Abstract
Lung parenchyma destruction (emphysema) is a major factor in the description of Chronic Obstructive Pulmonary Disease (COPD) and its prognosis. It is defined as an abnormal enlargement of air spaces distal to the terminal bronchioles and the destruction of alveolar walls. In CT imaging, the presence of emphysema is observed by a local decrease of the lung density and the diagnose is usually set as more than 5% of the lung below -950 HU, the so-called emphysema density mask. There is still debate, however, about the definition of this percentage and many researchers set it depending on the population under study. Additionally, the -950 HU threshold may vary depending on factors as the slice thickness or the respiratory phase of the acquisition. In this paper we propose (1) a statistical framework that provides an automatic definition of the density threshold based on the statistical characterization of air and lung parenchyma; (2) the definition of a statistical test for emphysema detection that accounts for the CT noise characteristics. Results show that this novel statistical framework improves the quantification of emphysema against a visual reference and improves the association of emphysema with the pulmonary function tests.