Diagnostic performance of two versions of an artificial intelligence system in interval breast cancer detection

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dc.authoridGuner, Davut Can/0000-0003-3141-6175en_US
dc.contributor.authorÇelik, Levent
dc.contributor.authorGuner, Davut Can
dc.contributor.authorÖzcaglayan, Omer
dc.contributor.authorÇubuk, Rahmi
dc.contributor.authorAribal, Mustafa Erkin
dc.date.accessioned2024-07-12T21:37:33Z
dc.date.available2024-07-12T21:37:33Z
dc.date.issued2023en_US
dc.department[Belirlenecek]en_US
dc.description.abstractBackground Various versions of artificial intelligence (AI) have been used as a diagnostic tool aid in the diagnosis of breast cancer. One of the most important problems in breast screening progmrams is interval breast cancer (IBC).Purpose To compare the diagnostic performance of Transpara v1.6 and v1.7 in the detection of IBC.Material and Methods Reports of screening mammograms of a total 2,248,665 of women were evaluated retrospectively. Of 2,129,486 mammograms reported as Breast Imaging Reporting and Data System (BIRADS) 1 and 2, the IBC group consisted of 323 cases who were diagnosed as having cancer on mammography and were correlated with pathology in second mammogram taken >30 days after first mammogram. Four hundred and forty-one were defined as the control group because they did not change over 2 years. Cancer risk scores of both groups were determined from 1 to 10 with Tranpara v1.6 and v1.7. Diagnostic performances of both versions were evaluated by the receiver operating characteristic curve.Results Cancer risk scores 1 and 10 in v1.7 increased compared to v1.6 (P < 0.001). In all cases, sensitivity for v1.6 was 56.6%, specificity was 90%, and, for v1.7, sensitivity was 65.9% and specificity was 90%, respectively. In all cases, area under the curve values were 0.812 for v1.6 and 0.856 for v1.7, which was higher in v1.7 (P < 0.001). Diagnostic performance of v1.7 was higher than v1.6 at the 7-12-month period (P < 0.001).Conclusion The present study showed that Tranpara v1.7 has a higher specificity, sensitivity and diagnostic performance in IBC determination than v1.6. AI systems can be used in breast screening as a secondary or third reader in screening programs.en_US
dc.identifier.doi10.1177/02841851231200785
dc.identifier.endpage2897en_US
dc.identifier.issn0284-1851
dc.identifier.issn1600-0455
dc.identifier.issue11en_US
dc.identifier.pmid37722761en_US
dc.identifier.scopus2-s2.0-85171482657en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage2891en_US
dc.identifier.urihttps://doi.org/10.1177/02841851231200785
dc.identifier.urihttps://hdl.handle.net/20.500.12415/6842
dc.identifier.volume64en_US
dc.identifier.wosWOS:001069575400001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoenen_US
dc.publisherSage Publications Ltden_US
dc.relation.ispartofActa Radiologicaen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKY04184
dc.subjectBreasten_US
dc.subjectNeoplasmsen_US
dc.subjectScreeningen_US
dc.subjectMammographyen_US
dc.subjectNeural Networksen_US
dc.titleDiagnostic performance of two versions of an artificial intelligence system in interval breast cancer detectionen_US
dc.typeArticle
dspace.entity.typePublication

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