artery volume measurements from thoracic CT images that can be performed with high reproducibility. Future work will involve automation for implementation in clinical workflows.

Paper Details

Date Published: 17 March 2015
PDF: 8 pages
Proc. SPIE 9417, Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging, 94172O (17 March 2015); doi: 10.1117/12.2076639
Show Author Affiliations
Tamas J. Lindenmaier, Robarts Research Institute (Canada)
The Univ. of Western Ontario (Canada)
Khadija Sheikh, Robarts Research Institute (Canada)
The Univ. of Western Ontario (Canada)
Emma Bluemke, Robarts Research Institute (Canada)
Igor Gyacskov, Robarts Research Institute (Canada)
Marco Mura, The Univ. of Western Ontario (Canada)
Christopher Licskai, The Univ. of Western Ontario (Canada)
Lisa Mielniczuk, Univ. of Ottawa (Canada)
Aaron Fenster, Robarts Research Institute (Canada)
The Univ. of Western Ontario (Canada)
Ian A. Cunningham, Robarts Research Institute (Canada)
The Univ. of Western Ontario (Canada)
Grace Parraga, Robarts Research Institute (Canada)
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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