Requirements for AI Development and Reporting for MRI Prostate Cancer Detection in Biopsy-Naive Men: PI-RADS Steering

Baris Turkbey1, Henkjan Huisman1, Andriy Fedorov1

  • 1From the Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182, Bldg 10, Room B3B85, Bethesda, MD 20892 (B.T.); Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (H.H.); Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (A.F., C.M.T.); The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Md (K.J.M.); Department of Radiology, Weill Cornell Medicine/New York Presbyterian, New York, NY (D.J.M.); Department of Radiological Sciences, Oncology and Pathology, Sapienza University, Rome, Italy (V.P.); Department of Radiology, University of Chicago, Chicago, Ill (A.O.); Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands (I.G.S.); Department of Surgery, Division of Urology, University of Maryland School of Medicine, Baltimore, Md (M.M.S.); Division of Surgery   Interventional Science, University College London, London, UK (C.M.M.); Department of Urology, University College London Hospitals NHS Foundation Trust, London, UK (C.M.M.); Department of Urinary and Vascular Imaging, Hospices Civils de Lyon, Hôpital Edouard Herriot, Lyon, France (O.R.); Faculté de Médecine Lyon Est, Université de Lyon, Université Lyon 1, Lyon, France (O.R.); Department of Radiology, University Hospitals Cleveland Medical Center/Case Western Reserve University School of Medicine, Cleveland, Ohio (L.K.B.); Paul Strickland Scanner Centre, Mount Vernon Hospital, Middlesex, UK (A.R.P.); Joint Department of Medical Imaging, Mount Sinai Hospital, Princess Margaret Hospital, University of Toronto, Toronto, Canada (M.A.H.); and Lunenfeld-Tanenbaum Research Institute, Toronto, Canada (M.A.H.).

Radiology
|April 15, 2025
PubMed
Summary

This guide outlines requirements for developing artificial intelligence (AI) models to detect prostate cancer (PCa) using MRI. It emphasizes data standards, performance metrics, and transparency for clinical translation.