Date of Degree
PhD (Doctor of Philosophy)
Eric A. Hoffman
CT is a powerful method for noninvasive assessment of the lung. Advancements to CT technology have guided the high-resolution structural and functional assessment of lung diseases. This has helped make the transition from characterizing the severity of lung disease to novel phenotyping of disease subtypes. Chronic obstructive pulmonary disease (COPD) is a spectrum of inflammatory lung disease affecting lung parenchyma, airways, and the pulmonary and systemic vasculature. Quantitative CT-based measures have largely focused on quantifying the extent of airway and parenchymal damage with disease. Recently perfusion CT method has been used to assess the pulmonary vascular bed. This technique was used to demonstrate a vascular etiology of smoking-associated centriacinar emphysema (CAE), a subtype of the COPD spectrum. However, technical challenges have limited the transition of this CT method to clinical studies to assess pulmonary vascular physiology. In this thesis, we introduce dual energy CT-perfused blood volume (DECT-PBV) as a novel image-based biomarker to assess peripheral pulmonary vascular dysfunction. Using this technique, we show that smoking-associated pulmonary perfusion heterogeneity, a marker of abnormal blood flow is a reversible process, in the midst of smoking-associated lung inflammation, and not a product of advanced lung disease. We demonstrate, via regional PBV measures and structural measures of the central pulmonary vessels, that the reversibility of pulmonary perfusion heterogeneity is a direct result of increased peripheral (downstream) parenchymal perfusion. We validate our quantitative imaging approach in a unique cohort of early CAE-susceptible smokers using a pharmaceutical intervention to dilate the pulmonary parenchymal vascular bed. The validated DECT approach and our novel DECT imaging findings extend our characterization of the vascular phenotype in inflammatory lung disease and provide a framework for future quantitative imaging studies of the lung to assess early intervention targeted to pulmonary vessels.
CT is a powerful method for noninvasive assessment of the lung. Advancements in the speed and spatial resolution has allowed for detailed assessment of small-scale changes in lung structure and function. This has helped transition CT from a tool purely for structural characterization of the lung in patients with lung disease to phenotyping novel sub populations with early disease based on differences in regional lung function.
In this thesis, we introduce dual energy CT-perfused blood volume (DECT-PBV) as a novel quantitative image-based biomarker to characterize early pulmonary vascular dysfunction in smoking-associated centri-acinar emphysema (CAE), a component of Chronic Obstructive Pulmonary Disease (COPD). We demonstrate that in smokers with early signs of CAE, there is an abnormal distribution of blood flow due to increase constriction of peripheral pulmonary vessels and the response to a conventional drug, used clinically to treat pulmonary hypertension, corrects this abnormal distribution by dilating peripheral vessels. We demonstrate this by measuring changes in central pulmonary arteries and changes in peripheral PBV in CAE-susceptible and non-susceptible smokers using sensitive CT methods.
This data supports the notion that vascular dysfunction in CAE-susceptible smokers is not a result of parenchymal (and peripheral pulmonary vasculature) damage but is rather associated with an early, intrinsically altered vascular response to smoking-associated parenchymal inflammation. DECT-PBV has a potential to differentiate early asymptomatic smokers with emphysema-dominant disease to determine if early intervention with drugs targeted to pulmonary vessels may aid in reversing lung destruction, by restoring blood flow to areas of the lung that are inflamed and poorly perfused, to prevent further lung destruction.
publicabstract, Centriacinar emphysema, Computed Tomography, COPD, Dual Energy, Perfused Blood Volume, Pulmonary vasodilation
Copyright 2016 Krishna S. Iyer