Application of Machine Learning to Breast MR Imaging.

Journal: Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Published Date: Jun 14, 2025

Abstract

The demand for breast imaging services continues to grow, driven by expanding indications in breast cancer diagnosis and treatment. This increasing demand underscores the potential role of artificial intelligence (AI) to enhance workflow efficiency as well as to further unlock the abundant imaging data to achieve improvements along the breast cancer pathway. Although AI has made significant advancements in mammography and digital breast tomosynthesis, with commercially available computer-aided detection (CAD systems) widely used for breast cancer screening and detection, its adoption in breast MRI has been slower. This lag is primarily attributed to the inherent complexity of breast MRI examinations and also hence the more limited availability of large, well-annotated publicly available breast MRI datasets. Despite these challenges, interest in AI implementation in breast MRI remains strong, fueled by the expanding use and indications for breast MRI. This article explores the implementation of AI in breast MRI across the breast cancer care pathway, highlighting its potential to revolutionize the way we detect and manage breast cancer. By addressing current challenges and examining emerging AI applications, we aim to provide a comprehensive overview of how AI is reshaping breast MRI and improving outcomes for patients.

Authors

  • Roberto Lo Gullo
    Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th Street, New York, NY, 10065, USA.
  • Vivien van Veldhuizen
    AI for Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands.
  • Tina Roa
    Department of Radiology, Columbia University Irving Medical Center, Vagelos College of Physicians and Surgeons, New York, NY, USA.
  • Panagiotis Kapetas
    Division of Molecular and Gender Imaging, Department of Biomedical Imaging and Image-Guided Therapy.
  • Jonas Teuwen
    Department of Radiology and Nuclear Medicine, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.
  • Katja Pinker
    Department of Radiology, Columbia University, Vagelos College of Physicians and Surgeons, New York, New York, USA.

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