Assessment of breast composition in MRI using artificial intelligence - A systematic review.

Journal: Radiography (London, England : 1995)
Published Date: Feb 20, 2025

Abstract

INTRODUCTION: Magnetic Resonance Imaging (MRI) performs a critical role in breast cancer diagnosis, especially for high-risk populations e.g. family history. MRI could take advantage of the implementation of artificial intelligence (AI). AI assessment of breast composition factors is less studied than those of lesion detection and classification. These factors are breast density, background parenchymal enhancement (BPE) and fibroglandular tissue (FGT), which are recognized breast cancer phenotypes.

Authors

  • P C Murphy
    Department of Radiology, Cork University Hospital, Cork, Ireland; Discipline of Medical Imaging and Radiation Therapy, University College Cork, Cork, Ireland. Electronic address: 121101106@umail.ucc.ie.
  • M McEntee
    The Discipline of Medical Imaging and Radiation Therapy, University College Cork, College Road, T12 K8AF Cork, Ireland; Syddansk Universitet, University of Southern Denmark Faculty of Health Sciences, Denmark; University of Sydney, Faculty of Medicine, Australia.
  • M Maher
    Department of Radiology, Cork University Hospital, Ireland.
  • M F Ryan
    Department of Radiology, Cork University Hospital, Cork, Ireland; Department of Radiology, College of Medicine and Health, University College Cork, Cork, Ireland. Electronic address: m.ryan@ucc.ie.
  • C Harman
    Department of Radiation Therapy, Cork University Hospital, Cork, Ireland. Electronic address: claire.harman@hse.ie.
  • A England
    The Discipline of Medical Imaging and Radiation Therapy, University College Cork, College Road, T12 K8AF Cork, Ireland.
  • N Moore
    Discipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Ireland.

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