Quantitative computed tomography based measures of vascular dysfunction for identifying COPD phenotypes and subphenotypes

Dougherty, Timothy M.

doi:10.17077/etd.q20lc7au

Cited by 2 publications

(2 citation statements)

References 49 publications

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“…The rate of progression of CT-quantifiable lung disease over several months is very minimal, and individuals with COPD are classified as a "rapid progressor" if they have a one-year increase in emphysema index greater than 1%. Therefore, it is not expected that there would be significant differences in the extent of emphysema or air-trapping between the time of the previous lung CT scan and the present study (10). At the time of the present study, quantitative lung imaging software (APOLLO, VIDA Diagnostics) was used to import, segment, and analyze the CT lung images.…”

Section: Subjectsmentioning

confidence: 96%

CT-measured lung air-trapping is associated with higher carotid artery stiffness in individuals with chronic obstructive pulmonary disease

Luehrs

Newell

Comellas

et al. 2018

Journal of Applied Physiology

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Early stages of chronic obstructive pulmonary disease (COPD) are characterized by the loss and narrowing of terminal bronchioles in the lung, resulting in “air-trapping,” often occurring before overt emphysema manifests. Individuals with an airway-predominant phenotype of COPD display extensive lung air-trapping and are at greater cardiovascular disease (CVD) risk than COPD patients with an emphysema-predominant phenotype. We hypothesized that the degree of computed tomography (CT)-quantified lung air-trapping would be associated with greater aortic and carotid artery stiffness and lower endothelial function, known biomarkers of CVD risk. Lung air-trapping was associated with greater aortic stiffness (carotid femoral pulse wave velocity, CFPWV) ( r = 0.60, P = 0.007) and carotid β-stiffness ( r = 0.75, P = 0.0001) among adults with ( n = 10) and without ( n = 9) a clinical diagnosis of COPD and remained significant after adjusting for blood pressure (BP) and smoking history (pack-years) (carotid β-stiffness: r = 0.68, P < 0.01; CFPWV r = 0.53, P = 0.03). The association between lung air-trapping and carotid β-stiffness remained significant after additionally adjusting for age and forced expiratory volume 1(FEV1) ( r = 0.64, P = 0.01). In the COPD group only ( n = 10), lung air-trapping remained associated with carotid β-stiffness ( r = 0.82, P = 0.05) after adjustment for age, pack-years, and FEV1. In contrast, no association was observed between CFPWV and lung air-trapping after adjustment for BP, pack-years, age, and FEV1 ( r = 0.12, P = 0.83). Lung air-trapping was not associated with endothelial function (brachial artery flow-mediated dilation) in the entire cohort ( P = 0.80) or in patients with COPD only ( P = 0.71). These data suggest that carotid artery stiffness may be a mechanism explaining the link between airway-predominant phenotypes of COPD and high CVD risk. NEW & NOTEWORTHY Previous cross-sectional studies have demonstrated greater large elastic artery stiffness and lower endothelium-dependent dilation in chronic obstructive pulmonary disease (COPD) patients compared with controls. Furthermore, COPD patients with emphysema have greater aortic stiffness than non-COPD controls, and the degree of stiffness is associated with emphysema severity. The present study is the first to demonstrate that even before overt emphysema manifests, lung air-trapping is associated with carotid artery stiffness in COPD patients independent of blood pressure, age, or smoking history.

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Section: Subjectsmentioning

confidence: 96%

CT-measured lung air-trapping is associated with higher carotid artery stiffness in individuals with chronic obstructive pulmonary disease

Luehrs

Newell

Comellas

et al. 2018

Journal of Applied Physiology

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“…Cluster 4 had the highest fSAD% and Emph% at baseline with increased fSAD% over one year. we defined the rapid-progressors (RPs) as having a one-year increase greater than 1% and the non-progressors (NPs) as having a one-year change between -0.5% and +0.5% (27). Cluster 2 had the smallest proportion of RPs while cluster 3 was characterized by the largest proportion of RPs (Table 4).…”

Section: Imaging-based Characteristicsmentioning

confidence: 99%

Longitudinal Imaging-Based Clusters in Former Smokers of the COPD Cohort Associate with Clinical Characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)

Zou

Choi

et al. 2020

Preprint

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Background: Quantitative CT (qCT) imaging-based cluster analysis identified clinically meaningful COPD former-smoker subgroups (clusters) based on cross-sectional data. We aimed to identify progression clusters for former smokers using longitudinal data.Patients and Methods: We selected 472 former smokers from SPIROMICS with a baseline visit and a one-year follow-up visit. A total of 150 qCT imaging-based variables, comprising 75 variables at baseline and their corresponding progression rates, were derived from the respective inspiration and expiration scans of the two visits. The COPD progression clusters identified were then associated with subject demography, clinical variables and biomarkers.Results: COPD severities at baseline increased with increasing cluster number. Cluster 1 patients were an obese subgroup with rapid progression of functional small airway disease percentage (fSAD%) and emphysema percentage (Emph%), and preserved FEV1%predicted but impairment of FEV1/FVC ratio over one year. Cluster 2 exhibited a decrease of fSAD% and Emph%, an increase of tissue fraction at total lung capacity, airway narrowing, and a reduced post-bronchodilator FEV1%predicted but preserved FEV1/FVC ratio over one year. Cluster 3 showed rapid expansion of Emph% and an attenuation of fSAD%. Cluster 4 demonstrated severe emphysema and fSAD and significant structural alterations at baseline with rapid progression of fSAD% over one year. Subjects with different progression patterns in the same cross-sectional cluster were identified by longitudinal clustering.Conclusions: qCT imaging-based metrics at two visits for former smokers allow for the derivation of four statistically stable clusters associated with unique progression patterns and clinical characteristics. Use of baseline variables and their progression rates enables identification of longitudinal clusters, resulting in a refinement of cross-sectional clusters.

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Quantitative computed tomography based measures of vascular dysfunction for identifying COPD phenotypes and subphenotypes

Cited by 2 publications

References 49 publications

CT-measured lung air-trapping is associated with higher carotid artery stiffness in individuals with chronic obstructive pulmonary disease

CT-measured lung air-trapping is associated with higher carotid artery stiffness in individuals with chronic obstructive pulmonary disease

Longitudinal Imaging-Based Clusters in Former Smokers of the COPD Cohort Associate with Clinical Characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)

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