Automated Computed Tomography Lung Densitometry in Bronchiectasis Patients

Rationale: Bronchiectasis is a complex and heterogeneous disease. Visual computed tomography (CT) scoring systems are used to assess disease severity, disease progression and predict outcomes in bronchiectasis although they have some limitations such as subjectivity, requirement of previous training and are time-consuming. Objective: To correlate quantitative CT lung densitometry measurements with pulmonary function test (PFT) and multidimensional prognostic scores in patients with bronchiectasis. Materials: and methods: From 2014 to 2017, 100 consecutive adult patients with non-cystic fibrosis bronchiectasis underwent inspiratory and expiratory volumetric chest CT and PFT (spirometry, plethysmograph, diffusing capacity of carbon monoxide measurement [DLCO]). Visual CT score (CF-CT score), CT lung densitometry parameters (kurtosis, skewness and expiratory/inspiratory mean lung density [E/I MLD]) and multidimensional prognostic scores (BSI and FACED) were calculated in all patients and correlated to PFT. Results: : CT lung densitometry parameters (kurtosis and skewness), correlated with forced expiratory volume in 1 second (FEV1) (R=0.32; p=0.001 and R=0.34; p<0.001) and DLCO (R=0.41 and R=0.43; p<0.001). Automated CT air trapping quantification (E/I MLD) showed correlation with residual volume (RV), multidimensional score FACED (R=0.63 and R=0.53; p<0.001) and performed better than the CF-CT score in the diagnosis of high-risk patients and severe air trapping. Conclusion: CT lung densitometry parameters showed correlations with PFT in non-cystic fibrosis bronchiectasis patients. Automated CT air trapping quantification performed better than visual CT score in the identification of high-risk patients and severe air trapping, suggesting it could be a useful tool in the evaluation of these patients, although further studies are needed to confirm these findings.