Literature DB >> 30273613

A Prospective Accuracy Study of Prostate Imaging Reporting and Data System Version 2 on Multiparametric Magnetic Resonance Imaging in Detecting Clinically Significant Prostate Cancer With Whole-mount Pathology.

Gianluca Giannarini1, Rossano Girometti2, Alessandro Crestani1, Marta Rossanese3, Mattia Calandriello1, Lorenzo Cereser2, Sandra Bednarova2, Claudio Battistella4, Stefano Sioletic5, Chiara Zuiani2, Claudio Valotto1, Vincenzo Ficarra6.   

Abstract

OBJECTIVE: To assess the accuracy of Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) in detecting clinically significant prostate cancer (csPCa) on multiparametric magnetic resonance imaging (mpMRI) using whole-mount sections after radical prostatectomy (RP) as reference standard.
METHODS: Forty-eight patients undergoing mpMRI before RP were prospectively enrolled. Two experienced radiologists independently scored and mapped imaging findings according to PI-RADS v2. One experienced uropathologist mapped cancers detected on whole-mount sections using the PI-RADS v2 sector scheme. Per-lesion and per-patient analyses were run. Primary outcomes were sensitivity and false discovery rate (FDR) in detecting csPCa using PI-RADS v2 score ≥3 and ≥4 as thresholds. Secondary outcome was inter-reader agreement.
RESULTS: On the per-lesion analysis, sensitivity and FDR at the PI-RADS v2 threshold score ≥3 were 0.75 and 0.17 for Reader 1, and 0.67 and 0.13 for Reader 2, respectively. At the PI-RADS v2 threshold score ≥4, sensitivity was slightly lower, and FDR nearly halved for both readers. On the per-patient analysis, sensitivity for csPCa at the PI-RADS v2 threshold score ≥3 was 0.85 for Reader 1, and 0.78 for Reader 2. At the PI-RADS v2 threshold score ≥4, sensitivity was slightly lower for both readers. Inter-reader agreement was substantial (k 0.72 and 0.65 for PI-RADS v2 threshold score ≥3 and ≥4, respectively).
CONCLUSION: In our prospective study with pathology after RP as standard of reference, PI-RADS v2 showed good sensitivity in detecting csPCa on mpMRI with substantial agreement between 2 experienced readers. Threshold score ≥4 had lower FDR.
Copyright © 2018. Published by Elsevier Inc.

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Year:  2018        PMID: 30273613     DOI: 10.1016/j.urology.2018.07.067

Source DB:  PubMed          Journal:  Urology        ISSN: 0090-4295            Impact factor:   2.649


  5 in total

1.  Evaluating the performance of clinical and radiological data in predicting prostate cancer in prostate imaging reporting and data system version 2.1 category 3 lesions of the peripheral and the transition zones.

Authors:  Caterina Gaudiano; Lorenzo Bianchi; Beniamino Corcioni; Francesca Giunchi; Riccardo Schiavina; Federica Ciccarese; Lorenzo Braccischi; Arianna Rustici; Michelangelo Fiorentino; Eugenio Brunocilla; Rita Golfieri
Journal:  Int Urol Nephrol       Date:  2021-11-25       Impact factor: 2.370

2.  A systematic review and meta-analysis of the diagnostic accuracy of biparametric prostate MRI for prostate cancer in men at risk.

Authors:  E J Bass; A Pantovic; M Connor; R Gabe; A R Padhani; A Rockall; H Sokhi; H Tam; M Winkler; H U Ahmed
Journal:  Prostate Cancer Prostatic Dis       Date:  2020-11-20       Impact factor: 5.554

3.  A PI-RADS-Based New Nomogram for Predicting Clinically Significant Prostate Cancer: A Cohort Study.

Authors:  Yueyue Zhang; Guiqi Zhu; Wenlu Zhao; Chaogang Wei; Tong Chen; Qi Ma; Yongsheng Zhang; Boxin Xue; Junkang Shen
Journal:  Cancer Manag Res       Date:  2020-05-19       Impact factor: 3.989

4.  Diagnostic performance of PI-RADS version 2.1 compared to version 2.0 for detection of peripheral and transition zone prostate cancer.

Authors:  Madhuri Monique Rudolph; Alexander Daniel Jacques Baur; Hannes Cash; Matthias Haas; Samy Mahjoub; Alexander Hartenstein; Charlie Alexander Hamm; Nick Lasse Beetz; Frank Konietschke; Bernd Hamm; Patrick Asbach; Tobias Penzkofer
Journal:  Sci Rep       Date:  2020-09-29       Impact factor: 4.379

5.  Using IVIM Parameters to Differentiate Prostate Cancer and Contralateral Normal Tissue through Fusion of MRI Images with Whole-Mount Pathology Specimen Images by Control Point Registration Method.

Authors:  Cheng-Chun Lee; Kuang-Hsi Chang; Feng-Mao Chiu; Yen-Chuan Ou; Jen-I Hwang; Kuan-Chun Hsueh; Hueng-Chuen Fan
Journal:  Diagnostics (Basel)       Date:  2021-12-12
  5 in total

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