An overview of utilizing artificial intelligence in localized prostate cancer imaging.

Journal: Expert review of medical devices
PMID: 40056148

Abstract

INTRODUCTION: Prostate cancer (PCa) is a leading cause of cancer-related deaths among men, and accurate diagnosis is critical for effective management. Multiparametric MRI (mpMRI) has become an essential tool in PCa diagnosis due to its superior spatial resolution which enables detailed anatomical, functional information and its resultant ability to detect clinically significant PCa. However, challenges such as subjective interpretation methods and high inter-reader variability remain. In recent years, artificial intelligence (AI) has emerged as a promising solution to enhance the diagnostic performance of mpMRI by automating key tasks such as prostate segmentation, lesion detection, classification.

Authors

  • Emma Stevenson
    Clinical Biochemistry, Gloucestershire Hospitals NHS Foundation Trust, Cheltenham, UK.
  • Omer Tarik Esengur
    Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Haoyue Zhang
    Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
  • Benjamin D Simon
    Molecular Imaging Branch, NCI, NIH, Bethesda, Maryland, USA (B.D.S., K.M.M., S.A.H., E.C.Y., P.L.C., B.T.); Institute of Biomedical Engineering, Department Engineering Science, University of Oxford, UK (B.D.S.).
  • Stephanie A Harmon
    Clinical Research Directorate, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Frederick, Maryland, USA.
  • Baris Turkbey
    Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

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