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dc.contributor.authorLarsen, Marthe
dc.contributor.authorOlstad, Camilla Flåt
dc.contributor.authorKoch, Henrik Wethe
dc.contributor.authorMartiniussen, Marit Almenning
dc.contributor.authorHoff, Solveig Kristin Roth
dc.contributor.authorLund-Hanssen, Håkon
dc.contributor.authorSolli, Helene
dc.contributor.authorMikalsen, Karl Øyvind
dc.contributor.authorAuensen, Steinar
dc.contributor.authorNygård, Jan Franz
dc.contributor.authorLång, Kristina
dc.contributor.authorChen, Yan
dc.contributor.authorHofvind, Solveig Sand-Hanssen
dc.date.accessioned2024-02-21T11:32:27Z
dc.date.available2024-02-21T11:32:27Z
dc.date.created2023-11-21T14:39:38Z
dc.date.issued2023
dc.identifier.citationLarsen, M., Olstad, C. F., Koch, H. W., Martiniussen, M. A., Hoff, S. R., Lund-Hanssen, H., ... & Hofvind, S. (2023). AI risk score on screening mammograms preceding breast cancer diagnosis. Radiology, 309(1), e230989.en_US
dc.identifier.issn0033-8419
dc.identifier.urihttps://hdl.handle.net/11250/3118964
dc.description.abstractMore than 38% of both screen-detected and interval cancers were assigned the highest artificial intelligence risk score on screening mammograms that preceded breast cancer diagnosis. Background Few studies have evaluated the role of artificial intelligence (AI) in prior screening mammography. Purpose To examine AI risk scores assigned to screening mammography in women who were later diagnosed with breast cancer. Materials and Methods Image data and screening information of examinations performed from January 2004 to December 2019 as part of BreastScreen Norway were used in this retrospective study. Prior screening examinations from women who were later diagnosed with cancer were assigned an AI risk score by a commercially available AI system (scores of 1–7, low risk of malignancy; 8–9, intermediate risk; and 10, high risk of malignancy). Mammographic features of the cancers based on the AI score were also assessed. The association between AI score and mammographic features was tested with a bivariate test. Results A total of 2787 prior screening examinations from 1602 women (mean age, 59 years ± 5.1 [SD]) with screen-detected (n = 1016) or interval (n = 586) cancers showed an AI risk score of 10 for 389 (38.3%) and 231 (39.4%) cancers, respectively, on the mammograms in the screening round prior to diagnosis. Among the screen-detected cancers with AI scores available two screening rounds (4 years) before diagnosis, 23.0% (122 of 531) had a score of 10. Mammographic features were associated with AI score for invasive screen-detected cancers (P < .001). Density with calcifications was registered for 13.6% (43 of 317) of screen-detected cases with a score of 10 and 4.6% (15 of 322) for those with a score of 1–7. Conclusion More than one in three cases of screen-detected and interval cancers had the highest AI risk score at prior screening, suggesting that the use of AI in mammography screening may lead to earlier detection of breast cancers.en_US
dc.language.isoengen_US
dc.publisherRadiological Society of Americaen_US
dc.titleAI Risk Score on Screening Mammograms Preceding Breast Cancer Diagnosisen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.rights.holderThe authorsen_US
dc.subject.nsiVDP::Medisinske Fag: 700en_US
dc.source.volume309en_US
dc.source.journalRadiologyen_US
dc.source.issue1en_US
dc.identifier.doi10.1148/radiol.230989
dc.identifier.cristin2199746
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2


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