Artificial intelligence as diagnostic aiding tool in cases of Prostate Imaging Reporting and Data System category 3: the results of retrospective multi-center cohort study

Purpose To study the effect of artificial intelligence (AI) on the diagnostic performance of radiologists in interpreting prostate mpMRI images of the PI-RADS 3 category. Methods In this multicenter study, 16 radiologists were invited to interpret prostate mpMRI cases with and without AI. The study...

Full description

Saved in:
Bibliographic Details
Published in:Abdominal imaging 2023-12, Vol.48 (12), p.3757-3765
Main Authors: Wang, Kexin, Xing, Zhangli, Kong, Zixuan, Yu, Yang, Chen, Yuntian, Zhao, Xiangpeng, Song, Bin, Wang, Xiangpeng, Wu, Pengsheng, Wang, Xiaoying, Xue, Yunjing
Format: Article
Language:English
Subjects:
Artificial intelligence
Confidence intervals
Data systems
Gastroenterology
Hepatology
Imaging
Medical diagnosis
Medical imaging
Medicine
Medicine & Public Health
Pelvis
Prostate
Prostate cancer
Radiology
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Purpose To study the effect of artificial intelligence (AI) on the diagnostic performance of radiologists in interpreting prostate mpMRI images of the PI-RADS 3 category. Methods In this multicenter study, 16 radiologists were invited to interpret prostate mpMRI cases with and without AI. The study included a total of 87 cases initially diagnosed as PI-RADS 3 by radiologists without AI, with 28 cases being clinically significant cancers (csPCa) and 59 cases being non-csPCa. The study compared the diagnostic efficacy between readings without and with AI, the reading time, and confidence levels. Results AI changed the diagnosis in 65 out of 87 cases. Among the 59 non-csPCa cases, 41 were correctly downgraded to PI-RADS 1-2, and 9 were incorrectly upgraded to PI-RADS 4-5. For the 28 csPCa cases, 20 were correctly upgraded to PI-RADS 4-5, and 5 were incorrectly downgraded to PI-RADS 1-2. Radiologists assisted by AI achieved higher diagnostic specificity and accuracy than those without AI [0.695 vs 0.000 and 0.736 vs 0.322, both P  
ISSN:2366-0058
2366-004X
2366-0058
DOI:10.1007/s00261-023-03989-9