An artificial intelligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: a blinded clinical validation and deployment study.

Journal: The Lancet. Digital health
Published Date:

Abstract

BACKGROUND: There is high demand to develop computer-assisted diagnostic tools to evaluate prostate core needle biopsies (CNBs), but little clinical validation and a lack of clinical deployment of such tools. We report here on a blinded clinical validation study and deployment of an artificial intelligence (AI)-based algorithm in a pathology laboratory for routine clinical use to aid prostate diagnosis.

Authors

  • Liron Pantanowitz
    Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
  • Gabriela M Quiroga-Garza
    Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
  • Lilach Bien
    Ibex Medical Analytics, Tel Aviv, Israel.
  • Ronen Heled
    Ibex Medical Analytics, Tel Aviv, Israel.
  • Daphna Laifenfeld
    Ibex Medical Analytics, Tel Aviv, Israel.
  • Chaim Linhart
    Ibex Medical Analytics, Tel Aviv, Israel.
  • Judith Sandbank
    Ibex Medical Analytics, Tel Aviv, Israel; Institute of Pathology, Maccabi Healthcare Services, Rehovot, Israel.
  • Anat Albrecht Shach
    Shamir Medical Center, Beer Yaakov, Israel.
  • Varda Shalev
    Institute of Health Research and Innovation, Maccabi Healthcare Services, Tel-Aviv, Israel.
  • Manuela Vecsler
    Ibex Medical Analytics, Tel Aviv, Israel.
  • Pamela Michelow
    Cytology Unit, Department of Anatomical Pathology, Faculty of Health Science, National Health Laboratory Service, University of the Witwatersrand, Johannesburg, South Africa.
  • Scott Hazelhurst
    School of Electrical & Information Engineering and Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa.
  • Rajiv Dhir
    Department of Pathology, University of Pittsburgh Medical Center Cancer Pavilion, Suite 201, 5150 Centre Ave, Pittsburgh, PA, 15232, USA.