Unsupervised extraction and quantification of the bronchial tree on ultra-low-dose vs. standard-dose CT

Automatic extraction of the tracheobronchial tree from high resolution CT data serves visual inspection by virtual endoscopy as well as computer aided measurement of clinical parameters along the airways. The purpose of this study is to show the feasibility of automatic extraction (segmentation) of the airway tree even in ultra-low-dose CT data (5-10 mAs), and to compare the performance of the airway extraction between ultra-low-dose and standard-dose (70-100 mAs) CT data. A direct performance comparison (instead of a mere simulation) was possible since for each patient both an ultra-low-dose and a standard-dose CT scan were acquired within the same examination session. The data sets were recorded with a multi-slice CT scanner at the Charite university hospital Berlin with 1 mm slice thickness. An automated tree extraction algorithm was applied to both the ultra-low-dose and the standard-dose CT data. No dose-specific parameter-tuning or image pre-processing was used. For performance comparison, the total length of all visually verified centerlines of each tree was accumulated for all airways beyond the tracheal carina. Correlation of the extracted total airway length for ultra-low-dose versus standard-dose for each patient showed that on average in the ultra-low-dose images 84% of the length of the standard-dose images was retrieved.