Can computer-aided diagnosis assist in the identification of prostate cancer on prostate MRI? a multi-center, multi-reader investigation.

Sonia Gaur,Yan Mee Law,Antonio C Westphalen,Sreya Doddakashi,Bradford J Wood,Anne Y Warren,Tatjana Antic,Andrei S Purysko,Nathan Lay,Stefano Sioletic,Joanna H Shih,Sherif Mehralivand,Peter L Choyke,Ismail Kabakus,Rajan T Gupta,Burak Argun,Peter A Pinto,Ronald M Summers,Tristan Barrett,Sandra Bednarova,Aytekin Oto,Jurgen J Fütterer,Ercan Karaarslan,Haytham Shebel,R Girometti ,Yeşim Sağlıcan ,Stephanie Harmon ,Cristina Magi‐Galluzzi ,Leonardo Kayat Bittencourt ,Daniel Margolis ,Ali Rıza Kural ,Barış Türkbey

doi:10.18632/oncotarget.26100

Abstract

For prostate cancer detection on prostate multiparametric MRI (mpMRI), the Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2) and computer-aided diagnosis (CAD) systems aim to widely improve standardization across radiologists and centers. Our goal was to evaluate CAD assistance in prostate cancer detection compared with conventional mpMRI interpretation in a diverse dataset acquired from five institutions tested by nine readers of varying experience levels, in total representing 14 globally spread institutions.Index lesion sensitivities of mpMRI-alone were 79% (whole prostate (WP)), 84% (peripheral zone (PZ)), 71% (transition zone (TZ)), similar to CAD at 76% (WP, p=0.39), 77% (PZ, p=0.07), 79% (TZ, p=0.15). Greatest CAD benefit was in TZ for moderately-experienced readers at PI-RADSv2 <3 (84% vs mpMRI-alone 67%, p=0.055). Detection agreement was unchanged but CAD-assisted read times improved (4.6 vs 3.4 minutes, p<0.001). At PI-RADSv2 ≥ 3, CAD improved patient-level specificity (72%) compared to mpMRI-alone (45%, p<0.001).PI-RADSv2 and CAD-assisted mpMRI interpretations have similar sensitivities across multiple sites and readers while CAD has potential to improve specificity and moderately-experienced radiologists’ detection of more difficult tumors in the center of the gland. The multi-institutional evidence provided is essential to future prostate MRI and CAD development.

Highlights

Men with suspected or known prostate cancer are increasingly evaluated with prostate multiparametric MRI because it aids in the detection of clinically significant disease [1,2,3,4]
Using moderately and highly experienced readers we observed that standardized PI-RADSv2 categorization and our computeraided diagnosis (CAD) system, optimized for quantitative parameters that can be extracted from images obtained across different manufacturers and institutions, showed similar baseline detection rates
Our findings suggest that standardization and interpretive assistance strategies such as PI-RADSv2 and CAD systems help readers detect cancer with reasonable accuracy, and CAD has potential to improve detection performance in the Transition zone (TZ)

Summary

Introduction

Men with suspected or known prostate cancer are increasingly evaluated with prostate multiparametric MRI (mpMRI) because it aids in the detection of clinically significant disease [1,2,3,4]. MpMRI has been criticized because of variability in quality of exams and inconsistent interpretations across clinical centers and physicians. To address some of these issues the Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2) was introduced in 2015 as a set of guidelines outlining standard acquisition parameters and a categorization system for cancer detection [5]. PIRADSv2 has been widely adopted and can achieve cancer detection rates up to 80-90%; it is associated with a steep learning curve and exhibits a high degree of inter-reader variability, likely reflecting inherent ambiguities in the classification scheme. Many centers report a mpMRI miss rate up to 16-30% [6,7,8,9,10,11]. A large scale, prospective, multicenter trial of PI-RADSv2 has not yet been performed

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