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22-09-2023 | Artificial Intelligence | Pelvis

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

Authors: Kexin Wang, Zhangli Xing, Zixuan Kong, Yang Yu, Yuntian Chen, Xiangpeng Zhao, Bin Song, Xiangpeng Wang, Pengsheng Wu, Xiaoying Wang, Yunjing Xue

Published in: Abdominal Radiology | Issue 12/2023

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Abstract

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 < 0.001]. Sensitivity with AI was not significantly different from that without AI [0.821 vs 1.000, P = 1.000]. AI reduced reading time significantly compared to without AI (mean: 351 seconds, P < 0.001). The diagnostic confidence score with AI was significantly higher than that without AI (Cohen Kappa: -0.016).

Conclusion

With the help of AI, there was an improvement in the diagnostic accuracy of PI-RADS category 3 cases by radiologists. There is also an increase in diagnostic efficiency and diagnostic confidence.
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Metadata
Title
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
Authors
Kexin Wang
Zhangli Xing
Zixuan Kong
Yang Yu
Yuntian Chen
Xiangpeng Zhao
Bin Song
Xiangpeng Wang
Pengsheng Wu
Xiaoying Wang
Yunjing Xue
Publication date
22-09-2023
Publisher
Springer US
Published in
Abdominal Radiology / Issue 12/2023
Print ISSN: 2366-004X
Electronic ISSN: 2366-0058
DOI
https://doi.org/10.1007/s00261-023-03989-9

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