PURPOSE: The aim of this study was to investigate the prognostic performance of multiparametric magnetic resonance imaging (mpMRI) and Prostate Imaging Reporting and Data System (PIRADS) score in predicting pathologic features in a cohort of patients eligible for active surveillance who underwent radical prostatectomy. METHODS: A total of 223 patients who fulfilled the criteria for "Prostate Cancer Research International: Active Surveillance", were included. Mp-1.5 Tesla MRI examination staging with endorectal coil was performed at least 6-8 weeks after TRUS-guided biopsy. In all patients, the likelihood of the presence of cancer was assigned using PIRADS score between 1 and 5. Outcomes of interest were: Gleason score upgrading, extra capsular extension (ECE), unfavorable prognosis (occurrence of both upgrading and ECE), large tumor volume (≥ 0.5 ml), and seminal vesicle invasion (SVI). Receiver Operating Characteristic (ROC) curves and Decision Curve Analyses (DCA) were performed for models with and without inclusion of PIRADS score. RESULTS: Multivariate analysis demonstrated the association of PIRADS score with upgrading (P < 0.0001), ECE (P < 0.0001), unfavorable prognosis (P < 0.0001), and large tumor volume (P = 0.002). ROC curves and DCA showed that models including PIRADS score resulted in greater net benefit for almost all the outcomes of interest, with the only exception of SVI. CONCLUSIONS: mpMRI and PIRADS scoring are feasible tools in clinical setting and could be used as decision-support systems for a more accurate selection of patients eligible for AS.

Predicting Pathological Features at Radical Prostatectomy in Patients with Prostate Cancer Eligible for Active Surveillance by Multiparametric Magnetic Resonance Imaging / O. de Cobelli, D. Terracciano, E. Tagliabue, S. Raimondi, D. Bottero, A. Cioffi, B. Jereczek-Fossa, G. Petralia, G. Cordima, G.L. Almeida, G. Lucarelli, C. Buonerba, D.V. Matei, G. Renne, G. Di Lorenzo, M. Ferro. - In: PLOS ONE. - ISSN 1932-6203. - 10:10(2015 Oct 07), pp. e0139696.1-e0139696.14.

Predicting Pathological Features at Radical Prostatectomy in Patients with Prostate Cancer Eligible for Active Surveillance by Multiparametric Magnetic Resonance Imaging

O. de Cobelli;B. Jereczek-Fossa;G. Petralia;
2015

Abstract

PURPOSE: The aim of this study was to investigate the prognostic performance of multiparametric magnetic resonance imaging (mpMRI) and Prostate Imaging Reporting and Data System (PIRADS) score in predicting pathologic features in a cohort of patients eligible for active surveillance who underwent radical prostatectomy. METHODS: A total of 223 patients who fulfilled the criteria for "Prostate Cancer Research International: Active Surveillance", were included. Mp-1.5 Tesla MRI examination staging with endorectal coil was performed at least 6-8 weeks after TRUS-guided biopsy. In all patients, the likelihood of the presence of cancer was assigned using PIRADS score between 1 and 5. Outcomes of interest were: Gleason score upgrading, extra capsular extension (ECE), unfavorable prognosis (occurrence of both upgrading and ECE), large tumor volume (≥ 0.5 ml), and seminal vesicle invasion (SVI). Receiver Operating Characteristic (ROC) curves and Decision Curve Analyses (DCA) were performed for models with and without inclusion of PIRADS score. RESULTS: Multivariate analysis demonstrated the association of PIRADS score with upgrading (P < 0.0001), ECE (P < 0.0001), unfavorable prognosis (P < 0.0001), and large tumor volume (P = 0.002). ROC curves and DCA showed that models including PIRADS score resulted in greater net benefit for almost all the outcomes of interest, with the only exception of SVI. CONCLUSIONS: mpMRI and PIRADS scoring are feasible tools in clinical setting and could be used as decision-support systems for a more accurate selection of patients eligible for AS.
Settore MED/24 - Urologia
Settore MED/36 - Diagnostica per Immagini e Radioterapia
7-ott-2015
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/323871
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