Rationale: In predominantly White populations, early chronic obstructive pulmonary disease (COPD) (i.e., COPD in people aged <50 yr) has been linked to higher hospitalization rates and mortality; however, the prevalence, risk factors, and population attributable risk (PAR) of early COPD remain to be determined in non-White populations. Objectives: We aimed to examine the prevalence, risk factors, and PARs of early COPD among Hispanic/Latino individuals, the largest U.S. minority group. Methods: We used baseline data from the Hispanic Community Health Study/Study of Latinos, a population-based probability sample of 16,415 Hispanic/Latino individuals aged 18-74 years. Participants aged <50 years were included (N = 7,323). Early COPD was defined as a forced expiratory volume in 1 second to forced vital capacity ratio less than the lower limit of normal. We used survey logistic regression analysis to identify risk factors and estimate the prevalence of early COPD. PARs of the risk factors identified were estimated. Results: A total of 524 participants met the criteria for early COPD, yielding a sex- and age-adjusted prevalence of 7.6% (95% confidence interval [CI], 6.8-8.6). Asthma (odds ratio [OR], 3.37; 95% CI, 2.57-4.41), smoking status (ever vs. never; OR, 1.65; 95% CI, 1.24-2.20), and chronic sinusitis (OR, 1.71; 95% CI, 1.09-2.66) were associated with increased odds of early COPD. Immigrants versus U.S.-born individuals have lower odds of early COPD (age at immigration <15 yr and living in the United States <10 yr; OR, 0.94; 95% CI, 0.39-2.27; age at immigration <15 yr and living in the United States ⩾10 yr; OR, 0.55; 95% CI, 0.37-0.84; age at immigration ⩾15 yr and living in the United States <10 yr; OR, 0.86; 95% CI, 0.57-1.30; and age at immigration ⩾15 yr and living in the United States ⩾10 yr; OR, 0.63; 95% CI, 0.42-0.95). Among smokers, pack-years was not associated with early COPD (5-9.9 vs. <5 pack-years; OR, 1.04; 95% CI, 0.59-1.82; ⩾10 vs. <5 pack-years; OR, 1.20; 95% CI, 0.74-1.94). The mean PAR for asthma, smoking status, and chronic sinusitis was 26.3% (95% CI, 22.1-30.3), 22.4% (95% CI, 17.4-27.1), and 6.9% (95% CI, 4.3-9.4), respectively. Conclusions: Among U.S. Hispanic/Latino individuals, asthma is one of the most important risk factors for early COPD, followed by smoking and chronic sinusitis. Immigrants appear to have a lower risk of early COPD than U.S.-born Hispanic/Latino individuals.

INTRODUCTION: Loss-of-function variants in both copies of the cystic fibrosis transmembrane conductance regulator (CFTR) gene cause cystic fibrosis (CF); however, there is evidence that reduction in CFTR function due to the presence of one deleterious variant can have clinical consequences. Here, we hypothesise that CFTR variants in individuals with a history of smoking are associated with chronic obstructive pulmonary disease (COPD) and related phenotypes. METHODS: Whole-genome sequencing was performed through the National Heart, Lung, and Blood Institute TOPMed (TransOmics in Precision Medicine) programme in 8597 subjects from the COPDGene (Genetic Epidemiology of COPD) study, an observational study of current and former smokers. We extracted clinically annotated CFTR variants and performed single-variant and variant-set testing for COPD and related phenotypes. Replication was performed in 2118 subjects from the ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) study. RESULTS: We identified 301 coding variants within the CFTR gene boundary: 147 of these have been reported in individuals with CF, including 36 CF-causing variants. We found that CF-causing variants were associated with chronic bronchitis in variant-set testing in COPDGene (one-sided p=0.0025; OR 1.53) and in meta-analysis of COPDGene and ECLIPSE (one-sided p=0.0060; OR 1.52). Single-variant testing revealed that the F508del variant was associated with chronic bronchitis in COPDGene (one-sided p=0.015; OR 1.47). In addition, we identified 32 subjects with two or more CFTR variants on separate alleles and these subjects were enriched for COPD cases (p=0.010). CONCLUSIONS: Cigarette smokers who carry one deleterious CFTR variant have higher rates of chronic bronchitis, while presence of two CFTR variants may be associated with COPD. These results indicate that genetically mediated reduction in CFTR function contributes to COPD related phenotypes, in particular chronic bronchitis.

Background Pulmonary and cardiac functions decline with age, but the associations of pulmonary dysfunction with cardiac function and heart failure (HF) risk in late life is not known. We aimed to determine the associations of percent predicted forced vital capacity (ppFVC) and the ratio of forced expired volume in 1 second (FEV1) to forced vital capacity (FVC; FEV1/FVC) with cardiac function and incident HF with preserved or reduced ejection fraction in late life. Methods and Results Among 3854 HF-free participants in the ARIC (Atherosclerosis Risk in Communities) cohort study who underwent echocardiography and spirometry at the fifth study visit (2011-2013), associations of FEV1/FVC and ppFVC with echocardiographic measures, cardiac biomarkers, and risk of HF, HF with preserved ejection fraction, and HF with reduced ejection fraction were assessed. Multivariable linear and Cox regression models adjusted for demographics, body mass index, coronary disease, atrial fibrillation, hypertension, and diabetes. Mean age was 75±5 years, 40% were men, 19% were Black, and 61% were ever smokers. Mean FEV1/FVC was 72±8%, and ppFVC was 98±17%. In adjusted analyses, lower FEV1/FVC and ppFVC were associated with higher NT-proBNP (N-terminal pro-B-type natriuretic peptide; both P<0.001) and pulmonary artery pressure (P<0.004). Lower ppFVC was also associated with higher left ventricular mass, left ventricular filling pressure, and high-sensitivity C-reactive protein (all P<0.01). Lower FEV1/FVC was associated with a trend toward higher risk of incident HF with preserved ejection fraction (hazard ratio [HR] per 10-point decrease, 1.31; 95% CI, 0.98-1.74; P=0.07) and HF with reduced ejection fraction (HR per 10-point decrease, 1.24; 95% CI, 0.91-1.70; P=0.18), but these associations did not reach statistical significance. Lower ppFVC was associated with incident HF with preserved ejection fraction (HR per 10-unit decrease, 1.21; 95% CI, 1.04-1.41; P=0.013) but not with HF with reduced ejection fraction (HR per 10-unit decrease, 0.90; 95% CI, 0.76-1.07; P=0.24). Conclusions Subclinical reductions in FEV1/FVC and ppFVC differentially associate with cardiac function and HF risk in late life.

BACKGROUND: Computed tomography (CT) imaging complements spirometry and may provide insight into racial disparities in respiratory health. OBJECTIVE: To determine the difference in emphysema prevalence between Black and White adults with different measures of normal spirometry results. DESIGN: Observational study using clinical data and spirometry from the CARDIA (Coronary Artery Risk Development in Young Adults) study obtained in 2015 to 2016 and CT scans done in 2010 to 2011. SETTING: 4 U.S. centers. PARTICIPANTS: Population-based sample of Black and White adults. MEASUREMENTS: Self-identified race and visually identified emphysema on CT in participants with different measures of "normal" spirometry results, calculated using standard race-specific and race-neutral reference equations. RESULTS: A total of 2674 participants (485 Black men, 762 Black women, 659 White men, and 768 White women) had both a CT scan and spirometry available for analysis. Among participants with a race-specific FEV1 between 80% and 99% of predicted, 6.5% had emphysema. In this group, emphysema prevalence was 3.9-fold (95% CI, 2.1- to 7.1-fold; 15.5% vs. 4.0%) higher among Black men than White men and 1.9-fold (CI, 1.0- to 3.8-fold; 6.6% vs. 3.4%) higher among Black women than White women. Among participants with a race-specific FEV1 between 100% and 120% of predicted, 4.0% had emphysema. In this category, Black men had a 6.4-fold (CI, 2.2- to 18.7-fold; 13.9% vs. 2.2%) higher prevalence of emphysema than White men, whereas Black and White women had a similar prevalence of emphysema (2.6% and 2.0%, respectively). The use of race-neutral equations to identify participants with an FEV1 percent predicted between 80% and 120% attenuated racial differences in emphysema prevalence among men and eliminated racial differences among women. LIMITATION: No CT scans were obtained during the most recent study visit (2015 to 2016) when spirometry was done. CONCLUSION: Emphysema is often present before spirometry findings become abnormal, particularly among Black men. Reliance on spirometry alone to differentiate lung health from lung disease may result in the underrecognition of impaired respiratory health and exacerbate racial disparities. PRIMARY FUNDING SOURCE: National Institutes of Health.

BACKGROUND: Interstitial lung abnormalities (ILA) may represent undiagnosed early-stage or subclinical interstitial lung disease (ILD). ILA are often observed incidentally in patients who subsequently develop clinically overt ILD. There is limited information on consensus definitions for, and the appropriate evaluation of, ILA. Early recognition of patients with ILD remains challenging, yet critically important. Expert consensus could inform early recognition and referral. RESEARCH QUESTION: Can consensus-based expert recommendations be identified to guide clinicians in the recognition, referral, and follow-up of patients with or at risk of developing early ILDs? STUDY DESIGN AND METHODS: Pulmonologists and radiologists with expertise in ILD participated in two iterative rounds of surveys. The surveys aimed to establish consensus regarding ILA reporting, identification of patients with ILA, and identification of populations that might benefit from screening for ILD. Recommended referral criteria and follow-up processes were also addressed. Threshold for consensus was defined a priori as ≥ 75% agreement or disagreement. RESULTS: Fifty-five experts were invited and 44 participated; consensus was reached on 39 of 85 questions. The following clinically important statements achieved consensus: honeycombing and traction bronchiectasis or bronchiolectasis indicate potentially progressive ILD; honeycombing detected during lung cancer screening should be reported as potentially significant (eg, with the Lung CT Screening Reporting and Data System "S-modifier" [Lung-RADS; which indicates clinically significant or potentially significant noncancer findings]), recommending referral to a pulmonologist in the radiology report; high-resolution CT imaging and full pulmonary function tests should be ordered if nondependent subpleural reticulation, traction bronchiectasis, honeycombing, centrilobular ground-glass nodules, or patchy ground-glass opacity are observed on CT imaging; patients with honeycombing or traction bronchiectasis should be referred to a pulmonologist irrespective of diffusion capacity values; and patients with systemic sclerosis should be screened with pulmonary function tests for early-stage ILD. INTERPRETATION: Guidance was established for identifying clinically relevant ILA, subsequent referral, and follow-up. These results lay the foundation for developing practical guidance on managing patients with ILA.

BACKGROUND: There are few clinically useful circulating biomarkers of lung function and lung disease. We hypothesized that genome-wide association studies (GWAS) of circulating proteins in conjunction with GWAS of pulmonary traits represents a clinically relevant approach to identifying causal proteins and therapeutically useful insights into mechanisms related to lung function and disease. STUDY QUESTION: Can an integrative genomic strategy using GWAS of plasma soluble receptor for advanced glycation end-products (sRAGE) levels in conjunction with GWAS of lung function traits identify putatively causal relations of sRAGE to lung function? STUDY DESIGN AND METHODS: Plasma sRAGE levels were measured in 6,861 Framingham Heart Study participants and GWAS of sRAGE was conducted to identify protein quantitative trait loci (pQTL), including cis-pQTL variants at the sRAGE protein-coding gene locus (AGER). We integrated sRAGE pQTL variants with variants from GWAS of lung traits. Colocalization of sRAGE pQTL variants with lung trait GWAS variants was conducted, and Mendelian randomization was performed using sRAGE cis-pQTL variants to infer causality of sRAGE for pulmonary traits. Cross-sectional and longitudinal protein-trait association analyses were conducted for sRAGE in relation to lung traits. RESULTS: Colocalization identified shared genetic signals for sRAGE with lung traits. Mendelian randomization analyses suggested protective causal relations of sRAGE to several pulmonary traits. Protein-trait association analyses demonstrated higher sRAGE levels to be cross-sectionally and longitudinally associated with preserved lung function. INTERPRETATION: sRAGE is produced by type I alveolar cells, and it acts as a decoy receptor to block the inflammatory cascade. Our integrative genomics approach provides evidence for sRAGE as a causal and protective biomarker of lung function, and the pattern of associations is suggestive of a protective role of sRAGE against restrictive lung physiology. We speculate that targeting the AGER/sRAGE axis may be therapeutically beneficial for the treatment and prevention of inflammation-related lung disease.

BACKGROUND: Most pulmonary conditions reduce FVC, but studies of patients with combined pulmonary fibrosis and emphysema demonstrate that reductions in FVC are less than expected when these two conditions coexist clinically. RESEARCH QUESTION: Do interstitial lung abnormalities (ILAs), chest CT imaging findings that may suggest an early stage of pulmonary fibrosis in individuals with undiagnosed disease, affect the association between emphysema and FVC? STUDY DESIGN AND METHODS: Measures of ILA and emphysema were available for 9,579 and 5,277 participants from phases 1 (2007-2011) and 2 (2012-2016) of the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease Study (COPDGene), respectively. ILA were defined by Fleischner Society guidelines. Adjusted linear regression models were used to assess the associations and interactions among ILA, emphysema, measures of spirometry, and lung function. RESULTS: ILA were present in 528 (6%) and 580 (11%) of participants in phases 1 and 2 of COPDGene, respectively. ILA modified the association between emphysema and FVC (P < .0001 for interaction) in both phases. In phase 1, in those without ILA, a 5% increase in emphysema was associated with a reduction in FVC (-110 mL; 95% CI, -121 to -100 mL; P < .0001); however, in those with ILA, it was not (-11 mL; 95% CI, -53 to 31; P = .59). In contrast, no interaction was found between ILA and emphysema on total lung capacity or on diffusing capacity of carbon monoxide. INTERPRETATION: The presence of ILA attenuates the reduction in FVC associated with emphysema.

PURPOSE: There are limited data on the relationship between neighborhood level factors and their association with lung health independent of individual socioeconomic status. We sought to determine whether baseline neighborhood level socioeconomic deprivation in young adults is associated with greater 20-year decline in lung function and higher risk of future lung disease, independent of baseline individual income, education, and smoking status. METHODS: This multicenter population-based cohort study included 2689 participants in Coronary Artery Risk Development in Young Adults (CARDIA) for whom neighborhood deprivation was determined at year 10 (baseline for study) and who had complete lung function measurements at years 10 and 30. Baseline neighborhood deprivation was defined using 1990 Census blocks as a combination of 4 factors involving median household income, poverty level, and educational achievement. The outcomes were decline in lung function over 20 years (year 10 to 30) and odds of emphysema (year 25). RESULTS: In multivariable regression models, greater baseline neighborhood deprivation was associated with greater decline in lung function (-2.34 mL/year excess annual decline in forced expiratory volume in 1 second (FEV1) in the highest versus lowest deprivation quartile (P = .014)). Furthermore, baseline neighborhood deprivation was independently associated with greater odds of emphysema (odds ratio [OR] 2.99, 95% confidence interval [CI] 1.42-6.30). CONCLUSIONS: Residence in neighborhoods with greater socioeconomic deprivation in young adulthood, independent of individual income and smoking, is associated with greater 20-year decline in forced expiratory volume in 1 second and higher risk of future emphysema.

Background Clustering key clinical characteristics of participants in the Severe Asthma Research Program (SARP), a large, multicenter prospective observational study of patients with asthma and healthy controls, has led to the identification of novel asthma phenotypes. Purpose To determine whether quantitative CT (qCT) could help distinguish between clinical asthma phenotypes. Materials and Methods A retrospective cross-sectional analysis was conducted with the use of qCT images (maximal bronchodilation at total lung capacity [TLC], or inspiration, and functional residual capacity [FRC], or expiration) from the cluster phenotypes of SARP participants (cluster 1: minimal disease; cluster 2: mild, reversible; cluster 3: obese asthma; cluster 4: severe, reversible; cluster 5: severe, irreversible) enrolled between September 2001 and December 2015. Airway morphometry was performed along standard paths (RB1, RB4, RB10, LB1, and LB10). Corresponding voxels from TLC and FRC images were mapped with use of deformable image registration to characterize disease probability maps (DPMs) of functional small airway disease (fSAD), voxel-level volume changes (Jacobian), and isotropy (anisotropic deformation index [ADI]). The association between cluster assignment and qCT measures was evaluated using linear mixed models. Results A total of 455 participants were evaluated with cluster assignments and CT (mean age ± SD, 42.1 years ± 14.7; 270 women). Airway morphometry had limited ability to help discern between clusters. DPM fSAD was highest in cluster 5 (cluster 1 in SARP III: 19.0% ± 20.6; cluster 2: 18.9% ± 13.3; cluster 3: 24.9% ± 13.1; cluster 4: 24.1% ± 8.4; cluster 5: 38.8% ± 14.4; P < .001). Lower whole-lung Jacobian and ADI values were associated with greater cluster severity. Compared to cluster 1, cluster 5 lung expansion was 31% smaller (Jacobian in SARP III cohort: 2.31 ± 0.6 vs 1.61 ± 0.3, respectively, P < .001) and 34% more isotropic (ADI in SARP III cohort: 0.40 ± 0.1 vs 0.61 ± 0.2, P < .001). Within-lung Jacobian and ADI SDs decreased as severity worsened (Jacobian SD in SARP III cohort: 0.90 ± 0.4 for cluster 1; 0.79 ± 0.3 for cluster 2; 0.62 ± 0.2 for cluster 3; 0.63 ± 0.2 for cluster 4; and 0.41 ± 0.2 for cluster 5; P < .001). Conclusion Quantitative CT assessments of the degree and intraindividual regional variability of lung expansion distinguished between well-established clinical phenotypes among participants with asthma from the Severe Asthma Research Program study. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Verschakelen in this issue.

BACKGROUND: Interstitial lung abnormalities (ILAs) are associated with increased mortality. It is unclear whether multimorbidity accounts for the mortality association or how strongly ILA is associated with mortality relative to other common age-associated diseases. We determined the association of ILA with all-cause mortality adjusted for multimorbidity, compared mortality associated with ILA and prevalent cardiovascular disease (CVD), diabetes mellitus, chronic kidney disease, chronic obstructive pulmonary disease and cancer and also determined the association between ILA and these diseases. METHODS: We measured ILA (none, indeterminant, definite) using blinded reads of CT images, prevalent chronic diseases and potential confounders in two observational cohorts, the Framingham Heart Study (FHS) (n=2449) and Age, Gene/Environment Susceptibility - Reykjavik Study (AGES-Reykjavik) (n=5180). We determined associations with mortality using Cox proportional hazards models and between ILA and diseases with multinomial logistic regression. RESULTS: Over a median (IQR) follow-up of 8.8 (1.4) years in FHS and 12.0 (7.7) years in AGES-Reykjavik, in adjusted models, ILAs were significantly associated with increased mortality (HR, 95% CI 1.95, 1.23 to 3.08, p=0.0042, in FHS; HR 1.60, 1.41 to 1.82, p<0.0001, in AGES-Reykjavik) adjusted for multimorbidity. In both cohorts, the association of ILA with mortality was of similar magnitude to the association of most other diseases. In adjusted models, ILAs were associated only with prevalent kidney disease (OR, 95% CI 1.90, 1.01 to 3.57, p=0.0452) in FHS and with prevalent CVD (OR 1.42, 1.12 to 1.81, p=0.0040) in AGES-Reykjavik. CONCLUSIONS: ILAs were associated with mortality adjusted for multimorbidity and were similarly associated with increased mortality compared with several common chronic diseases. ILAs were not consistently associated with the prevalence of these diseases themselves.

Artificial intelligence (AI) is transforming the way we perform advanced imaging. From high-resolution image reconstruction to predicting functional response from clinically acquired data, AI is promising to revolutionize clinical evaluation of lung performance, pushing the boundary in pulmonary functional imaging for patients suffering from respiratory conditions. In this review, we overview the current developments and expound on some of the encouraging new frontiers. We focus on the recent advances in machine learning and deep learning that enable reconstructing images, quantitating, and predicting functional responses of the lung. Finally, we shed light on the potential opportunities and challenges ahead in adopting AI for functional lung imaging in clinical settings.

BACKGROUND: Cardiorespiratory fitness is not limited by pulmonary mechanical reasons in the majority of adults. However, the degree to which lung function contributes to exercise response patterns among ostensibly healthy individuals remains unclear. METHODS: We examined 2314 Framingham Heart Study participants who underwent cardiopulmonary exercise testing (CPET) and pulmonary function testing. We investigated the association of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC and diffusing capacity of the lung for carbon monoxide (D LCO) with the primary outcome of peak oxygen uptake (V'O2 ) along with other CPET parameters using multivariable linear regression. Finally, we investigated the association of total and peripheral pulmonary blood vessel volume with peak V'O2 . RESULTS: We found lower FEV1, FVC and D LCO were associated with lower peak V'O2 . For example, a 1 L lower FEV1 and FVC was associated with a 7.1% (95% CI 5.1-9.1%) and 6.0% (95% CI 4.3-7.7%) lower peak V'O2 , respectively. By contrast, FEV1/FVC was not associated with peak V'O2 . Lower lung function was associated with lower oxygen uptake efficiency slope, oxygen pulse slope, V'O2 at anaerobic threshold (AT), minute ventilation (V'E) at AT and breathing reserve. In addition, lower total and peripheral pulmonary blood vessel volume were associated with lower peak V'O2 . CONCLUSIONS: In a large, community-based cohort of adults, we found lower FEV1, FVC and D LCO were associated with lower exercise capacity, as well as oxygen uptake efficiency slope and ventilatory efficiency. In addition, lower total and peripheral pulmonary blood vessel volume were associated with lower peak V'O2 . These findings underscore the importance of lung function and blood vessel volume as contributors to overall exercise capacity.

The main objective of this work is to develop and evaluate an artificial intelligence system based on deep learning capable of automatically identifying, quantifying, and characterizing COVID-19 pneumonia patterns in order to assess disease severity and predict clinical outcomes, and to compare the prediction performance with respect to human reader severity assessment and whole lung radiomics. We propose a deep learning based scheme to automatically segment the different lesion subtypes in nonenhanced CT scans. The automatic lesion quantification was used to predict clinical outcomes. The proposed technique has been independently tested in a multicentric cohort of 103 patients, retrospectively collected between March and July of 2020. Segmentation of lesion subtypes was evaluated using both overlapping (Dice) and distance-based (Hausdorff and average surface) metrics, while the proposed system to predict clinically relevant outcomes was assessed using the area under the curve (AUC). Additionally, other metrics including sensitivity, specificity, positive predictive value and negative predictive value were estimated. 95% confidence intervals were properly calculated. The agreement between the automatic estimate of parenchymal damage (%) and the radiologists' severity scoring was strong, with a Spearman correlation coefficient (R) of 0.83. The automatic quantification of lesion subtypes was able to predict patient mortality, admission to the Intensive Care Units (ICU) and need for mechanical ventilation with an AUC of 0.87, 0.73 and 0.68 respectively. The proposed artificial intelligence system enabled a better prediction of those clinically relevant outcomes when compared to the radiologists' interpretation and to whole lung radiomics. In conclusion, deep learning lesion subtyping in COVID-19 pneumonia from noncontrast chest CT enables quantitative assessment of disease severity and better prediction of clinical outcomes with respect to whole lung radiomics or radiologists' severity score.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a disease of accelerated aging and is associated with comorbid conditions including osteoporosis and sarcopenia. These extrapulmonary conditions are highly prevalent yet frequently underdiagnosed and overlooked by pulmonologists in COPD treatment and management. There is evidence supporting a role for bone-muscle crosstalk which may compound osteoporosis and sarcopenia risk in COPD. Chest CT is commonly utilized in COPD management, and we evaluated its utility to identify low bone mineral density (BMD) and reduced pectoralis muscle area (PMA) as surrogates for osteoporosis and sarcopenia. We then tested whether BMD and PMA were associated with morbidity and mortality in COPD. METHODS: BMD and PMA were analyzed from chest CT scans of 8468 COPDGene participants with COPD and controls (smoking and non-smoking). Multivariable regression models tested the relationship of BMD and PMA with measures of function (6-min walk distance (6MWD), handgrip strength) and disease severity (percent emphysema and lung function). Multivariable Cox proportional hazards models were used to evaluate the relationship between sex-specific quartiles of BMD and/or PMA derived from non-smoking controls with all-cause mortality. RESULTS: COPD subjects had significantly lower BMD and PMA compared with controls. Higher BMD and PMA were associated with increased physical function and less disease severity. Participants with the highest BMD and PMA quartiles had a significantly reduced mortality risk (36% and 46%) compared to the lowest quartiles. CONCLUSIONS: These findings highlight the potential for CT-derived BMD and PMA to characterize osteoporosis and sarcopenia using equipment available in the pulmonary setting.

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.

BACKGROUND: Despite improvement in treatment strategies of atrial fibrillation (AF), a considerable number of patients still experience recurrence of atrial tachyarrhythmia (ATA) following catheter ablation (CA). This study aimed to investigate the prognostic value of left atrial (LA) deformation analysis in a large group of patients undergoing CA for AF. METHODS: This study included 678 patients with AF. Echocardiography including two-dimensional speckle tracking echocardiography (2DSTE) was performed in all patients prior to CA. Logistic regression analysis was used to assess the association between ATA recurrence and LA strain during reservoir phase (LASr), LA strain during contraction phase (LASct), and LA strain during conduit phase (LAScd). RESULTS: During one-year follow-up, 274 (40%) experienced ATA recurrence. Median age of the included study population was 63.2 years (IQR: 55.5, 69.5) and 485 (72%) were male. Patients with recurrence had lower LASr (22.6% vs. 25.1%, p = 0.001) and LASct (10.7% vs. 12.4%, p < 0.001). No difference in LAScd was observed. After adjusting for potential clinical and echocardiographic confounders LASr (OR = 1.04, CI95% [1.01; 1.07], p = 0.015, per 1% decrease) and LASct (OR = 1.06, CI95% [1.02; 1.11], p = 0.007, per 1% decrease) remained independent predictors of recurrence. However, in patients with a normal-sized LA (LA volume index<34 mL/m2), only LASct remained an independent predictor of recurrence (OR = 1.07, CI95% [1.01; 1.12], p = 0.012, per 1% decrease). CONCLUSION: In patients undergoing CA for AF, LA deformation analysis by 2DSTE could be of use in risk stratification in clinical practice regarding ATA recurrence, even in patients with a normal-sized LA.

BACKGROUND: Body composition measures, specifically low weight or reduced muscle mass, are associated with mortality in COPD, but the effect of longitudinal body composition changes is undefined. RESEARCH QUESTION: Is the longitudinal loss of fat-free mass (FFM) associated with increased mortality, including in those with initially normal or elevated body composition metrics? STUDY DESIGN AND METHODS: Participants with complete data for at least one visit in the COPDGene study (n = 9,268) and the ECLIPSE study (n = 1,760) were included and monitored for 12 and 8 years, respectively. Pectoralis muscle area (PMA) was derived from thoracic CT scans and used as a proxy for FFM. A longitudinal mixed submodel for PMA and a Cox proportional hazards submodel for survival were fitted on a joint distribution, using a shared random intercept parameter and Markov chain Monte Carlo parameter estimation. RESULTS: Both cohorts demonstrated a left-shifted distribution of baseline FFM, not reflected in BMI, and an increase in all-cause mortality risk associated with longitudinal loss of PMA. For each 1-cm2 PMA loss, mortality increased 3.1% (95% CI, 2.4%-3.7%; P < .001) in COPDGene, and 2.4% (95% CI, 0.9%-4.0%; P < .001) in ECLIPSE. Increased mortality risk was independent of enrollment values for BMI and disease severity [BODE (body mass, airflow obstruction, dyspnea, and exercise capacity) index quartiles] and was significant even in participants with initially greater than average PMA. INTERPRETATION: Longitudinal loss of PMA is associated with increased all-cause mortality, regardless of BMI or initial muscle mass. Consideration of novel screening tests and further research into mechanisms contributing to muscle decline may improve risk stratification and identify novel therapeutic targets in ever smokers.

BACKGROUND: Radiomics, defined as quantitative features extracted from images, provide a non-invasive means of assessing malignant versus benign pulmonary nodules. In this study, we evaluate the consistency with which perinodular radiomics extracted from low-dose computed tomography images serve to identify malignant pulmonary nodules. MATERIALS AND METHODS: Using the National Lung Screening Trial (NLST), we selected individuals with pulmonary nodules between 4mm to 20mm in diameter. Nodules were segmented to generate four distinct datasets; 1) a Tumor dataset containing tumor-specific features, 2) a 10 mm Band dataset containing parenchymal features between the segmented nodule boundary and 10mm out from the boundary, 3) a 15mm Band dataset, and 4) a Tumor Size dataset containing the maximum nodule diameter. Models to predict malignancy were constructed using support-vector machine (SVM), random forest (RF), and least absolute shrinkage and selection operator (LASSO) approaches. Ten-fold cross validation with 10 repetitions per fold was used to evaluate the performance of each approach applied to each dataset. RESULTS: With respect to the RF, the Tumor, 10mm Band, and 15mm Band datasets achieved areas under the receiver-operator curve (AUC) of 84.44%, 84.09%, and 81.57%, respectively. Significant differences in performance were observed between the Tumor and 15mm Band datasets (adj. p-value <0.001). However, when combining tumor-specific features with perinodular features, the 10mm Band + Tumor and 15mm Band + Tumor datasets (AUC 87.87% and 86.75%, respectively) performed significantly better than the Tumor Size dataset (66.76%) or the Tumor dataset. Similarly, the AUCs from the SVM and LASSO were 84.71% and 88.91%, respectively, for the 10mm Band + Tumor. CONCLUSIONS: The combined 10mm Band + Tumor dataset improved the differentiation between benign and malignant lung nodules compared to the Tumor datasets across all methodologies. This demonstrates that parenchymal features capture novel diagnostic information beyond that present in the nodule itself. (data agreement: NLST-163).