Literature DB >> 29210092

Comparison of digital and film chest radiography for detection and medical surveillance of silicosis in a setting with a high burden of tuberculosis.

Alfred Franzblau1, Jim teWaterNaude2,3, Ananda Sen1, Hannah d'Arcy1, Jacqueline S Smilg4,5, Khanyakude S Mashao6,7, Cristopher A Meyer8, James E Lockey9, Rodney I Ehrlich3.   

Abstract

BACKGROUND: Continuing use of analog film and digital chest radiography for screening and surveillance for pneumoconiosis and tuberculosis in lower and middle income countries raises questions of equivalence of disease detection. This study compared analog to digital images for intra-rater agreement across formats and prevalence of changes related to silicosis and tuberculosis among South African gold miners using the International Labour Organization classification system.
METHODS: Miners with diverse radiological presentations of silicosis and tuberculosis were recruited. Digital and film chest images on each subject were classified by four expert readers.
RESULTS: Readings of film and soft copy digital images showed no significant differences in prevalence of tuberculosis or silicosis, and intra-rater agreement across formats was fair to good. Hard copy images yielded higher prevalences.
CONCLUSION: Film and digital soft copy images show consistent prevalence of findings, and generally fair to good intra-rater agreement for findings related to silicosis and tuberculosis.
© 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  digital radiographs; pneumoconiosis; silicosis; surveillance; tuberculosis

Mesh:

Year:  2017        PMID: 29210092     DOI: 10.1002/ajim.22803

Source DB:  PubMed          Journal:  Am J Ind Med        ISSN: 0271-3586            Impact factor:   2.214


  2 in total

1.  Accuracy of Computer-Aided Detection of Occupational Lung Disease: Silicosis and Pulmonary Tuberculosis in Ex-Miners from the South African Gold Mines.

Authors:  Rodney Ehrlich; Stephen Barker; Jim Te Water Naude; David Rees; Barry Kistnasamy; Julian Naidoo; Annalee Yassi
Journal:  Int J Environ Res Public Health       Date:  2022-09-29       Impact factor: 4.614

2.  Using Artificial Intelligence for High-Volume Identification of Silicosis and Tuberculosis: A Bio-Ethics Approach.

Authors:  Jerry M Spiegel; Rodney Ehrlich; Annalee Yassi; Francisco Riera; James Wilkinson; Karen Lockhart; Stephen Barker; Barry Kistnasamy
Journal:  Ann Glob Health       Date:  2021-07-01       Impact factor: 2.462

  2 in total

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