PI-RADS Prostate Imaging – Reporting and Data System: 2015, Version 2

By J. Weinreb, Jelle O. Barentsz, Peter L. Choyke, F. Cornud, M. Haider, K. Macura, D. Margolis, M. Schnall, F. Shtern, C. Tempany and 2 more. European Urology, 2015

2,906 citations recorded by the source corpus.

The Prostate Imaging – Reporting and Data System Version 2 (PI-RADS™ v2) is the product of an international collaboration of the American College of Radiology (ACR), European Society of Uroradiology (ESUR), and AdMetech Foundation. It is designed to promote global standardization and diminish variation in the acquisition, interpretation, and reporting of prostate multiparametric magnetic resonance imaging (mpMRI) examination, and it is based on the best available evidence and expert consensus opinion. It establishes minimum acceptable technical parameters for prostate mpMRI, simplifies and standardizes terminology and content of reports, and provides assessment categories that summarize levels of suspicion or risk of clinically significant prostate cancer that can be used to assist selection of patients for biopsies and management. It is intended to be used in routine clinical practice and also to facilitate data collection and outcome monitoring for research.

Subfields: Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/ad4e5d99b9eb32f8f5af5f77017d54902f13cb32

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In Radiology, Nuclear Medicine and Imaging

1. Anwar R. Padhani
2. Andrew B. Rosenkrantz
3. Jelle O. Barentsz

Citations in the corpus

• Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2. (2019, methodology): “In PI-RADS v2, DCE MRI was a required component of mpMRI examinations undertaken for the detection of csPCa [4], although it had a very limited role and was used only when positive to elevate a finding in the PZ with a T2W score of 3–4.”
• Computer‐aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI (2018, methodology): “The Prostate Imaging Reporting and Data System (PI-RADS) was designed to standardize mp-MRI sequence acquisition and reporting and increase the sensitivity of PCa identification by introducing a 5-score strategy to reveal the likelihood of clinically significant disease: highly unlikely (score 1), u”
• Computer‐aided diagnosis of prostate cancer on magnetic resonance imaging using a convolutional neural network algorithm (2018, background): “After many rounds of validation, some limitations remained, and the updated version 2, which is designed to promote global standardisation and diminish variation in the interpretation of prostate MRI examinations, was developed [2].”
• MRI-Targeted or Standard Biopsy for Prostate-Cancer Diagnosis (2018, neutral): “(%) 23 (9) 55 (22) −13 (−19 to −7) <0.”