A multicenter study of artificial intelligence-aided software for detecting visible clinically significant prostate cancer on mpMRI.

ABSTRACT:

Background

AI-based software may improve the performance of radiologists when detecting clinically significant prostate cancer (csPCa). This study aims to compare the performance of radiologists in detecting MRI-visible csPCa on MRI with and without AI-based software.

Materials and methods

In total, 480 multiparametric MRI (mpMRI) images were retrospectively collected from eleven different MR devices, with 349 csPCa lesions in 180 (37.5%) cases. The csPCa areas were annotated based on pathology. Sixteen radiologists from four hospitals participated in reading. Each radiologist was randomly assigned to 30 cases and diagnosed twice. Half cases were interpreted without AI, and the other half were interpreted with AI. After four weeks, the cases were read again in switched mode.

SUBMITTER: Sun Z 

PROVIDER: S-EPMC10149551 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature