3D Airway Tree Reconstruction in Healthy Subjects and Emphysema

Several algorithms for the segmentation of the 3D human airway tree from computed tomography (CT) images have recently been proposed, but the effects of lung volume and the presence of emphysema on segmentation accuracy has not been investigated. Two different sets of CT images taken on nine healthy subjects and nine patients with severe emphysema (FEV₁ = 19 ± 4.1 SD % pred) were used to reconstruct the trachea-bronchial tree by a region-growing algorithm at two different lung volumes: total lung capacity (TLC) and residual volume (RV). The sixth generation was reached in 67% of the healthy subjects and 22% of the emphysematous patients at TLC. At RV, fifth generation was reached in 33 and 11% of healthy subjects and emphysematous patients. At TLC, 67 ± 2 and 39 ± 2% of airways belonging to the fourth generation were successfully reconstructed, respectively in healthy and emphysematous subjects. At RV, the percentage of successful reconstruction was 33 ± 2 and 16 ± 2%, respectively. Segmentation was significantly influenced by the presence of disease (P < 0.001) and lung volume (P < 0.001) at which the CT scans were acquired. Airway tree reconstruction performed by means of a region-growing algorithm depends on lung volume and presence of emphysema, both of which have significant effect, even at the level of lobar and segmental bronchi.