Annals of Biomedical Engineering

, Volume 39, Issue 6, pp 1805-1814

Open Access This content is freely available online to anyone, anywhere at any time.

Detecting Alterations in Pulmonary Airway Development with Airway-by-Airway Comparison

  • DongYoub LeeAffiliated withDepartment of Mechanical and Aerospace Engineering, University of California Email author 
  • , Neil WillitsAffiliated withDepartment of Statistics, University of California
  • , Anthony S. WexlerAffiliated withDepartment of Mechanical and Aerospace Engineering, University of CaliforniaAir Quality Research Center, University of CaliforniaDepartment of Civil and Environmental Engineering, University of CaliforniaDepartment of Land, Air and Water Resources, University of California


Neonatal and postnatal exposures to air pollutants have adverse effects on lung development resulting in airway structure changes. Usually, generation-averaged analysis of airway geometric parameters is employed to differentiate between pulmonary airway trees. However, this method is limited, especially for monopodial branching trees such as in rat airways, because both quite proximal and less proximal airways that have very different structure and function may be in the same generation. To avoid limitations inherent in generation averaging, we developed a method that compares two trees airway-by-airway using micro CT image data from rat lungs. This computerized technique (1) identifies the geometry and architecture of the conducting airways from CT images, (2) extracts the main tree, (3) associates paired airways from the two different trees, and (4) develops summary statistics on the degree of similarity between populations of animals. By comparing the trees airway-by-airway, we found that the variance in airway length of the group exposed to diffusion flame particles (DFP) is significantly larger than the group raised in filtered air (FA). This method also found that rotation angle of the DFP group is significantly larger than FA, which is not as certain in the generation-based analysis. We suggest that airway-by-airway analysis complements generation-based averaging for detecting airway alterations.


Development disruption Pulmonary airways CT image Rat lungs Airway-by-airway comparison Diffusion flame particles