Assessing pulmonary hypertension in COPD. Is there a role for computed tomography?

Abstract

Pulmonary hypertension (PH) is a common complication of chronic obstructive pulmonary disease (COPD) and is associated with increased morbidity and mortality. Reference standard method to diagnose PH is right heart catheterization. Several non-invasive imaging techniques have been employed in the detection of PH. Among them, computed tomography (CT) is the most commonly used for phenotyping and detecting complications of COPD. Several CT findings have also been described in patients with severe PH. Nevertheless, CT analysis is currently based on visual findings which can lead to reproducibility failure. Therefore, there is a need for quantification in order to assess objective criteria. In this review, progresses in automated analyses of CT parameters and their values in predicting PH and COPD outcomes are presented.

Keywords:

• computed tomography
• pulmonary hypertension
• COPD
• prediction

Acknowledgment

This study has received funding from the Laboratory of Excellence TRAIL, ANR-10-LABX-57.

Abbreviations

AO, aorta; COPD, chronic obstructive pulmonary disease; CMR, cardiac magnetic resonance; CT, computed tomography; FEV₁, forced expiratory volume in 1 second; FVC, forced volume capacity; HU, Hounsfield units; LAA%, low-attenuation area percentage; m, s, dPAP, mean, systolic, diastolic pulmonary arterial pressure; MAP, Main Pulmonary Artery truncus; MRI, magnetic resonance imaging; NA, not attributed; NPV, negative predictive value; PA, pulmonary artery; PaO₂, arterial partial pressure of oxygen (mmHg); PFT: pulmonary Function test; PH, pulmonary hypertension; PPV, positive predictive value; RHC, right heart catheterization; RV, right ventricle; WA, bronchial Wall Area (mm); WT, mean bronchial Wall Thickness (mm); 6MWT, 6 mins walk tests; %CSA_<5, percentage of total cross-sectional area of vessels less than 5 mm² normalized by lung area.

Author contributions

All authors contributed to data analysis, drafting or revising the article, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.

Disclosure

Professor Laurent reports personal fees from Boehringer-Ingelheim, Roche, and Chiesi, outside the submitted work. Professor Pierre-Olivier Girodet reports personal fees, non-financial support from Novartis, personal fees, non-financial support from Chiesi, personal fees, non-financial support from Boehringer-Ingelheim, personal fees, non-financial support from AstraZeneca, personal fees, non-financial support from ALK, outside the submitted work. Professor Patrick Berger reports grants from Novartis, personal fees, non-financial support from AstraZeneca, personal fees, non-financial support from Menarini, personal fees, non-financial support from Circassia, personal fees, non-financial support from Sanofi, personal fees from Teva, outside the submitted work; in addition, Prof Berger has a patent Geometric characterization of airways using MRI. 22605-FR pending. The authors report no other conflicts of interest in this work.