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Quantitative computed tomography based measures of vascular dysfunction for identifying COPD phenotypes and subphenotypes

Chronic obstructive pulmonary disease (COPD) is a debilitating lung disease almost exclusively related to tobacco smoke. COPD symptoms are typical of numerous other ailments making it difficult to diagnose and track. Technological advancements in CT imaging have allowed clinicians and researchers to expand simple structural information to functional information. These advancements have helped to increase the use of CT imaging in the study of smoking related lung disease.
In this thesis, we investigate observations from a previous study which suggested pulmonary artery constriction in inflamed lung regions promotes emphysema progression in smokers susceptible to emphysema. We use CT data from a 1 year longitudinal study to evaluate the pulmonary artery dimensions in rapid and non-progressing emphysema subjects. We show that the enlargement of arteries predicts emphysema progression and can be used to identify subjects showing signs of rapid emphysema progression.
We attempt to further our ability to use dual energy computed tomography (DECT) for longitudinal and multi-center studies by developing a DECT perfusion blood volume (PBV) imaging protocol with low radiation dose and diluted contrast. We demonstrate that we can reduce radiation dose by up to 34% with the advanced technology of Siemens SOMATOM Force scanner.
Finally, we use DECT PBV imaging to compare perfusion heterogeneity in a multi-center study with both GE and Siemens scanners. We show that perfusion heterogeneity is increased in lung regions showing signs of emphysema, but scanner model/manufacturer appears to be the most important factor as data from the GE scanner had greater noise and thus increased perfusion heterogeneity.

Identiferoai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-6714
Date01 August 2016
CreatorsDougherty, Timothy M.
ContributorsHoffman, Eric A.
PublisherUniversity of Iowa
Source SetsUniversity of Iowa
LanguageEnglish
Detected LanguageEnglish
Typethesis
Formatapplication/pdf
SourceTheses and Dissertations
RightsCopyright 2016 Timothy M. Dougherty

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