{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T09:15:06Z","timestamp":1791969306488,"version":"4.3.4"},"reference-count":20,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T00:00:00Z","timestamp":1752537600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T00:00:00Z","timestamp":1752537600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100005688","name":"Gottfried und Julia Bangerter-Rhyner-Stiftung","doi-asserted-by":"publisher","award":["0152-2023"],"award-info":[{"award-number":["0152-2023"]}],"id":[{"id":"10.13039\/501100005688","id-type":"DOI","asserted-by":"publisher"}]}],"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>Enhance mammography quality to increase cancer detection by implementing continuous AI-driven feedback mechanisms, ensuring reliable, consistent, and high-quality screening by the \u2018Perfect\u2019, \u2018Good\u2019, \u2018Moderate\u2019, and \u2018Inadequate\u2019 (PGMI) criteria.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>\n                      To assess the impact of the AI software \u2018b-box\n                      <jats:sup>TM<\/jats:sup>\n                      \u2019 on mammography quality, we conducted a comparative analysis of PGMI scores. We evaluated scores 50 days before (A) and after the software\u2019s implementation in 2021 (B), along with assessments made in the first week of August 2022 (C1) and 2023 (C2), comparing them to evaluations conducted by two readers. Except for postsurgical patients, we included all diagnostic and screening mammograms from one tertiary hospital.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 4577 mammograms from 1220 women (mean age: 59, range: 21\u201394, standard deviation: 11.18) were included. 1728 images were obtained before (A) and 2330 images after the 2021 software implementation (B), along with 269 images in 2022 (C1) and 250 images in 2023 (C2). The results indicated a significant improvement in diagnostic image quality (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.01). The percentage of \u2018Perfect\u2019 examinations rose from 22.34% to 32.27%, while \u2018Inadequate\u2019 images decreased from 13.31% to 5.41% in 2021, continuing the positive trend with 4.46% and 3.20% \u2018inadequate\u2019 images in 2022 and 2023, respectively (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.01).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Using a reliable software platform to perform AI-driven quality evaluation in real-time has the potential to make lasting improvements in image quality, support radiographers\u2019 professional growth, and elevate institutional quality standards and documentation simultaneously.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Question<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>How can AI-powered quality assessment reduce inadequate mammographic quality, which is known to impact sensitivity and increase the risk of interval cancers<\/jats:italic>\n                      ?\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Findings<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>AI implementation decreased \u2018inadequate\u2019 mammograms from 13.31% to 3.20% and substantially improved parenchyma visualization, with consistent subgroup trends<\/jats:italic>\n                      .\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Clinical relevance<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>By reducing \u2018inadequate\u2019 mammograms and enhancing imaging quality, AI-driven tools improve diagnostic reliability and support better outcomes in breast cancer screening<\/jats:italic>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Graphical Abstract<\/jats:title>\n                  <\/jats:sec>","DOI":"10.1007\/s00330-025-11812-w","type":"journal-article","created":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T15:29:36Z","timestamp":1752593376000},"page":"55-63","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Enhancing breast positioning quality through real-time AI feedback"],"prefix":"10.1007","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9949-7912","authenticated-orcid":false,"given":"Raphael","family":"Sexauer","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Friederike","family":"Riehle","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karol","family":"Borkowski","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlotta","family":"Ruppert","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Silke","family":"Potthast","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Noemi","family":"Schmidt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,15]]},"reference":[{"key":"11812_CR1","doi-asserted-by":"publisher","first-page":"976","DOI":"10.3390\/cancers12040976","volume":"12","author":"A Dibden","year":"2020","unstructured":"Dibden A, Offman J, Duffy SW, Gabe R (2020) Worldwide review and meta-analysis of cohort studies measuring the effect of mammography screening programmes on incidence-based breast cancer mortality. 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Their involvement was restricted to providing software support and did not affect the research findings. The remaining authors declare no conflicts of interest.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"One of the authors (Raphael Sexauer) has significant statistical expertise; however, no complex statistical methods were necessary for this paper.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Statistics and biometry"}},{"value":"Written informed consent was waived by the Institutional Review Board (retrospective nature).","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Institutional Review Board approval was obtained.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"No study subjects or cohorts have been previously reported.","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Study subjects or cohorts overlap"}},{"order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}