Principal Component Analysis of Quantitative Computed Tomography Features and Visual Emphysema Scores: Association With Lung Function Decline

<p>Emphysema is characterized by the damage of the alveoli (air sacs) in the lungs and occurs in patients with Chronic Obstructive Pulmonary Disease (COPD). It is clinically evaluated visually by a radiologist who subjectively scores the severity of the disease on computed tomography (CT) images. However, there are limitations to this method, including inherent inter- and intra-observer variability. A solution to overcome these limitations is the use of fully automated and objective quantitative CT (QCT) measurements. However, it has been shown in literature that visual score outperforms single QCT measurements when predicting mortality, despite its subjectivity. In this thesis, we explore the use of multiple QCTs in combination by principal component analysis (PCA), and its ability to predict COPD disease progression (lung function decline), independent of visual scoring.</p>