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.

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 (PRM^Emph) and non-emphysematous air trapping (i.e. functional small airway disease, PRM^fSAD). PRM was first compared with other biomarkers for emphysema (Perc15) and air trapping (E/I-ratio_MLD). Consequently, linear regression models were utilized to study associations of PRM measurements with clinical parameters.

166 participants were included with a mean ± SD age of 50.5 ± 17.7 years. Both PRM^Emph and PRM^fSAD were more strongly correlated with lung function parameters as compared to Perc15 and E/I-ratio_MLD. PRM^Emph and PRM^fSAD 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 PRM^fSAD was mainly associated with total lung capacity (TLC) (β = −7.90, p < 0.001), alveolar volume (VA) (β = 7.79, p < 0.001), and residual volume (β = 6.78, p < 0.001), whilst PRM^Emph was primarily associated with Kco (β = 8.95, p < 0.001), VA (β = −6.21, p < 0.001), and TLC (β = 6.20, p < 0.001).

PRM strongly associates with the presence and severity of COPD. PRM therefore appears to be a valuable tool in differentiating COPD phenotypes.