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Abstract #1410

Assessing the performance of AI assistance for prostate MRI: a two-center study involving radiologists with different experience levels

Zhaonan Sun1 and Xiaoying Wang1
1Radiology, Peking University First Hospital, Beijing, China

Synopsis

Keywords: Diagnosis/Prediction, Cancer

Motivation: There is a pressing need for quantitative, objective diagnostic tools to support radiologists in improving the accuracy and efficiency of detecting clinically significant prostate cancer (csPCa) using multiparametric MRI (mpMRI).

Goal(s): To assess the performance of experienced and less-experienced radiologists in detecting csPCa, with and without AI assistance.

Approach: Researchers compared the performance of experienced and less-experienced radiologists in interpreting scans, both with and without AI assistance, using data from 900 patients.

Results: The findings suggest that AI can enhance diagnostic accuracy and confidence in prostate MRI readings, particularly for those with less experience in the field.

Impact: This research demonstrate how AI can assist radiologist in interpreting multiparametric prostate mpMRI, thereby facilitating broader clinical implementation of AI technologies in routine practice.

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Keywords