Artificial Intelligence-based CT Assessment of Bronchiectasis: The COPDGene Study.

Radiology

From the Division of Pulmonary and Critical Care Medicine (A.A.D., W.R.D., A.T., J.L.O., G.R.W.), Department of Radiology (P.N., Rubén San José Estépar, Raúl San José Estépar), Division of Sleep Medicine and Circadian Disorders (W.W.), and Channing Division of Network Medicine (E.K.S.), Brigham and Women's Hospital, Harvard Medical School, 15 Francis St, Boston, MA 02115; Department of Radiology, University of California-San Diego, San Diego, Calif (A.Y., S.K.); Division of Pulmonary Diseases and Critical Care, University of Texas-San Antonio, San Antonio, Tex (D.J.M.); Department of Biomedical Sciences, Humanitas University, Milan, Italy (S.A.); Respiratory Unit, IRCCS Humanitas Research Hospital, Milan, Italy (S.A.); Department of Pulmonary Disease and Critical Care Medicine, Mayo Clinic, Rochester, Minn (T.R.A.); and Department of Epidemiology, Colorado School of Public Health, University of Colorado, Aurora, Colo (K.A.Y., G.L.K.).

Published: April 2023

Background CT is the standard method used to assess bronchiectasis. A higher airway-to-artery diameter ratio (AAR) is typically used to identify enlarged bronchi and bronchiectasis; however, current imaging methods are limited in assessing the extent of this metric in CT scans. Purpose To determine the extent of AARs using an artificial intelligence-based chest CT and assess the association of AARs with exacerbations over time. Materials and Methods In a secondary analysis of ever-smokers from the prospective, observational, multicenter COPDGene study, AARs were quantified using an artificial intelligence tool. The percentage of airways with AAR greater than 1 (a measure of airway dilatation) in each participant on chest CT scans was determined. Pulmonary exacerbations were prospectively determined through biannual follow-up (from July 2009 to September 2021). Multivariable zero-inflated regression models were used to assess the association between the percentage of airways with AAR greater than 1 and the total number of pulmonary exacerbations over follow-up. Covariates included demographics, lung function, and conventional CT parameters. Results Among 4192 participants (median age, 59 years; IQR, 52-67 years; 1878 men [45%]), 1834 had chronic obstructive pulmonary disease (COPD). During a 10-year follow-up and in adjusted models, the percentage of airways with AARs greater than 1 (quartile 4 vs 1) was associated with a higher total number of exacerbations (risk ratio [RR], 1.08; 95% CI: 1.02, 1.15; = .01). In participants meeting clinical and imaging criteria of bronchiectasis (ie, clinical manifestations with ≥3% of AARs >1) versus those who did not, the RR was 1.37 (95% CI: 1.31, 1.43; < .001). Among participants with COPD, the corresponding RRs were 1.10 (95% CI: 1.02, 1.18; = .02) and 1.32 (95% CI: 1.26, 1.39; < .001), respectively. Conclusion In ever-smokers with chronic obstructive pulmonary disease, artificial intelligence-based CT measures of bronchiectasis were associated with more exacerbations over time. Clinical trial registration no. NCT00608764 © RSNA, 2022 See also the editorial by Schiebler and Seo in this issue.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10068886PMC
http://dx.doi.org/10.1148/radiol.221109DOI Listing

Publication Analysis

Top Keywords

artificial intelligence-based
12
percentage airways
12
copdgene study
8
assess association
8
exacerbations time
8
airways aar
8
aar greater
8
pulmonary exacerbations
8
total number
8
chronic obstructive
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!