Automatic classification of pulmonary function in COPD patients using trachea analysis in chest CT scans

OBJECTIVES:Tracheal morphologic change during breathing may be related to COPD severity. We investigated if automatic shape analysis of the trachea from inspiration and expiration computed tomography (CT) scans can improve CT-based classification of COPD patients into GOLD stages. MATERIALS AND METHODS: A database of 187 subjects of GOLD stages 0 through 4 was constructed. The trachea was automatically segmented on an automatically determined axial section 1 cm above the carina from both the inspiration and expiration scans. The tracheal shape (TS), encoded by the length of rays cast from the center of the trachea, and emphysema score (ES) at -950 HU on the inspiration scan, were used as features for classification. A nearest mean statistical classifier was trained to assign subjects to GOLD stage based on three sets of features: ES, TS, and ES+TS. RESULTS: Accuracy of GOLD stage classification was 42%, 41%, and 51% for ES, TS, and ES+TS, respectively. For distinguishing non-COPD subjects (GOLD 0) versus COPD patients (GOLD 1-4), accuracies were 67%, 72% and 80%. CONCLUSIONS: Tracheal shape can be extracted automatically from CT scans and is related to pulmonary function. Including tracheal shape features together with density mask scores improves CT-based detection and quantification of COPD.