Electronic Thesis and Dissertation Repository

Degree

Doctor of Philosophy

Program

Medical Biophysics

Supervisor

Dr. Grace Parraga

Abstract

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death in the world. Identifying clinically relevant COPD phenotypes has the potential to reduce the global burden of COPD by helping to alleviate symptoms, slow disease progression and prevent exacerbation by stratifying patient cohorts and forming targeted treatment plans. In this regard, quantitative pulmonary imaging with hyperpolarized 3He magnetic resonance imaging (MRI) and thoracic computed tomography (CT) have emerged as ways to identify and measure biomarkers of lung structure and function. 3He MRI may be used as a tool to probe both functional and structural properties of the lung whereby static-ventilation maps allow the direct visualization of ventilated lung regions and 3He apparent diffusion coefficient maps show the lung microstructure at alveolar scales. At the same time, thoracic CT provides quantitative measurements of lung density and airway wall and lumen dimensions. Together, MRI and CT may be used to characterize the relative contributions of airways disease and emphysema on overall lung function, providing a way to phenotype underlying disease processes in a way that conventional measurements of airflow, taken at the mouth, cannot. Importantly, structure-function measurements obtained from 3He MRI and CT can be extracted from the whole-lung or from individual lung lobes, providing direct information on specific lung regions. In this thesis, my goal was to identify pulmonary imaging phenotypes to provide a better understanding of COPD pathophysiology in ex-smokers with and without airflow limitation. This thesis showed: 1) ex-smokers without airflow limitation had imaging evidence of subclinical lung and vascular disease, 2) pulmonary abnormalities in ex- smokers without airflow limitation were spatially related to airways disease and very mild emphysema, and, 3) in ex-smokers with COPD, there were distinct apical-basal lung phenotypes associated with disease severity. Collectively, these findings provide strong evidence that quantitative pulmonary imaging phenotypes may be used to characterize the underlying pathophysiology of very mild or early COPD and in patients with severe disease.

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