The PI-CAI Challenge: Public Training and Development Dataset

  • Anindo Saha (Contributor)
  • Jasper Jonathan Twilt (Contributor)
  • Joeran Sander Bosma (Contributor)
  • Bram van Ginneken (Contributor)
  • Derya Yakar (Contributor)
  • Mattijs Elschot (Contributor)
  • Jeroen Veltman (Contributor)
  • Jurgen Fütterer (Contributor)
  • Maarten de Rooij (Contributor)
  • Henkjan Huisman (Contributor)

Dataset

Description

This dataset represents the PI-CAI: Public Training and Development Dataset. It contains 1500 anonymized prostate biparametric MRI scans from 1476 patients, acquired between 2012-2021, at three centers (Radboud University Medical Center, University Medical Center Groningen, Ziekenhuis Groep Twente) based in The Netherlands.


The PI-CAI challenge is an all-new grand challenge that aims to validate the diagnostic performance of artificial intelligence and radiologists at clinically significant prostate cancer (csPCa) detection/diagnosis in MRI, with histopathology and follow-up (≥ 3 years) as the reference standard, in a retrospective setting. The study hypothesizes that state-of-the-art AI algorithms, trained using thousands of patient exams, are non-inferior to radiologists reading bpMRI.


Key aspects of the PI-CAI study design have been established in conjunction with an international scientific advisory board of 16 experts in prostate AI, radiology and urology —to unify and standardize present-day guidelines, and to ensure meaningful validation of prostate AI towards clinical translation (Reinke et al., 2021).
Date made available10-Jun-2022
PublisherZENODO

Keywords on Datasets

  • prostate cancer
  • magnetic resonance imaging
  • computer-aided detection and diagnosis
  • radiologists
  • artificial intelligence

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