ESUR/ESUI position paper: developing artificial intelligence for precision diagnosis of prostate cancer using magnetic resonance imaging.

Journal: European radiology
Published Date:

Abstract

Artificial intelligence developments are essential to the successful deployment of community-wide, MRI-driven prostate cancer diagnosis. AI systems should ensure that the main benefits of biopsy avoidance are delivered while maintaining consistent high specificities, at a range of disease prevalences. Since all current artificial intelligence / computer-aided detection systems for prostate cancer detection are experimental, multiple developmental efforts are still needed to bring the vision to fruition. Initial work needs to focus on developing systems as diagnostic supporting aids so their results can be integrated into the radiologists' workflow including gland and target outlining tasks for fusion biopsies. Developing AI systems as clinical decision-making tools will require greater efforts. The latter encompass larger multicentric, multivendor datasets where the different needs of patients stratified by diagnostic settings, disease prevalence, patient preference, and clinical setting are considered. AI-based, robust, standard operating procedures will increase the confidence of patients and payers, thus enabling the wider adoption of the MRI-directed approach for prostate cancer diagnosis. KEY POINTS: • AI systems need to ensure that the benefits of biopsy avoidance are delivered with consistent high specificities, at a range of disease prevalence. • Initial work has focused on developing systems as diagnostic supporting aids for outlining tasks, so they can be integrated into the radiologists' workflow to support MRI-directed biopsies. • Decision support tools require a larger body of work including multicentric, multivendor studies where the clinical needs, disease prevalence, patient preferences, and clinical setting are additionally defined.

Authors

  • Tobias Penzkofer
    Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, USA.
  • Anwar R Padhani
    From the Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Rickmansworth Road, Northwood, Middlesex HA6 2RN, England (A.R.P.); and Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, Md (B.T.).
  • Baris Turkbey
    Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Masoom A Haider
    Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
  • Henkjan Huisman
    Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Jochen Walz
    Institut Paoli-Calmettes, Service de chirurgie urologique, Marseille, France.
  • Georg Salomon
    Martini Klinik-Prostate Cancer Center, University Hospital Hamburg Eppendorf, Hamburg, Germany.
  • Ivo G Schoots
    Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
  • Jonathan Richenberg
    Department of Imaging, BSUH NHS Trust, Brighton, UK.
  • Geert Villeirs
    Department of Radiology and Nuclear Medicine, Ghent University Hospital, Ghent, Belgium.
  • Valeria Panebianco
    Department of Radiological Sciences, Oncology and Pathology, Sapienza/Policlinico Umberto I, Rome, Italy.
  • Olivier Rouviere
    Hospices Civils de Lyon, Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Lyon, France.
  • Vibeke Berg Logager
    Radiological Department, Copenhagen University Hospital in Herlev-Gentofte, Herlev, Denmark.
  • Jelle Barentsz
    Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.