ArticleBreast cancer research and treatment2017
Volumetric breast density affects performance of digital screening mammography.
Article in Breast cancer research and treatment, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 3 of them syntheses that pooled it.
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Who cites it
80 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Supplemental Screening as an Adjunct to Mammography for Breast Cancer Screening in People With Dense Breasts: A Health Technology Assessment.Ontario health technology assessment series · 2023Pooled it
- Mammographic breast density and the risk of breast cancer: A systematic review and meta-analysis.Breast (Edinburgh, Scotland) · 2022Pooled it
- The impact of patient characteristics and lifestyle factors on the risk of an ipsilateral event after a primary DCIS: A systematic review.Breast (Edinburgh, Scotland) · 2020Pooled it
- Re-attendance in supplemental breast MRI screening rounds of the DENSE trial for women with extremely dense breasts.European radiology · 2024Trial
- Comparison of three algorithms to measure breast density on mammograms in a population-based screening cohort.European radiology · 2026Article
- Traumatic breast pseudohernia presenting as a fungating mass during lactation: Multimodality imaging findings.Radiology case reports · 2026Article
- Cost-effectiveness of abbreviated breast MRI and contrast-enhanced mammography for women with extremely dense breasts in a national breast cancer screening program: a micro-simulation study.Breast (Edinburgh, Scotland) · 2026Article
- Adapted foundation models for breast MRI triaging in contrast-enhanced and non-contrast-enhanced protocols.European radiology · 2026Article
- Bridging the gap: clinical practice, guidelines, reimbursement and real-world challenges in breast imaging - webinar highlights.Future oncology (London, England) · 2026Article
- Article
- Supplemental Breast Ultrasound in Mammography Screening for Women with Critically Dense Breasts.Cancers · 2026Article
- Leveraging deep learning to infer continuous predictions from ordinal labels in medical imaging.PLOS digital health · 2026Article
- Advances in the study of the breast carcinoma exosomal microRNAs: From basic mechanisms to clinical applications (Review).International journal of oncology · 2026Review
- Review
- Article
- Application of CAD Systems in Breast Cancer Diagnosis Using Machine Learning Techniques: An Overview of Systematic Reviews.Bioengineering (Basel, Switzerland) · 2025Review
- Assessing the generalisation of artificial intelligence across mammography manufacturers.PLOS digital health · 2025Article
- Cancer screening in patients with acromegaly: a plea for a personalized approach and international registries.Reviews in endocrine & metabolic disorders · 2025Review
- Personalized screening based on risk and density: prevalence data from the RIBBS study.La Radiologia medica · 2025Observational
- Scanning K-edge subtraction (SKES) imaging with laser-compton x-ray sources.Medical physics · 2025Article
20 more citing papers are in PubMed but not listed here.
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8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo determine to what extent automatically measured volumetric mammographic density influences screening performance when using digital mammography (DM).
methodsWe collected a consecutive series of 111,898 DM examinations (2003-2011) from one screening unit of the Dutch biennial screening program (age 50-75 years). Volumetric mammographic density was automatically assessed using Volpara. We determined screening performance measures for four density categories comparable to the American College of Radiology (ACR) breast density categories.
resultsOf all the examinations, 21.6% were categorized as density category 1 ('almost entirely fatty') and 41.5, 28.9, and 8.0% as category 2-4 ('extremely dense'), respectively. We identified 667 screen-detected and 234 interval cancers. Interval cancer rates were 0.7, 1.9, 2.9, and 4.4‰ and false positive rates were 11.2, 15.1, 18.2, and 23.8‰ for categories 1-4, respectively (both p-trend < 0.001). The screening sensitivity, calculated as the proportion of screen-detected among the total of screen-detected and interval tumors, was lower in higher density categories: 85.7, 77.6, 69.5, and 61.0% for categories 1-4, respectively (p-trend < 0.001).
conclusionsVolumetric mammographic density, automatically measured on digital mammograms, impacts screening performance measures along the same patterns as established with ACR breast density categories. Since measuring breast density fully automatically has much higher reproducibility than visual assessment, this automatic method could help with implementing density-based supplemental screening.
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