Evaluation of pathologically confirmed benign inflammatory breast diseases using artificial intelligence on ultrasound images

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dc.authorid0000-0003-3122-4499
dc.authorid0000-0003-0958-6581
dc.authorid0000-0002-4437-9310
dc.authorid0000-0002-9452-9276
dc.authorid0000-0003-0128-6947
dc.authorid0000-0003-3468-7712
dc.contributor.authorDurur Subaşı, Irmak
dc.contributor.authorEren, Abdulkadir
dc.contributor.authorGüngören, Fatma Zeynep
dc.contributor.authorBasım, Pelin
dc.contributor.authorGezen, Fazlı Cem
dc.contributor.authorÇakır, Aslı
dc.contributor.authorErol, Cengiz
dc.contributor.authorKoska, İlker Özgür
dc.date.accessioned2023-11-17T05:49:42Z
dc.date.available2023-11-17T05:49:42Z
dc.date.issued2024
dc.departmentİstanbul Medipol Üniversitesi, Uluslararası Tıp Fakültesi, Dahili Tıp Bilimleri Bölümü, Radyoloji Ana Bilim Dalı
dc.departmentİstanbul Medipol Üniversitesi, Tıp Fakültesi, Dahili Tıp Bilimleri Bölümü, Radyoloji Ana Bilim Dalı
dc.departmentİstanbul Medipol Üniversitesi, Tıp Fakültesi, Cerrahi Tıp Bilimleri Bölümü, Genel Cerrahi Ana Bilim Dalı
dc.departmentİstanbul Medipol Üniversitesi, Tıp Fakültesi, Cerrahi Tıp Bilimleri Bölümü, Tıbbi Patoloji Ana Bilim Dalı
dc.description.abstractObjectives: It was aimed to use AI retrospectively to evaluate US images of pathologically confirmed benign inflammatory lesions, to compare the results of AI with our US reports, and to test the reliability of AI in itself. Methods: US images of 71 histopathologically confirmed benign inflammatory breast lesions were analysed by the FDA-approved AI programme (Koios Decision Support) using 2 orthogonal projections. The lesions' probability of malignancy based on AI and BI-RADS categories of the lesion based on initial US interpretations were recorded. Categories obtained by both systems were divided into 2 groups as unsuspicious and suspicious in terms of malignancy and compared statistically. Reliability of AI was also evaluated. Results: No statistically significant difference was found in the lesions' likelihood of malignancy based on the AI and initial US interpretations (P = .512). Additionally, a positive and substantial association (?-b = 0.458, P < .001) between the levels of suspicion by AI and the initial US interpretation reports was discovered, as per Kendall-b correlation analysis. With a Cronbach alpha correlation coefficient of 0.727, the reliability was high for AI. Conclusions: Benign inflammatory breast lesions may show suspicious appearances in terms of malignancy with US and AI. Artificial intelligence produces results comparable to radiologists' US reports for benign inflammatory diseases.
dc.identifier.citationDurur Subaşı, I., Eren, A., Güngören, F. Z., Basım, P., Gezen, F. C., Çakır, A. ... Koska, İ. Ö. (2024). Evaluation of pathologically confirmed benign inflammatory breast diseases using artificial intelligence on ultrasound images. Revista de Senologia y Patologia Mamaria, 37(1). https://dx.doi.org/10.1016/j.senol.2023.100558
dc.identifier.doi10.1016/j.senol.2023.100558
dc.identifier.issn0214-1582
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85175701968
dc.identifier.scopusqualityQ4
dc.identifier.urihttps://dx.doi.org/10.1016/j.senol.2023.100558
dc.identifier.urihttps://hdl.handle.net/20.500.12511/11793
dc.identifier.volume37
dc.identifier.wos001112070600001en_US
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorDurur Subaşı, Irmak
dc.institutionauthorEren, Abdulkadir
dc.institutionauthorGüngören, Fatma Zeynep
dc.institutionauthorBasım, Pelin
dc.institutionauthorGezen, Fazlı Cem
dc.institutionauthorÇakır, Aslı
dc.institutionauthorErol, Cengiz
dc.language.isoen
dc.publisherSpanish Society of Senology and Breast Pathology
dc.relation.ispartofRevista de Senologia y Patologia Mamariaen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.subjectArtificial Intelligence
dc.subjectBreast Imaging Reporting Data System
dc.subjectDiagnostic Ultrasound
dc.titleEvaluation of pathologically confirmed benign inflammatory breast diseases using artificial intelligence on ultrasound images
dc.title.alternativeEvaluación de lesiones de mama benignas patológicamente confirmadas utilizando inteligencia artificial en las imágenes ecográficas
dc.typeArticle

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