Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge (Study Protocol)
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 signif...
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creator | Saha, Anindo Twilt, Jasper Jonathan Bosma, Joeran Sander van Ginneken, Bram Yakar, Derya Elschot, Mattijs Veltman, Jeroen Fütterer, Jurgen de Rooij, Maarten Huisman, Henkjan |
description | 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). |
doi_str_mv | 10.5281/zenodo.6522363 |
format | Report |
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subjects | artificial intelligence computer-aided detection and diagnosis magnetic resonance imaging prostate cancer radiologists |
title | Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge (Study Protocol) |
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