ArticleJournal of medical radiation sciences2020
Full-field digital mammography: the '30% rule' and influences on visualisation of the pectoralis major muscle on the craniocaudal view of the breast.
Article in Journal of medical radiation sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Comparison of two automated PGMI-based software tools for breast positioning quality assessment in DBT screening.European radiology experimental · 2026Article
- Automated Software Evaluation in Screening Mammography: A Scoping Review of Image Quality and Technique Assessment.Current oncology (Toronto, Ont.) · 2025Article
- Full-field digital mammography: the '30% rule' and influences on visualisation of the pectoralis major muscle on the craniocaudal view of the breast.Journal of medical radiation sciences · 2020Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
introductionTo investigate compliance to the '30% rule' and key factors which may influence visualisation of the pectoralis major muscle (PMM) on the craniocaudal (CC) view of the breast.
methodsA retrospective review of 2688 paired full-field digital mammography (FFDM) CC view mammograms of women attending BreastScreen NSW between August and October 2015 was undertaken. PMM visualisation and measurements of PMM width and length, compressed breast thickness, the posterior nipple line (PNL) and age were recorded. Statistical analysis was performed using descriptive and inferential statistics to investigate associations between key breast measurements, age and PMM visualisation.
resultsPMM visualisation was reported in 10.4% of images unilaterally (one breast, left or right only), 14.1% bilaterally (both left and right breasts) and 24.5% overall (unilateral and bilateral combined). There was little or no correlations between PMM length or width and age, breast compressed thickness or PNL. Multiple logistic regression analysis found that up to 15% of the variance in visualisation of the PMM was accounted for by the predictors overall. While some predictors provided a statistically significant contribution to the model, the contribution was small and the odds ratio for all predictors approximated 1.
conclusionThis research could not replicate the '30% rule', and visualisation of the PMM was determined not to be influenced by the variables investigated. The significance of the 'rule' itself must be challenged where the vast majority of images (70-85%) do not comply, and there is no requirement for repeat imaging if the 'rule' is not met. Further research should be undertaken to validate this study including analysis of diagnostic images for comparison.
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