Multiparametric magnetic resonance imaging and active surveillance: How to better select insignificant prostate cancer?

Abstract

To evaluate the role of multiparametric magnetic resonance imaging in improving the predictive accuracy of the Prostate Cancer Research International: Active Surveillance and Epstein criteria for active surveillance in prostate cancer. A retrospective study was carried out with 126 prostate cancer patients treated with robot-assisted radical prostatectomy, but eligible for active surveillance according to the Prostate Cancer Research International: Active Surveillance criteria; 63 patients were also eligible according to the Epstein criteria. All patients underwent preoperative multiparametric magnetic resonance imaging, after at least 6 weeks from biopsy. The images from the multiparametric magnetic resonance imaging were assessed, and diagrams showing prostate sextants were used to designate regions of abnormalities within the prostate. Findings in the prostate were assigned to one of five categories according the Prostate Imaging-Reporting and Data System guidelines (v1.0), and considered positive for prostate cancer if the final Prostate Imaging-Reporting and Data System guidelines were >3 and negative if ≤3. Multivariate logistic regression analysis was carried out to evaluate the gain in accuracy of the Prostate Cancer Research International: Active Surveillance and Epstein criteria when added to multiparametric magnetic resonance imaging. Decision curve analysis was carried out to identify the net benefit of each model. The inclusion of multiparametric magnetic resonance imaging to the Epstein criteria and the Prostate Cancer Research International: Active Surveillance multivariate model significantly increased their accuracy in predicting pathologically-confirmed insignificant prostate cancer by 7% and 5%, respectively. At the decision curve analysis evaluation, the model including the Prostate Cancer Research International: Active Surveillance criteria and multiparametric magnetic resonance imaging improved the clinical risk prediction over the other models. The present findings suggest that multiparametric magnetic resonance imaging is able to increase the predictive accuracy of Prostate Cancer Research International: Active Surveillance and Epstein criteria to identify prostate cancer patients eligible for active surveillance.