A mammography image set for research purposes using BI-RADS density classification

Mercer, CE ORCID: https://orcid.org/0000-0002-7848-3036, Hogg, P ORCID: https://orcid.org/0000-0002-6506-0827, Kelly, J, Borgan, R, Millington, S, Hilton, B, Enion, D and Wheelan, P 2014, 'A mammography image set for research purposes using BI-RADS density classification' , Radiologic Technology, 85 (6) , pp. 609-613.

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Purpose Breast density categorization consistency is important when performing research, and minimization of interoperator and intraoperator variability is essential. This research aimed to validate a set of mammography images for visual breast density estimation to achieve consistency in future research projects and to determine observer performance. Methods Using the Breast Imaging Reporting and Data System (BI-RADS) as the visual grading scale, 50 mammography images were scored for density grade by 8 observers. Results Six of 8 observers achieved near-complete intraobserver agreement (kappa  0.81). Strong agreement among observers (kappa  0.61-0.8) was found in 10 of 28 paired observation episodes on the first iteration and 12 of 28 on the second. No observers demonstrated a delta variance above 1. Fleiss’ kappa was used to evaluate concordance among all observers on the first and second iterations (first iteration, 0.64; second iteration, 0.56). Discussion This research illustrates the difficulties of comparing observer visual performance scores because differences can exist when studies are repeated by and among individuals. Conclusion We confirmed that the 50 images were suitable for research purposes. Some variability existed among observers; however, overall density classification agreement was strong. Future research should include repeating this study with digitally acquired images.

Item Type: Article
Themes: Health and Wellbeing
Schools: Schools > School of Health and Society > Centre for Health Sciences Research
Journal or Publication Title: Radiologic Technology
Publisher: American Society of Radiologic Technologists
Refereed: Yes
ISSN: 0033-8397
Related URLs:
Funders: Non funded research
Depositing User: P Hogg
Date Deposited: 27 Nov 2014 16:39
Last Modified: 15 Feb 2022 18:50
URI: https://usir.salford.ac.uk/id/eprint/33187

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