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

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.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/1410
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Zhaonan Sun, Xiaoying Wang
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Artificial Intelligence in Healthcare and Education
article

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

Zhaonan Sun, Xiaoying Wang
article en

Abstract

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.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 82%
Artificial Intelligence in Healthcare and Education
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Assessing the performance of AI assistance for prostate MRI: a two-center study involving radiologists with different experience levels — Zhaonan Sun, Xiaoying Wang · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2025) | TGRS Research Map | TGRS