Differentiation of quantitative CT imaging phenotypes in asthma versus COPD

Abstract

IntroductionQuantitative CT (QCT) imaging-based metrics have quantified disease alterations in asthma and chronic obstructive pulmonary disease (COPD), respectively. We seek to characterise the similarity and disparity between these groups using QCT-derived airway and parenchymal metrics.MethodsAsthma and COPD subjects (former-smoker status) were selected with a criterion of post-bronchodilator FEV1 <80%. Healthy non-smokers were included as a control group. Inspiratory and expiratory QCT images of 75 asthmatic, 215 COPD and 94 healthy subjects were evaluated. We compared three segmental variables: airway circularity, normalised wall thickness and normalised hydraulic diameter, indicating heterogeneous airway shape, wall thickening and luminal narrowing, respectively. Using an image registration, we also computed six lobar variables including per cent functional small-airway disease, per cent emphysema, tissue fraction at inspiration, fractional-air-volume change, Jacobian and functional metric characterising anisotropic deformation.ResultsCompared with healthy subjects, both asthma and COPD subjects demonstrated a decreased airway circularity especially in large and upper lobar airways, and a decreased normalised hydraulic diameter in segmental airways. Besides, COPD subjects had more severe emphysema and small-airway disease, as well as smaller regional tissue fraction and lung deformation, compared with asthmatic subjects. The difference of emphysema, small-airway disease and tissue fraction between asthma and COPD was more prominent in upper and middle lobes.ConclusionsPatients with asthma and COPD, with a persistent FEV1 <80%, demonstrated similar alterations in airway geometry compared with controls, but different degrees of alterations in parenchymal regions. Density-based metrics measured at upper and middle lobes were found to be discriminant variables between patients with asthma and COPD.

The lower limit of normal versus a fixed ratio to assess airflow limitation: will the debate ever end?

“…Another potential limitation is the absence of chest computed tomography measurements of the airways and lung parenchyma. These measurements are providing new insights into lung diseases in general and airflow limitation in particular [11].…”

The Link between Asthma and Bronchiectasis: State of the Art

“…In fact, the airways remodeling is commonly observed in asthma, and it is characterized by radiological signs such as thickening of the bronchial wall [81][82][83][84], bronchial dilations [85], mucus plug, and air trapping. Several studies supported by the Severe Asthma Research Program showed that these radiological signs are associated with a more severe disease [81][82][83][86][87][88][89][90][91][92], until to real clinical -radiological clusters [93]. Despite some literature correlating radiological imaging and asthma, at the time being few clinical trials showed a relationship between bronchiectasis and disease severity.…”

Longitudinal Imaging-Based Clusters in Former Smokers of the COPD Cohort Associate with Clinical Characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)

“…Cluster analysis of clinical variables by Burgel et al (10) concluded that COPD patients with similar airflow obstruction may belong to different phenotypes and may differ in symptoms, outcomes, age and comorbidities. Besides clinical variables, qCT imaging-based machine learning of diseased lungs has advanced recently, and multiscale imaging-based cluster analyses have provided clinically meaningful clusters in both asthma and COPD cohorts (11)(12)(13)(14). By considering inter-site and inter-subject variations through normalization schemes (15,16), their approach enabled the analysis of datasets acquired by multiple centers utilizing multiple make and model CT scanners.…”