Literature DB >> 35119914

Quality in MR reporting (include improvements in acquisition using AI).

Liang Wang1, Daniel J Margolis2, Min Chen3, Xinming Zhao4, Qiubai Li5, Zhenghan Yang1, Jie Tian6,7, Zhenchang Wang1.   

Abstract

The high quality of MRI reporting of the prostate is the most critical component of the service provided by a radiologist. Prostate MRI structured reporting with PI-RADS v. 2.1 has been proven to improve consistency, quality, guideline-based care in the management of prostate cancer. There is room for improved accuracy of prostate mpMRI reporting, particularly as PI-RADS core criteria are subjective for radiologists. The application of artificial intelligence may support radiologists in interpreting MRI scans. This review addresses the quality of prostate multiparametric MRI (mpMRI) structured reporting (include improvements in acquisition using artificial intelligence) in terms of size of prostate gland, imaging quality, lesion location, lesion size, TNM staging, sector map, and discusses the future prospects of quality in MR reporting.

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Mesh:

Year:  2022        PMID: 35119914      PMCID: PMC8978223          DOI: 10.1259/bjr.20210816

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  33 in total

1.  Abbreviated Biparametric Versus Standard Multiparametric MRI for Diagnosis of Prostate Cancer: A Systematic Review and Meta-Analysis.

Authors:  Zhen Kang; Xiangde Min; Jeffrey Weinreb; Qiubai Li; Zhaoyan Feng; Liang Wang
Journal:  AJR Am J Roentgenol       Date:  2018-12-04       Impact factor: 3.959

2.  Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis.

Authors:  Renato Cuocolo; Maria Brunella Cipullo; Arnaldo Stanzione; Valeria Romeo; Roberta Green; Valeria Cantoni; Andrea Ponsiglione; Lorenzo Ugga; Massimo Imbriaco
Journal:  Eur Radiol       Date:  2020-06-30       Impact factor: 5.315

3.  Evidence-Based Reporting: A Method to Optimize Prostate MRI Communications With Referring Physicians.

Authors:  Michael J Magnetta; Ashley L Donovan; Bruce L Jacobs; Benjamin J Davies; Alessandro Furlan
Journal:  AJR Am J Roentgenol       Date:  2017-11-01       Impact factor: 3.959

4.  Classification of Cancer at Prostate MRI: Deep Learning versus Clinical PI-RADS Assessment.

Authors:  Patrick Schelb; Simon Kohl; Jan Philipp Radtke; Manuel Wiesenfarth; Philipp Kickingereder; Sebastian Bickelhaupt; Tristan Anselm Kuder; Albrecht Stenzinger; Markus Hohenfellner; Heinz-Peter Schlemmer; Klaus H Maier-Hein; David Bonekamp
Journal:  Radiology       Date:  2019-10-08       Impact factor: 11.105

5.  Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries.

Authors:  Hyuna Sung; Jacques Ferlay; Rebecca L Siegel; Mathieu Laversanne; Isabelle Soerjomataram; Ahmedin Jemal; Freddie Bray
Journal:  CA Cancer J Clin       Date:  2021-02-04       Impact factor: 508.702

6.  End-to-end prostate cancer detection in bpMRI via 3D CNNs: Effects of attention mechanisms, clinical priori and decoupled false positive reduction.

Authors:  Anindo Saha; Matin Hosseinzadeh; Henkjan Huisman
Journal:  Med Image Anal       Date:  2021-06-29       Impact factor: 8.545

Review 7.  Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2.

Authors:  Baris Turkbey; Andrew B Rosenkrantz; Masoom A Haider; Anwar R Padhani; Geert Villeirs; Katarzyna J Macura; Clare M Tempany; Peter L Choyke; Francois Cornud; Daniel J Margolis; Harriet C Thoeny; Sadhna Verma; Jelle Barentsz; Jeffrey C Weinreb
Journal:  Eur Urol       Date:  2019-03-18       Impact factor: 20.096

8.  Multiparametric prostate MRI quality assessment using a semi-automated PI-QUAL software program.

Authors:  Francesco Giganti; Sydney Lindner; Jonathan W Piper; Veeru Kasivisvanathan; Mark Emberton; Caroline M Moore; Clare Allen
Journal:  Eur Radiol Exp       Date:  2021-11-05

9.  Automatic prostate and prostate zones segmentation of magnetic resonance images using DenseNet-like U-net.

Authors:  Nader Aldoj; Federico Biavati; Florian Michallek; Sebastian Stober; Marc Dewey
Journal:  Sci Rep       Date:  2020-08-31       Impact factor: 4.379

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  1 in total

1.  Innovations in prostate cancer: introductory editorial.

Authors:  Jurgen J Fütterer; Chan Kyo Kim; Daniel J Margolis
Journal:  Br J Radiol       Date:  2022-03       Impact factor: 3.039

  1 in total

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