scholarly journals Evaluation of Prostate Imaging Reporting and Data System Classification in the Prediction of Tumor Aggressiveness in Targeted Magnetic Resonance Imaging/Ultrasound-Fusion Biopsy

2017 ◽  
Vol 99 (2) ◽  
pp. 177-185 ◽  
Author(s):  
Angelika Borkowetz ◽  
Ivan Platzek ◽  
Marieta Toma ◽  
Theresa Renner ◽  
Roman Herout ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Data System ◽  
Tumor Aggressiveness ◽  
Resonance Imaging ◽  
Fusion Biopsy ◽  
Prostate Imaging

scholarly journals Comparing Prostate Imaging-Reporting and Data System Version 2 (PI-RADSv2) Category 1 and 2 Groups: Clinical Implication of Negative Multiparametric Magnetic Resonance Imaging

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Jung Kwon Kim ◽  
Hak Jong Lee ◽  
Sung Il Hwang ◽  
Gheeyoung Choe ◽  
Sung Kyu Hong
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Gleason Score ◽  
Univariate Analysis ◽  
Data System ◽  
Resonance Imaging ◽  
Fusion Biopsy ◽  
Prostate Imaging ◽  
Gleason Pattern ◽  
Clinical Databases

Objectives. To evaluate the clinicopathological differences between Prostate Imaging-Reporting and Data System (PI-RADS) version 2 (v2) category 1 and 2 groups. Materials and Methods. We retrospectively reviewed our two institutional clinical databases: (1) transrectal ultrasound (TRUS)/magnetic resonance imaging (MRI) fusion biopsy cohort (n=706) and (2) radical prostatectomy (RP) cohort (n=1403). Subsequently, we performed comparative analyses between PI-RADSv2 category 1 and 2 groups. Clinically significant prostate cancer (csPCa) was defined as the presence of Gleason score GS≥3+4 in a single biopsy core, and adverse pathology (AP) was defined as high-grade (primary Gleason pattern 4 or any pattern 5) and/or non-organ-confined disease (pT3/N1). We also performed multivariate logistic regression analyses for AP. Results. In the TRUS/MRI fusion biopsy cohort, no significant differences in detection rates of all cancer (18.2% vs. 29.0%, respectively, P=0.730) or csPCa (9.1% vs. 9.9%, respectively, P=0.692) were observed between PI-RADSv2 category 1 and 2 groups. There were no significant differences in pathologic outcomes including Gleason score (≥4+3, 21.2% vs. 29.9%, respectively, P=0.420) or detection rate of AP (27.3% vs. 33.8%, respectively, P=0.561) between the two groups in the RP cohort either. PI-RADSv2 category 1 or 2 had no significant association with AP, even in univariate analysis (P=0.299). Conclusions. PI-RADSv2 categories 1 and 2 had similar performance to predict clinicopathological outcomes. Consequently, these two categories may be unified into a single category. Negative mpMRI does not guarantee the absence of AP, as with csPCa.

scholarly journals Standardization of Multiparametric Prostate MR Imaging Using PI-RADS

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Joyce G. R. Bomers ◽  
Jelle O. Barentsz
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Mr Imaging ◽  
Scoring System ◽  
Data System ◽  
Single Parameter ◽  
Resonance Imaging ◽  
Multiparametric Imaging ◽  
Prostate Imaging ◽  
Magnetic Resonance Imaging Mri

The purpose of this paper is to introduce and describe the Prostate Imaging and Reporting Archiving Data System (PI-RADS). For every single parameter the PI-RADS scoring system will be explained and magnetic resonance imaging (MRI) examples will be given. In the end two patient cases are presented to explain the overall interpretation score in multiparametric imaging.

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