A systematic scoping review exploring variation in practice in specimen mammography for Intraoperative Margin Analysis in Breast Conserving Surgery and the role of artificial intelligence in optimising diagnostic accuracy.

Journal: European journal of radiology
PMID: 39393216

Abstract

PURPOSE: Specimen Mammography (SM) is commonly used in Breast Conserving Surgery (BCS) for intraoperative margin analysis. A systematic scoping review was conducted to identify sources of methodological variation in Specimen Mammography Interpretation (SMI) and assess the role of Artificial Intelligence (AI) techniques to optimise Diagnostic Accuracy (DA).

Authors

  • Thomas J E Hubbard
    Faculty of Health and Life Sciences, University of Exeter, Exeter, UK; Royal Devon University Healthcare NHS Trust, Exeter, UK. Electronic address: tjehubbard@doctors.org.uk.
  • Ola Shams
    Royal Devon University Healthcare NHS Trust, Exeter, UK.
  • Benjamin Gardner
    School of Physics and Astronomy, University of Exeter, Exeter EX4 4QL, UK. N.Stone@exeter.ac.uk.
  • Finley Gibson
    Institute for Data Science and Artificial Intelligence, University of Exeter, Exeter, UK.
  • Sareh Rowlands
    Department of Computer Science, Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK.
  • Tim Harries
    Department of Physics and Astronomy, Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK.
  • Nick Stone
    Department of Physics and Astronomy, Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK.

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