Few studies have examined associations between long-term exposure to fine particulate matter (PM2.5) and lung function decline in adults.
To determine if exposure to traffic and PM2.5 is associated ...with longitudinal changes in lung function in a population-based cohort in the Northeastern United States, where pollution levels are relatively low.
FEV1 and FVC were measured up to two times between 1995 and 2011 among 6,339 participants of the Framingham Offspring or Third Generation studies. We tested associations between residential proximity to a major roadway and PM2.5 exposure in 2001 (estimated by a land-use model using satellite measurements of aerosol optical thickness) and lung function. We examined differences in average lung function using mixed-effects models and differences in lung function decline using linear regression models. Current smokers were excluded. Models were adjusted for age, sex, height, weight, pack-years, socioeconomic status indicators, cohort, time, season, and weather.
Living less than 100 m from a major roadway was associated with a 23.2 ml (95% confidence interval CI, -44.4 to -1.9) lower FEV1 and a 5.0 ml/yr (95% CI, -9.0 to -0.9) faster decline in FEV1 compared with more than 400 m. Each 2 μg/m(3) increase in average of PM2.5 was associated with a 13.5 ml (95% CI, -26.6 to -0.3) lower FEV1 and a 2.1 ml/yr (95% CI, -4.1 to -0.2) faster decline in FEV1. There were similar associations with FVC. Associations with FEV1/FVC ratio were weak or absent.
Long-term exposure to traffic and PM2.5, at relatively low levels, was associated with lower FEV1 and FVC and an accelerated rate of lung function decline.
Short-term exposure to ambient air pollution has been associated with lower lung function. Few studies have examined whether these associations are detectable at relatively low levels of pollution ...within current U.S. Environmental Protection Agency (EPA) standards.
To examine exposure to ambient air pollutants within EPA standards and lung function in a large cohort study.
We included 3,262 participants of the Framingham Offspring and Third Generation cohorts living within 40 km of the Harvard Supersite monitor in Boston, Massachusetts (5,358 examinations, 1995-2011) who were not current smokers, with previous-day pollutant levels in compliance with EPA standards. We compared lung function (FEV1 and FVC) after previous-day exposure to particulate matter less than 2.5 μm in diameter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) in the "moderate" range of the EPA Air Quality Index to exposure in the "good" range. We also examined linear relationships between moving averages of pollutant concentrations 1, 2, 3, 5, and 7 days before spirometry and lung function.
Exposure to pollutant concentrations in the "moderate" range of the EPA Air Quality Index was associated with a 20.1-ml lower FEV1 for PM2.5 (95% confidence interval CI, -33.4, -6.9), a 30.6-ml lower FEV1 for NO2 (95% CI, -60.9, -0.2), and a 55.7-ml lower FEV1 for O3 (95% CI, -100.7, -10.8) compared with the "good" range. The 1- and 2-day moving averages of PM2.5, NO2, and O3 before testing were negatively associated with FEV1 and FVC.
Short-term exposure to PM2.5, NO2, and O3 within current EPA standards was associated with lower lung function in this cohort of adults.
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.
Despite substantial progress in reducing the global impact of many non-communicable diseases, including heart disease and cancer, morbidity and mortality due to chronic respiratory disease continues ...to increase. Many factors have contributed to what must now be considered a public health emergency: failure to limit the sale and consumption of tobacco products, unchecked exposure to environmental pollutants across the life course, and the ageing of the global population (partly as a result of improved outcomes for other conditions). In particular, we advocate for: broader understanding of risk factors (including the devastating effects of global poverty) and the preventive measures necessary to avoid future cases of COPD, disruptive approaches to diagnosis that are not solely based on spirometric airflow limitation but also involve identification of early pathological changes that are more amenable to reversal, classification of the disease into types that share pathophysiological similarities and could lead to novel preventive and therapeutic approaches, and a new approach to the diagnosis and assessment of exacerbations of COPD that focuses on disease mechanisms. An acute worsening of COPD is termed an exacerbation, and such episodes account for a substantial proportion of the attributable cost of the disease and are associated with accelerated lung function loss, prolonged impairments in quality of life, and similar prognosis to many stage III or IV solid organ malignancies.
We provide a single-cell atlas of idiopathic pulmonary fibrosis (IPF), a fatal interstitial lung disease, by profiling 312,928 cells from 32 IPF, 28 smoker and nonsmoker controls, and 18 chronic ...obstructive pulmonary disease (COPD) lungs. Among epithelial cells enriched in IPF, we identify a previously unidentified population of aberrant basaloid cells that coexpress basal epithelial, mesenchymal, senescence, and developmental markers and are located at the edge of myofibroblast foci in the IPF lung. Among vascular endothelial cells, we identify an ectopically expanded cell population transcriptomically identical to bronchial restricted vascular endothelial cells in IPF. We confirm the presence of both populations by immunohistochemistry and independent datasets. Among stromal cells, we identify IPF myofibroblasts and invasive fibroblasts with partially overlapping cells in control and COPD lungs. Last, we confirm previous findings of profibrotic macrophage populations in the IPF lung. Our comprehensive catalog reveals the complexity and diversity of aberrant cellular populations in IPF.
Deep learning is a powerful tool that may allow for improved outcome prediction.
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.
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.
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).
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.
The relationship between the development and/or progression of interstitial lung abnormalities (ILA) and clinical outcomes has not been previously investigated.
To determine the risk factors for, and ...the clinical consequences of, having ILA progression in participants from the Framingham Heart Study.
ILA were assessed in 1,867 participants who had serial chest computed tomography (CT) scans approximately 6 years apart. Mixed effect regression (and Cox) models were used to assess the association between ILA progression and pulmonary function decline (and mortality).
During the follow-up period 660 (35%) participants did not have ILA on either CT scan, 37 (2%) had stable to improving ILA, and 118 (6%) had ILA with progression (the remaining participants without ILA were noted to be indeterminate on at least one CT scan). Increasing age and increasing copies of the MUC5B promoter polymorphism were associated with ILA progression. After adjustment for covariates, ILA progression was associated with a greater FVC decline when compared with participants without ILA (20 ml; SE, ±6 ml; P = 0.0005) and with those with ILA without progression (25 ml; SE, ±11 ml; P = 0.03). Over a median follow-up time of approximately 4 years, after adjustment, ILA progression was associated with an increase in the risk of death (hazard ratio, 3.9; 95% confidence interval, 1.3-10.9; P = 0.01) when compared with those without ILA.
These findings demonstrate that ILA progression in the Framingham Heart Study is associated with an increased rate of pulmonary function decline and increased risk of death.
: This document provides clinical recommendations for the pharmacologic treatment of chronic obstructive pulmonary disease (COPD). It represents a collaborative effort on the part of a panel of ...expert COPD clinicians and researchers along with a team of methodologists under the guidance of the American Thoracic Society.
: Comprehensive evidence syntheses were performed on all relevant studies that addressed the clinical questions and critical patient-centered outcomes agreed upon by the panel of experts. The evidence was appraised, rated, and graded, and recommendations were formulated using the Grading of Recommendations, Assessment, Development, and Evaluation approach.
: After weighing the quality of evidence and balancing the desirable and undesirable effects, the guideline panel made the following recommendations:
) a strong recommendation for the use of long-acting β
-agonist (LABA)/long-acting muscarinic antagonist (LAMA) combination therapy over LABA or LAMA monotherapy in patients with COPD and dyspnea or exercise intolerance;
) a conditional recommendation for the use of triple therapy with inhaled corticosteroids (ICS)/LABA/LAMA over dual therapy with LABA/LAMA in patients with COPD and dyspnea or exercise intolerance who have experienced one or more exacerbations in the past year;
) a conditional recommendation for ICS withdrawal for patients with COPD receiving triple therapy (ICS/LABA/LAMA) if the patient has had no exacerbations in the past year;
) no recommendation for or against ICS as an additive therapy to long-acting bronchodilators in patients with COPD and blood eosinophilia, except for those patients with a history of one or more exacerbations in the past year requiring antibiotics or oral steroids or hospitalization, for whom ICS is conditionally recommended as an additive therapy;
) a conditional recommendation against the use of maintenance oral corticosteroids in patients with COPD and a history of severe and frequent exacerbations; and
) a conditional recommendation for opioid-based therapy in patients with COPD who experience advanced refractory dyspnea despite otherwise optimal therapy.
: The task force made recommendations regarding the pharmacologic treatment of COPD based on currently available evidence. Additional research in populations that are underrepresented in clinical trials is needed, including studies in patients with COPD 80 years of age and older, those with multiple chronic health conditions, and those with a codiagnosis of COPD and asthma.
The Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study, which began in 2007, is an ongoing multicenter observational cohort study of more than 10,000 current and former ...smokers. The study is aimed at understanding the etiology, progression, and heterogeneity of chronic obstructive pulmonary disease (COPD). In addition to genetic analysis, the participants have been extensively characterized by clinical questionnaires, spirometry, volumetric inspiratory and expiratory computed tomography, and longitudinal follow-up, including follow-up computed tomography at 5 years after enrollment. The purpose of this state-of-the-art review is to summarize the major advances in our understanding of COPD resulting from the imaging findings in the COPDGene study. Imaging features that are associated with adverse clinical outcomes include early interstitial lung abnormalities, visual presence and pattern of emphysema, the ratio of pulmonary artery to ascending aortic diameter, quantitative evaluation of emphysema, airway wall thickness, and expiratory gas trapping. COPD is characterized by the early involvement of the small conducting airways, and the addition of expiratory scans has enabled measurement of small airway disease. Computational advances have enabled indirect measurement of nonemphysematous gas trapping. These metrics have provided insights into the pathogenesis and prognosis of COPD and have aided early identification of disease. Important quantifiable extrapulmonary findings include coronary artery calcification, cardiac morphology, intrathoracic and extrathoracic fat, and osteoporosis. Current active research includes identification of novel quantitative measures for emphysema and airway disease, evaluation of dose reduction techniques, and use of deep learning for phenotyping COPD.
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