Association of musculoskeletal involvement with lung function and mortality in patients with idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive disease associated with high mortality. Low muscle mass, frailty and sarcopenia lead to functional impairment that negatively impact quality of life and survival but are not used in clinical practice. We aimed to determine the association of Fat-free mass index (FFMI) and frailty with lung function, exercise tolerance and survival in patients with IPF. In this study, 70 patients with IPF underwent assessment of body composition, lung function, 6-min walk distance (6MWD) testing, hand grip strength, quality of life (QoL) assessment by St. George's Respiratory questionnaire (SGRQ) and frailty assessment using the SHARE-FI tool. FFMI was calculated using pectoralis muscle cross-sectional area (PM-CSA) on CT chest images and the lowest quartile defined reduced muscle mass. Sarcopenia was defined as low FFMI and handgrip strength. Regression analyses were conducted to determine predictive value of frailty, low FFMI and sarcopenia on clinical outcomes. The Cox proportional hazards model was used to analyze the impact of FFMI and frailty score on survival. The mean age was 70 years with moderate impairment in lung function (mean ppFVC 68.5%, ppDLCO 45.6%). Baseline forced vital capacity (p < 0.001), diffusion capacity of lung for carbon monoxide (p =  < 0.01), 6WMD (p < 0.05) were significantly lower in frail patients compared to non-frail patients. BMI was found to closely correlate with FFMI (r = 0.79, p < 0.001), but not with frailty score (r = - 0.2, p = 0.07). Frailty was a significant predictor of FVC, DLCO, 6MWD, SGRQ scores when adjusted for age and gender. Muscle mass and sarcopenia were significant predictors of FVC, DLCO, but not 6MWD or QoL scores. Multivariate cox-proportional hazards ratio model adjusting for age and gender showed that frailty was significantly associated with increased mortality (HR = 2.6, 95% CI 1.1-6.1). Low FFMI (HR = 1.3, 95% CI 0.6-2.8), and sarcopenia (HR = 2.1, 95% CI 0.8-5.3), though associated with a trend to increased mortality, were not statistically significant. Frailty is associated with lower lung function and higher mortality in patients with IPF. Longitudinal evaluations are necessary to further determine the associations between low FFMI, sarcopenia and frailty with outcomes in IPF.

Dysanapsis is differentially related to lung function trajectories with distinct structural and functional patterns in COPD and variable risk for adverse outcomes

Background

Abnormal lung function trajectories are associated with increased risk of chronic obstructive pulmonary disease (COPD) and premature mortality; several risk factors for following these trajectories have been identified. Airway under-sizing dysanapsis (small airway lumens relative to lung size), is associated with an increased risk for COPD. The relationship between dysanapsis and lung function trajectories at risk for adverse outcomes of COPD is largely unexplored. We test the hypothesis that dysanapsis differentially affects distinct lung function trajectories associated with adverse outcomes of COPD.

Methods

To identify lung function trajectories, we applied Bayesian trajectory analysis to longitudinal FEV1 and FVC Z-scores in the COPDGene Study, an ongoing longitudinal study that collected baseline data from 2007 to 2012. To ensure clinical relevance, we selected trajectories based on risk stratification for all-cause mortality and prospective exacerbations of COPD (ECOPD). Dysanapsis was measured in baseline COPDGene CT scans as the airway lumen-to-lung volume (a/l) ratio. We compared a/l ratios between trajectories and evaluated their association with trajectory assignment, controlling for previously identified risk factors. We also assigned COPDGene participants for whom only baseline data is available to their most likely trajectory and repeated our analysis to further evaluate the relationship between trajectory assignment and a/l ratio measures.

Findings

We identified seven trajectories: supranormal, reference, and five trajectories at increased risk for mortality and exacerbations. Three at-risk trajectories are characterized by varying degrees of concomitant FEV1 and FVC impairments and exhibit airway predominant COPD patterns as assessed by quantitative CT imaging. These trajectories have lower a/l ratio values and increased risk for mortality and ECOPD compared to the reference trajectory. Two at-risk trajectories are characterized by disparate levels of FEV1 and FVC impairment and exhibit mixed airway and emphysema COPD patterns on quantitative CT imaging. These trajectories have markedly lower a/l ratio values compared to both the reference trajectory and airway-predominant trajectories and are at greater risk for mortality and ECOPD compared to the airway-predominant trajectories. These findings were observed among the participants with baseline-only data as well.

Interpretation

The degree of dysanapsis appears to portend patterns of progression leading to COPD. Assignment of individuals-including those without spirometric obstruction-to distinct trajectories is possible in a clinical setting and may influence management strategies. Strategies that combine CT-assessed dysanapsis together with spirometric measures of lung function and smoke exposure assessment are likely to further improve trajectory assignment accuracy, thereby improving early detection of those most at risk for adverse outcomes.

Funding

United States National Institute of Health, COPD Foundation, and Brigham and Women's Hospital.

Myeloid Heterogeneity Mediates Acute Exacerbations of Pulmonary Fibrosis

Epidemiological evidence indicates that exposure to particulate matter is linked to the development of idiopathic pulmonary fibrosis (IPF) and increases the incidence of acute exacerbations of IPF. In addition to accelerating the rate of lung function decline, exposure to fine particulate matter (particulate matter smaller than 2.5 μm [PM2.5]) is a risk factor for increased mortality in subjects with IPF. In this article, we show that exposure to PM2.5 mediates monocyte recruitment and fibrotic progression in mice with established fibrosis. In mice with established fibrosis, bronchoalveolar lavage cells showed monocyte/macrophage heterogeneity after exposure to PM2.5. These cells had a significant inflammatory and anti-inflammatory signature. The mixed heterogeneity of cells contributed to the proinflammatory and anti-inflammatory response. Although monocyte-derived macrophages were recruited to the lung in bleomycin-injured mice treated with PM2.5, recruitment of monocytes expressing Ly6Chi to the lung promoted progression of fibrosis, reduced lung aeration on computed tomography, and impacted lung compliance. Ly6Chi monocytes isolated from PM2.5-exposed fibrotic mice showed enhanced expression of proinflammatory markers compared with fibrotic mice exposed to vehicle. Moreover, IPF bronchoalveolar lavage cells treated ex vivo with PM2.5 showed an exaggerated inflammatory response. Targeting Ly6Chi monocyte recruitment inhibited fibrotic progression in mice. Moreover, the adoptive transfer of Ly6Chi monocytes exacerbated established fibrosis. These observations suggest that enhanced recruitment of Ly6Chi monocytes with a proinflammatory phenotype mediates acute exacerbations of pulmonary fibrosis, and targeting these cells may provide a potential novel therapeutic target to protect against acute exacerbations of IPF.

Altered sphingolipid pathway in SARS-CoV-2 infected human lung tissue

Introduction

The SARS-CoV-2 mediated COVID-19 pandemic has impacted millions worldwide. Hyper-inflammatory processes, including cytokine storm, contribute to long-standing tissue injury and damage in COVID-19. The metabolism of sphingolipids as regulators of cell survival, differentiation, and proliferation has been implicated in inflammatory signaling and cytokine responses. Sphingosine-kinase-1 (SK1) and ceramide-synthase-2 (CERS2) generate metabolites that regulate the anti- and pro-apoptotic processes, respectively. Alterations in SK1 and CERS2 expression may contribute to the inflammation and tissue damage during COVID-19. The central objective of this study is to evaluate structural changes in the lung post-SARS-CoV-2 infection and to investigate whether the sphingolipid rheostat is altered in response to SARS-CoV-2 infection.

Methods

Central and peripheral lung tissues from COVID-19+ or control autopsies and resected lung tissue from COVID-19 convalescents were subjected to histologic evaluation of airspace and collagen deposisiton, and immunohistochemical evaluation of SK1 and CERS2.

Results

Here, we report significant reduction in air space and increase in collagen deposition in lung autopsy tissues from patients who died from COVID-19 (COVID-19+) and COVID-19 convalescent individuals. SK1 expression increased in the lungs of COVID-19+ autopsies and COVID-19 convalescent lung tissue compared to controls and was mostly associated with Type II pneumocytes and alveolar macrophages. No significant difference in CERS2 expression was noted. SARS-CoV-2 infection upregulates SK1 and increases the ratio of SK1 to CERS2 expression in lung tissues of COVID-19 autopsies and COVID-19 convalescents.

Discussion

These data suggest an alteration in the sphingolipid rheostat in lung tissue during COVID-19, suggesting a potential contribution to the inflammation and tissue damage associated with viral infection.

Influence of Pulsatility and Inflow Waveforms on Tracheal Airflow Dynamics in Healthy Older Adults

Tracheal collapsibility is a dynamic process altering local airflow dynamics. Patient-specific simulation is a powerful technique to explore the physiological and pathological characteristics of human airways. One of the key considerations in implementing airway computations is choosing the right inlet boundary conditions that can act as a surrogate model for understanding realistic airflow simulations. To this end, we numerically examine airflow patterns under the influence of different profiles, i.e., flat, parabolic, and Womersley, and compare these with a realistic inlet obtained from experiments. Simulations are performed in ten patient-specific cases with normal and rapid breathing rates during the inhalation phase of the respiration cycle. At normal breathing, velocity and vorticity contours reveal primary flow structures on the sagittal plane that impart strength to cross-plane vortices. Rapid breathing, however, encounters small recirculation zones. Quantitative flow metrics are evaluated using time-averaged wall shear stress (TAWSS) and oscillatory shear index (OSI). Overall, the flow metrics encountered in a real velocity profile are in close agreement with parabolic and Womersley profiles for normal conditions, however, the Womersley inlet alone conforms to a realistic profile under rapid breathing conditions.

FEV1/FVC Severity Stages for Chronic Obstructive Pulmonary Disease

Rationale: The diagnosis of chronic obstructive pulmonary disease (COPD) is based on a low FEV1/FVC ratio, but the severity of COPD is classified using FEV1% predicted (ppFEV1). Objectives: To test a new severity classification scheme for COPD using FEV1/FVC ratio, a more robust measure of airflow obstruction than ppFEV1. Methods: In COPDGene (Genetic Epidemiology of COPD) (N = 10,132), the severity of airflow obstruction was categorized by Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages 1-4 (ppFEV1 of ⩾80%, ⩾50-80%, ⩾30-50%, and <30%). A new severity classification (STaging of Airflow obstruction by Ratio; STAR) was tested in COPDGene-FEV1/FVC ⩾0.60 to <0.70, ⩾0.50 to <0.60, ⩾0.40 to <0.50, and <0.40, respectively, for stages 1-4-and applied to the combined Pittsburgh SCCOR and Emphysema COPD Research Registry for replication (N = 2,017). Measurements and Main Results: The agreements (weighted Bangdiwala B values) between GOLD and the new FEV1/FVC ratio severity stages were 0.89 in COPDGene and 0.88 in the Pittsburgh cohort. In COPDGene and the Pittsburgh cohort, compared with GOLD staging, STAR provided significant discrimination between the absence of airflow obstruction and stage 1 for all-cause mortality, respiratory quality of life, dyspnea, airway wall thickness, exacerbations, and lung function decline. No major differences were noted for emphysema, small airway disease, and 6-minute-walk distance. The STAR classification system identified a greater number of adults with stage 3/4 disease who would be eligible for lung transplantation and lung volume reduction procedure evaluations. Conclusions: The new STAR severity classification scheme provides discrimination for mortality that is similar to the GOLD classification but with a more uniform gradation of disease severity. STAR differentiates patients' symptoms, disease burden, and prognosis better than the existing scheme based on ppFEV1, and is less sensitive to race/ethnicity and other demographic characteristics.

Parameter D: New Measure of Airflow Obstruction

Rationale: Currently used spirometry measures of airflow obstruction are influenced by demographics, predominantly by age, complicating selection of diagnostic thresholds for the presence of airflow obstruction. Objectives: To develop diagnostic thresholds for Parameter D, a new metric for detection of airflow obstruction, which quantifies the rate of rise of expiratory volume over time. Methods: We analyzed spirometry data of normal subjects enrolled in the 2007-2008, 2009-2010, and 2011-2012 NHANES (National Health and Nutrition Examination Survey) cohorts and calculated Parameter D using the expiratory volume-time curve. Relationships between demographics and lung function (forced expiratory volume in 1 second [FEV1], FEV1/forced vital capacity [FVC], and Parameter D) were tested using generalized linear models in NHANES and UK Biobank. The variation in lung function explained by demographics was estimated using R2. A diagnostic threshold was developed for Parameter D using population-based percentiles. Based on concordance between the lower limit of normal (LLN) for FEV1/FVC and the Parameter D threshold, four groups were identified: normal (no airflow obstruction by either criterion), D+chronic obstructive pulmonary disease (D+COPD; positive by Parameter D only), D-COPD (positive by LLN only), and COPD (positive by both criteria), and associations with structural lung disease, exacerbations, and mortality were tested using multivariable analyses. Results: In contrast to FEV1 and FEV1/FVC, demographics cumulatively explained only 9% of the variance in Parameter D in NHANES (n = 4,945) and 3% in UK BioBank (n = 109,623). In COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease) (n = 9,542), a diagnostic threshold of -3.15 resulted in the identification of an additional 10.8% of participants with airflow obstruction. A total of 3.7% had FEV1/FVC < LLN but were missed by the Parameter D threshold. Compared with subjects in the normal group, after adjustment for age, sex, race, body mass index, pack-years of smoking, and current smoking status, D+COPD was associated with worse structural lung disease (odds ratio [OR] for ⩾5% emphysema, 1.71; 95% confidence interval [CI], 1.37-2.12; OR for functional small airway disease ⩾ 15%, 2.1; 95% CI, 1.79-2.67) and significant symptoms (OR for modified Medical Research Council dyspnea score ⩾ 2, 1.25; 95% CI, 1.07-1.47; OR for St. George's respiratory questionnaire ⩾ 25, 1.31; 95% CI, 1.13-1.53), a greater frequency of exacerbations (incidence rate ratio, 1.26; 95% CI, 1.10-1.46), and higher mortality (hazard ratio, 1.32; 95% CI, 1.10-1.57). Over 5 years, 28% of the D+COPD group versus 8% of normal group progressed to COPD by traditional criteria. Conclusions: Parameter D is not affected by age, and a normal population-based diagnostic threshold results in the early identification of additional individuals with airflow obstruction with a substantial amount of structural lung disease and respiratory symptoms.

Radiomics for Improved Detection of Chronic Obstructive Pulmonary Disease in Low-Dose and Standard-Dose Chest CT Scans

Background Approximately half of adults with chronic obstructive pulmonary disease (COPD) remain undiagnosed. Chest CT scans are frequently acquired in clinical practice and present an opportunity to detect COPD. Purpose To assess the performance of radiomics features in COPD diagnosis using standard-dose and low-dose CT models. Materials and Methods This secondary analysis included participants enrolled in the Genetic Epidemiology of COPD, or COPDGene, study at baseline (visit 1) and 10 years after baseline (visit 3). COPD was defined by a forced expiratory volume in the 1st second of expiration to forced vital capacity ratio less than 0.70 at spirometry. The performance of demographics, CT emphysema percentage, radiomics features, and a combined feature set derived from inspiratory CT alone was evaluated. CatBoost (Yandex), a gradient boosting algorithm, was used to perform two classification experiments to detect COPD; the two models were trained and tested on standard-dose CT data from visit 1 (model I) and low-dose CT data from visit 3 (model II). Classification performance of the models was evaluated using area under the receiver operating characteristic curve (AUC) and precision-recall curve analysis. Results A total of 8878 participants (mean age, 57 years ± 9 [SD]; 4180 female, 4698 male) were evaluated. Radiomics features in model I achieved an AUC of 0.90 (95% CI: 0.88, 0.91) in the standard-dose CT test cohort versus demographics (AUC, 0.73; 95% CI: 0.71, 0.76; P < .001), emphysema percentage (AUC, 0.82; 95% CI 0.80, 0.84; P < .001), and combined features (AUC, 0.90; 95% CI: 0.89, 0.92; P = .16). Model II, trained on low-dose CT scans, achieved an AUC of 0.87 (95% CI: 0.83, 0.91) on the 20% held-out test set for radiomics features compared with demographics (AUC, 0.70; 95% CI: 0.64, 0.75; P = .001), emphysema percentage (AUC, 0.74; 95% CI: 0.69, 0.79; P = .002), and combined features (AUC, 0.88; 95% CI: 0.85, 0.92; P = .32). Density and texture features were the majority of the top 10 features in the standard-dose model, whereas shape features of lungs and airways were significant contributors in the low-dose CT model. Conclusion A combination of features representing parenchymal texture and lung and airway shape on inspiratory CT scans can be used to accurately detect COPD. ClinicalTrials.gov registration no. NCT00608764 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Vliegenthart in this issue.

Deep Learning Utilizing Suboptimal Spirometry Data to Improve Lung Function and Mortality Prediction in the UK Biobank

Background

Spirometry measures lung function by selecting the best of multiple efforts meeting pre-specified quality control (QC), and reporting two key metrics: forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC). We hypothesize that discarded submaximal and QC-failing data meaningfully contribute to the prediction of airflow obstruction and all-cause mortality.

Methods

We evaluated volume-time spirometry data from the UK Biobank. We identified "best" spirometry efforts as those passing QC with the maximum FVC. "Discarded" efforts were either submaximal or failed QC. To create a combined representation of lung function we implemented a contrastive learning approach, Spirogram-based Contrastive Learning Framework (Spiro-CLF), which utilized all recorded volume-time curves per participant and applied different transformations (e.g. flow-volume, flow-time). In a held-out 20% testing subset we applied the Spiro-CLF representation of a participant's overall lung function to 1) binary predictions of FEV1/FVC < 0.7 and FEV1 Percent Predicted (FEV1PP) < 80%, indicative of airflow obstruction, and 2) Cox regression for all-cause mortality.

Findings

We included 940,705 volume-time curves from 352,684 UK Biobank participants with 2-3 spirometry efforts per individual (66.7% with 3 efforts) and at least one QC-passing spirometry effort. Of all spirometry efforts, 24.1% failed QC and 37.5% were submaximal. Spiro-CLF prediction of FEV1/FVC < 0.7 utilizing discarded spirometry efforts had an Area under the Receiver Operating Characteristics (AUROC) of 0.981 (0.863 for FEV1PP prediction). Incorporating discarded spirometry efforts in all-cause mortality prediction was associated with a concordance index (c-index) of 0.654, which exceeded the c-indices from FEV1 (0.590), FVC (0.559), or FEV1/FVC (0.599) from each participant's single best effort.

Interpretation

A contrastive learning model using raw spirometry curves can accurately predict lung function using submaximal and QC-failing efforts. This model also has superior prediction of all-cause mortality compared to standard lung function measurements.

Funding

MHC is supported by NIH R01HL137927, R01HL135142, HL147148, and HL089856.BDH is supported by NIH K08HL136928, U01 HL089856, and an Alpha-1 Foundation Research Grant.DH is supported by NIH 2T32HL007427-41EKS is supported by NIH R01 HL152728, R01 HL147148, U01 HL089856, R01 HL133135, P01 HL132825, and P01 HL114501.PJC is supported by NIH R01HL124233 and R01HL147326.SPB is supported by NIH R01HL151421 and UH3HL155806.TY, FH, and CYM are employees of Google LLC.

Access to Pulmonary Rehabilitation among Medicare Beneficiaries with Chronic Obstructive Pulmonary Disease

Rationale: Pulmonary rehabilitation (PR) remains substantially underused as a treatment modality for chronic obstructive pulmonary disease (COPD). A major barrier to the uptake of PR is the poor availability of and access to PR. Objectives: To quantify patients' access to PR centers in the United States. Methods: Using the 100% Medicare population with coverage for 2018, four geodesic distance-based buffers of 10-, 15-, 25-, and 50-mi radii around the geographic centroid of each ZIP code with at least one beneficiary with COPD were created. Street addresses of PR centers across the continental United States were geocoded. We calculated the distance between the residential ZIP code centroid and the closest PR center. The proportions of individuals with at least one PR center available within the four distance buffers were calculated overall as well as in metropolitan, micropolitan, small-town, and rural areas. Results: Of 62,930,784 Medicare beneficiaries, 10,376,949 (16.5%) had COPD. There were 1,696 PR centers across the United States, with one PR center for every 6,030 individuals with COPD. Mean distance to the nearest PR center was 12.4 (standard deviation, 16.6) mi. Overall, the proportions of individuals with COPD who had PR centers available within 10-, 15-, 25-, and 50-mi radii were 61.5%, 73.2%, 86.6%, and 97.1%, respectively. Proportions for rural areas were 11.3%, 24.3%, 53.4%, and 88.6%, respectively. Compared with those living in metropolitan areas, those living in rural areas were 95% less likely to have PR centers within 10 mi of their residences (odds ratio, 0.048 [95% confidence interval, 0.039-0.057]). Conclusions: In a nationally representative sample of Medicare beneficiaries, we found that two-fifths of adults with COPD overall, and eight in nine of those in rural areas, have poor access to PR.

Idiopathic pulmonary fibrosis is more strongly associated with coronary artery disease than chronic obstructive pulmonary disease

INTRODUCTION

Previous studies have shown that the population attributable risk of low forced expiratory volume in one second (FEV₁) for coronary artery disease (CAD) is substantial. FEV₁ can be low either because of airflow obstruction or ventilatory restriction. It is not known if low FEV₁ arising from spirometric obstruction or restriction are differently associated with CAD.

METHODS

We analyzed high resolution computed tomography (CT) scans acquired at full inspiration in lifetime non-smoker adults with no lung disease (controls) and those with chronic obstructive pulmonary disease enrolled in the Genetic Epidemiology of COPD (COPDGene) study. We also analyzed CT scans of adults with idiopathic pulmonary fibrosis (IPF) from a cohort of patients attending a quaternary referral clinic. Participants with IPF were matched 1:1 by FEV₁ %predicted to adults with COPD and 1:1 by age to lifetime non-smokers. Coronary artery calcium (CAC), a surrogate for CAD, was measured by visual quantification on CT using the Weston score. Significant CAC was defined as Weston score ≥7. Multivariable regression models were used to test the association of the presence of COPD or IPF with CAC, with adjustment for age, sex, body-mass-index, smoking status, hypertension, diabetes mellitus, and hyperlipidemia.

RESULTS

We included 732 subjects in the study; 244 with IPF, 244 with COPD, and 244 lifetime non-smokers. The mean (SD) age was 72.6 (8.1), 62.6 (7.4), and 67.3 (6.6) years, and median (IQR) CAC was 6 (6), 2 (6), and 1 (4), in IPF, COPD, and non-smokers, respectively. On multivariable analyses, the presence of COPD was associated with higher CAC compared to non-smokers (adjusted regression coefficient, β = 1.10 ± SE0.51; P = 0.031). The presence of IPF was also associated with higher CAC compared to non-smokers (β = 03.43 ± SE0.41; P < 0.001). The adjusted odds ratio for having significant CAC was 1.3, 95% CI 0.6 to 2.8; P = 0.53 in COPD and 5.6, 95% CI 2.9 to 10.9; P < 0.001 in IPF, compared to non-smokers. In sex stratified analyses, these associations were mainly noted in women.

CONCLUSION

Adults with IPF displayed higher coronary artery calcium than those with COPD after accounting for age and lung function impairment.

Predicting severe chronic obstructive pulmonary disease exacerbations using quantitative CT: a retrospective model development and external validation study

BACKGROUND

Quantitative CT is becoming increasingly common for the characterisation of lung disease; however, its added potential as a clinical tool for predicting severe exacerbations remains understudied. We aimed to develop and validate quantitative CT-based models for predicting severe chronic obstructive pulmonary disease (COPD) exacerbations.

METHODS

We analysed the Subpopulations and Intermediate Outcome Measures In COPD Study (SPIROMICS) cohort, a multicentre study done at 12 clinical sites across the USA, of individuals aged 40-80 years from four strata: individuals who never smoked, individuals who smoked but had normal spirometry, individuals who smoked and had mild to moderate COPD, and individuals who smoked and had severe COPD. We used 3-year follow-up data to develop logistic regression classifiers for predicting severe exacerbations. Predictors included age, sex, race, BMI, pulmonary function, exacerbation history, smoking status, respiratory quality of life, and CT-based measures of density gradient texture and airway structure. We externally validated our models in a subset from the Genetic Epidemiology of COPD (COPDGene) cohort. Discriminative model performance was assessed using the area under the receiver operating characteristic curve (AUC), which was also compared with other predictors, including exacerbation history and the BMI, airflow obstruction, dyspnoea, and exercise capacity (BODE) index. We evaluated model calibration using calibration plots and Brier scores.

FINDINGS

Participants in SPIROMICS were enrolled between Nov 12, 2010, and July 31, 2015. Participants in COPDGene were enrolled between Jan 10, 2008, and April 15, 2011. We included 1956 participants from the SPIROMICS cohort who had complete 3-year follow-up data: the mean age of the cohort was 63·1 years (SD 9·2) and 1017 (52%) were men and 939 (48%) were women. Among the 1956 participants, 434 (22%) had a history of at least one severe exacerbation. For the CT-based models, the AUC was 0·854 (95% CI 0·852-0·855) for at least one severe exacerbation within 3 years and 0·931 (0·930-0·933) for consistent exacerbations (defined as ≥1 acute episode in each of the 3 years). Models were well calibrated with low Brier scores (0·121 for at least one severe exacerbation; 0·039 for consistent exacerbations). For the prediction of at least one severe event during 3-year follow-up, AUCs were significantly higher with CT biomarkers (0·854 [0·852-0·855]) than exacerbation history (0·823 [0·822-0·825]) and BODE index 0·812 [0·811-0·814]). 6965 participants were included in the external validation cohort, with a mean age of 60·5 years (SD 8·9). In this cohort, AUC for at least one severe exacerbation was 0·768 (0·767-0·769; Brier score 0·088).

INTERPRETATION

CT-based prediction models can be used for identification of patients with COPD who are at high risk of severe exacerbations. The newly identified CT biomarkers could potentially enable investigation into underlying disease mechanisms responsible for exacerbations.

FUNDING

National Institutes of Health and the National Heart, Lung, and Blood Institute.

Sex Differences in Airways at Chest CT: Results from the COPDGene Cohort

Background The prevalence of chronic obstructive pulmonary disease (COPD) in women is fast approaching that in men, and women experience greater symptom burden. Although sex differences in emphysema have been reported, differences in airways have not been systematically characterized. Purpose To evaluate whether structural differences in airways may underlie some of the sex differences in COPD prevalence and clinical outcomes. Materials and Methods In a secondary analyses of a multicenter study of never-, current-, and former-smokers enrolled from January 2008 to June 2011 and followed up longitudinally until November 2020, airway disease on CT images was quantified using seven metrics: airway wall thickness, wall area percent, and square root of the wall thickness of a hypothetical airway with internal perimeter of 10 mm (referred to as Pi10) for airway wall; and lumen diameter, airway volume, total airway count, and airway fractal dimension for airway lumen. Least-squares mean values for each airway metric were calculated and adjusted for age, height, ethnicity, body mass index, pack-years of smoking, current smoking status, total lung capacity, display field of view, and scanner type. In ever-smokers, associations were tested between each airway metric and postbronchodilator forced expiratory volume in 1 second (FEV1)-to-forced vital capacity (FVC) ratio, modified Medical Research Council dyspnea scale, St George's Respiratory Questionnaire score, and 6-minute walk distance. Multivariable Cox proportional hazards models were created to evaluate the sex-specific association between each airway metric and mortality. Results In never-smokers (n = 420), men had thicker airway walls than women as quantified on CT images for segmental airway wall area percentage (least-squares mean, 47.68 ± 0.61 [standard error] vs 45.78 ± 0.55; difference, -1.90; P = .02), whereas airway lumen dimensions were lower in women than men after accounting for height and total lung capacity (segmental lumen diameter, 8.05 mm ± 0.14 vs 9.05 mm ± 0.16; difference, -1.00 mm; P < .001). In ever-smokers (n = 9363), men had greater segmental airway wall area percentage (least-squares mean, 52.19 ± 0.16 vs 48.89 ± 0.18; difference, -3.30; P < .001), whereas women had narrower segmental lumen diameter (7.80 mm ± 0.05 vs 8.69 mm ± 0.04; difference, -0.89; P < .001). A unit change in each of the airway metrics (higher wall or lower lumen measure) resulted in lower FEV1-to-FVC ratio, more dyspnea, poorer respiratory quality of life, lower 6-minute walk distance, and worse survival in women compared with men (all P < .01). Conclusion Airway lumen sizes quantified at chest CT were smaller in women than in men after accounting for height and lung size, and these lower baseline values in women conferred lower reserves against respiratory morbidity and mortality for equivalent changes compared with men. © RSNA, 2022 Online supplemental material is available for this article.

Extracellular Vesicle Mediated Tumor-Stromal Crosstalk Within an Engineered Lung Cancer Model

Tumor-stromal interactions within the tumor microenvironment (TME) influence lung cancer progression and response to therapeutic interventions, yet traditional in vitro studies fail to replicate the complexity of these interactions. Herein, we developed three-dimensional (3D) lung tumor models that mimic the human TME and demonstrate tumor-stromal crosstalk mediated by extracellular vesicles (EVs). EVs released by tumor cells, independent of p53 status, and fibroblasts within the TME mediate immunomodulatory effects; specifically, monocyte/macrophage polarization to a tumor-promoting M2 phenotype within this 3D-TME. Additionally, immune checkpoint inhibition in a 3D model that included T cells showed an inhibition of tumor growth and reduced hypoxia within the TME. Thus, perfused 3D tumor models incorporating diverse cell types provide novel insights into EV-mediated tumor-immune interactions and immune-modulation for existing and emerging cancer therapies.

Computed Tomography-based Airway Surface Area-to-Volume Ratio for Phenotyping Airway Remodeling in Chronic Obstructive Pulmonary Disease

Rationale: Airway remodeling in chronic obstructive pulmonary disease (COPD) is due to luminal narrowing and/or loss of airways. Existing computed tomographic metrics of airway disease reflect only components of these processes. With progressive airway narrowing, the ratio of the airway luminal surface area to volume (SA/V) should increase, and with predominant airway loss, SA/V should decrease.Objectives: To phenotype airway remodeling in COPD.Methods: We analyzed the airway trees of 4,325 subjects with COPD Global Initiative for Chronic Obstructive Lung Disease stages 0 to 4 and 73 nonsmokers enrolled in the multicenter COPDGene (Genetic Epidemiology of COPD) cohort. Surface area and volume measurements were estimated for the subtracheal airway tree to derive SA/V. We performed multivariable regression analyses to test associations between SA/V and lung function, 6-minute-walk distance, St. George's Respiratory Questionnaire, change in FEV₁, and mortality, adjusting for demographics, total airway count, airway wall thickness, and emphysema. On the basis of the change in SA/V over 5 years, we categorized subjects into predominant airway narrowing [positive ∆(SA/V) more than 0] and predominant airway loss [negative ∆(SA/V) less than 0] and compared survival between the two groups.Measurements and Main Results: Airway SA/V was independently associated with FEV₁/FVC (β = 0.12; 95% confidence interval [CI], 0.09-0.14; P < 0.001) and FEV₁% predicted (β = 20.10; 95% CI, 15.13-25.08; P < 0.001). Airway SA/V was also independently associated with 6-minute-walk distance, respiratory quality of life, and lung function decline. Compared with subjects with predominant airway narrowing (n = 2,914; 66.3%), those with predominant airway loss (n = 1,484; 33.7%) had worse survival (adjusted hazard ratio for all-cause mortality = 1.58; 95% CI, 1.18-2.13; P = 0.002).Conclusions: Computed tomography-based airway SA/V is an imaging biomarker of airway remodeling and provides differential information on predominant airway narrowing and loss in COPD. SA/V is associated with respiratory morbidity, lung function decline, and survival.

Structural airway imaging metrics are differentially associated with persistent chronic bronchitis

BACKGROUND

Chronic bronchitis (CB) is strongly associated with cigarette smoking, but not all smokers develop CB. We aimed to evaluate whether measures of structural airway disease on CT are differentially associated with CB.

METHODS

In smokers between ages 45 and 80 years, and with Global Initiative for Obstructive Lung Disease stages 0-4, CB was defined by the classic definition. Airway disease on CT was quantified by (i) wall area percent (WA%) of segmental airways; (ii) Pi10, the square root of the wall area of a hypothetical airway with 10 mm internal perimeter; (iii) total airway count (TAC) and (iv) airway fractal dimension (AFD), a measure of the complex branching pattern and remodelling of airways. CB was also assessed at the 5-year follow-up visit.

MEASUREMENTS AND MAIN RESULTS

Of 8917 participants, 1734 (19.4%) had CB at baseline. Airway measures were significantly worse in those with CB compared with those without CB: WA% 54.5 (8.8) versus 49.8 (8.3); Pi10 2.58 (0.67) versus 2.28 (0.59) mm; TAC 156.7 (81.6) versus 177.8 (91.1); AFD 1.477 (0.091) versus 1.497 (0.092) (all p<0.001). On follow-up of 5517 participants at 5 years, 399 (7.2%) had persistent CB. With adjustment for between-visits changes in smoking status and lung function, greater WA% and Pi10 were associated with significantly associated with persistent CB, adjusted OR per SD change 1.75, 95% CI 1.56 to 1.97; p<0.001 and 1.66, 95% CI 1.42 to 1.86; p<0.001, respectively. Higher AFD and TAC were associated with significantly lower odds of persistent CB, adjusted OR per SD change 0.76, 95% CI 0.67 to 0.86; p<0.001 and 0.69, 95% CI 0.60 to 0.80; p<0.001, respectively.

CONCLUSIONS

Higher baseline AFD and TAC are associated with a lower risk of persistent CB, irrespective of changes in smoking status, suggesting preserved airway structure can confer a reserve against CB.

Brd4-p300 inhibition downregulates Nox4 and accelerates lung fibrosis resolution in aged mice

Tissue regeneration capacity declines with aging in association with heightened oxidative stress. Expression of the oxidant-generating enzyme, NADPH oxidase 4 (Nox4), is elevated in aged mice with diminished capacity for fibrosis resolution. Bromodomain-containing protein 4 (Brd4) is a member of the bromodomain and extraterminal (BET) family of proteins that function as epigenetic "readers" of acetylated lysine groups on histones. In this study, we explored the role of Brd4 and its interaction with the p300 acetyltransferase in the regulation of Nox4 and the in vivo efficacy of a BET inhibitor to reverse established age-associated lung fibrosis. BET inhibition interferes with the association of Brd4, p300, and acetylated histone H4K16 with the Nox4 promoter in lung fibroblasts stimulated with the profibrotic cytokine, TGF-β1. A number of BET inhibitors, including I-BET-762, JQ1, and OTX015, downregulate Nox4 gene expression and activity. Aged mice with established and persistent lung fibrosis recover capacity for fibrosis resolution with OTX015 treatment. This study implicates epigenetic regulation of Nox4 by Brd4 and p300 and supports BET/Brd4 inhibition as an effective strategy for the treatment of age-related fibrotic lung disease.

Deep neural network analyses of spirometry for structural phenotyping of chronic obstructive pulmonary disease

BACKGROUNDCurrently recommended traditional spirometry outputs do not reflect the relative contributions of emphysema and airway disease to airflow obstruction. We hypothesized that machine-learning algorithms can be trained on spirometry data to identify these structural phenotypes.METHODSParticipants enrolled in a large multicenter study (COPDGene) were included. The data points from expiratory flow-volume curves were trained using a deep-learning model to predict structural phenotypes of chronic obstructive pulmonary disease (COPD) on CT, and results were compared with traditional spirometry metrics and an optimized random forest classifier. Area under the receiver operating characteristic curve (AUC) and weighted F-score were used to measure the discriminative accuracy of a fully convolutional neural network, random forest, and traditional spirometry metrics to phenotype CT as normal, emphysema-predominant (>5% emphysema), airway-predominant (Pi10 > median), and mixed phenotypes. Similar comparisons were made for the detection of functional small airway disease phenotype (>20% on parametric response mapping).RESULTSAmong 8980 individuals, the neural network was more accurate in discriminating predominant emphysema/airway phenotypes (AUC 0.80, 95%CI 0.79-0.81) compared with traditional measures of spirometry, FEV1/FVC (AUC 0.71, 95%CI 0.69-0.71), FEV1% predicted (AUC 0.70, 95%CI 0.68-0.71), and random forest classifier (AUC 0.78, 95%CI 0.77-0.79). The neural network was also more accurate in discriminating predominant emphysema/small airway phenotypes (AUC 0.91, 95%CI 0.90-0.92) compared with FEV1/FVC (AUC 0.80, 95%CI 0.78-0.82), FEV1% predicted (AUC 0.83, 95%CI 0.80-0.84), and with comparable accuracy with random forest classifier (AUC 0.90, 95%CI 0.88-0.91).CONCLUSIONSStructural phenotypes of COPD can be identified from spirometry using deep-learning and machine-learning approaches, demonstrating their potential to identify individuals for targeted therapies.TRIAL REGISTRATIONClinicalTrials.gov NCT00608764.FUNDINGThis study was supported by NIH grants K23 HL133438 and R21EB027891 and an American Thoracic Foundation 2018 Unrestricted Research Grant. The COPDGene study is supported by NIH grants NHLBI U01 HL089897 and U01 HL089856. The COPDGene study (NCT00608764) is also supported by the COPD Foundation through contributions made to an Industry Advisory Committee comprising AstraZeneca, Boehringer-Ingelheim, GlaxoSmithKline, Novartis, and Sunovion.

Airway Remodeling in Ferrets with Cigarette Smoke Induced COPD using µCT Imaging

RATIONALE

Structural changes to airway morphology such as increased bronchial wall thickness (BWT) and airway wall area are cardinal features of chronic obstructive pulmonary disease (COPD). Ferrets are a recently established animal model uniquely exhibiting similar clinical and pathological characteristics of COPD as humans, including chronic bronchitis.

OBJECTIVES

Develop a µCT method for evaluating structural changes to the airways in ferrets, and assess whether the effects of smoking induce changes consistent with chronic bronchitis in humans.

METHODS

Ferrets were exposed to mainstream cigarette smoke or air control twice daily for 6 months. µCT was conducted in vivo at 6 months; a longitudinal cohort was imaged monthly. Manual measurements of BWT, luminal diameter (LD), and BWT:LD ratio were conducted, and confirmed by a semi-automated algorithm. The square root of bronchial wall area (WA) vs. luminal perimeter was determined on an individual ferret basis.

MEASUREMENTS AND MAIN RESULTS

Smoke exposed ferrets reproducibly demonstrated 34% increased BWT (P<0.001); along with increased LD, and BWT:LD ratio vs. air controls. Regression indicated the effect of smoking on BWT persisted despite controlling for covariates. Semi-automated measurements replicated findings. WA for the theoretical median airway luminal perimeter of 4 mm (Pi4) was elevated 4.4% in smoke exposed ferrets (P=0.015). Increased BWT and Pi4 developed steadily over time.

CONCLUSIONS

µCT-based airway measurements in ferrets are feasible and reproducible. Smoke exposed ferrets develop increased BWT and Pi4, changes similar to humans with chronic bronchitis. µCT can be used as a significant translational platform to measure dynamic airway morphological changes.

Imaging Advances in Chronic Obstructive Pulmonary Disease. Insights from the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) Study

The Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study, which began in 2007, is an ongoing multicenter observational cohort study of more than 10,000 current and former smokers. The study is aimed at understanding the etiology, progression, and heterogeneity of chronic obstructive pulmonary disease (COPD). In addition to genetic analysis, the participants have been extensively characterized by clinical questionnaires, spirometry, volumetric inspiratory and expiratory computed tomography, and longitudinal follow-up, including follow-up computed tomography at 5 years after enrollment. The purpose of this state-of-the-art review is to summarize the major advances in our understanding of COPD resulting from the imaging findings in the COPDGene study. Imaging features that are associated with adverse clinical outcomes include early interstitial lung abnormalities, visual presence and pattern of emphysema, the ratio of pulmonary artery to ascending aortic diameter, quantitative evaluation of emphysema, airway wall thickness, and expiratory gas trapping. COPD is characterized by the early involvement of the small conducting airways, and the addition of expiratory scans has enabled measurement of small airway disease. Computational advances have enabled indirect measurement of nonemphysematous gas trapping. These metrics have provided insights into the pathogenesis and prognosis of COPD and have aided early identification of disease. Important quantifiable extrapulmonary findings include coronary artery calcification, cardiac morphology, intrathoracic and extrathoracic fat, and osteoporosis. Current active research includes identification of novel quantitative measures for emphysema and airway disease, evaluation of dose reduction techniques, and use of deep learning for phenotyping COPD.

COPDGene® 2019: Redefining the Diagnosis of Chronic Obstructive Pulmonary Disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) remains a major cause of morbidity and mortality. Present-day diagnostic criteria are largely based solely on spirometric criteria. Accumulating evidence has identified a substantial number of individuals without spirometric evidence of COPD who suffer from respiratory symptoms and/or increased morbidity and mortality. There is a clear need for an expanded definition of COPD that is linked to physiologic, structural (computed tomography [CT]) and clinical evidence of disease. Using data from the COPD Genetic Epidemiology study (COPDGene®), we hypothesized that an integrated approach that includes environmental exposure, clinical symptoms, chest CT imaging and spirometry better defines disease and captures the likelihood of progression of respiratory obstruction and mortality.

METHODS

Four key disease characteristics - environmental exposure (cigarette smoking), clinical symptoms (dyspnea and/or chronic bronchitis), chest CT imaging abnormalities (emphysema, gas trapping and/or airway wall thickening), and abnormal spirometry - were evaluated in a group of 8784 current and former smokers who were participants in COPDGene® Phase 1. Using these 4 disease characteristics, 8 categories of participants were identified and evaluated for odds of spirometric disease progression (FEV1 > 350 ml loss over 5 years), and the hazard ratio for all-cause mortality was examined.

RESULTS

Using smokers without symptoms, CT imaging abnormalities or airflow obstruction as the reference population, individuals were classified as Possible COPD, Probable COPD and Definite COPD. Current Global initiative for obstructive Lung Disease (GOLD) criteria would diagnose 4062 (46%) of the 8784 study participants with COPD. The proposed COPDGene® 2019 diagnostic criteria would add an additional 3144 participants. Under the new criteria, 82% of the 8784 study participants would be diagnosed with Possible, Probable or Definite COPD. These COPD groups showed increased risk of disease progression and mortality. Mortality increased in patients as the number of their COPD characteristics increased, with a maximum hazard ratio for all cause-mortality of 5.18 (95% confidence interval [CI]: 4.15-6.48) in those with all 4 disease characteristics.

CONCLUSIONS

A substantial portion of smokers with respiratory symptoms and imaging abnormalities do not manifest spirometric obstruction as defined by population normals. These individuals are at significant risk of death and spirometric disease progression. We propose to redefine the diagnosis of COPD through an integrated approach using environmental exposure, clinical symptoms, CT imaging and spirometric criteria. These expanded criteria offer the potential to stimulate both current and future interventions that could slow or halt disease progression in patients before disability or irreversible lung structural changes develop.

The Peak Index: Spirometry Metric for Airflow Obstruction Severity and Heterogeneity

Rationale: Chronic obstructive pulmonary disease (COPD) is characterized by airflow limitation. Spirometry loops are not smooth curves and have undulations and peaks that likely reflect heterogeneity of airflow.Objectives: To assess whether the Peak Index, the number of peaks adjusted for lung size, is associated with clinical outcomes.Methods: We analyzed spirometry data of 9,584 participants enrolled in the COPDGene study and counted the number of peaks in the descending part of the expiratory flow-volume curve from the peak expiratory flow to end-expiration. We adjusted the peaks count for the volume of the lungs from peak expiratory flow to end-expiration to derive the Peak Index. Multivariable regression analyses were performed to test associations between the Peak Index and lung function, respiratory morbidity, structural lung disease on computed tomography (CT), forced expiratory volume in 1 second (FEV1) decline, and mortality.Results: The Peak Index progressively increased from Global Initiative for Chronic Obstructive Lung Disease stage 0 through 4 (P < 0.001). On multivariable analysis, the Peak Index was significantly associated with CT emphysema (adjusted β = 0.906; 95% confidence interval [CI], 0.789 to 1.023; P < 0.001) and small airways disease (adjusted β = 1.367; 95% CI, 1.188 to 1.545; P < 0.001), St. George's Respiratory Questionnaire score (adjusted β = 1.075; 95% CI, 0.807 to 1.342; P < 0.001), 6-minute-walk distance (adjusted β = -1.993; 95% CI, -3.481 to -0.506; P < 0.001), and FEV1 change over time (adjusted β = -1.604; 95% CI, -2.691 to -0.516; P = 0.004), after adjustment for age, sex, race, body mass index, current smoking status, pack-years of smoking, and FEV1. The Peak Index was also associated with the BODE (body mass index, airflow obstruction, dyspnea, and exercise capacity) index and mortality (P < 0.001).Conclusions: The Peak Index is a spirometry metric that is associated with CT measures of lung disease, respiratory morbidity, lung function decline, and mortality.Clinical trial registered with www.clinicaltrials.gov (NCT00608764).

Centrilobular emphysema and coronary artery calcification: mediation analysis in the SPIROMICS cohort

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is associated with a two-to-five fold increase in the risk of coronary artery disease independent of shared risk factors. This association is hypothesized to be mediated by systemic inflammation but this link has not been established.

METHODS

We included 300 participants enrolled in the SPIROMICS cohort, 75 each of lifetime non-smokers, smokers without airflow obstruction, mild-moderate COPD, and severe-very severe COPD. We quantified emphysema and airway disease on computed tomography, characterized visual emphysema subtypes (centrilobular and paraseptal) and airway disease, and used the Weston visual score to quantify coronary artery calcification (CAC). We used the Sobel test to determine whether markers of systemic inflammation mediated a link between spirometric and radiographic features of COPD and CAC.

RESULTS

FEV1/FVC but not quantitative emphysema or airway wall thickening was associated with CAC (p = 0.036), after adjustment for demographics, diabetes mellitus, hypertension, statin use, and CT scanner type. To explain this discordance, we examined visual subtypes of emphysema and airway disease, and found that centrilobular emphysema but not paraseptal emphysema or bronchial thickening was independently associated with CAC (p = 0.019). MMP3, VCAM1, CXCL5 and CXCL9 mediated 8, 8, 7 and 16% of the association between FEV1/FVC and CAC, respectively. Similar biomarkers partially mediated the association between centrilobular emphysema and CAC.

CONCLUSIONS

The association between airflow obstruction and coronary calcification is driven primarily by the centrilobular subtype of emphysema, and is linked through bioactive molecules implicated in the pathogenesis of atherosclerosis.

TRIAL REGISTRATION

ClinicalTrials.gov: Identifier: NCT01969344 .

Airway fractal dimension predicts respiratory morbidity and mortality in COPD

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is characterized by airway remodeling. Characterization of airway changes on computed tomography has been challenging due to the complexity of the recurring branching patterns, and this can be better measured using fractal dimensions.

METHODS

We analyzed segmented airway trees of 8,135 participants enrolled in the COPDGene cohort. The fractal complexity of the segmented airway tree was measured by the Airway Fractal Dimension (AFD) using the Minkowski-Bougliand box-counting dimension. We examined associations between AFD and lung function and respiratory morbidity using multivariable regression analyses. We further estimated the extent of peribronchial emphysema (%) within 5 mm of the airway tree, as this is likely to affect AFD. We classified participants into 4 groups based on median AFD, percentage of peribronchial emphysema, and estimated survival.

RESULTS

AFD was significantly associated with forced expiratory volume in one second (FEV1; P < 0.001) and FEV1/forced vital capacity (FEV1/FVC; P < 0.001) after adjusting for age, race, sex, smoking status, pack-years of smoking, BMI, CT emphysema, air trapping, airway thickness, and CT scanner type. On multivariable analysis, AFD was also associated with respiratory quality of life and 6-minute walk distance, as well as exacerbations, lung function decline, and mortality on longitudinal follow-up. We identified a subset of participants with AFD below the median and peribronchial emphysema above the median who had worse survival compared with participants with high AFD and low peribronchial emphysema (adjusted hazards ratio [HR]: 2.72; 95% CI: 2.20-3.35; P < 0.001), a substantial number of whom were not identified by traditional spirometry severity grades.

CONCLUSION

Airway fractal dimension as a measure of airway branching complexity and remodeling in smokers is associated with respiratory morbidity and lung function change, offers prognostic information additional to traditional CT measures of airway wall thickness, and can be used to estimate mortality risk.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT00608764.

FUNDING

This study was supported by NIH K23 HL133438 (SPB) and the COPDGene study (NIH Grant Numbers R01 HL089897 and R01 HL089856). The COPDGene project is also supported by the COPD Foundation through contributions made to an Industry Advisory Board comprised of AstraZeneca, Boehringer Ingelheim, Novartis, Pfizer, Siemens, Sunovion and GlaxoSmithKline.

Signs of Gas Trapping in Normal Lung Density Regions in Smokers

RATIONALE

A substantial proportion of subjects without overt airflow obstruction have significant respiratory morbidity and structural abnormalities as visualized by computed tomography. Whether regions of the lung that appear normal using traditional computed tomography criteria have mild disease is not known.

OBJECTIVES

To identify subthreshold structural disease in normal-appearing lung regions in smokers.

METHODS

We analyzed 8,034 subjects with complete inspiratory and expiratory computed tomographic data participating in the COPDGene Study, including 103 lifetime nonsmokers. The ratio of the mean lung density at end expiration (E) to end inspiration (I) was calculated in lung regions with normal density (ND) by traditional thresholds for mild emphysema (-910 Hounsfield units) and gas trapping (-856 Hounsfield units) to derive the ND-E/I ratio. Multivariable regression analysis was used to measure the associations between ND-E/I, lung function, and respiratory morbidity.

MEASUREMENTS AND MAIN RESULTS

The ND-E/I ratio was greater in smokers than in nonsmokers, and it progressively increased from mild to severe chronic obstructive pulmonary disease severity. A proportion of 26.3% of smokers without airflow obstruction had ND-E/I greater than the 90th percentile of normal. ND-E/I was independently associated with FEV₁ (adjusted β = -0.020; 95% confidence interval [CI], -0.032 to -0.007; P = 0.001), St. George's Respiratory Questionnaire scores (adjusted β = 0.952; 95% CI, 0.529 to 1.374; P < 0.001), 6-minute-walk distance (adjusted β = -10.412; 95% CI, -12.267 to -8.556; P < 0.001), and body mass index, airflow obstruction, dyspnea, and exercise capacity index (adjusted β = 0.169; 95% CI, 0.148 to 0.190; P < 0.001), and also with FEV₁ change at follow-up (adjusted β = -3.013; 95% CI, -4.478 to -1.548; P = 0.001).

CONCLUSIONS

Subthreshold gas trapping representing mild small airway disease is prevalent in normal-appearing lung regions in smokers without airflow obstruction, and it is associated with respiratory morbidity. Clinical trial registered with www.clinicaltrials.gov (NCT00608764).

Computed Tomography Measure of Lung at Risk and Lung Function Decline in Chronic Obstructive Pulmonary Disease

RATIONALE

The rate of decline of lung function is greater than age-related change in a substantial proportion of patients with chronic obstructive pulmonary disease, even after smoking cessation. Regions of the lung adjacent to emphysematous areas are subject to abnormal stretch during respiration, and this biomechanical stress likely influences emphysema initiation and progression.

OBJECTIVES

To assess whether quantifying this penumbra of lung at risk would predict FEV₁ decline.

METHODS

We analyzed paired inspiratory-expiratory computed tomography images at baseline of 680 subjects participating in a large multicenter study (COPDGene) over approximately 5 years. By matching inspiratory and expiratory images voxel by voxel using image registration, we calculated the Jacobian determinant, a measure of local lung expansion and contraction with respiration. We measured the distance between each normal voxel to the nearest emphysematous voxel, and quantified the percentage of normal voxels within each millimeter distance from emphysematous voxels as mechanically affected lung (MAL). Multivariable regression analyses were performed to assess the relationship between the Jacobian determinant, MAL, and FEV₁ decline.

MEASUREMENTS AND MAIN RESULTS

The mean (SD) rate of decline in FEV₁ was 39.0 (58.6) ml/yr. There was a progressive decrease in the mean Jacobian determinant of both emphysematous and normal voxels with increasing disease stage (P < 0.001). On multivariable analyses, the mean Jacobian determinant of normal voxels within 2 mm of emphysematous voxels (MAL₂) was significantly associated with FEV₁ decline. In mild-moderate disease, for participants at or above the median MAL₂ (threshold, 36.9%), the mean decline in FEV₁ was 56.4 (68.0) ml/yr versus 43.2 (59.9) ml/yr for those below the median (P = 0.044).

CONCLUSIONS

Areas of normal-appearing lung are mechanically influenced by emphysematous areas and this lung at risk is associated with lung function decline. Clinical trial registered with www.clinicaltrials.gov (NCT00608764).

Biomechanical CT metrics are associated with patient outcomes in COPD

BACKGROUND

Traditional metrics of lung disease such as those derived from spirometry and static single-volume CT images are used to explain respiratory morbidity in patients with COPD, but are insufficient. We hypothesised that the mean Jacobian determinant, a measure of local lung expansion and contraction with respiration, would contribute independently to clinically relevant functional outcomes.

METHODS

We applied image registration techniques to paired inspiratory-expiratory CT scans and derived the Jacobian determinant of the deformation field between the two lung volumes to map local volume change with respiration. We analysed 490 participants with COPD with multivariable regression models to assess strengths of association between traditional CT metrics of disease and the Jacobian determinant with respiratory morbidity including dyspnoea (modified Medical Research Council), St Georges Respiratory Questionnaire (SGRQ) score, 6-min walk distance (6MWD) and the Body Mass Index, Airflow Obstruction, Dyspnoea and Exercise Capacity (BODE) index, as well as all-cause mortality.

RESULTS

The Jacobian determinant was significantly associated with SGRQ (adjusted regression coefficient β=-11.75,95% CI -21.6 to -1.7; p=0.020), and with 6MWD (β=321.15, 95% CI 134.1 to 508.1; p<0.001), independent of age, sex, race, body mass index, FEV₁, smoking pack-years, CT emphysema, CT gas trapping, airway wall thickness and CT scanner type. The mean Jacobian determinant was also independently associated with the BODE index (β=-0.41, 95% CI -0.80 to -0.02; p=0.039) and mortality on follow-up (adjusted HR=4.26, 95% CI 0.93 to 19.23; p=0.064).

CONCLUSIONS

Biomechanical metrics representing local lung expansion and contraction improve prediction of respiratory morbidity and mortality and offer additional prognostic information beyond traditional measures of lung function and static single-volume CT metrics.

TRIAL REGISTRATION NUMBER

NCT00608764; Post-results.

CT-derived Biomechanical Metrics Improve Agreement Between Spirometry and Emphysema

RATIONALE AND OBJECTIVES

Many patients with chronic obstructive pulmonary disease (COPD) have marked discordance between forced expiratory volume in 1 second (FEV1) and degree of emphysema on computed tomography (CT). Biomechanical differences between these patients have not been studied. We aimed to identify reasons for the discordance between CT and spirometry in some patients with COPD.

MATERIALS AND METHODS

Subjects with Global initiative for chronic Obstructive Lung Disease stages I-IV from a large multicenter study (The Genetic Epidemiology of COPD) were arranged by percentiles of %predicted FEV1 and emphysema on CT. Three categories were created using differences in percentiles: Catspir with predominant airflow obstruction/minimal emphysema, CatCT with predominant emphysema/minimal airflow obstruction, and Catmatched with matched FEV1 and emphysema. Image registration was used to derive Jacobian determinants, a measure of lung elasticity, anisotropy, and strain tensors, to assess biomechanical differences between groups. Regression models were created with the previously mentioned categories as outcome variable, adjusting for demographics, scanner type, quantitative CT-derived emphysema, gas trapping, and airway thickness (model 1), and after adding biomechanical CT metrics (model 2).

RESULTS

Jacobian determinants, anisotropy, and strain tensors were strongly associated with FEV1. With Catmatched as control, model 2 predicted Catspir and CatCT better than model 1 (Akaike information criterion 255.8 vs. 320.8). In addition to demographics, the strongest independent predictors of FEV1 were Jacobian mean (β = 1.60,95%confidence intervals [CI] = 1.16 to 1.98; P < 0.001), coefficient of variation (CV) of Jacobian (β = 1.45,95%CI = 0.86 to 2.03; P < 0.001), and CV of strain (β = 1.82,95%CI = 0.68 to 2.95; P = 0.001). CVs of Jacobian and strain are both potential markers of biomechanical lung heterogeneity.

CONCLUSIONS

CT-derived measures of lung mechanics improve the link between quantitative CT and spirometry, offering the potential for new insights into the linkage between regional parenchymal destruction and global decrement in lung function in patients with COPD.

Computed Tomography Image Matching in Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD), characterized by progressive airflow obstruction due to the combined effects of emphysema and small airways disease, is associated with high morbidity and mortality. The complex link between emphysema and airways disease is associated with significant heterogeneity in clinical presentation. Spirometry is the current gold standard for diagnosis and stratification of the severity of airflow obstruction in COPD. Although spirometry is simple to use, it does not enable the separation of emphysema from airways disease. Computed tomography (CT), on the other hand, provides the anatomic localization of disease and has been increasingly used to phenotype COPD. The majority of current CT measures are extracted from a single-volume CT scan and although useful to characterize emphysema and airways disease, they do not link structural and functional abnormalities. Alternatively, CT image matching combines information from both inspiratory and expiratory CT scans, thus enabling determination of functional changes such as regional ventilation and mechanical properties of the lung. In this review, we discuss recent applications of CT image matching that provide clinically meaningful information beyond spirometry and single-volume CT scan measures.

Registration-based lung mechanical analysis of chronic obstructive pulmonary disease (COPD) using a supervised machine learning framework

RATIONALE AND OBJECTIVES

This study evaluated the performance of computed tomography (CT)-derived biomechanical based features of lung function and the presence and severity of chronic obstructive pulmonary disease (COPD). It performed well when compared to CT-derived density and textural features of lung function and the presence and severity of COPD.

MATERIALS AND METHODS

A total of 162 subjects (Global Initiative for Chronic Obstructive Lung Disease [GOLD] stages 0-4 and nonsmokers) subjects with CT scan performed at total lung capacity or expiration to functional residual capacity were evaluated. CT-derived biomechanical, density, and textural feature sets were compared to forced expiratory volume in 1 second (FEV1)%, FEV1/forced vital capacity, and total St. George's respiratory questionnaire scores. The ability of these feature sets to assess the presence and severity of COPD was also evaluated. Optimal features are selected by linear forward feature selection and the classification is done using k nearest neighbor learning algorithm.

RESULTS

The proposed biomechanical features showed good correlations with the pulmonary function tests and health status metrics. In COPD versus non-COPD classification, biomechanical feature set achieved an area under the curve (AUC) of 0.85 performing well in comparison to density (AUC = 0.83) and texture (AUC = 0.89) feature sets. Classifying the subjects into the severity of GOLD stage using biomechanical features (AUC = 0.81) performed better than the density- and texture-based feature sets, AUC = 0.76 and 0.73, respectively. The biomechanical features performed better alone than in combination with the other two feature sets.

CONCLUSION

This study shows the effectiveness of CT-derived biomechanical measures in the assessment of airflow obstruction and quality of life in subjects with COPD. CT-derived biomechanical features performed well in assessing the presence and severity of COPD.