Asbestos-induced and Smoking-related Disease: Apportioning Pulmonary Function Deficit by Using Thin-Section CT

Copley, Susan J.; Lee, Gary; Hansell, David M.; Sivakumaran, Pathmanathan; Rubens, Michael B.; Taylor, A J Newman; Rudd, Robin; Musk, A.W.; Wells, Athol U.

doi:10.1148/radiol.2421051167

Cited by 26 publications

(19 citation statements)

References 25 publications

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“…These results are consistent with those from the current investigation in that DL CO values were particularly reduced at baseline, even when most of the other PFTs, including spiromtery, were within the limits of normality. A recent study by Copley et al [2007] illustrates the difficulty in quantifying the severity of asbestos-related lung disease by using PFTs in isolation. The authors found that combined HRCT variables predicted 57% of the variability in DL CO in 133 asbestos-exposed subjects, despite considerable variation in the proportion of coexisting pathologic conditions.…”

Section: Discussionmentioning

confidence: 99%

Lung diffusing capacity relates better to short‐term progression on HRCT abnormalities than spirometry in mild asbestosis

Nogueira

Nápolis

Bagatin

et al. 2010

American J Industrial Med

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Section: Discussionmentioning

confidence: 99%

Lung diffusing capacity relates better to short‐term progression on HRCT abnormalities than spirometry in mild asbestosis

Nogueira

Nápolis

Bagatin

et al. 2010

American J Industrial Med

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“…Such variation has been confirmed in other studies examining lung pattern type, with an interobserver variation of 81% (kappa of 0.48) and a similar intraobserver variation (kappa of 0.37 to 0.78) (7). Other visual scoring system have been suggested by Remy-Jardin et al (8) or Copley et al (9). However, in their studies, the reproducibility of the scoring systems was not assessed and their scoring systems were semi-quantitative methods.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Usual Interstitial Pneumonia and Nonspecific Interstitial Pneumonia: Quantification of Disease Severity and Discrimination between Two Diseases on HRCT Using a Texture-Based Automated System

et al. 2011

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ObjectiveTo evaluate the usefulness of an automated system for quantification and discrimination of usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP).Materials and MethodsAn automated system to quantify six regional high-resolution CT (HRCT) patterns: normal, NL; ground-glass opacity, GGO; reticular opacity, RO; honeycombing, HC; emphysema, EMPH; and consolidation, CONS, was developed using texture and shape features. Fifty-four patients with pathologically proven UIP (n = 26) and pathologically proven NSIP (n = 28) were included as part of this study. Inter-observer agreement in measuring the extent of each HRCT pattern between the system and two thoracic radiologists were assessed in 26 randomly selected subsets using an interclass correlation coefficient (ICC). A linear regression analysis was used to assess the contribution of each disease pattern to the pulmonary function test parameters. The discriminating capacity of the system between UIP and NSIP was evaluated using a binomial logistic regression.ResultsThe overall ICC showed acceptable agreement among the system and the two radiologists (r = 0.895 for the abnormal lung volume fraction, 0.706 for the fibrosis fraction, 0.895 for NL, 0.625 for GGO, 0.626 for RO, 0.893 for HC, 0.800 for EMPH, and 0.430 for CONS). The volumes of NL, GGO, RO, and EMPH contribute to forced expiratory volume during one second (FEV1) (r = 0.72, β values, 0.84, 0.34, 0.34 and 0.24, respectively) and forced vital capacity (FVC) (r = 0.76, β values, 0.82, 0.28, 0.21 and 0.34, respectively). For diffusing capacity (DLco), the volumes of NL and HC were independent contributors in opposite directions (r = 0.65, β values, 0.64, -0.21, respectively). The automated system can help discriminate between UIP and NSIP with an accuracy of 82%.ConclusionThe automated quantification system of regional HRCT patterns can be useful in the assessment of disease severity and may provide reliable agreement with the radiologists' results. In addition, this system may be useful in differentiating between UIP and NSIP.

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“…Pairon et al reported that pleural plaques may be an independent risk factor for lung cancer and could be used as an additional criterion for lung cancer CT screening of high-risk population 2. In a study evaluating asbestos-induced CT findings by Copley et al , pleural plaques showed the best inter-reader agreement (κ=0.88) compared with other findings in the lungs such as traction bronchiectasis, parenchymal bands, coarseness of fibrosis, subpleural lines and interstitial lines 18. Therefore, identification of pleural abnormalities on CT may affect risk stratification and clinical management of patients.…”

Section: Discussionmentioning

confidence: 99%

“…Minor pleural changes are defined as non-specific, slight, focal thickening or irregularities of the pleura that are identifiable on CT. Pleural plaques are defined as well-demarcated areas of pleural thickening, seen as elevated flat or nodular lesions that often contain calcification (figure 1). 17 Diffuse pleural thickening is defined as a continuous sheet of pleural thickening with tapering margins 18. The first reader reviewed all CT scans for the pleural abnormalities.…”

Section: Methodsmentioning

confidence: 99%

Pleural abnormalities in the Framingham Heart Study: prevalence and CT image features

et al. 2017

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Background The prevalence of pleural abnormalities in the general population is an epidemiologically important index of asbestos exposure, which has not been investigated since a radiography-based study in 1980. Methods We examined 2633 chest CT scans (mean 59.2 years, 50% female) from the Framingham Heart Study (FHS) for the presence and image characteristics of pleural plaques and diffuse pleural thickening. Demographics and pulmonary function were stratified by the presence of pleural abnormalities in association with interstitial lung abnormalities (ILA). Results Pleural abnormalities were present in 1.5% (95% CI: 1.1–2.1%). Pleural lesions were most commonly bilateral (90.0%), multiple (77.5%), calcified (97.5%), and commonly involved posterior (lower: 92.5%, middle: 87.5%), anterior (upper: 77.5%, middle: 77.5%), and diaphragmatic areas (72.5%). Participants with pleural abnormalities were significantly older (75.7 years, p<0.0001), male (92.5%, p<0.0001), former or current smokers (80.0%, p<0.001) with higher pack-years (33.3, p<0.0001). No significant reduction was noted in pulmonary function measures (p=0.07–0.94) when adjusted for the associated covariates, likely due to small number of cases with pleural abnormalities. Information about prior history of asbestos exposure and occupation was not available. Conclusions Pleural plaques and diffuse pleural thickening are present on CT in 1.5% of the FHS cohort. The current prevalence of the pleural abnormalities is smaller than that reported in the previous population-based study using chest radiography, likely representing lower asbestos exposure in recent decades. The posterior portion of the pleura is most frequently involved but the anterior portion is also commonly involved.

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Asbestos-induced and Smoking-related Disease: Apportioning Pulmonary Function Deficit by Using Thin-Section CT

Abstract: The proposed CT system provides a semiquantitative method for assessing the relative contribution of asbestos-induced pleuropulmonary disease and smoking-related emphysema to functional impairment.

Cited by 26 publications

References 25 publications

Lung diffusing capacity relates better to short‐term progression on HRCT abnormalities than spirometry in mild asbestosis

Lung diffusing capacity relates better to short‐term progression on HRCT abnormalities than spirometry in mild asbestosis

Comparison of Usual Interstitial Pneumonia and Nonspecific Interstitial Pneumonia: Quantification of Disease Severity and Discrimination between Two Diseases on HRCT Using a Texture-Based Automated System

Pleural abnormalities in the Framingham Heart Study: prevalence and CT image features

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