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Patterns of progressive massive fibrosis on modern coal miner chest radiographs.

ABSTRACT: Clinical teaching generally asserts that large opacities of progressive massive fibrosis (PMF) on chest radiographs present primarily bilaterally in the upper lung zones, and with an elevated background profusion of small opacities. However, the contemporary basis for these descriptions is limited.Radiographs taken for the Coal Workers' Health Surveillance Program during 2000-2015 and previously determined to have large opacities ("PMF radiographs", n?=?204), and a random sample previously deemed free of large opacities (n?=22), were independently reevaluated by three National Institute for Occupational Safety and Health (NIOSH) B Readers. Large opacities were noted primarily in the upper right (41%) or upper left (28%) lung zone, but 31% were in middle or lower zones. Unilateral involvement was observed in 34% of readings, with right lung predominance (82%). The median small opacity profusion category for the radiographs with PMF was 2/1. The number of large opacities was not correlated with small opacity profusion category. The "classic" descriptions of PMF as bilateral, associated with elevated background profusions of small pneumoconiotic opacities, were each absent in a third of miners.

SUBMITTER: Halldin CN

PROVIDER: S-EPMC6864224 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Patterns of progressive massive fibrosis on modern coal miner chest radiographs.

Halldin Cara N CN Blackley David J DJ Markle Travis T Cohen Robert A RA Laney A Scott AS

Archives of environmental & occupational health 20190520 3

Clinical teaching generally asserts that large opacities of progressive massive fibrosis (PMF) on chest radiographs present primarily bilaterally in the upper lung zones, and with an elevated background profusion of small opacities. However, the contemporary basis for these descriptions is limited.Radiographs taken for the Coal Workers' Health Surveillance Program during 2000-2015 and previously determined to have large opacities ("PMF radiographs", <i>n</i> = 204), and a random sample previousl ...[more]

PMID: 31107177

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Project description:RATIONALE:There has been a resurgence of progressive massive fibrosis (PMF) in the United States, particularly among central Appalachian miners. OBJECTIVES:We characterized the proportion of PMF among former U.S. coal miners applying for Federal Black Lung Program benefits, 1970-2016. METHODS:Data from the U.S. Department of Labor were used to characterize trends in proportion of PMF cases, defined as an approved black lung claim with a determination of PMF, among all miners who filed for federal benefits between January 1, 1970, and December 31, 2016. Joinpoint, logistic, and linear regression models were used to identify changes in the proportion of claimants with PMF over time. RESULTS:There were 4,679 unique PMF cases among claimants for federal black lung benefits between 1970 and 2016, with 2,474 miners determined to have PMF since 1996. The number of PMF cases among Federal Black Lung Program claimants fell from 404 (0.5% of claimants) in 1978 to a low of 18 cases (0.6%) in 1988, and then increased to 353 cases (8.3%) in 2014. The proportion of federal black lung benefits claimants with PMF has been increasing since 1978 (0.06% annual percent change [APC]; 95% confidence interval [CI], 0.05-0.07%; P < 0.0001), and began increasing at a significantly increased rate after 1996 (0.26% APC; 95% CI, 0.25-0.28%; P < 0.0001). Most miners with PMF (84%) last mined in West Virginia, Kentucky, Pennsylvania, or Virginia. Since 1970, the proportion of claimants with PMF has increased significantly among miners who last worked in Kentucky (16.6% APC; 95% CI, 16.5-16.7%), Pennsylvania (4.7% APC; 95% CI, 4.6-4.8%), Tennessee (16.1% APC; 95% CI, 15.7-16.4%), West Virginia (16.8% APC; 95% CI, 16.6-16.9%), and most sharply among miners last working in Virginia (31.5% APC; 95% CI, 31.2-31.7%), where in 2009, more than 17% of claimants received a PMF determination. The proportion of PMF determinations for the rest of the United States has not exceeded 4%. CONCLUSIONS:There has been a resurgence of PMF, particularly in central Appalachian miners. The resurgence of this preventable disease points to the need for improved primary and secondary prevention of dust-related lung disease in U.S. coal miners.

Project description:IntroductionWhat is known about checklists for interpreting chest radiographs? The question will guide the development of the inclusion criteria for the scoping review. Breaking down the scoping review question will allow the evaluation of inclusion and exclusion criteria for the protocol. The eligibility of the proposed research question will be assessed using the Population or Participants, Concept and Context (PCC) framework.BackgroundX-ray reporting can be standardised using checklists. Checklists may reduce the time needed to produce a comprehensive X-ray report and improve the quality and consistency of detecting abnormalities on chest radiographs. This scoping review aims to map the available literature on what is known about checklists for interpreting chest radiographs.MethodsWe will follow the methodological framework for scoping reviews originally described by Arksey and O'Malley. The scoping review will include articles that describe checklists for reducing diagnostic errors, checklists for analysing chest radiographs, checklists for identifying abnormalities on chest radiographs and checklists for reporting chest radiographs in all settings. Search terms are chest radiographs, checklists, and chest X-rays. We will search for peer-reviewed articles and grey literature including dissertations and theses. We will search online databases including Ovid Medline and Ebscohost, to identify articles published in English from 1994 to 2022. The searched articles will undergo two levels of screening, first the title and abstract screening, then a full-text screening by two reviewers. Data from the selected articles will be extracted, using a tested extraction form and charted using the Joanna Briggs Institute guidelines.ResultsThe results will be collated, summarised and discussed including any limitations of the included articles. The articles will be summarised in a table, as well as narratively. The distribution of studies will be summarised quantitatively and the numerical analysis will provide an overview and identify knowledge gaps. Content analysis will map different checklists available for chest interpretation.DiscussionThe results of the scoping review will be used to develop a checklist that will be used by medical doctors in collaboration with radiographers working in settings where there are no radiologists on-site, for interpreting chest radiographs.Systematic review registrationScoping review protocol registered with Open Science Framework on 27 July 2022. Registration https://doi.org/10.17605/OSF.IO/JS5PQ.

Project description:BackgroundLung cancer is the second most common and the most fatal form of cancer. Although annual low-dose computed tomography is used as the primary method of cancer screening, it presents challenges regarding resources as well as potential health risks from radiation exposure. Chest radiography (CXR), though less effective, is used frequently and commonly. Moreover, often in clinical settings, CXR is the first imaging modality used; computed tomography is subsequently performed if abnormalities are detected on CXRs. This study examined whether controlling for distractors and time constraints, as well as side-by-side comparison of multiple CXRs in clinical settings can aid earlier detection of radiological abnormalities indicative of lung cancer lesions.MethodsThirty-two attending physicians in the Republic of Korea examined 1,750 radiographs of 50 lung cancer cases. Using "hot spot" technology, participants indicated the possible locations of cancer lesions on each radiograph. Subsequently, the same radiographs, cropped to focus the anatomical regions where lung cancers were diagnosed, were shown side-by-side to the participants. The participants were asked to identify the radiograph which first enabled the diagnosis of lung cancer and which first showed a possible lesion.ResultsRemoval of systemic constraints alone significantly improved lesion identification by 221.72±9.69 days. Presenting radiographs side-by-side, cropped to relevant areas, had an additional significant and positive impact on cancer detection in both hidden and open areas on CXRs. Also, lesions were detected at smaller sizes and earlier than when actually diagnosed.ConclusionsCXR with improved methods and settings provides an easily accessible and low-risk imaging method for earlier detection of lung cancer compared to current clinical imaging settings. Further, this study demonstrates the potential effectiveness of programs that allow side-by-side comparisons of cropped areas of multiple radiographs to detect radiological abnormalities.

Project description:ObjectivesThe goal of this study was to assess whether a deep learning estimate of age from a chest radiograph image (CXR-Age) can predict longevity beyond chronological age.BackgroundChronological age is an imperfect measure of longevity. Biological age, a measure of overall health, may improve personalized care. This paper proposes a new way to estimate biological age using a convolutional neural network that takes as input a CXR image and outputs a chest x-ray age (in years) as a measure of long-term mortality risk.MethodsCXR-Age was developed using CXR from 116,035 individuals and validated in 2 held-out testing sets: 1) 75% of the CXR arm of PLCO (Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial) (N = 40,967); and 2) the CXR arm of NLST (National Lung Screening Trial) (N = 5,414). CXR-Age was compared to chronological age and a multivariable regression model of chronological age, risk factors, and radiograph findings to predict all-cause and cardiovascular mortality with a maximum 23 years and 13 years of follow-up, respectively. The primary outcome was observed mortality; results are provided for the testing datasets only.ResultsIn the PLCO testing dataset, a 5-year increase in CXR-Age carried a higher risk of all-cause mortality than a 5-year increase in chronological age (CXR-Age hazard ratio [HR]: 2.26 [95% confidence interval (CI): 2.24 to 2.29] vs. chronological age HR: 1.77 [95% CI: 1.75 to 1.78]; p < 0.001). A similar pattern was found for cardiovascular mortality (CXR-Age cause-specific HR: 2.45 per 5 years [95% CI: 2.34 to 2.56] vs. chronological age HR: 1.82 per 5 years [95% CI: 1.74 to 1.90]). Similar results were seen for both outcomes in the NLST external testing dataset. Adding CXR-Age to the multivariable model resulted in significant improvements for predicting both outcomes in both testing datasets (p < 0.001 for all comparisons).ConclusionsBased on a CXR image, CXR-Age predicted long-term all-cause and cardiovascular mortality.

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Patterns of progressive massive fibrosis on modern coal miner chest radiographs.

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Patterns of progressive massive fibrosis on modern coal miner chest radiographs.

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