Report Open Access

Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge (Study Protocol)

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

Other(s)
Barentsz, Jelle; Bjartell, Anders; Bonekamp, David; Giannarini, Gianluca; Kalpathy-Cramer, Jayashree; Kasivisvanathan, Veeru; Maier-Hein, Klaus H.; Padhani, Anwar R.; Panebianco, Valeria; Rouviere, Olivier; Rusu, Mirabela; Salomon, Georg; van den Bergh, Roderick; Villeirs, Geert

This document represents the preregistration of the PI-CAI challenge study design, in compliance with MICCAI-BIAS reporting guidelines.

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 (1.4 MB)
Name Size
pi-cai_bias_.pdf
md5:feac922e05c53b58ee2a3e8b716b73da
1.4 MB Download
904
732
views
downloads
All versions This version
Views 904465
Downloads 732377
Data volume 993.1 MB512.2 MB
Unique views 765399
Unique downloads 636330

Share

Cite as