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Role of PI-RADS Version 2 for Prediction of Upgrading in Biopsy-Proven Prostate Cancer With Gleason Score 6
Authors:Wan Song  Seok Hwan Bang  Hwang Gyun Jeon  Byong Chang Jeong  Seong Il Seo  Seong Soo Jeon  Han Yong Choi  Chan Kyo Kim  Hyun Moo Lee
Affiliation:1. Department of Urology, Ewha Womans University School of Medicine, Seoul, Korea;2. Department of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea;3. Department of Urology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea;4. Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
Abstract:

Introduction

The objective of this study was to investigate the effect of Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) on prediction of postoperative Gleason score (GS) upgrading for patients with biopsy GS 6 prostate cancer.

Patients and Methods

We retrospectively reviewed 443 patients who underwent magnetic resonance imaging (MRI) and radical prostatectomy for biopsy-proven GS 6 prostate cancer between January 2011 and December 2013. Preoperative clinical variables and pathologic GS were examined, and all MRI findings were assessed with PI-RADSv2. Receiver operating characteristic curves were used to compare predictive accuracies of multivariate logistic regression models with or without PI-RADSv2.

Results

Of the total 443 patients, 297 (67.0%) experienced GS upgrading postoperatively. PI-RADSv2 scores 1 to 3 and 4 to 5 were identified in 157 (25.4%) and 286 (64.6%) patients, respectively, and the rate of GS upgrading was 54.1% and 74.1%, respectively (P < .001). In multivariate analysis, prostate-specific antigen density > 0.16 ng/mL2, number of positive cores ≥ 2, maximum percentage of cancer per core > 20, and PI-RADSv2 score 4 to 5 were independent predictors influencing GS upgrading (each P < .05). When predictive accuracies of multivariate models with or without PI-RADSv2 were compared, the model including PI-RADSv2 was shown to have significantly higher accuracy (area under the curve, 0.729 vs. 0.703; P = .041).

Conclusion

Use of PI-RADSv2 is an independent predictor of postoperative GS upgrading and increases the predictive accuracy of GS upgrading. PI-RADSv2 might be used as a preoperative imaging tool to determine risk classification and to help counsel patients with regard to treatment decision and prognosis of disease.
Keywords:Magnetic resonance imaging  PI-RADSv2  Prostate cancer  Radical prostatectomy  Upgrading
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