Trachea Shape Analysis from Inspiration and Expiration Thoracic Computed Tomography Scans

L. Gallardo-Estrella, B. van Ginneken, O.M. Mets, P. Zanen, P.A. de Jong, C.M. Schaefer-Prokop and E.M. van Rikxoort

in: Annual Meeting of the Radiological Society of North America, 2012

Abstract

PURPOSE Changes in trachea shape during breathing may be related to chronic obstructive pulmonary disease (COPD). This study presents a method to automatically measure shape changes of the trachea from paired inspiration and expiration computed tomography (CT) scans and investigates the influence on COPD GOLD stage classification. METHOD AND MATERIALS A database of 184 subjects well distributed over GOLD stages 0 to 4 who received inspiration CT (16x0.75mm, 120-140 kVp, 30-160 mAs), expiration CT (90 kVp, 20 mAs) and pulmonary function testing on the same day was constructed. We developed software to automatically extract the lungs, the trachea and the carina in all scans based on region growing and morphological processing. The shape of the trachea (TS) was encoded in axial sections by the length of eight equiangular rays cast from the center of gravity of the trachea. TS was computed in the inspiration scan in three axial slices 1.5, 2.5, 3.5 cm above the carina, and in corresponding expiration sections obtained using elastic registration based on B-spline deformations and mutual information on the slices from the inspiration scan. The inspiration and expiration features were concatenated and norrmalized by dividing by the length of the longest ray in the inspiration scan. In addition, an emphysema score (ES) was computed as the percentage of lung voxels below -950 HU in inspiration scans. The database was divided into a training set and a test set with equal size and distribution of GOLD stages. A linear discriminant classifier was trained to classify subjects into GOLD stage based on ES, TS or ES+TS. For the last two feature sets, Principal Component Analysis was applied to reduce the number of features. RESULTS The percentages of subjects correctly classified were 35%, 33% and 44% for the feature sets ES, TS and ES+TS. Thus, including tracheal shape features improved performance with 9 percentage points compared to using only an emphysema measure. Using ES+TS the percentage of subjects assigned to either the correct class or a class neighbouring the correct one was 80%. CONCLUSION Tracheal morphology changes can be extracted automatically from CT scans. Combining the proposed trachea shape features with emphysema score, classification into GOLD stages improved substantially. CLINICAL RELEVANCE/APPLICATION Trachea morphology in inspiration and expiration scans can provide useful information for GOLD stage classification of COPD.