Jeremy T Hua, Carlyne D Cool, Heather A Lowers, Leonard H T Go, Lauren M Zell-Baran, Emily A Sarver, Kirsten S Almberg, Kathy D Pang, Susan M Majka, Angela D Franko, Naseema I Vorajee, Robert A Cohen, Cecile S Rose
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引用次数: 0
Abstract
Context.—: Current approaches for characterizing retained lung dust using pathologists' qualitative assessment or scanning electron microscopy with energy-dispersive spectroscopy (SEM/EDS) have limitations.
Objective.—: To explore polarized light microscopy coupled with image-processing software, termed quantitative microscopy-particulate matter (QM-PM), as a tool to characterize in situ dust in lung tissue of US coal miners with progressive massive fibrosis.
Design.—: We developed a standardized protocol using microscopy images to characterize the in situ burden of birefringent crystalline silica/silicate particles (mineral density) and carbonaceous particles (pigment fraction). Mineral density and pigment fraction were compared with pathologists' qualitative assessments and SEM/EDS analyses. Particle features were compared between historical (born before 1930) and contemporary coal miners, who likely had different exposures following changes in mining technology.
Results.—: Lung tissue samples from 85 coal miners (62 historical and 23 contemporary) and 10 healthy controls were analyzed using QM-PM. Mineral density and pigment fraction measurements with QM-PM were comparable to consensus pathologists' scoring and SEM/EDS analyses. Contemporary miners had greater mineral density than historical miners (186 456 versus 63 727/mm3; P = .02) and controls (4542/mm3), consistent with higher amounts of silica/silicate dust. Contemporary and historical miners had similar particle sizes (median area, 1.00 versus 1.14 μm2; P = .46) and birefringence under polarized light (median grayscale brightness: 80.9 versus 87.6; P = .29).
Conclusions.—: QM-PM reliably characterizes in situ silica/silicate and carbonaceous particles in a reproducible, automated, accessible, and time/cost/labor-efficient manner, and shows promise as a tool for understanding occupational lung pathology and targeting exposure controls.
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