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