Introduction
Asthma is a disease with functional airway reversibility through the aid of inhaled corticosteroids and bronchodilator, whereas chronic obstructive pulmonary disease (COPD) is a disease with persistent airflow limitation.1–3 According to recent reports,4 5 around 15%–45% of patients with COPD may have asthma–COPD overlap, so-called ACO. In previous studies,6 7 some asthmatic patients were of neutrophilic dominance with chronic airway functional alteration, while some patients with COPD were of eosinophilic dominance with airway reversibility.8 9 Thus, objective differentiation of the two populations is essential for proper treatments. Meanwhile, two National Institutes of Health (NIH)-supported multicentre studies, SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS)10 and Severe Asthma Research Program (SARP),11 have been established to identify genetic, environmental and clinical phenotypes for COPD and asthma, respectively. SARP excluded patients with a smoking history, while SPIROMICS, except healthy subjects, excluded never-smokers. By the study designs, the recruited subjects are less likely to be ACO. With these populations, we pursue to investigate the imaging-based similarity and disparity between two respiratory diseases.
Quantitative CT (QCT) imaging has successfully identified unique structural and functional phenotypes for asthma and COPD, respectively. For instance, Aysola et al 12 found that asthmatics had an increase of wall area percentage depending on severity, and Busacker et al 13 found an increase of air trapping in severe asthmatics. Using the same imaging datasets from SARP, Choi et al 14 15 demonstrated that existing imaging-based metrics were problematic due to intersubject and intersite variability, resulting in inaccurate estimation. To address these issues, they developed a new air-trapping measure and new normalisation schemes for luminal hydraulic diameter and wall thickness.14 15 These studies demonstrated that on average severe asthmatics were characterised by airway narrowing, wall thickening and air trapping. In addition, with an image registration technique, they demonstrated regional alterations of deformational metrics in severe asthmatics.16 The sensitive imaging-based metrics derived from multiple studies were then integrated to identify clinically meaningful subgroups of asthma.17
In patients with COPD, structural and functional alterations have been assessed by QCT imaging-based variables including luminal diameter,18 wall thickness,19 air trapping (or functional small-airway disease) and emphysema. Existing assessment of air trapping in COPD was also problematic because air trapping at expiration contains some portion of emphysema at inspiration. Therefore, Galban et al 20 employed an image registration technique to dissociate the portion of emphysema from air trapping, allowing for characterisation of three subgroups, that is, emphysema-dominant, functional small-airway disease-dominant and normal groups. In addition to the CT density mapping, image registration provided local deformational metrics including air-volume change, the determinant of Jacobian (Jacobian; a measure of volume change), anisotropic deformation index (ADI; a measure of the magnitude of directional preference in volume change), slab rod index (a measure of the nature of directional preference in volume change) and more.21 Bodduluri et al 22 used the image registration metrics to perform a supervised learning for the purpose of distinguishing patients with COPD from non-COPD subjects. Further, Smith et al 19 compared wall thicknesses of patients with COPD and non-COPD subjects, and found thinner airway walls in patients with COPD than non-COPD subjects when wall thickness is compared at the same location.
QCT imaging-based variables have been employed in a variety of studies to identify local or global alterations in airway dimension and lobar function. Although there are several studies to compare airway structure or lung function between asthma and COPD,23–25 the numbers of subjects under investigation were limited. Therefore, this study aims to investigate the similarity and disparity between large cohorts of asthma and COPD subjects acquired from SARP and SPIROMICS, especially those with overlapping clinical symptoms of chronic functional alterations measured by post-bronchodilator FEV1 <80%. In order to assess structure and function at global and lobar levels, we employed multiscale imaging-based variables,14–17 including local airway structural variables at inspiration scan, and lobar/global functional variables at expiration scan. We further employed image registration metrics including Jacobian, ADI and functional small-airway disease percentage (fSAD%) and emphysematous lung percentage (Emph%).