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    AboutPolicies Privacy NoticeBlack Country Healthcare NHS Foundation TrustCoventry and Warwickshire Partnership NHS TrustDudley Group NHS Foundation TrustGeorge Eliot Hospital NHS TrustSandwell and West Birmingham NHS TrustSouth Warwickshire University NHS Foundation TrustUniversity Hospitals Birmingham NHS Foundation TrustUniversity Hospitals Coventry and Warwickshire NHS TrustWalsall Healthcare NHS Trust

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    A Prospective Analysis of Screen-Detected Cancers Recalled and Not Recalled by Artificial Intelligence.

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    Author
    Smith, Samantha J
    Bradley, Sally Anne
    Walker-Stabeler, Katie
    Siafakas, Michael
    Smith, Samantha
    Affiliation
    Samantha J Smith, MHSc, Sally Anne Bradley, MB.ChB, Katie Walker-Stabeler, MSc, Michael Siafakas, MS, MD
    Publication date
    2024-05-27
    Subject
    Oncology. Pathology.
    Radiology
    
    Metadata
    Show full item record
    Abstract
    Objective: The use of artificial intelligence has potential in assisting many aspects of imaging interpretation. We undertook a prospective service evaluation from March to October 2022 of Mammography Intelligent Assessment (MIA) operating "silently" within our Breast Screening Service, with a view to establishing its performance in the local population and setting. This evaluation addressed the performance of standalone MIA vs conventional double human reading of mammograms. Methods: MIA analyzed 8779 screening events over an 8-month period. The MIA outcome did not influence the decisions made on the clinical pathway. Cases were reviewed approximately 6 weeks after the screen reading decision when human reading and/or MIA indicated a recall. Results: There were 146 women with positive concordance between human reading and MIA (human reader and MIA recalled) in whom 58 breast cancers were detected. There were 270 women with negative discordance (MIA no recall, human reader recall) for whom 19 breast cancers and 1 breast lymphoma were detected, with 1 cancer being an incidental finding at assessment. Six hundred and four women had positive discordance (MIA recall, human reader no recall) in whom 2 breast cancers were detected at review. The breast cancers demonstrated a wide spectrum of mammographic features, sites, sizes, and pathologies, with no statistically significant difference in features between the negative discordant and positive concordant cases. Conclusion: Of 79 breast cancers identified by human readers, 18 were not identified by MIA, and these had no specific features or site to suggest a systematic error for MIA analysis of 2D screening mammograms. Keywords: National Health Service Breast Screening Programme; artificial intelligence; breast cancer screening; digital mammography; double reading
    Citation
    Smith SJ, Bradley SA, Walker-Stabeler K, Siafakas M. A Prospective Analysis of Screen-Detected Cancers Recalled and Not Recalled by Artificial Intelligence. J Breast Imaging. 2024 May 27:wbae027. doi: 10.1093/jbi/wbae027. Epub ahead of print. PMID: 38801724.
    Type
    Article
    Handle
    http://hdl.handle.net/20.500.14200/4859
    DOI
    10.1093/jbi/wbae027
    PMID
    38801724
    Journal
    Journal of Breast Imaging
    Publisher
    Oxford University Press
    ae974a485f413a2113503eed53cd6c53
    10.1093/jbi/wbae027
    Scopus Count
    Collections
    Radiology
    Oncology

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