Proteomic Biomarkers of Quantitative Interstitial Abnormalities in COPDGene and CARDIA Lung Study.

Rationale: Quantitative interstitial abnormalities (QIAs) are early measures of lung injury automatically detected on chest computed tomography scans. QIAs are associated with impaired respiratory health and share features with advanced lung diseases, but their biological underpinnings are not well understood. Objectives: To identify novel protein biomarkers of QIAs using high-throughput plasma proteomic panels within two multicenter cohorts. Methods: We measured the plasma proteomics of 4,383 participants in an older, ever-smoker cohort (COPDGene [Genetic Epidemiology of Chronic Obstructive Pulmonary Disease]) and 2,925 participants in a younger population cohort (CARDIA [Coronary Artery Disease Risk in Young Adults]) using the SomaLogic SomaScan assays. We measured QIAs using a local density histogram method. We assessed the associations between proteomic biomarker concentrations and QIAs using multivariable linear regression models adjusted for age, sex, body mass index, smoking status, and study center (Benjamini-Hochberg false discovery rate-corrected P ⩽ 0.05). Measurements and Main Results: In total, 852 proteins were significantly associated with QIAs in COPDGene and 185 in CARDIA. Of the 144 proteins that overlapped between COPDGene and CARDIA, all but one shared directionalities and magnitudes. These proteins were enriched for 49 Gene Ontology pathways, including biological processes in inflammatory response, cell adhesion, immune response, ERK1/2 regulation, and signaling; cellular components in extracellular regions; and molecular functions including calcium ion and heparin binding. Conclusions: We identified the proteomic biomarkers of QIAs in an older, smoking population with a higher prevalence of pulmonary disease and in a younger, healthier community cohort. These proteomics features may be markers of early precursors of advanced lung diseases.

Preacinar Arterial Dilation Mediates Outcomes of Quantitative Interstitial Abnormalities in the COPDGene Study.

Rationale: Quantitative interstitial abnormalities (QIAs) are a computed tomography (CT) measure of early parenchymal lung disease associated with worse clinical outcomes, including exercise capacity and symptoms. The presence of pulmonary vasculopathy in QIAs and its role in the QIA-outcome relationship is unknown. Objectives: To quantify radiographic pulmonary vasculopathy in QIAs and determine whether this vasculopathy mediates the QIA-outcome relationship. Methods: Ever-smokers with QIAs, outcomes, and pulmonary vascular mediator data were identified from the Genetic Epidemiology of COPD (COPDGene) study cohort. CT-based vascular mediators were right ventricle-to-left ventricle ratio, pulmonary artery-to-aorta ratio, and preacinar intraparenchymal arterial dilation (pulmonary artery volume, 5-20 mm2 in cross-sectional area, normalized to total arterial volume). Outcomes were 6-minute walk distance and a modified Medical Council Research Council Dyspnea Scale score of 2 or higher. Adjusted causal mediation analyses were used to determine whether the pulmonary vasculature mediated the QIA effect on outcomes. Associations of preacinar arterial dilation with select plasma biomarkers of pulmonary vascular dysfunction were examined. Measurements and Main Results: Among 8,200 participants, QIA burden correlated positively with vascular damage measures, including preacinar arterial dilation. Preacinar arterial dilation mediated 79.6% of the detrimental impact of QIA on 6-minute walk distance (56.2-100%; P < 0.001). Pulmonary artery-to-aorta ratio was a weak mediator, and right ventricle-to-left ventricle ratio was a suppressor. Similar results were observed in the relationship between QIA and modified Medical Council Research Council dyspnea score. Preacinar arterial dilation correlated with increased pulmonary vascular dysfunction biomarker levels, including angiopoietin-2 and N-terminal brain natriuretic peptide. Conclusions: Parenchymal QIAs deleteriously impact outcomes primarily through pulmonary vasculopathy. Preacinar arterial dilation may be a novel marker of pulmonary vasculopathy in QIAs.

Association of Acute Respiratory Disease Events with Quantitative Interstitial Abnormality Progression at CT in Individuals with a History of Smoking.

Background Acute respiratory disease (ARD) events are often thought to be airway-disease related, but some may be related to quantitative interstitial abnormalities (QIAs), which are subtle parenchymal abnormalities on CT scans associated with morbidity and mortality in individuals with a smoking history. Purpose To determine whether QIA progression at CT is associated with ARD and severe ARD events in individuals with a history of smoking. Materials and Methods This secondary analysis of a prospective study included individuals with a 10 pack-years or greater smoking history recruited from multiple centers between November 2007 and July 2017. QIA progression was assessed between baseline (visit 1) and 5-year follow-up (visit 2) chest CT scans. Episodes of ARD were defined as increased cough or dyspnea lasting 48 hours and requiring antibiotics or corticosteroids, whereas severe ARD episodes were those requiring an emergency room visit or hospitalization. Episodes were recorded via questionnaires completed every 3 to 6 months. Multivariable logistic regression and zero-inflated negative binomial regression models adjusted for comorbidities (eg, emphysema, small airway disease) were used to assess the association between QIA progression and episodes between visits 1 and 2 (intercurrent) and after visit 2 (subsequent). Results A total of 3972 participants (mean age at baseline, 60.7 years ± 8.6 [SD]; 2120 [53.4%] women) were included. Annual percentage QIA progression was associated with increased odds of one or more intercurrent (odds ratio [OR] = 1.29 [95% CI: 1.06, 1.56]; P = .01) and subsequent (OR = 1.26 [95% CI: 1.05, 1.52]; P = .02) severe ARD events. Participants in the highest quartile of QIA progression (≥1.2%) had more frequent intercurrent ARD (incidence rate ratio [IRR] = 1.46 [95% CI: 1.14, 1.86]; P = .003) and severe ARD (IRR = 1.79 [95% CI: 1.18, 2.73]; P = .006) events than those in the lowest quartile (≤-1.7%). Conclusion QIA progression was independently associated with higher odds of severe ARD events during and after radiographic progression, with higher frequency of intercurrent severe events in those with faster progression. Clinical trial registration no. NCT00608764 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Little in this issue.

Quantification of Emphysema Progression at CT Using Simultaneous Volume, Noise, and Bias Lung Density Correction.

Background CT attenuation is affected by lung volume, dosage, and scanner bias, leading to inaccurate emphysema progression measurements in multicenter studies. Purpose To develop and validate a method that simultaneously corrects volume, noise, and interscanner bias for lung density change estimation in emphysema progression at CT in a longitudinal multicenter study. Materials and Methods In this secondary analysis of the prospective Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study, lung function data were obtained from participants who completed baseline and 5-year follow-up visits from January 2008 to August 2017. CT emphysema progression was measured with volume-adjusted lung density (VALD) and compared with the joint volume-noise-bias-adjusted lung density (VNB-ALD). Reproducibility was studied under change of dosage protocol and scanner model with repeated acquisitions. Emphysema progression was visually scored in 102 randomly selected participants. A stratified analysis of clinical characteristics was performed that considered groups based on their combined lung density change measured by VALD and VNB-ALD. Results A total of 4954 COPDGene participants (mean age, 60 years ± 9 [SD]; 2511 male, 2443 female) were analyzed (1329 with repeated reduced-dose acquisition in the follow-up visit). Mean repeatability coefficients were 30 g/L ± 0.46 for VALD and 14 g/L ± 0.34 for VNB-ALD. VALD measurements showed no evidence of differences between nonprogressors and progressors (mean, -5.5 g/L ± 9.5 vs -8.6 g/L ± 9.6; P = .11), while VNB-ALD agreed with visual readings and showed a difference (mean, -0.67 g/L ± 4.8 vs -4.2 g/L ± 5.5; P < .001). Analysis of progression showed that VNB-ALD progressors had a greater decline in forced expiratory volume in 1 second (-42 mL per year vs -32 mL per year; Tukey-adjusted P = .002). Conclusion Simultaneously correcting volume, noise, and interscanner bias for lung density change estimation in emphysema progression at CT improved repeatability analyses and agreed with visual readings. It distinguished between progressors and nonprogressors and was associated with a greater decline in lung function metrics. Clinical trial registration no. NCT00608764 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Goo in this issue.

Deep Learning Assessment of Progression of Emphysema and Fibrotic Interstitial Lung Abnormality.

Rationale: Although studies have evaluated emphysema and fibrotic interstitial lung abnormality individually, less is known about their combined progression. Objectives: To define clinically meaningful progression of fibrotic interstitial lung abnormality in smokers without interstitial lung disease and evaluate the effects of fibrosis and emphysema progression on mortality. Methods: Emphysema and pulmonary fibrosis were assessed on the basis of baseline and 5-year follow-up computed tomography scans of 4,450 smokers in the COPDGene Study using deep learning algorithms. Emphysema was classified as absent, trace, mild, moderate, confluent, or advanced destructive. Fibrosis was expressed as a percentage of lung volume. Emphysema progression was defined as an increase by at least one grade. A hybrid distribution and anchor-based method was used to determine the minimal clinically important difference in fibrosis. The relationship between progression and mortality was evaluated using multivariable shared frailty models using an age timescale. Measurements and Main Results: The minimal clinically important difference for fibrosis was 0.58%. On the basis of this threshold, 2,822 (63%) had progression of neither emphysema nor fibrosis, 841 (19%) had emphysema progression alone, 512 (12%) had fibrosis progression alone, and 275 (6.2%) had progression of both. Compared with nonprogressors, hazard ratios for mortality were 1.42 (95% confidence interval, 1.11-1.82) in emphysema progressors, 1.49 (1.14-1.94) in fibrosis progressors, and 2.18 (1.58-3.02) in those with progression of both emphysema and fibrosis. Conclusions: In smokers without known interstitial lung disease, small changes in fibrosis may be clinically significant, and combined progression of emphysema and fibrosis is associated with increased mortality.

Suspected Interstitial Lung Disease in COPDGene Study.

Rationale: Although interstitial lung abnormalities (ILA), specific patterns of incidentally-detected abnormal density on computed tomography, have been associated with abnormal lung function and increased mortality, it is unclear if a subset with incidental interstitial lung disease (ILD) accounts for these adverse consequences. Objectives: To define the prevalence and risk factors of suspected ILD and assess outcomes. Methods: Suspected ILD was evaluated in the COPDGene (Chronic Obstructive Pulmonary Disease Genetic Epidemiology) study, defined as ILA and at least one additional criterion: definite fibrosis on computed tomography, FVC less than 80% predicted, or DLCO less than 70% predicted. Multivariable linear, longitudinal, and Cox proportional hazards regression models were used to assess associations with St. George's Respiratory Questionnaire, 6-minute-walk test, supplemental oxygen use, respiratory exacerbations, and mortality. Measurements and Main Results: Of 4,361 participants with available data, 239 (5%) had evidence for suspected ILD, whereas 204 (5%) had ILA without suspected ILD. In multivariable analyses, suspected ILD was associated with increased St. George's Respiratory Questionnaire score (mean difference [MD], 3.9 points; 95% confidence interval [CI], 0.6-7.1; P = 0.02), reduced 6-minute-walk test (MD, -35 m; 95% CI, -56 m to -13 m; P = 0.002), greater supplemental oxygen use (odds ratio [OR], 2.3; 95% CI, 1.1-5.1; P = 0.03) and severe respiratory exacerbations (OR, 2.9; 95% CI, 1.1-7.5; P = 0.03), and higher mortality (hazard ratio, 2.4; 95% CI, 1.2-4.6; P = 0.01) compared with ILA without suspected ILD. Risk factors associated with suspected ILD included self-identified Black race (OR, 2.0; 95% CI, 1.1-3.3; P = 0.01) and pack-years smoking history (OR, 1.2; 95% CI, 1.1-1.3; P = 0.0005). Conclusions: Suspected ILD is present in half of those with ILA in COPDGene and is associated with exercise decrements and increased symptoms, supplemental oxygen use, severe respiratory exacerbations, and mortality.

Rheumatoid arthritis, quantitative parenchymal lung features, and mortality among smokers.

OBJECTIVES: There have been limited investigations of the prevalence and mortality impact of quantitative computed tomography (QCT) parenchymal lung features in rheumatoid arthritis (RA). We examined the cross-sectional prevalence and mortality associations of QCT features, comparing RA and non-RA participants. METHODS: We identified participants with and without RA in COPDGene, a multicentre cohort study of current or former smokers. Using a k-nearest neighbor quantifier, high resolution CT chest scans were scored for percentage of normal lung, interstitial changes, and emphysema. We examined associations between QCT features and RA using multivariable linear regression. After dichotomizing participants at the 75th percentile for each QCT feature among non-RA participants, we investigated mortality associations by RA/non-RA status and quartile 4 vs quartiles 1-3 of QCT features using Cox regression. We assessed for statistical interactions between RA and QCT features. RESULTS: We identified 82 RA cases and 8820 non-RA comparators. In multivariable linear regression, RA was associated with higher percentage of interstitial changes (ß = 1.7 ± 0.5, p= 0.0008) but not emphysema (ß = 1.3 ± 1.7, p= 0.44). Participants with RA and >75th percentile of emphysema had significantly higher mortality than non-RA participants (HR 5.86, 95%CI 3.75-9.13) as well as RA participants (HR 5.56, 95%CI 2.71-11.38) with ≤75th percentile of emphysema. There were statistical interactions between RA and emphysema for mortality (multiplicative p= 0.014; attributable proportion 0.53, 95%CI 0.30-0.70). CONCLUSIONS: Using machine learning-derived QCT data in a cohort of smokers, RA was associated with higher percentage of interstitial changes. The combination of RA and emphysema conferred >5-fold higher mortality.

Bronchial epithelial gene expression and interstitial lung abnormalities.

INTRODUCTION: Interstitial lung abnormalities (ILA) often represent early fibrotic changes that can portend a progressive fibrotic phenotype. In particular, the fibrotic subtype of ILA is associated with increased mortality and rapid decline in lung function. Understanding the differential gene expression that occurs in the lungs of participants with fibrotic ILA may provide insight into development of a useful biomarker for early detection and therapeutic targets for progressive pulmonary fibrosis. METHODS: Measures of ILA and gene expression data were available in 213 participants in the Detection of Early Lung Cancer Among Military Personnel (DECAMP1 and DECAMP2) cohorts. ILA was defined using Fleischner Society guidelines and determined by sequential reading of computed tomography (CT) scans. Primary analysis focused on comparing gene expression in ILA with usual interstitial pneumonia (UIP) pattern with those with no ILA. RESULTS: ILA was present in 51 (24%) participants, of which 16 (7%) were subtyped as ILA with a UIP pattern. One gene, pro platelet basic protein (PPBP) and seventeen pathways (e.g. TNF-α signalling) were significantly differentially expressed between those with a probable or definite UIP pattern of ILA compared to those without ILA. 16 of these 17 pathways, but no individual gene, met significance when comparing those with ILA to those without ILA. CONCLUSION: Our study demonstrates that abnormal inflammatory processes are apparent in the bronchial airway gene expression profiles of smokers with and without lung cancer with ILA. Future studies with larger and more diverse populations will be needed to confirm these findings.

Plasma metabolomics and quantitative interstitial abnormalities in ever-smokers.

BACKGROUND: Quantitative interstitial abnormalities (QIA) are an automated computed tomography (CT) finding of early parenchymal lung disease, associated with worse lung function, reduced exercise capacity, increased respiratory symptoms, and death. The metabolomic perturbations associated with QIA are not well known. We sought to identify plasma metabolites associated with QIA in smokers. We also sought to identify shared and differentiating metabolomics features between QIA and emphysema, another smoking-related advanced radiographic abnormality. METHODS: In 928 former and current smokers in the Genetic Epidemiology of COPD cohort, we measured QIA and emphysema using an automated local density histogram method and generated metabolite profiles from plasma samples using liquid chromatography-mass spectrometry (Metabolon). We assessed the associations between metabolite levels and QIA using multivariable linear regression models adjusted for age, sex, body mass index, smoking status, pack-years, and inhaled corticosteroid use, at a Benjamini-Hochberg False Discovery Rate p-value of ≤ 0.05. Using multinomial regression models adjusted for these covariates, we assessed the associations between metabolite levels and the following CT phenotypes: QIA-predominant, emphysema-predominant, combined-predominant, and neither- predominant. Pathway enrichment analyses were performed using MetaboAnalyst. RESULTS: We found 85 metabolites significantly associated with QIA, with overrepresentation of the nicotinate and nicotinamide, histidine, starch and sucrose, pyrimidine, phosphatidylcholine, lysophospholipid, and sphingomyelin pathways. These included metabolites involved in inflammation and immune response, extracellular matrix remodeling, surfactant, and muscle cachexia. There were 75 metabolites significantly different between QIA-predominant and emphysema-predominant phenotypes, with overrepresentation of the phosphatidylethanolamine, nicotinate and nicotinamide, aminoacyl-tRNA, arginine, proline, alanine, aspartate, and glutamate pathways. CONCLUSIONS: Metabolomic correlates may lend insight to the biologic perturbations and pathways that underlie clinically meaningful quantitative CT measurements like QIA in smokers.

CT imaging determinants of persistent hypoxemia in acute intermediate-risk pulmonary embolism.

The factors associated with persistent hypoxemia after pulmonary embolus (PE) are not well understood. Predicting the need for oxygen post discharge at the time of diagnosis using available CT imaging will enable better discharge planning. To examine the relationship between CT derived imaging markers (automated computation of arterial small vessel fraction, pulmonary artery diameter to aortic diameter ratio (PA:A), right to left ventricular diameter ratio (RV:LV) and new oxygen requirement at the time of discharge in patients diagnosed with acute intermediate-risk PE. CT measurements were obtained in a retrospective cohort of patients with acute-intermediate risk PE admitted to Brigham and Women's Hospital between 2009 and 2017. Twenty one patients without a history of lung disease requiring home oxygen and 682 patients without discharge oxygen requirements were identified. There was an increased median PA:A ratio (0.98 vs. 0.92, p = 0.02) and arterial small vessel fraction (0.32 vs. 0.39, p = 0.001) in the oxygen-requiring group], but no difference in the median RV:LV ratio (1.20 vs. 1.20, p = 0.74). Being in the upper quantile for the arterial small vessel fraction was associated with decreased odds of oxygen requirement (OR 0.30 [0.10-0.78], p = 0.02). Loss of arterial small vessel volume as measured by arterial small vessel fraction and an increase in the PA:A ratio at the time of diagnosis were associated with the presence of persistent hypoxemia on discharge in acute intermediate-risk PE.

Mucus Plugs Persist in Asthma, and Changes in Mucus Plugs Associate with Changes in Airflow over Time.

Rationale: Cross-sectional analysis of mucus plugs in computed tomography (CT) lung scans in the Severe Asthma Research Program (SARP)-3 showed a high mucus plug phenotype. Objectives: To determine if mucus plugs are a persistent asthma phenotype and if changes in mucus plugs over time associate with changes in lung function. Methods: In a longitudinal analysis of baseline and Year 3 CT lung scans in SARP-3 participants, radiologists generated mucus plug scores to assess mucus plug persistence over time. Changes in mucus plug score were analyzed in relation to changes in lung function and CT air trapping measures. Measurements and Main Results: In 164 participants, the mean (range) mucus plug score was similar at baseline and Year 3 (3.4 [0-20] vs. 3.8 [0-20]). Participants and bronchopulmonary segments with a baseline plug were more likely to have plugs at Year 3 than those without baseline plugs (risk ratio, 2.8; 95% confidence interval [CI], 2.0-4.1; P < 0.001; and risk ratio, 5.0; 95% CI, 4.5-5.6; P < 0.001, respectively). The change in mucus plug score from baseline to Year 3 was significantly negatively correlated with change in FEV1% predicted (rp = -0.35; P < 0.001) and with changes in CT air trapping measures (all P values < 0.05). Conclusions: Mucus plugs identify a persistent asthma phenotype, and susceptibility to mucus plugs occurs at the subject and the bronchopulmonary segment level. The association between change in mucus plug score and change in airflow over time supports a causal role for mucus plugs in mechanisms of airflow obstruction in asthma.

Emphysema Progression at CT by Deep Learning Predicts Functional Impairment and Mortality: Results from the COPDGene Study.

Background Visual assessment remains the standard for evaluating emphysema at CT; however, it is time consuming, is subjective, requires training, and is affected by variability that may limit sensitivity to longitudinal change. Purpose To evaluate the clinical and imaging significance of increasing emphysema severity as graded by a deep learning algorithm on sequential CT scans in cigarette smokers. Materials and Methods A secondary analysis of the prospective Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study participants was performed and included baseline and 5-year follow-up CT scans from 2007 to 2017. Emphysema was classified automatically according to the Fleischner emphysema grading system at baseline and 5-year follow-up using a deep learning model. Baseline and change in clinical and imaging parameters at 5-year follow-up were compared in participants whose emphysema progressed versus those who did not. Kaplan-Meier analysis and multivariable Cox regression were used to assess the relationship between emphysema score progression and mortality. Results A total of 5056 participants (mean age, 60 years ± 9 [SD]; 2566 men) were evaluated. At 5-year follow-up, 1293 of the 5056 participants (26%) had emphysema progression according to the Fleischner grading system. This group demonstrated progressive airflow obstruction (forced expiratory volume in 1 second [percent predicted]: -3.4 vs -1.8), a greater decline in 6-minute walk distance (-177 m vs -124 m), and greater progression in quantitative emphysema extent (adjusted lung density: -1.4 g/L vs 0.5 g/L; percentage of lung voxels with CT attenuation less than -950 HU: 0.6 vs 0.2) than those with nonprogressive emphysema (P < .001 for each). Multivariable Cox regression analysis showed a higher mortality rate in the group with emphysema progression, with an estimated hazard ratio of 1.5 (95% CI: 1.2, 1.8; P < .001). Conclusion An increase in Fleischner emphysema grade on sequential CT scans using an automated deep learning algorithm was associated with increased functional impairment and increased risk of mortality. ClinicalTrials.gov registration no. NCT00608764 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Grenier in this issue.

Interstitial lung abnormalities are associated with decreased mean telomere length.

BACKGROUND: Interstitial lung abnormalities (ILA) share many features with idiopathic pulmonary fibrosis; however, it is not known if ILA are associated with decreased mean telomere length (MTL). METHODS: Telomere length was measured with quantitative PCR in the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) and Age Gene/Environment Susceptibility Reykjavik (AGES-Reykjavik) cohorts and Southern blot analysis was used in the Framingham Heart Study (FHS). Logistic and linear regression were used to assess the association between ILA and MTL; Cox proportional hazards models were used to assess the association between MTL and mortality. RESULTS: In all three cohorts, ILA were associated with decreased MTL. In the COPDGene and AGES-Reykjavik cohorts, after adjustment there was greater than twofold increase in the odds of ILA when comparing the shortest quartile of telomere length to the longest quartile (OR 2.2, 95% CI 1.5-3.4, p=0.0001, and OR 2.6, 95% CI 1.4-4.9, p=0.003, respectively). In the FHS, those with ILA had shorter telomeres than those without ILA (-767 bp, 95% CI 76-1584 bp, p=0.03). Although decreased MTL was associated with chronic obstructive pulmonary disease (OR 1.3, 95% CI 1.1-1.6, p=0.01) in COPDGene, the effect estimate was less than that noted with ILA. There was no consistent association between MTL and risk of death when comparing the shortest quartile of telomere length in COPDGene and AGES-Reykjavik (HR 0.82, 95% CI 0.4-1.7, p=0.6, and HR 1.2, 95% CI 0.6-2.2, p=0.5, respectively). CONCLUSION: ILA are associated with decreased MTL.

Relationship between Emphysema Progression at CT and Mortality in Ever-Smokers: Results from the COPDGene and ECLIPSE Cohorts.

Background The relationship between emphysema progression and long-term outcomes is unclear. Purpose To determine the relationship between emphysema progression at CT and mortality among participants with emphysema. Materials and Methods In a secondary analysis of two prospective observational studies, COPDGene (clinicaltrials.gov, NCT00608764) and Evaluation of Chronic Obstructive Pulmonary Disease Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE; clinicaltrials.gov, NCT00292552), emphysema was measured at CT at two points by using the volume-adjusted lung density at the 15th percentile of the lung density histogram (hereafter, lung density perc15) method. The association between emphysema progression rate and all-cause mortality was analyzed by using Cox regression adjusted for ethnicity, sex, baseline age, pack-years, and lung density, baseline and change in smoking status, forced expiratory volume in 1 second, and 6-minute walk distance. In COPDGene, respiratory mortality was analyzed by using the Fine and Gray method. Results A total of 5143 participants (2613 men [51%]; mean age, 60 years ± 9 [standard deviation]) in COPDGene and 1549 participants (973 men [63%]; mean age, 62 years ± 8) in ECLIPSE were evaluated, of which 2097 (40.8%) and 1179 (76.1%) had emphysema, respectively. Baseline imaging was performed between January 2008 and December 2010 for COPDGene and January 2006 and August 2007 for ECLIPSE. Follow-up imaging was performed after 5.5 years ± 0.6 in COPDGene and 3.0 years ± 0.2 in ECLIPSE, and mortality was assessed over the ensuing 5 years in both. For every 1 g/L per year faster rate of decline in lung density perc15, all-cause mortality increased by 8% in COPDGene (hazard ratio [HR], 1.08; 95% CI: 1.01, 1.16; P = .03) and 6% in ECLIPSE (HR, 1.06; 95% CI: 1.00, 1.13; P = .045). In COPDGene, respiratory mortality increased by 22% (HR, 1.22; 95% CI: 1.13, 1.31; P < .001) for the same increase in the rate of change in lung density perc15. Conclusion In ever-smokers with emphysema, emphysema progression at CT was associated with increased all-cause and respiratory mortality. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Lee and Park in this issue.

Smaller Left Ventricle Size at Noncontrast CT Is Associated with Lower Mortality in COPDGene Participants.

Background Smokers with chronic obstructive pulmonary disease (COPD) have smaller left ventricles (LVs) due to reduced preload. Skeletal muscle wasting is also common in COPD, but less is known about its contribution to LV size. Purpose To explore the relationships between CT metrics of emphysema, venous vascular volume, and sarcopenia with the LV epicardial volume (LVEV) (myocardium and chamber) estimated from chest CT images in participants with COPD and then to determine the clinical relevance of the LVEV in multivariable models, including sex and anthropomorphic metrics. Materials and Methods The COPDGene study (ClinicalTrials.gov identifier: NCT00608764) is an ongoing prospective longitudinal observational investigation that began in 2006. LVEV, distal pulmonary venous blood volume for vessels smaller than 5 mm2 in cross section (BV5), CT emphysema, and pectoralis muscle area were retrospectively extracted from 3318 nongated, unenhanced COPDGene CT scans. Multivariable linear and Cox regression models were used to explore the association between emphysema, venous BV5, pectoralis muscle area, and LVEV as well as the association of LVEV with health status using the St George's Respiratory Questionnaire, 6-minute walk distance, and all-cause mortality. Results The median age of the cohort was 64 years (interquartile range, 57-70 years). Of the 2423 participants, 1806 were men and 617 were African American. The median LVEV between Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1 and GOLD 4 COPD was reduced by 13.9% in women and 17.7% in men (P < .001 for both). In fully adjusted models, higher emphysema percentage (ß = -4.2; 95% confidence interval [CI]: -5.0, -3.4; P < .001), venous BV5 (ß = 7.0; 95% CI: 5.7, 8.2; P < .001), and pectoralis muscle area (ß = 2.7; 95% CI: 1.2, 4.1; P < .001) were independently associated with reduced LVEV. Reductions in LVEV were associated with improved health status (ß = 0.3; 95% CI: 0.1, 0.4) and 6-minute walk distance (ß = -12.2; 95% CI: -15.2, -9.3). These effects were greater in women than in men. The effect of reduced LVEV on mortality (hazard ratio: 1.07; 95% CI: 1.05, 1.09) did not vary by sex. Conclusion In women more than men with chronic obstructive pulmonary disease, a reduction in the estimated left ventricle epicardial volume correlated with a loss of pulmonary venous vasculature, greater pectoralis muscle sarcopenia, and lower all-cause mortality. © RSNA, 2020 Online supplemental material is available for this article.

Arterial Vascular Pruning, Right Ventricular Size, and Clinical Outcomes in Chronic Obstructive Pulmonary Disease. A Longitudinal Observational Study.

Rationale: Cor pulmonale (right ventricular [RV] dilation) and cor pulmonale parvus (RV shrinkage) are both described in chronic obstructive pulmonary disease (COPD). The identification of emphysema as a shared risk factor suggests that additional disease characterization is needed to understand these widely divergent cardiac processes.Objectives: To explore the relationship between computed tomography measures of emphysema and distal pulmonary arterial morphology with RV volume, and their association with exercise capacity and mortality in ever-smokers with COPD enrolled in the COPDGene Study.Methods: Epicardial (myocardium and chamber) RV volume (RVEV), distal pulmonary arterial blood vessel volume (arterial BV5: vessels <5 mm2 in cross-section), and objective measures of emphysema were extracted from 3,506 COPDGene computed tomography scans. Multivariable linear and Cox regression models and the log-rank test were used to explore the association between emphysema, arterial BV5, and RVEV with exercise capacity (6-min-walk distance) and all-cause mortality.Measurements and Main Results: The RVEV was approximately 10% smaller in Global Initiative for Chronic Obstructive Lung Disease stage 4 versus stage 1 COPD (P < 0.0001). In multivariable modeling, a 10-ml decrease in arterial BV5 (pruning) was associated with a 1-ml increase in RVEV. For a given amount of emphysema, relative preservation of the arterial BV5 was associated with a smaller RVEV. An increased RVEV was associated with reduced 6-minute-walk distance and in those with arterial pruning an increased mortality.Conclusions: Pulmonary arterial pruning is associated with clinically significant increases in RV volume in smokers with COPD and is related to exercise capacity and mortality in COPD.Clinical trial registered with www.clinicaltrials.gov (NCT00608764).

Pulmonary vascular density: comparison of findings on computed tomography imaging with histology.

BACKGROUND: Exposure to cigarette smoke has been shown to lead to vascular remodelling. Computed tomography (CT) imaging measures of vascular pruning have been associated with pulmonary vascular disease, an important morbidity associated with smoking. In this study we compare CT-based measures of distal vessel loss to histological vascular and parenchymal changes. METHODS: A retrospective review of 80 patients who had undergone lung resection identified patients with imaging appropriate for three-dimensional (3D) vascular reconstruction (n=18) and a second group for two-dimensional (2D) analysis (n=19). Measurements of the volume of the small vessels (3D) and the cross-sectional area of the small vessels (<5 mm2 cross-section) were computed. Histological measures of cross-sectional area of the vasculature and loss of alveoli septa were obtained for all subjects. RESULTS: The 2D cross-sectional area of the vasculature on CT imaging was associated with the histological vascular cross-sectional area (r=0.69; p=0.001). The arterial small vessel volume assessed by CT correlated with the histological vascular cross-sectional area (r=0.50; p=0.04), a relationship that persisted even when adjusted for CT-derived measures of emphysema in a regression model. CONCLUSIONS: Loss of small vessel volume in CT imaging of smokers is associated with histological loss of vascular cross-sectional area. Imaging-based quantification of pulmonary vasculature provides a noninvasive method to study the multiscale effects of smoking on the pulmonary circulation.

Semi-quantitative visual assessment of chest radiography is associated with clinical outcomes in critically ill patients.

BACKGROUND: Respiratory pathology is a major driver of mortality in the intensive care unit (ICU), even in the absence of a primary respiratory diagnosis. Prior work has demonstrated that a visual scoring system applied to chest radiographs (CXR) is associated with adverse outcomes in ICU patients with Acute Respiratory Distress Syndrome (ARDS). We hypothesized that a simple, semi-quantitative CXR score would be associated with clinical outcomes for the general ICU population, regardless of underlying diagnosis. METHODS: All individuals enrolled in the Registry of Critical Illness at Brigham and Women's Hospital between June 2008 and August 2018 who had a CXR within 24 h of admission were included. Each patient's CXR was assigned an opacification score of 0-4 in each of four quadrants with the total score being the sum of all four quadrants. Multivariable negative binomial, logistic, and Cox regression, adjusted for age, sex, race, immunosuppression, a history of chronic obstructive pulmonary disease, a history of congestive heart failure, and APACHE II scores, were used to assess the total score's association with ICU length of stay (LOS), duration of mechanical ventilation, in-hospital mortality, 60-day mortality, and overall mortality, respectively. RESULTS: A total of 560 patients were included. Higher CXR scores were associated with increased mortality; for every one-point increase in score, in-hospital mortality increased 10% (OR 1.10, CI 1.05-1.16, p < 0.001) and 60-day mortality increased by 12% (OR 1.12, CI 1.07-1.17, p < 0.001). CXR scores were also independently associated with both ICU length of stay (rate ratio 1.06, CI 1.04-1.07, p < 0.001) and duration of mechanical ventilation (rate ratio 1.05, CI 1.02-1.07, p < 0.001). CONCLUSIONS: Higher values on a simple visual score of a patient's CXR on admission to the medical ICU are associated with increased in-hospital mortality, 60-day mortality, overall mortality, length of ICU stay, and duration of mechanical ventilation.

Disease Staging and Prognosis in Smokers Using Deep Learning in Chest Computed Tomography.

RATIONALE: Deep learning is a powerful tool that may allow for improved outcome prediction. OBJECTIVES: To determine if deep learning, specifically convolutional neural network (CNN) analysis, could detect and stage chronic obstructive pulmonary disease (COPD) and predict acute respiratory disease (ARD) events and mortality in smokers. METHODS: A CNN was trained using computed tomography scans from 7,983 COPDGene participants and evaluated using 1,000 nonoverlapping COPDGene participants and 1,672 ECLIPSE participants. Logistic regression (C statistic and the Hosmer-Lemeshow test) was used to assess COPD diagnosis and ARD prediction. Cox regression (C index and the Greenwood-Nam-D'Agnostino test) was used to assess mortality. MEASUREMENTS AND MAIN RESULTS: In COPDGene, the C statistic for the detection of COPD was 0.856. A total of 51.1% of participants in COPDGene were accurately staged and 74.95% were within one stage. In ECLIPSE, 29.4% were accurately staged and 74.6% were within one stage. In COPDGene and ECLIPSE, the C statistics for ARD events were 0.64 and 0.55, respectively, and the Hosmer-Lemeshow P values were 0.502 and 0.380, respectively, suggesting no evidence of poor calibration. In COPDGene and ECLIPSE, CNN predicted mortality with fair discrimination (C indices, 0.72 and 0.60, respectively), and without evidence of poor calibration (Greenwood-Nam-D'Agnostino P values, 0.307 and 0.331, respectively). CONCLUSIONS: A deep-learning approach that uses only computed tomography imaging data can identify those smokers who have COPD and predict who are most likely to have ARD events and those with the highest mortality. At a population level CNN analysis may be a powerful tool for risk assessment.