{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T20:08:36Z","timestamp":1787342916560,"version":"build-2736575974"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2024,2,23]],"date-time":"2024-02-23T00:00:00Z","timestamp":1708646400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,2,23]],"date-time":"2024-02-23T00:00:00Z","timestamp":1708646400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100007465","name":"UiT The Arctic University of Norway","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100007465","id-type":"DOI","asserted-by":"crossref"}]}],"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 compare the location of AI markings on screening mammograms with cancer location on diagnostic mammograms, and to classify interval cancers with high AI score as false negative, minimal sign, or true negative.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In a retrospective study from 2022, we compared the performance of an AI system with independent double reading according to cancer detection. We found 93% (880\/949) of the screen-detected cancers, and 40% (122\/305) of the interval cancers to have the highest AI risk score (AI score of 10). In this study, four breast radiologists reviewed mammograms from 126 randomly selected screen-detected cancers and all 120 interval cancers with an AI score of 10. The location of the AI marking was stated as correct\/not correct in craniocaudal and mediolateral\u00a0oblique view. Interval cancers with an AI score of 10 were classified as false negative, minimal sign significant\/non-specific, or true negative.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>All screen-detected cancers and 78% (93\/120) of the interval cancers with an AI score of 10 were correctly located by the\u00a0AI\u00a0system. The AI markings matched in both views for 79% (100\/126) of the screen-detected cancers and 22% (26\/120) of the interval cancers. For interval cancers with an AI score of 10, 11% (13\/120) were correctly located and classified as false negative, 10% (12\/120) as minimal sign significant, 26% (31\/120) as minimal sign non-specific, and 31% (37\/120) as true negative.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>AI markings corresponded to cancer location for all screen-detected cancers and 78% of the interval cancers\u00a0with\u00a0high\u00a0AI score, indicating a potential for reducing the number of interval cancers. However, it is uncertain whether interval cancers with subtle findings in only one view are actionable for recall in a true screening setting.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Clinical relevance statement<\/jats:title>\n                    <jats:p>In this study, AI markings corresponded to the location of the\u00a0cancer in a high percentage of cases, indicating that the AI system accurately identifies the cancer location in mammograms with a high AI score.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:italic>\u2022 All screen-detected and 78% of the interval cancers with high AI risk score (AI score of 10) had AI markings in one or two views corresponding to the location of the cancer on diagnostic images.<\/jats:italic>\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:italic>\u2022 Among all 120 interval cancers with an AI score of 10, 21% (25\/120) were classified as a false negative or minimal sign significant and had AI markings matching the cancer location, suggesting they may be visible on prior screening.<\/jats:italic>\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:italic>\u2022 Most of the correctly located interval cancers matched only in one view, and the majority were classified as either true negative or minimal sign non-specific, indicating low potential for being detected earlier in a real screening setting.<\/jats:italic>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00330-024-10662-2","type":"journal-article","created":{"date-parts":[[2024,2,23]],"date-time":"2024-02-23T14:02:19Z","timestamp":1708696939000},"page":"6158-6167","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["How do AI markings on screening mammograms correspond to cancer location? An informed review of 270 breast cancer cases in BreastScreen Norway"],"prefix":"10.1007","volume":"34","author":[{"given":"Henrik Wethe","family":"Koch","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marthe","family":"Larsen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hauke","family":"Bartsch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marit Almenning","family":"Martiniussen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bodil Margrethe","family":"Styr","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siri","family":"Fagerheim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ingfrid Helene Salvesen","family":"Haldorsen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0178-8939","authenticated-orcid":false,"given":"Solveig","family":"Hofvind","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,2,23]]},"reference":[{"key":"10662_CR1","doi-asserted-by":"publisher","first-page":"209","DOI":"10.3322\/caac.21660","volume":"71","author":"H Sung","year":"2021","unstructured":"Sung H, Ferlay J, Siegel RL et al (2021) Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. 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The study was approved by the Regional Committee for Medical and Health Research Ethics (#13294).","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"A retrospective study of screening examinations performed in Rogaland, as a part of BreastScreen Norway 2010\u20132018 was the basis for this study: Koch HW, Larsen M, Bartsch H, Kurz KD, Hofvind S (2023) Artificial intelligence in BreastScreen Norway: a retrospective analysis of a cancer-enriched sample including 1254 breast cancer cases. Eur Radiol 33:3735\u20133743. The submitted study is a follow-up study of the paper in Eur Radiol, aimed at providing a deeper understanding of the validity of the AI markings on screening mammograms.","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Study subjects or cohorts overlap"}},{"value":"\u2022 an informed review of screening and diagnostic mammograms\u2022 retrospective\u2022 registry study \/ observational study\u2022 performed at one institution","order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}