Abstract

You have accessJournal of UrologyImaging/Radiology I1 Apr 2014PD4-11 INCREASING ELIGIBILITY FOR PROSTATE CANCER ACTIVE SURVEILLANCE: THE VALUE OF MULTIPARAMETRIC MRI FOR THE PREDICTION OF PATHOLOGICAL DOWNGRADING AFTER RADICAL PROSTATECTOMY IN PATIENTS WITH BIOPSY-PROVEN GLEASON 3 + 4 PROSTATE CANCER Tatsuo Gondo, Hedvig Hricak, Evis Sala, Junting Zheng, Chaya S. Moskowitz, Melanie Bernstein, Peter T. Scardino, James A. Eastham, and Hebert Alberto Vargas Tatsuo GondoTatsuo Gondo More articles by this author , Hedvig HricakHedvig Hricak More articles by this author , Evis SalaEvis Sala More articles by this author , Junting ZhengJunting Zheng More articles by this author , Chaya S. MoskowitzChaya S. Moskowitz More articles by this author , Melanie BernsteinMelanie Bernstein More articles by this author , Peter T. ScardinoPeter T. Scardino More articles by this author , James A. EasthamJames A. Eastham More articles by this author , and Hebert Alberto VargasHebert Alberto Vargas More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.02.232AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Men with Gleason Score (GS) 3+4 prostate cancer (PCa) on biopsy are excluded from most active surveillance (AS) programs. However, some of these men are found to have GS 3+3 after radical prostatectomy (RP) and could potentially have been eligible for AS. We assessed the value of pre-treatment 3-Tesla multiparametric magnetic resonance imaging (mpMRI) for predicting GS downgrading after RP in patients with GS 3+4 PCa on biopsy. METHODS This retrospective study included 304 patients with biopsy-proven (≥12 cores) GS 3+4 PCa who underwent mpMRI before RP between 2011 and 2013. On T2-weighted imaging [T2] and three mpMRI combinations (T2+diffusion-weighted imaging [DWI], T2+dynamic contrast-enhanced-MRI [DCE-MRI], and T2+DWI+DCE-MRI), a radiologist scored the presence of a dominant tumor using a 5-point index scale (1-definitely absent to 5-definitely present). Univariate and multivariable logistic regressions were used to examine the association between clinical and MRI features and GS downgrading. Diagnostic performance in identifying patients with GS downgrading was evaluated by estimating areas under the curves (AUC) using the predicted probabilities from logistic regressions. RESULTS GS was downgraded after RP in 28/304 patients (9.2%). In predicting GS downgrading, T2+DWI (AUC = 0.89) performed significantly better than T2 alone (AUC = 0.72; p <.001) and T2+DCE (AUC = 0.73; p <.001), while T2+DWI+DCE (AUC = 0.89) performed no better thanT2+DWI (p = 0.48). We developed a clinical model to predict downgrading using prostate specific antigen (PSA), PSA density, percent of positives cores with Gleason pattern 4 cancer, and maximum percent of Gleason pattern 4 cancer involvement within a single core. On multivariable analysis, the clinical+mpMRI model incorporating T2+DWI (AUC = 0.92) predicted GS downgrading significantly better than the clinical model (AUC = 0.73; p < 0.001). CONCLUSIONS By identifying patients diagnosed with GS 3+4 on biopsy who would likely have their disease downgraded at surgery, mpMRI could improve the ability of identifying patients who are potential candidates for AS. However, further evaluations with longer follow-up periods will be necessary to confirm that downgrading on MRI is associated with positive oncologic outcomes. © 2014FiguresReferencesRelatedDetails Volume 191Issue 4SApril 2014Page: e55 Advertisement Copyright & Permissions© 2014MetricsAuthor Information Tatsuo Gondo More articles by this author Hedvig Hricak More articles by this author Evis Sala More articles by this author Junting Zheng More articles by this author Chaya S. Moskowitz More articles by this author Melanie Bernstein More articles by this author Peter T. Scardino More articles by this author James A. Eastham More articles by this author Hebert Alberto Vargas More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

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