Literature DB >> 28657843

Interreader Agreement of Prostate Imaging Reporting and Data System Version 2 Using an In-Bore MRI-Guided Prostate Biopsy Cohort: A Single Institution's Initial Experience.

Daniel I Glazer1, William W Mayo-Smith1, Nisha I Sainani1, Cheryl A Sadow1, Mark G Vangel2, Clare M Tempany1, Ruth M Dunne1.   

Abstract

OBJECTIVE: The purpose of this study is to determine the interobserver agreement of the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) for diagnosing prostate cancer using in-bore MRI-guided prostate biopsy as the reference standard.
MATERIALS AND METHODS: Fifty-nine patients underwent in-bore MRI-guided prostate biopsy between January 21, 2010, and August 21, 2013, and underwent diagnostic multiparametric MRI 6 months or less before biopsy. A single index lesion per patient was selected after retrospective review of MR images. Three fellowship-trained abdominal radiologists (with 1-11 years' experience) blinded to clinical information interpreted all studies according to PI-RADSv2. Interobserver agreement was assessed using Cohen kappa statistics.
RESULTS: Thirty-eight lesions were in the peripheral zone and 21 were in the transition zone. Cancer was diagnosed in 26 patients (44%). Overall PI-RADS scores were higher for all biopsy-positive lesions (mean ± SD, 3.9 ± 1.1) than for biopsy-negative lesions (3.1 ± 1.0; p < 0.0001) and for clinically significant lesions (4.2 ± 1.0) than for clinically insignificant lesions (3.1 ± 1.0; p < 0.0001). Overall suspicion score interobserver agreement was moderate (κ = 0.45). There was moderate interobserver agreement among overall PI-RADS scores in the peripheral zone (κ = 0.46) and fair agreement in the transition zone (κ = 0.36).
CONCLUSION: PI-RADSv2 scores were higher in the biopsy-positive group. PI-RADSv2 showed moderate interobserver agreement among abdominal radiologists with no prior experience using the scoring system.

Entities:  

Keywords:  PI-RADS; multiparametric MRI; prostate cancer

Mesh:

Year:  2017        PMID: 28657843      PMCID: PMC5613666          DOI: 10.2214/AJR.16.17551

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  24 in total

1.  Image registration for targeted MRI-guided transperineal prostate biopsy.

Authors:  Andriy Fedorov; Kemal Tuncali; Fiona M Fennessy; Junichi Tokuda; Nobuhiko Hata; William M Wells; Ron Kikinis; Clare M Tempany
Journal:  J Magn Reson Imaging       Date:  2012-05-29       Impact factor: 4.813

2.  Inter-reader agreement of the ESUR score for prostate MRI using in-bore MRI-guided biopsies as the reference standard.

Authors:  L Schimmöller; M Quentin; C Arsov; R S Lanzman; A Hiester; R Rabenalt; G Antoch; P Albers; D Blondin
Journal:  Eur Radiol       Date:  2013-06-12       Impact factor: 5.315

3.  Use of the percentage of free prostate-specific antigen to enhance differentiation of prostate cancer from benign prostatic disease: a prospective multicenter clinical trial.

Authors:  W J Catalona; A W Partin; K M Slawin; M K Brawer; R C Flanigan; A Patel; J P Richie; J B deKernion; P C Walsh; P T Scardino; P H Lange; E N Subong; R E Parson; G H Gasior; K G Loveland; P C Southwick
Journal:  JAMA       Date:  1998-05-20       Impact factor: 56.272

Review 4.  Prostate cancer detection and diagnosis: the role of MR and its comparison with other diagnostic modalities--a radiologist's perspective.

Authors:  Tobias Penzkofer; Clare M Tempany-Afdhal
Journal:  NMR Biomed       Date:  2013-09-03       Impact factor: 4.044

5.  Prostate Cancer: Interobserver Agreement and Accuracy with the Revised Prostate Imaging Reporting and Data System at Multiparametric MR Imaging.

Authors:  Berrend G Muller; Joanna H Shih; Sandeep Sankineni; Jamie Marko; Soroush Rais-Bahrami; Arvin Koruthu George; Jean J M C H de la Rosette; Maria J Merino; Bradford J Wood; Peter Pinto; Peter L Choyke; Baris Turkbey
Journal:  Radiology       Date:  2015-06-18       Impact factor: 11.105

6.  Assessment of PI-RADS v2 for the Detection of Prostate Cancer.

Authors:  Moritz Kasel-Seibert; Thomas Lehmann; René Aschenbach; Felix V Guettler; Mohamed Abubrig; Marc-Oliver Grimm; Ulf Teichgraeber; Tobias Franiel
Journal:  Eur J Radiol       Date:  2016-01-19       Impact factor: 3.528

Review 7.  Multiparametric MRI of prostate cancer: an update on state-of-the-art techniques and their performance in detecting and localizing prostate cancer.

Authors:  John V Hegde; Robert V Mulkern; Lawrence P Panych; Fiona M Fennessy; Andriy Fedorov; Stephan E Maier; Clare M C Tempany
Journal:  J Magn Reson Imaging       Date:  2013-05       Impact factor: 4.813

8.  Histology core-specific evaluation of the European Society of Urogenital Radiology (ESUR) standardised scoring system of multiparametric magnetic resonance imaging (mpMRI) of the prostate.

Authors:  Timur H Kuru; Matthias C Roethke; Philip Rieker; Wilfried Roth; Michael Fenchel; Markus Hohenfellner; Heinz-Peter Schlemmer; Boris A Hadaschik
Journal:  BJU Int       Date:  2013-08-13       Impact factor: 5.588

9.  ESUR prostate MR guidelines 2012.

Authors:  Jelle O Barentsz; Jonathan Richenberg; Richard Clements; Peter Choyke; Sadhna Verma; Geert Villeirs; Olivier Rouviere; Vibeke Logager; Jurgen J Fütterer
Journal:  Eur Radiol       Date:  2012-02-10       Impact factor: 5.315

Review 10.  Multiparametric MRI in the PSA screening era.

Authors:  Arvin K George; Peter A Pinto; Soroush Rais-Bahrami
Journal:  Biomed Res Int       Date:  2014-08-27       Impact factor: 3.411

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  10 in total

1.  Segmentation of the Prostate Transition Zone and Peripheral Zone on MR Images with Deep Learning.

Authors:  Michelle Bardis; Roozbeh Houshyar; Chanon Chantaduly; Karen Tran-Harding; Alexander Ushinsky; Chantal Chahine; Mark Rupasinghe; Daniel Chow; Peter Chang
Journal:  Radiol Imaging Cancer       Date:  2021-05

2.  Interreader Variability of Prostate Imaging Reporting and Data System Version 2 in Detecting and Assessing Prostate Cancer Lesions at Prostate MRI.

Authors:  Matthew D Greer; Joanna H Shih; Nathan Lay; Tristan Barrett; Leonardo Bittencourt; Samuel Borofsky; Ismail Kabakus; Yan Mee Law; Jamie Marko; Haytham Shebel; Maria J Merino; Bradford J Wood; Peter A Pinto; Ronald M Summers; Peter L Choyke; Baris Turkbey
Journal:  AJR Am J Roentgenol       Date:  2019-03-27       Impact factor: 3.959

3.  Prostate Imaging-Reporting and Data System Steering Committee: PI-RADS v2 Status Update and Future Directions.

Authors:  Anwar R Padhani; Jeffrey Weinreb; Andrew B Rosenkrantz; Geert Villeirs; Baris Turkbey; Jelle Barentsz
Journal:  Eur Urol       Date:  2018-06-13       Impact factor: 20.096

Review 4.  Identification of Tumor-Specific MRI Biomarkers Using Machine Learning (ML).

Authors:  Rima Hajjo; Dima A Sabbah; Sanaa K Bardaweel; Alexander Tropsha
Journal:  Diagnostics (Basel)       Date:  2021-04-21

5.  18F-Choline PET/mpMRI for Detection of Clinically Significant Prostate Cancer: Part 1. Improved Risk Stratification for MRI-Guided Transrectal Prostate Biopsies.

Authors:  Matthew S Davenport; Jeffrey S Montgomery; Lakshmi Priya Kunju; Javed Siddiqui; Prasad R Shankar; Thekkelnaycke Rajendiran; Xia Shao; Eunjee Lee; Brian Denton; Christine Barnett; Morand Piert
Journal:  J Nucl Med       Date:  2019-08-16       Impact factor: 11.082

6.  Prognostic Significance for Long-Term Outcomes Following Radical Prostatectomy in Men with Prostate Cancer: Evaluation with Prostate Imaging Reporting and Data System Version 2.

Authors:  Ran Kim; Chan Kyo Kim; Jung Jae Park; Jae Hun Kim; Seong Il Seo; Seong Soo Jeon; Hyun Moo Lee
Journal:  Korean J Radiol       Date:  2019-02       Impact factor: 3.500

Review 7.  Machine learning applications in prostate cancer magnetic resonance imaging.

Authors:  Renato Cuocolo; Maria Brunella Cipullo; Arnaldo Stanzione; Lorenzo Ugga; Valeria Romeo; Leonardo Radice; Arturo Brunetti; Massimo Imbriaco
Journal:  Eur Radiol Exp       Date:  2019-08-07

8.  Structured reporting in radiologic education - Potential of different PI-RADS versions in prostate MRI controlled by in-bore MR-guided biopsies.

Authors:  Marietta Garmer; Julia Karpienski; Dietrich Hw Groenemeyer; Birgit Wagener; Lars Kamper; Patrick Haage
Journal:  Br J Radiol       Date:  2021-12-16       Impact factor: 3.039

9.  Combining prostate-specific antigen density with prostate imaging reporting and data system score version 2.1 to improve detection of clinically significant prostate cancer: A retrospective study.

Authors:  Yin Lei; Tian Jie Li; Peng Gu; Yu Kun Yang; Lei Zhao; Chao Gao; Juan Hu; Xiao Dong Liu
Journal:  Front Oncol       Date:  2022-09-23       Impact factor: 5.738

10.  Factors Influencing Variability in the Performance of Multiparametric Magnetic Resonance Imaging in Detecting Clinically Significant Prostate Cancer: A Systematic Literature Review.

Authors:  Armando Stabile; Francesco Giganti; Veeru Kasivisvanathan; Gianluca Giannarini; Caroline M Moore; Anwar R Padhani; Valeria Panebianco; Andrew B Rosenkrantz; Georg Salomon; Baris Turkbey; Geert Villeirs; Jelle O Barentsz
Journal:  Eur Urol Oncol       Date:  2020-03-17
  10 in total

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