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ABSTRACT: Background
The Prostate Imaging Reporting and Data System (PI-RADS) provides guidelines for risk stratification of lesions detected on multiparametric MRI (mpMRI) of the prostate but suffers from high intra/interreader variability.Purpose
To develop an artificial intelligence (AI) solution for PI-RADS classification and compare its performance with an expert radiologist using targeted biopsy results.Study type
Retrospective study including data from our institution and the publicly available ProstateX dataset.Population
In all, 687 patients who underwent mpMRI of the prostate and had one or more detectable lesions (PI-RADS score >1) according to PI-RADSv2.Field strength/sequence
T2 -weighted, diffusion-weighted imaging (DWI; five evenly sp
SUBMITTER: Sanford T
PROVIDER: S-EPMC8942293 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature