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Updated: Jun 15, 2026

A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
Comparing film and digital radiographs for reliability of pneumoconiosis classifications: a modeling approach
Ananda Sen1, Shih-Yuan Lee, Brenda W Gillespie
1Center for Statistical Consultation and Research, University of Michigan, Ann Arbor, MI, USA.
Rationale And Objectives:
The International Labour Office (ILO) system for classifying chest radiographic changes related to inhalation of pathogenic dusts is predicated on film-screen radiography. Digital radiography has replaced film in many centers. Digital images can be printed on film ("hard copy") or can be viewed at a computer workstation ("soft copy"). The goal of the present investigation was to compare the inter-reader and intra-reader agreement of ILO classifications for pneumoconiosis across image formats.
Materials And Methods:
Traditional film radiographs, hard copy digital images, and soft copy digital images from 107 subjects were read by six B readers. A multiple reader version of the inter-reader kappa statistic was compared across image formats. Intra-reader kappa comparisons were carried out using an iterative least-squares approach (unadjusted analysis) as well as a two-stage regression model adjusting for readers and subject-level covariates.
Results:
There were few significant differences in the inter-reader and intra-reader agreement across formats. For parenchymal abnormalities, inter-reader and intra-reader kappa values ranged from 0.536 to 0.646, and 0.65 to 0.77, respectively. In the covariate-adjusted analysis film-screen radiography was generally associated with a numerically greater reliability (ie, higher kappa values) than the other image formats, although differences were rarely statistically significant.
Conclusion:
Film-screen radiographs, hard copy digital images, and soft copy digital images yielded similar reliability measures. These findings provide further support to the recommendation that soft copy digital images can be used for the recognition and classification of dust-related parenchymal abnormalities using the ILO system.
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