{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T11:45:20Z","timestamp":1793101520500,"version":"4.5.0"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T00:00:00Z","timestamp":1721174400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T00:00:00Z","timestamp":1721174400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur Radiol"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To assess the performance of breast cancer screening by category of breast density and age in a UK screening cohort.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Raw full-field digital mammography data from a single site in the UK, forming a consecutive 3-year cohort of women aged 50 to 70 years from 2016 to 2018, were obtained retrospectively. Breast density was assessed using Volpara software. Examinations were grouped by density category and age group (50\u201360 and 61\u201370 years) to analyse screening performance. Statistical analysis was performed to determine the association between density categories and age groups. Volumetric breast density was assessed as a binary classifier of interval cancers (ICs) to find an optimal density threshold.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Forty-nine thousand nine-hundred forty-eight screening examinations (409 screen-detected cancers (SDCs) and 205 ICs) were included in the analysis. Mammographic sensitivity, SDC\/(SDC\u2009+\u2009IC), decreased with increasing breast density from 75.0% for density a (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.839, comparisons made to category b), to 73.5%, 59.8% (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.001), and 51.3% (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001) in categories b, c, and d, respectively. IC rates were highest in the densest categories with rates of 1.8 (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.039), 3.2, 5.7 (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001), and 7.9 (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001) per thousand for categories a, b, c, and d, respectively. The recall rate increased with breast density, leading to more false positive recalls, especially in the younger age group. There was no significant difference between the optimal density threshold found, 6.85, and that Volpara defined as the b\/c boundary, 7.5.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The performance of screening is significantly reduced with increasing density with IC rates in the densest category four times higher than in women with fatty breasts. False positives are a particular issue for the younger subgroup without prior examinations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Clinical relevance statement<\/jats:title>\n                    <jats:p>In women attending screening there is significant underdiagnosis of breast cancer in those with dense breasts, most marked in the highest density category but still three times higher than in women with fatty breasts in the second highest category.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>\n                            <jats:italic>Breast density can mask cancers leading to underdiagnosis on mammography.<\/jats:italic>\n                          <\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>\n                            <jats:italic>Interval cancer rate increased with breast density categories \u2018a\u2019 to \u2018d\u2019; 1.8 to 7.9 per thousand.<\/jats:italic>\n                          <\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>\n                            <jats:italic>Recall rates increased with increasing breast density, leading to more false positive recalls.<\/jats:italic>\n                          <\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00330-024-10951-w","type":"journal-article","created":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T06:01:58Z","timestamp":1721196118000},"page":"177-187","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":56,"title":["Breast density effect on the sensitivity of digital screening mammography in a UK cohort"],"prefix":"10.1007","volume":"35","author":[{"given":"Nicholas R.","family":"Payne","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarah E.","family":"Hickman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Black","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew N.","family":"Priest","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sue","family":"Hudson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0124-9962","authenticated-orcid":false,"given":"Fiona J.","family":"Gilbert","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,7,17]]},"reference":[{"key":"10951_CR1","doi-asserted-by":"publisher","first-page":"2087","DOI":"10.1016\/S0140-6736(05)67887-7","volume":"366","author":"M Clarke","year":"2005","unstructured":"Clarke M, Collins R, Darby S et al (2005) Effects of radiotherapy and of differences in the extent of surgery for early breast cancer on local recurrence and 15-year survival: an overview of the randomised trials. 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Additionally, FJG, NRP, and SEH have research agreements with iCAD, Lunit, Merantix, ScreenPoint Medical, Therapixel, and Volpara.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"One of the authors has significant statistical expertise.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Statistics and biometry"}},{"value":"Written informed consent was waived by the Institutional Review Board, however efforts were made to publicise the use of the data including signposting to the ability to opt-out.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Health Research Authority (HRA) Research Ethics Committee 20\/LO\/0104, HRA Confidentially Advisory Group (CAG) 20\/CAG\/0009, and Public Health England Research Advisory Committee BSPRAC_090.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"No overlap exists for studies on breast density. However, a subset of the cohort has been used in a separate study of breast cancer AI tools which is in press (\u201cArtificial intelligence system prompt accuracy for interval breast cancer detection in screening mammography,\u201d forthcoming in RADIOLOGY).","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Study subjects or cohorts overlap"}},{"order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}