Literature DB >> 26984751

A practical primer on PI-RADS version 2: a pictorial essay.

Gary Lloyd Horn1, Peter Florin Hahn2, Shahin Tabatabaei3, Mukesh Harisinghani2.   

Abstract

Multiparametric magnetic resonance imaging has become an established method for evaluating the prostate for clinically significant prostate adenocarcinoma. Criteria have been developed for categorizing MRI findings, the most frequently used of which is the PI-RADS system. The PI-RADS V2 document provides separate image interpretation and clinical grading sections. Within this article we give an overview of the integrated, algorithmic way, we approach prostate MRI, show images corresponding to each PI-RADS category, and provide several illustrative cases.

Entities:  

Keywords:  Magnetic resonance imaging; PI-RADS; Prostate; Prostatic neoplasms

Mesh:

Substances:

Year:  2016        PMID: 26984751     DOI: 10.1007/s00261-016-0705-z

Source DB:  PubMed          Journal:  Abdom Radiol (NY)


  4 in total

Review 1.  Advances in Prostate Cancer Magnetic Resonance Imaging and Positron Emission Tomography-Computed Tomography for Staging and Radiotherapy Treatment Planning.

Authors:  Drew Moghanaki; Baris Turkbey; Neha Vapiwala; Behfar Ehdaie; Steven J Frank; Patrick W McLaughlin; Mukesh Harisinghani
Journal:  Semin Radiat Oncol       Date:  2016-08-31       Impact factor: 5.934

Review 2.  Essentials of Statistical Methods for Assessing Reliability and Agreement in Quantitative Imaging.

Authors:  Arash Anvari; Elkan F Halpern; Anthony E Samir
Journal:  Acad Radiol       Date:  2017-12-11       Impact factor: 3.173

3.  All over the map: An interobserver agreement study of tumor location based on the PI-RADSv2 sector map.

Authors:  Matthew D Greer; Joanna H Shih; Tristan Barrett; Sandra Bednarova; Ismail Kabakus; Yan Mee Law; Haytham Shebel; Maria J Merino; Bradford J Wood; Peter A Pinto; Peter L Choyke; Baris Turkbey
Journal:  J Magn Reson Imaging       Date:  2018-01-17       Impact factor: 4.813

Review 4.  Variability and Standardization of Quantitative Imaging: Monoparametric to Multiparametric Quantification, Radiomics, and Artificial Intelligence.

Authors:  Akifumi Hagiwara; Shohei Fujita; Yoshiharu Ohno; Shigeki Aoki
Journal:  Invest Radiol       Date:  2020-09       Impact factor: 10.065

  4 in total

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