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Thesis Format

Integrated Article

Degree

Master of Science

Program

Medical Biophysics

Supervisor

Parraga, Grace

Abstract

Chronic obstructive pulmonary disease (COPD) is a progressive and debilitating disease resulting in chronic cough, shortness of breath, activity limitation and decreased pulmonary function. Developments in imaging technology have provided sensitive and reliable modalities for evaluating regional lung function and disease progression, and there is a growing interest in the role of imaging the vasculature in COPD. The ability to predict whether a patient is at risk of accelerated decline is important to disease management strategies. We hypothesize that CT blood vessel volume measurements are significantly different in ex-smokers without COPD than in those with this disease and will be related to disease severity. 90 participants completed both baseline and follow-up visits: 41 ex-smokers without COPD (71±10yrs) and 49 participants with COPD (71±8yrs). From baseline to follow-up, RA950 increased significantly for ex-smokers and GOLD II participants, while PV1 decreased significantly for GOLD I. There were no differences in VDP when grouped according to change in FEV1. Participants whose FEV1 increased by more than 20mL/year experienced a significantly smaller change in RA950 compared to those whose FEV1 decreased by more than 40mL. Independent samples t-tests indicate a significant difference in the rate of PV1 progression between COPD groups with and without emphysema, but not VDP or RA950. Emphysema, or COPD phenotype, is related to vascular structure within the lung and the progression of vascular remodelling. Future work should include investigations of sex-differences in airways disease, and the use of machine learning to predict disease progression with optimized CT imaging parameters.

Summary for Lay Audience

Chronic obstructive pulmonary disease (COPD) is a progressive and debilitating disease resulting in chronic cough, breathlessness, activity limitation and reduced lung function. Developments in imaging technology have permitted the evaluation and visualization of the complex effects of COPD within the lung. The ability to predict how a patient’s disease will progress is important to managing it. Further, we do not fully understand how the disease develops, progresses, and how to predict who will get worse quickly. We can use MRI ventilation to image the lungs and see where air can or cannot go, which has allowed us to better understand their function. Similarly, measurements of small vessels that may be associated with inflammation, destruction, and disappear with damage, may help us better understand the disease process. We hypothesize that measurements of small blood vessel volume are significantly different in participants without COPD than in those with this disease and related to disease severity. We evaluated 90 participants: 41 ex-smokers without COPD and 49 participants with COPD at baseline and 2.5 years later. Ex-smokers and moderate COPD participants had more emphysema at follow-up, while participants with mild COPD had decreased small vessel volume and no change in emphysema. Both ex-smokers and participants with COPD had less ventilated lung at follow-up. Participants whose clinical measurements of lung function increased from baseline to follow-up experienced an increase in emphysema but significantly less change in small blood vessel volume compared to those whose lung function decreased the most in our sample. Participants with COPD who did not have emphysema experienced a decrease in small vessel volume. Vascular structure within the lung and how it changes with disease appears to be related to emphysema and disease severity. Measuring small vessel volume was more sensitive to changes in clinical lung function than lung ventilation. This research demonstrates that using multiple modalities to evaluate lung disease over time can help researchers and clinicians to better predict a patient’s outcome and provide more specific and timely treatment.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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