Automated CT-based measurements of radial and longitudinal expansion of airways due to breathing-related lung volume change

Background

Respiratory function is impaired in chronic obstructive pulmonary disease (COPD). Automation of multi-volume CT-based measurements of different components of breathing-related airway deformations will help understand multi-pathway impairments in respiratory mechanics in COPD.

Purpose

To develop and evaluate multi-volume chest CT-based automated measurements of breathing-related radial and longitudinal expansion of individual airways between inspiratory and expiratory lung volumes.

Methods

We developed a method to compute breathing-related airway deformation metrics and applied it to total lung capacity (TLC) and functional residual capacity (FRC) chest CT scans. The computational pipeline involves: (1) segmentation of airways; (2) skeletonization of airways; (3) labeling of anatomical airway segments at TLC and FRC; and (4) computation of radial and longitudinal expansion metrics of individual airways across lung volumes. Radial expansion (∆CSA) of an airway is computed as the percent change of its cross-sectional area (CSA) between two lung volumes. Longitudinal expansion (∆L) of an airway is computed as the percent change in its airway path-length from the carina between lung volumes. These measures are summarized at different airway anatomic generations. Agreement of automated measures with their manually derived values was examined in terms of concordance correlation coefficient (CCC) of automated measures with those derived using manual outlining. Intra-class correlation coefficient (ICC) of automated measures from repeat CT scans (n = 37) was computed to assess repeatability. The method was also applied to a set of participants from the Genetic Epidemiology of COPD (COPDGene) Iowa cohort, distributed across COPD severity groups (n = 4 × 60).

Results

The CCC values for the automated ∆CSA measure with manually derived values were 0.930 at the trachea, 0.898 at primary bronchi, and greater than 0.95 at pre-segmental and segmental airways; these CCC values were consistently greater than 0.95 for ∆L at all airway generations. ICC values for repeatability of ∆CSA were 0.974, 0.950, 0.943, and 0.901 at trachea, primary bronchi, pre-segmental, and segmental airways, respectively; these ICC values for ∆L were 0.973, 0.954, and 0.952 at primary bronchi, pre-segmental, and segmental airways, respectively. ∆CSA values were significantly reduced (p < 0.001) with increasing COPD severity at each of primary bronchi, pre-segmental, and segmental airways. Significantly lower ∆L values were observed for moderate (p = 0.042 at pre-segmental and p = 0.037 at segmental) and severe (p = 0.019 at pre-segmental and p < 0.001 at segmental) COPD groups as compared to the preserved lung function group. Body mass index (BMI) and smoking status were found to significantly associate with ∆CSA at segmental airways (r = 0.17 and −0.19, respectively; significance threshold = 0.13), while age and sex were significantly associated with ∆L (r = −0.21 and −0.17, respectively); COPD severity was significantly associated with both ∆CSA and ∆L (r = −0.35 and −0.22, respectively).

Conclusion

Our CT-based automated measures of breathing-related radial and longitudinal expansion of airways are repeatable and in agreement with manually derived values. Automation of different airway mechanical biomarkers and their observed significant associations with age, sex, BMI, smoking, and COPD severity establish an effective tool to investigate multi-pathway impairments of respiratory mechanics in COPD and other lung diseases.