Abstract
Rationale: Interstitial lung abnormalities (ILAs) are visually identified changes on chest computed tomography (CT) scans that may represent early or mild pulmonary fibrosis. Quantitative interstitial abnormalities (QIAs) measure potential parenchymal lung injury on chest CT scans using an automated algorithm. It is not known if combining these visual and quantitative assessments improves prediction of imaging progression. Objectives: To assess the utility of quantitative imaging to predict imaging progression of ILAs and adverse clinical outcomes in a cohort of smokers. Methods: ILA presence, subtypes, and progression, as well as QIAs, were assessed on chest CT scans from participants ∼5 years apart in the COPDGene (Genetic Epidemiology of COPD) study. Multivariable logistic regression assessed associations with ILA progression, and Cox proportional hazards assessed the relationship between ILA progression and mortality. Measurements and Main Results: A total of 4,373 participants had serial CT scans, and 544 (12%) had ILAs on at least one; of those, 391 (72%) had imaging visual progression, and 153 (28%) did not. Specific imaging features were associated progression (e.g., traction bronchiectasis; odds ratio, 3.1; 95% confidence interval [CI], 1.3-7.3; P = 0.003). Among those with ILAs, baseline quantitative measures (QIAs and FVC) were not associated with progression; however, visual imaging progression was associated with increased longitudinal change of QIAs (mean difference, 6.5%; 95% CI, 4.9-8.1%; P < 0.0001). In ILAs, QIA increase was associated with an increased rate of mortality independent of FVC decline (hazard ratio, 1.05; 95% CI, 1.01-1.09; P = 0.009). Conclusions: Baseline quantitative measures (QIAs and FVC) were not associated with visual ILA progression; however, longitudinal change in QIAs was correlated with imaging progression and adverse clinical outcomes.