Computed tomographic abnormalities in COPD

Cigarette smoking remains common around the world and is a well-known cause of chronic obstructive pulmonary disease (COPD). The pathological hallmarks of COPD include tissue destruction, i.e. emphysema, and inflammation of the small and large airways. COPD is diagnosed using lung function tests, but it has been shown that smoking-related changes already exist before lung function declines below a predefined threshold. Also, lung function tests are unable to differentiate between different phenotypes of COPD, which is important information regarding their treatment. Computed tomography (CT) is an imaging technique that can be used as a non-invasive biomarker able to capture multiple characteristics of COPD. A major strength is that it provides high resolution local data both on structure and function. This thesis evaluates which biomarker criteria CT scans of the chest fulfill in assessing smoking-related changes in subjects with both early and more advanced disease and to investigate the role in more personalized assessment and phenotyping. For this purpose, this thesis presented data on several technical aspects of automated CT-analysis for COPD, the clinical validation of CT-measurements, and the importance of recognizing radiological features in terms of respiratory mortality. We found that the application of CT-derived measurements in COPD can be twofold. First, CT-measurements can be used in identifying smoking-related changes at an early stage before lung function decline, which can facilitate early diagnosis and prevention of further lung damage and/or application of treatment. Second, CT-biomarkers can aid in phenotyping COPD, which can improve personalized treatment planning. With this, patients with early disease and with more advanced disease can benefit from the developments in CT-quantification. By using CT, insight will be gained in the development of the disease and will reveal information on subgroups of COPD that can benefit from more specific treatment.