Published June 10, 2022 | Version v2.0
Dataset Open

The PI-CAI Challenge: Public Training and Development Dataset

  • 1. Department of Medical Imaging, Radboud University Medical Center, The Netherlands
  • 2. Department of Radiology, Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, The Netherlands
  • 3. Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Norway
  • 4. Department of Radiology, Ziekenhuis Groep Twente, The Netherlands

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).

Files

picai_public_images_fold0.zip

Files (26.9 GB)

Name Size Download all
md5:bd06674082883348303979bec15d9c2c
19.9 kB Download
md5:b0cdd8f5fb7733ca585dca3541586a34
5.4 GB Preview Download
md5:d7c8cd0efc0e7f264df8d5acf860662f
5.2 GB Preview Download
md5:5ac0caf27cfe94dfc04bb408a971b351
5.3 GB Preview Download
md5:6602bce3d0882d7b9c2153d880c97e96
5.5 GB Preview Download
md5:8941720d8a8ee66571691cfb10dbee66
5.6 GB Preview Download
md5:3ef8691b42259a6b908c85b68d00e114
4.3 kB Preview Download

Additional details

Related works

Is documented by
Report: 10.5281/zenodo.6522364 (DOI)

Funding

ProCAncer-I – An AI Platform integrating imaging data and models, supporting precision care through prostate cancer’s continuum 952159
European Commission