RATIONALE: Occupational exposures at the WTC site after September 11, 2001 have been associated with several presumably inflammatory lower airway diseases. In this study, we describe the trajectories of expiratory air flow decline, identify subgroups with adverse progression, and investigate the association of a quantitative computed tomography (QCT) imaging measurement of airway wall thickness, and other risk factors for adverse progression. METHODS: We examined the trajectories of expiratory air flow decline in a group of 799 former WTC workers and volunteers with QCT-measured (with two independent systems) wall area percent (WAP) and at least 3 periodic spirometries. We calculated individual regression lines for first-second forced expiratory volume (FEV), identified subjects with rapidly declining and increasing ("gainers"), and compared them to subjects with normal and "stable" FEV decline. We used multivariate logistic regression to model decliner vs. stable trajectories. RESULTS: The mean longitudinal FEVslopes for the entire study population, and its stable, decliner, and gainer subgroups were, respectively, - 35.8, - 8, - 157.6, and + 173.62 ml/year. WAP was associated with "decliner" status (OR 1.08, 95% CI 1.02, 1.14, per 5% increment) compared to stable. Age, weight gain, baseline FEV percent predicted, bronchodilator response, and pre-WTC occupational exposures were also significantly associated with accelerated FEV decline. Analyses of gainers vs. stable subgroup showed WAP as a significant predictor in unadjusted but not consistently in adjusted analyses. CONCLUSIONS: The apparent normal age-related rate of FEV decline results from averaging widely divergent trajectories. WAP is significantly associated with accelerated air flow decline in WTC workers.

Purpose To determine if interstitial features at chest CT enhance the effect of emphysema on clinical disease severity in smokers without clinical pulmonary fibrosis. Materials and Methods In this retrospective cohort study, an objective CT analysis tool was used to measure interstitial features (reticular changes, honeycombing, centrilobular nodules, linear scar, nodular changes, subpleural lines, and ground-glass opacities) and emphysema in 8266 participants in a study of chronic obstructive pulmonary disease (COPD) called COPDGene (recruited between October 2006 and January 2011). Additive differences in patients with emphysema with interstitial features and in those without interstitial features were analyzed by using t tests, multivariable linear regression, and Kaplan-Meier analysis. Multivariable linear and Cox regression were used to determine if interstitial features modified the effect of continuously measured emphysema on clinical measures of disease severity and mortality. Results Compared with individuals with emphysema alone, those with emphysema and interstitial features had a higher percentage predicted forced expiratory volume in 1 second (absolute difference, 6.4%; P < .001), a lower percentage predicted diffusing capacity of lung for carbon monoxide (DLCO) (absolute difference, 7.4%; P = .034), a 0.019 higher right ventricular-to-left ventricular (RVLV) volume ratio (P = .029), a 43.2-m shorter 6-minute walk distance (6MWD) (P < .001), a 5.9-point higher St George's Respiratory Questionnaire (SGRQ) score (P < .001), and 82% higher mortality (P < .001). In addition, interstitial features modified the effect of emphysema on percentage predicted DLCO, RVLV volume ratio, 6WMD, SGRQ score, and mortality (P for interaction < .05 for all). Conclusion In smokers, the combined presence of interstitial features and emphysema was associated with worse clinical disease severity and higher mortality than was emphysema alone. In addition, interstitial features enhanced the deleterious effects of emphysema on clinical disease severity and mortality.

BACKGROUND: Emphysema has considerable variability in its regional distribution. Craniocaudal emphysema distribution is an important predictor of the response to lung volume reduction. However, there is little consensus regarding how to define upper lobe-predominant and lower lobe-predominant emphysema subtypes. Consequently, the clinical and genetic associations with these subtypes are poorly characterized. METHODS: We sought to identify subgroups characterized by upper-lobe or lower-lobe emphysema predominance and comparable amounts of total emphysema by analyzing data from 9,210 smokers without alpha-1-antitrypsin deficiency in the Genetic Epidemiology of COPD (COPDGene) cohort. CT densitometric emphysema was measured in each lung lobe. Random forest clustering was applied to lobar emphysema variables after regressing out the effects of total emphysema. Clusters were tested for association with clinical and imaging outcomes at baseline and at 5-year follow-up. Their associations with genetic variants were also compared. RESULTS: Three clusters were identified: minimal emphysema (n = 1,312), upper lobe-predominant emphysema (n = 905), and lower lobe-predominant emphysema (n = 796). Despite a similar amount of total emphysema, the lower-lobe group had more severe airflow obstruction at baseline and higher rates of metabolic syndrome compared with subjects with upper-lobe predominance. The group with upper-lobe predominance had greater 5-year progression of emphysema, gas trapping, and dyspnea. Differential associations with known COPD genetic risk variants were noted. CONCLUSIONS: Subgroups of smokers defined by upper-lobe or lower-lobe emphysema predominance exhibit different functional and radiological disease progression rates, and the upper-lobe predominant subtype shows evidence of association with known COPD genetic risk variants. These subgroups may be useful in the development of personalized treatments for COPD.

RATIONALE: The relationship between longitudinal lung function trajectories, chest computed tomography (CT) imaging, and genetic predisposition to chronic obstructive pulmonary disease (COPD) has not been explored. OBJECTIVES: 1) To model trajectories using a data-driven approach applied to longitudinal data spanning adulthood in the Normative Aging Study (NAS), and 2) to apply these models to demographically similar subjects in the COPDGene (Genetic Epidemiology of COPD) Study with detailed phenotypic characterization including chest CT. METHODS: We modeled lung function trajectories in 1,060 subjects in NAS with a median follow-up time of 29 years. We assigned 3,546 non-Hispanic white males in COPDGene to these trajectories for further analysis. We assessed phenotypic and genetic differences between trajectories and across age strata. MEASUREMENTS AND MAIN RESULTS: We identified four trajectories in NAS with differing levels of maximum lung function and rate of decline. In COPDGene, 617 subjects (17%) were assigned to the lowest trajectory and had the greatest radiologic burden of disease (P < 0.01); 1,283 subjects (36%) were assigned to a low trajectory with evidence of airway disease preceding emphysema on CT; 1,411 subjects (40%) and 237 subjects (7%) were assigned to the remaining two trajectories and tended to have preserved lung function and negligible emphysema. The genetic contribution to these trajectories was as high as 83% (P = 0.02), and membership in lower lung function trajectories was associated with greater parental histories of COPD, decreased exercise capacity, greater dyspnea, and more frequent COPD exacerbations. CONCLUSIONS: Data-driven analysis identifies four lung function trajectories. Trajectory membership has a genetic basis and is associated with distinct lung structural abnormalities.

Adiponectin has been proposed as a biomarker of disease severity and progression in chronic obstructive pulmonary disease (COPD) and associated with spirometry-defined COPD and with computed tomography (CT)-measured emphysema. Increased adiponectin plays a role in other diseases including diabetes/metabolic syndrome, cardiovascular disease and osteoporosis. Previous studies of adiponectin and COPD have not assessed the relationship of adiponectin to airway disease in smokers and have not evaluated the effect of other comorbid diseases on the relationship of adiponectin and lung disease. We postulated that adiponectin levels would associate with both airway disease and emphysema in smokers with and without COPD, and further postulated that body composition and the comorbid diseases of osteoporosis, cardiovascular disease and diabetes might influence adiponectin levels. Current and former smokers from the COPD Genetic Epidemiology study (COPDGene) (n= 424) were assigned to 4 groups based on CT lung characteristics and volumetric Bone Density (vBMD). Emphysema (% low attenuation area at -950) and airway disease (Wall area %) were used to assess smoking-related lung disease (SRLD). Group 1) Normal Lung with Normal vBMD; Group 2) Normal Lung and Osteoporosis; Group 3) SRLD with Normal vBMD; Group 4) SRLD with Osteoporosis. Cardiovascular disease (CVD), diabetes, C-reactive protein (CRP) and T-cadherin (soluble receptor for adiponectin) levels were defined for each group. Body composition was derived from chest CT. Multivariable regression assessed effects of emphysema, wall area %, bone density, comorbid diseases and other key factors on log adiponectin. Group 4, SRLD with Osteoporosis, had significantly higher adiponectin levels compared to other groups and the effect persisted in adjusted models. Systemic inflammation (by CRP) was associated with SRLD in Groups 3 and 4 but not with osteoporosis alone. In regression models, lower bone density and worse emphysema were associated with higher adiponectin. Airway disease was associated with higher adiponectin levels when T-cadherin was added to the model. Male gender, greater muscle and fat were associated with lower adiponectin. Adiponectin is increased with both airway disease and emphysema in smokers. Bone density, and fat and muscle composition are all significant factors predicting adiponectin that should be considered when it is used as a biomarker of COPD. Increased adiponectin from chronic inflammation may play a role in the progression of bone loss in COPD and other lung diseases.

Many automatic image analysis algorithms in medical imaging require a good initialization to work properly. A similar problem occurs in many imaging-based clinical workflows, which depend on anatomical landmarks. The localization of anatomic structures based on a defined context provides with a solution to that problem, which turns out to be more challenging in medical imaging where labeled images are difficult to obtain. We propose a two-stage process to detect and regress 2D bounding boxes of predefined anatomical structures based on a 2D surrounding context. First, we use a deep convolutional neural network (DCNN) architecture to detect the optimal slice where an anatomical structure is present, based on relevant landmark features. After this detection, we employ a similar architecture to perform a 2D regression with the aim of proposing a bounding box where the structure is encompassed. We trained and tested our system for 57 anatomical structures defined in axial, sagittal and coronal planes with a dataset of 504 labeled Computed Tomography (CT) scans. We compared our method with a well-known object detection algorithm (Viola Jones) and with the inter-rater error for two human experts. Despite the relatively small number of scans and the exhaustive number of structures analyzed, our method obtained promising and consistent results, which proves our architecture very generalizable to other anatomical structures.

In quantitative magnetic resonance mapping, the variable flip angle (VFA) steady state spoiled gradient recalled echo (SPGR) imaging technique is popular as it provides a series of high resolution weighted images in a clinically feasible time. Fast, linear methods that estimate maps from these weighted images have been proposed, such as DESPOT1 and iterative re-weighted linear least squares. More accurate, non-linear least squares (NLLS) estimators are in play, but these are generally much slower and require careful initialization. In this paper, we present NOVIFAST, a novel NLLS-based algorithm specifically tailored to VFA SPGR mapping. By exploiting the particular structure of the SPGR model, a computationally efficient, yet accurate and precise map estimator is derived. Simulation and in vivo human brain experiments demonstrate a twenty-fold speed gain of NOVIFAST compared with conventional gradient-based NLLS estimators while maintaining a high precision and accuracy. Moreover, NOVIFAST is eight times faster than the efficient implementations of the variable projection (VARPRO) method. Furthermore, NOVIFAST is shown to be robust against initialization.

RATIONALE: Expiratory central airway collapse is associated with respiratory morbidity independent of underlying lung disease. However, not all smokers develop expiratory central airway collapse, and the etiology of expiratory central airway collapse in adult smokers is unclear. Paraseptal emphysema in the paratracheal location, by untethering airway walls, may predispose smokers to developing expiratory central airway collapse. OBJECTIVES: To evaluate whether paratracheal paraseptal emphysema is associated with expiratory central airway collapse. METHODS: We analyzed paired inspiratory and expiratory computed tomography scans from participants enrolled in a multicenter study (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease) of smokers aged 45 to 80 years. Expiratory central airway collapse was defined as greater than or equal to 50% reduction in cross-sectional area of the trachea during expiration. In a nested case-control design, participants with and without expiratory central airway collapse were included in a 1:2 fashion, and inspiratory scans were further analyzed using the Fleischner Society criteria for presence of centrilobular emphysema, paraseptal emphysema, airway wall thickening, and paratracheal paraseptal emphysema (maximal diameter ≥ 0.5 cm). RESULTS: A total of 1,320 patients were included, 440 with and 880 without expiratory central airway collapse. Those with expiratory central airway collapse were older, had higher body mass index, and were less likely to be men or current smokers. Paratracheal paraseptal emphysema was more frequent in those with expiratory central airway collapse than control subjects (16.6 vs. 11.8%; P = 0.016), and after adjustment for age, race, sex, body mass index, smoking pack-years, and forced expiratory volume in 1 second, paratracheal paraseptal emphysema was independently associated with expiratory central airway collapse (adjusted odds ratio, 1.53; 95% confidence interval, 1.18-1.98; P = 0.001). Furthermore, increasing size of paratracheal paraseptal emphysema (maximal diameter of at least 1 cm and 1.5 cm) was associated with greater odds of expiratory central airway collapse (adjusted odds ratio, 1.63; 95% confidence interval, 1.18-2.25; P = 0.003 and 1.77; 95% confidence interval, 1.19-2.64; P = 0.005, respectively). CONCLUSIONS: Paraseptal emphysema adjacent to the trachea is associated with expiratory central airway collapse. The identification of this risk factor on inspiratory scans should prompt further evaluation for expiratory central airway collapse. Clinical trial registered with ClinicalTrials.gov (NCT 00608764).

BACKGROUND: Low muscle mass is associated with increased mortality in the general population but its prognostic value in at-risk smokers, those without expiratory airflow obstruction, is unknown. We aimed to test the hypothesis that reduced muscle mass is associated with increased mortality in at-risk smokers. METHODS: Measures of both pectoralis and paravertebral erector spinae muscle cross-sectional area (PMA and PVMA, respectively) as well as emphysema on chest computed tomography (CT) scans were performed in 3705 current and former at-risk smokers (≥10 pack-years) aged 45-80 years enrolled into the COPDGene Study between 2008 and 2013. Vital status was ascertained through death certificate. The association between low muscle mass and mortality was assessed using Cox regression analysis. RESULTS: During a median of 6.5 years of follow-up, 212 (5.7%) at-risk smokers died. At-risk smokers in the lowest (vs. highest) sex-specific quartile of PMA but not PVMA had 84% higher risk of death in adjusted models for demographics, smoking, dyspnea, comorbidities, exercise capacity, lung function, emphysema on CT, and coronary artery calcium content (hazard ratio [HR] 1.85 95% Confidence interval [1.14-3.00] P = 0.01). Results were consistent when the PMA index (PMA/height) was used instead of quartiles. The association between PMA and death was modified by smoking status (P = 0.04). Current smokers had a significantly increased risk of death (lowest vs. highest PMA quartile, HR 2.25 [1.25-4.03] P = 0.007) while former smokers did not. CONCLUSIONS: Low muscle mass as measured on chest CT scans is associated with increased mortality in current smokers without airflow obstruction. TRIAL REGISTRATION: NCT00608764.

RATIONALE: Loss of the peripheral pulmonary vasculature, termed vascular pruning, is associated with disease severity in patients with chronic obstructive pulmonary disease. OBJECTIVES: To determine if pulmonary vascular pruning is associated with asthma severity and exacerbations. METHODS: We measured the total pulmonary blood vessel volume (TBV) and the blood vessel volume of vessels less than 5 mm2 in cross-sectional area (BV5) and of vessels less than 10 mm2 (BV10) in cross-sectional area on noncontrast computed tomographic scans of participants from the Severe Asthma Research Program. Lower values of the BV5 to TBV ratio (BV5/TBV) and the BV10 to TBV ratio (BV10/TBV) represented vascular pruning (loss of the peripheral pulmonary vasculature). MEASUREMENTS AND MAIN RESULTS: Compared with healthy control subjects, patients with severe asthma had more pulmonary vascular pruning. Among those with asthma, those with poor asthma control had more pruning than those with well-controlled disease. Pruning of the pulmonary vasculature was also associated with lower percent predicted FEV1 and FVC, greater peripheral and sputum eosinophilia, and higher BAL serum amyloid A/lipoxin A4 ratio but not with low-attenuation area or with sputum neutrophilia. Compared with individuals with less pruning, individuals with the most vascular pruning had 150% greater odds of reporting an asthma exacerbation (odds ratio, 2.50; confidence interval, 1.05-5.98; P = 0.039 for BV10/TBV) and reported 45% more asthma exacerbations during follow-up (incidence rate ratio, 1.45; confidence interval, 1.02-2.06; P = 0.036 for BV10/TBV). CONCLUSIONS: Pruning of the peripheral pulmonary vasculature is associated with asthma severity, control, and exacerbations, and with lung function and eosinophilia.

Recent studies show that pulmonary vascular diseases may specifically affect arteries or veins through different physiologic mechanisms. To detect changes in the two vascular trees, physicians manually analyze the chest computed tomography (CT) image of the patients in search of abnormalities. This process is time consuming, difficult to standardize, and thus not feasible for large clinical studies or useful in real-world clinical decision making. Therefore, automatic separation of arteries and veins in CT images is becoming of great interest, as it may help physicians to accurately diagnose pathological conditions. In this paper, we present a novel, fully automatic approach to classify vessels from chest CT images into arteries and veins. The algorithm follows three main steps: first, a scale-space particles segmentation to isolate vessels; then a 3-D convolutional neural network (CNN) to obtain a first classification of vessels; finally, graph-cuts' optimization to refine the results. To justify the usage of the proposed CNN architecture, we compared different 2-D and 3-D CNNs that may use local information from bronchus- and vessel-enhanced images provided to the network with different strategies. We also compared the proposed CNN approach with a random forests (RFs) classifier. The methodology was trained and evaluated on the superior and inferior lobes of the right lung of 18 clinical cases with noncontrast chest CT scans, in comparison with manual classification. The proposed algorithm achieves an overall accuracy of 94%, which is higher than the accuracy obtained using other CNN architectures and RF. Our method was also validated with contrast-enhanced CT scans of patients with chronic thromboembolic pulmonary hypertension to demonstrate that our model generalizes well to contrast-enhanced modalities. The proposed method outperforms state-of-the-art methods, paving the way for future use of 3-D CNN for artery/vein classification in CT images.

There are few studies looking at the pulmonary circulation in subjects with bronchiectasis. We aimed to evaluate the intraparenchymal pulmonary vascular structure, using noncontrast chest computed tomography (CT), and its clinical implications in smokers with radiographic bronchiectasis. Visual bronchiectasis scoring and quantitative assessment of the intraparenchymal pulmonary vasculature were performed on CT scans from 486 smokers. Clinical, lung function and 6-min walk test (6MWT) data were also collected. The ratio of blood vessel volume in vessels <5 mm in cross-section (BV5) to total blood vessel volume (TBV) was used as measure of vascular pruning, with lower values indicating more pruning. Whole-lung and lobar BV5/TBV values were determined, and regression analyses were used to assess the differences in BV5/TBV between subjects with and without bronchiectasis. 155 (31.9%) smokers had bronchiectasis, which was, on average, mild in severity. Compared to subjects without bronchiectasis, those with lower-lobe bronchiectasis had greater vascular pruning in adjusted models. Among subjects with bronchiectasis, those with vascular pruning had lower forced expiratory volume in 1 s and 6MWT distance compared to those without vascular pruning. Smokers with mild radiographic bronchiectasis appear to have pruning of the distal pulmonary vasculature and this pruning is associated with measures of disease severity.

RATIONALE: There are limited data on factors in young adulthood that predict future lung disease. OBJECTIVES: To determine the relationship between respiratory symptoms, loss of lung health, and incident respiratory disease in a population-based study of young adults. METHODS: We examined prospective data from 2,749 participants in the CARDIA (Coronary Artery Risk Development in Young Adults) study who completed respiratory symptom questionnaires at baseline and 2 years later and repeated spirometry measurements over 30 years. MEASUREMENTS AND MAIN RESULTS: Cough or phlegm, episodes of bronchitis, wheeze, shortness of breath, and chest illnesses at both baseline and Year 2 were the main predictor variables in models assessing decline in FEV and FVC from Year 5 to Year 30, incident obstructive and restrictive lung physiology, and visual emphysema on thoracic computed tomography scan. After adjustment for covariates, including body mass index, asthma, and smoking, report of any symptom was associated with -2.71 ml/yr excess decline in FEV (P < 0.001) and -2.18 in FVC (P < 0.001) as well as greater odds of incident (prebronchodilator) obstructive (odds ratio [OR], 1.63; 95% confidence interval [CI], 1.24-2.14) and restrictive (OR, 1.40; 95% CI, 1.09-1.80) physiology. Cough-related symptoms (OR, 1.56; 95% CI, 1.13-2.16) were associated with greater odds of future emphysema. CONCLUSIONS: Persistent respiratory symptoms in young adults are associated with accelerated decline in lung function, incident obstructive and restrictive physiology, and greater odds of future radiographic emphysema.

Alpha-1 antitrypsin deficiency (AATD) is characterized by low serum levels of or dysfunctional alpha-1 proteinase inhibitor. In the lung parenchyma, this results in a loss of protection against the activity of serine proteases, particularly neutrophil elastase. The resultant imbalance in protease and antiprotease activity leads to an increased risk for the development of early-onset emphysema and COPD. As in traditional smoke-related COPD, the assessment of the severity and disease progression of lung disease in AATD is conventionally based on lung function; however, pulmonary function tests are unable to discriminate between emphysema and airways disease, the two hallmark pathologic features of COPD. CT imaging has been used as a tool to further characterize lung structure and evaluate therapeutic interventions in AATD-related COPD. Moreover, recent advances in quantitative CT have significantly improved our assessment of the lung architecture, which has provided investigators and clinicians with a more detailed evaluation of the extent and severity of emphysema and airways disease in AATD. In addition, serial CT imaging measures are becoming increasingly important, as they provide a tool to monitor emphysema progression. This review describes the principles of CT technology and the role of CT imaging in assessing pulmonary disease progression in AATD, including the effect of therapeutic interventions.

BACKGROUND: Cigarette smoking is the strongest risk factor for COPD. Smoking burden is frequently measured in pack-years, but the relative contribution of cigarettes smoked per day versus duration towards the development of structural lung disease, airflow obstruction and functional outcomes is not known. METHODS: We analysed cross-sectional data from a large multicentre cohort (COPDGene) of current and former smokers. Primary outcome was airflow obstruction (FEV/FVC); secondary outcomes included five additional measures of disease: FEV, CT emphysema, CT gas trapping, functional capacity (6 min walk distance, 6MWD) and respiratory morbidity (St George's Respiratory Questionnaire, SGRQ). Generalised linear models were estimated to compare the relative contribution of each smoking variable with the outcomes, after adjustment for age, race, sex, body mass index, CT scanner, centre, age of smoking onset and current smoking status. We also estimated adjusted means of each outcome by categories of pack-years and combined groups of categorised smoking duration and cigarettes/day, and estimated linear trends of adjusted means for each outcome by categorised cigarettes/day, smoking duration and pack-years. RESULTS: 10 187 subjects were included. For FEV/FVC, standardised beta coefficient for smoking duration was greater than for cigarettes/day and pack-years (P<0.001). After categorisation, there was a linear increase in adjusted means FEV/FVC with increase in pack-years (regression coefficient β=-0.023±SE0.003; P=0.003) and duration over all ranges of smoking cigarettes/day (β=-0.041±0.004; P<0.001) but a relatively flat slope for cigarettes/day across all ranges of smoking duration (β=-0.009±0.0.009; P=0.34). Strength of association of duration was similarly greater than pack-years for emphysema, gas trapping, FEV, 6MWD and SGRQ. CONCLUSION: Smoking duration alone provides stronger risk estimates of COPD than the composite index of pack-years. TRIAL REGISTRATION NUMBER: Post-results; NCT00608764.