ArticleThe British journal of radiology2017
An investigation into the mammographic appearances of missed breast cancers when recall rates are reduced.
Article in The British journal of radiology, 2017. 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.
- Impact of Prior Mammograms on Radiologists and Radiographers' Detection of Different Breast Cancer Lesion Types.Journal of medical radiation sciences · 2025Article
- Radiomic analysis of cohort-specific diagnostic errors in reading dense mammograms using artificial intelligence.The British journal of radiology · 2025Article
- Using Radiomics-Based Machine Learning to Create Targeted Test Sets to Improve Specific Mammography Reader Cohort Performance: A Feasibility Study.Journal of personalized medicine · 2023Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study investigated whether certain mammographic appearances of breast cancer are missed when radiologists read at lower recall rates.
methods5 radiologists read 1 identical test set of 200 mammographic (180 normal cases and 20 abnormal cases) 3 times and were requested to adhere to 3 different recall rate conditions: free recall, 15% and 10%. The radiologists were asked to mark the locations of suspicious lesions and provide a confidence rating for each decision. An independent expert radiologist identified the various types of cancers in the test set, including the presence of calcifications and the lesion location, including specific mammographic density.
resultsRadiologists demonstrated lower sensitivity and receiver operating characteristic area under the curve for non-specific density/asymmetric density (H = 6.27, p = 0.04 and H = 7.35, p = 0.03, respectively) and mixed features (H = 9.97, p = 0.01 and H = 6.50, p = 0.04, respectively) when reading at 15% and 10% recall rates. No significant change was observed on cancer characterized with stellate masses (H = 3.43, p = 0.18 and H = 1.23, p = 0.54, respectively) and architectural distortion (H = 0.00, p = 1.00 and H = 2.00, p = 0.37, respectively). Across all recall conditions, stellate masses were likely to be recalled (90.0%), whereas non-specific densities were likely to be missed (45.6%).
conclusionCancers with a stellate mass were more easily detected and were more likely to continue to be recalled, even at lower recall rates. Cancers with non-specific density and mixed features were most likely to be missed at reduced recall rates. Advances in knowledge: Internationally, recall rates vary within screening mammography programs considerably, with a range between 1% and 15%, and very little is known about the type of breast cancer appearances found when radiologists interpret screening mammograms at these various recall rates. Therefore, understanding the lesion types and the mammographic appearances of breast cancers that are affected by readers' recall decisions should be investigated.
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