Prospective Clinical Implementation of Paige Prostate Detect Artificial Intelligence Assistance in the Detection of Prostate Cancer in Prostate Biopsies: CONFIDENT P Trial Implementation of Artificial Intelligence Assistance in Prostate Cancer Detection.

Journal: JCO clinical cancer informatics
PMID: 40036728

Abstract

PURPOSE: Pathologists diagnose prostate cancer (PCa) on hematoxylin and eosin (HE)-stained sections of prostate needle biopsies (PBx). Some laboratories use costly immunohistochemistry (IHC) for all cases to optimize workflow, often exceeding reimbursement for the full specimen. Despite the rise in digital pathology and artificial intelligence (AI) algorithms, clinical implementation studies are scarce. This prospective clinical trial evaluated whether an AI-assisted workflow for detecting PCa in PBx reduces IHC use while maintaining diagnostic safety standards.

Authors

  • Rachel N Flach
    Department of Pathology, University Medical Centre Utrecht, Utrecht, The Netherlands.
  • Carmen van Dooijeweert
    Department of Pathology, University Medical Centre Utrecht, Utrecht, The Netherlands c.vandooijeweert-3@umcutrecht.nl.
  • Tri Q Nguyen
    Pathology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Mitchell Lynch
    Department of Pathology, Gelre Hospital, Apeldoorn, the Netherlands.
  • Trudy N Jonges
    Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands.
  • Richard P Meijer
    1 Department of Radiotherapy, University Medical Center Utrecht, Utrecht, the Netherlands.
  • Britt B M Suelmann
    Department of Medical Oncology, University Medical Center Utrecht, Utrecht, the Netherlands.
  • Peter-Paul M Willemse
    Department of Oncological Urology, University Medical Center Utrecht, Utrecht, the Netherlands.
  • Nikolas Stathonikos
    Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands.
  • Paul J van Diest
    Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands.

Keywords

External Resources

Popular Topics
Recent Journals