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

Esther Pompe*, Craig J. Galban, Brian D. Ross, Leo Koenderman, Nick H. T. ten Hacken, Dirkje S. Postma, Maarten van den Berge, Pim A. de Jong, Jan-Willem J. Lammers, Firdaus A. Mohamed Hoesein

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

59 Citations (Scopus)

Abstract

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-ratio(MLD)). 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-ratio(MLD). 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) (beta = -7.90, p <0.001), alveolar volume (VA) (beta = 7.79, p <0.001), and residual volume (beta = 6.78, p <0.001), whilst PRMEmph was primarily associated with Kco (beta = 8.95, p <0.001), VA (beta = -6.21, p <0.001), and TLC (beta = 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. (C) 2016 Elsevier Ltd. All rights reserved.

Original languageEnglish
Pages (from-to)48-55
Number of pages8
JournalRespiratory Medicine
Volume123
DOIs
Publication statusPublished - Feb-2017

Keywords

  • Computed tomography
  • Parametric response mapping
  • Copd
  • Phenotypes
  • Emphysema
  • Small airway disease
  • EXERCISE CAPACITY
  • FLOW LIMITATION
  • LUNG-FUNCTION
  • COPD
  • EMPHYSEMA
  • PHENOTYPES
  • PROGRESSION
  • STATEMENT
  • SMOKERS
  • FUTURE

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