Imaging-derived biomarkers in Asthma: Current status and future perspectives.

Asthma is a common disorder affecting around 315 million individuals worldwide. The heterogeneity of asthma is becoming increasingly important in the era of personalized treatment and response assessment. Several radiological imaging modalities are available in asthma including chest x-ray, computed tomography (CT) and magnetic resonance imaging (MRI) scanning. In addition to qualitative imaging, quantitative imaging could play an important role in asthma imaging to identify phenotypes with distinct disease course and response to therapy, including biologics. MRI in asthma is mainly performed in research settings given cost, technical challenges, and there is a need for standardization. Imaging analysis applications of artificial intelligence (AI) to subclassify asthma using image analysis have demonstrated initial feasibility, though additional work is necessary to inform the role of AI in clinical practice.

Parametric response mapping on chest computed tomography associates with clinical and functional parameters in chronic obstructive pulmonary disease.

BACKGROUND: In the search for specific phenotypes of chronic obstructive pulmonary disease (COPD) computed tomography (CT) derived Parametric Response Mapping (PRM) has been introduced. This study evaluates the association between PRM and currently available biomarkers of disease severity in COPD. METHODS: Smokers with and without COPD were characterized based on questionnaires, pulmonary function tests, body plethysmography, and low-dose chest CT scanning. PRM was used to calculate the amount of emphysema (PRMEmph) and non-emphysematous air trapping (i.e. functional small airway disease, PRMfSAD). PRM was first compared with other biomarkers for emphysema (Perc15) and air trapping (E/I-ratioMLD). Consequently, linear regression models were utilized to study associations of PRM measurements with clinical parameters. RESULTS: 166 participants were included with a mean ± SD age of 50.5 ± 17.7 years. Both PRMEmph and PRMfSAD were more strongly correlated with lung function parameters as compared to Perc15 and E/I-ratioMLD. PRMEmph and PRMfSAD were higher in COPD participants than non-COPD participants (14.0% vs. 1.1%, and 31.6% vs. 8.2%, respectively, both p < 0.001) and increased with increasing GOLD stage (all p < 0.001). Multivariate analysis showed that PRMfSAD was mainly associated with total lung capacity (TLC) (ß = -7.90, p < 0.001), alveolar volume (VA) (ß = 7.79, p < 0.001), and residual volume (ß = 6.78, p < 0.001), whilst PRMEmph was primarily associated with Kco (ß = 8.95, p < 0.001), VA (ß = -6.21, p < 0.001), and TLC (ß = 6.20, p < 0.001). CONCLUSIONS: PRM strongly associates with the presence and severity of COPD. PRM therefore appears to be a valuable tool in differentiating COPD phenotypes.

Smokers with emphysema and small airway disease on computed tomography have lower bone density.

Osteoporosis is more common in patients with COPD and in smokers. The aim of this study was to assess whether measures of emphysema and airway disease on computed tomography (CT) were associated with lower bone density or vertebral fractures in smokers with and without COPD. For this purpose, we included participants from the NELSON lung cancer screening trial. Bone density was measured as Hounsfield Units in the first lumbar vertebra, and vertebral fractures were assessed semiquantitatively. The 15th percentile method (Perc15) was used to assess emphysema, and the airway lumen perimeter (Pi10) was used for airway wall thickness. Expiratory/inspiratory-ratiomean lung density (E/I-ratioMLD) was used as a measure for air trapping and tracheal index to assess tracheal deformity. Linear regression models and logistic regression models were used to assess associations between CT biomarkers, bone density, and presence of fractures. Exactly 1,093 male participants were eligible for analysis. Lower Perc15 and higher E/I-ratioMLD were significantly associated with lower bone density (b=-1.27, P=0.02 and b=-0.37, P=0.02, respectively). Pi10 and tracheal index were not associated with bone density changes. CT-derived biomarkers were not associated with fracture prevalence. Bone density is lower with increasing extent of emphysema and small airway disease but is not associated with large airway disease and tracheal deformity. This may indicate the necessity to measure bone density early in smokers with emphysema and air trapping to prevent vertebral fractures.