Literature DB >> 29341356

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

Matthew D Greer1, Joanna H Shih2, Tristan Barrett3, Sandra Bednarova4, Ismail Kabakus5, Yan Mee Law6, Haytham Shebel7, Maria J Merino8, Bradford J Wood9, Peter A Pinto10, Peter L Choyke1, Baris Turkbey1.   

Abstract

BACKGROUND: Prostate imaging reporting and data system version 2 (PI-RADSv2) recommends a sector map for reporting findings of prostate cancer mulitparametric MRI (mpMRI). Anecdotally, radiologists may demonstrate inconsistent reproducibility with this map.
PURPOSE: To evaluate interobserver agreement in defining prostate tumor location on mpMRI using the PI-RADSv2 sector map. STUDY TYPE: Retrospective. POPULATION: Thirty consecutive patients who underwent mpMRI between October, 2013 and March, 2015 and who subsequently underwent prostatectomy with whole-mount processing. FIELD STRENGTH: 3T mpMRI with T2 W, diffusion-weighted imaging (DWI) (apparent diffusion coefficient [ADC] and b-2000), dynamic contrast-enhanced (DCE). ASSESSMENT: Six radiologists (two high, two intermediate, and two low experience) from six institutions participated. Readers were blinded to lesion location and detected up to four lesions as per PI-RADSv2 guidelines. Readers marked the long-axis of lesions, saved screen-shots of each lesion, and then marked the lesion location on the PI-RADSv2 sector map. Whole-mount prostatectomy specimens registered to the MRI served as ground truth. Index lesions were defined as the highest grade lesion or largest lesion if grades were equivalent. STATISTICAL TEST: Agreement was calculated for the exact, overlap, and proportion of agreement.
RESULTS: Readers detected an average of 1.9 lesions per patient (range 1.6-2.3). 96.3% (335/348) of all lesions for all readers were scored PI-RADS ≥3. Readers defined a median of 2 (range 1-18) sectors per lesion. Agreement for detecting index lesions by screen shots was 83.7% (76.1%-89.9%) vs. 71.0% (63.1-78.3%) overlap agreement on the PI-RADS sector map (P < 0.001). Exact agreement for defining sectors of detected index lesions was only 21.2% (95% confidence interval [CI]: 14.4-27.7%) and rose to 49.0% (42.4-55.3%) when overlap was considered. Agreement on defining the same level of disease (ie, apex, mid, base) was 61.4% (95% CI 50.2-71.8%). DATA
CONCLUSION: Readers are highly likely to detect the same index lesion on mpMRI, but exhibit poor reproducibility when attempting to define tumor location on the PI-RADSv2 sector map. The poor agreement of the PI-RADSv2 sector map raises concerns its utility in clinical practice. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2018;48:482-490.
© 2018 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  PI-RADSv2; interobserver agreement; prostate mpMRI

Mesh:

Year:  2018        PMID: 29341356      PMCID: PMC7983160          DOI: 10.1002/jmri.25948

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  17 in total

1.  Accuracy and agreement of PIRADSv2 for prostate cancer mpMRI: A multireader study.

Authors:  Matthew D Greer; Anna M Brown; Joanna H Shih; Ronald M Summers; Jamie Marko; Yan Mee Law; Sandeep Sankineni; Arvin K George; Maria J Merino; Peter A Pinto; Peter L Choyke; Baris Turkbey
Journal:  J Magn Reson Imaging       Date:  2016-07-08       Impact factor: 4.813

2.  Interobserver Reproducibility of the PI-RADS Version 2 Lexicon: A Multicenter Study of Six Experienced Prostate Radiologists.

Authors:  Andrew B Rosenkrantz; Luke A Ginocchio; Daniel Cornfeld; Adam T Froemming; Rajan T Gupta; Baris Turkbey; Antonio C Westphalen; James S Babb; Daniel J Margolis
Journal:  Radiology       Date:  2016-04-01       Impact factor: 11.105

Review 3.  A practical primer on PI-RADS version 2: a pictorial essay.

Authors:  Gary Lloyd Horn; Peter Florin Hahn; Shahin Tabatabaei; Mukesh Harisinghani
Journal:  Abdom Radiol (NY)       Date:  2016-05

4.  Comparison of MR/ultrasound fusion-guided biopsy with ultrasound-guided biopsy for the diagnosis of prostate cancer.

Authors:  M Minhaj Siddiqui; Soroush Rais-Bahrami; Baris Turkbey; Arvin K George; Jason Rothwax; Nabeel Shakir; Chinonyerem Okoro; Dima Raskolnikov; Howard L Parnes; W Marston Linehan; Maria J Merino; Richard M Simon; Peter L Choyke; Bradford J Wood; Peter A Pinto
Journal:  JAMA       Date:  2015-01-27       Impact factor: 56.272

5.  The zonal anatomy of the prostate.

Authors:  J E McNeal
Journal:  Prostate       Date:  1981       Impact factor: 4.104

6.  Evaluation of the 'Prostate Interdisciplinary Communication and Mapping Algorithm for Biopsy and Pathology' (PIC-MABP).

Authors:  Daniel Junker; Thomas R W Herrmann; Markus Bader; Jasmin Bektic; Gregor Henkel; Stephan Kruck; Markus Sandbichler; David Schilling; Georg Schäfer; Udo Nagele
Journal:  World J Urol       Date:  2015-07-01       Impact factor: 4.226

7.  Diagnostic Value of Guided Biopsies: Fusion and Cognitive-registration Magnetic Resonance Imaging Versus Conventional Ultrasound Biopsy of the Prostate.

Authors:  Daniel T Oberlin; David D Casalino; Frank H Miller; Richard S Matulewicz; Kent T Perry; Robert B Nadler; Shilajit Kundu; William J Catalona; Joshua J Meeks
Journal:  Urology       Date:  2016-03-07       Impact factor: 2.649

8.  Prospective randomized trial comparing magnetic resonance imaging (MRI)-guided in-bore biopsy to MRI-ultrasound fusion and transrectal ultrasound-guided prostate biopsy in patients with prior negative biopsies.

Authors:  Christian Arsov; Robert Rabenalt; Dirk Blondin; Michael Quentin; Andreas Hiester; Erhard Godehardt; Helmut E Gabbert; Nikolaus Becker; Gerald Antoch; Peter Albers; Lars Schimmöller
Journal:  Eur Urol       Date:  2015-06-23       Impact factor: 20.096

9.  Shape analysis of the prostate: establishing imaging specifications for the design of a transurethral imaging device for prostate brachytherapy guidance.

Authors:  David R Holmes; Brian J Davis; Christopher C Goulet; Torrence M Wilson; Lance A Mynderse; Keith M Furutani; Jon J Camp; Richard A Robb
Journal:  Brachytherapy       Date:  2014-06-21       Impact factor: 2.362

10.  Magnetic resonance imaging for the detection, localisation, and characterisation of prostate cancer: recommendations from a European consensus meeting.

Authors:  Louise Dickinson; Hashim U Ahmed; Clare Allen; Jelle O Barentsz; Brendan Carey; Jurgen J Futterer; Stijn W Heijmink; Peter J Hoskin; Alex Kirkham; Anwar R Padhani; Raj Persad; Philippe Puech; Shonit Punwani; Aslam S Sohaib; Bertrand Tombal; Arnauld Villers; Jan van der Meulen; Mark Emberton
Journal:  Eur Urol       Date:  2010-12-21       Impact factor: 20.096

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  10 in total

1.  Intra- and interreader reproducibility of PI-RADSv2: A multireader study.

Authors:  Clayton P Smith; Stephanie A Harmon; Tristan Barrett; Leonardo K Bittencourt; Yan Mee Law; Haytham Shebel; Julie Y An; Marcin Czarniecki; Sherif Mehralivand; Mehmet Coskun; Bradford J Wood; Peter A Pinto; Joanna H Shih; Peter L Choyke; Baris Turkbey
Journal:  J Magn Reson Imaging       Date:  2018-12-21       Impact factor: 4.813

2.  Simplified PI-RADS with Biparametric MRI: A Practical Approach to Improve Management of PI-RADS Version 2 Category 3 Lesions.

Authors:  Michele Scialpi; Pietro Scialpi; Maria Cristina Aisa; Eugenio Martorana; Alfredo D'Andrea
Journal:  Radiology       Date:  2018-11-06       Impact factor: 11.105

Review 3.  PI-RADS v2: Current standing and future outlook.

Authors:  Clayton P Smith; Barış Türkbey
Journal:  Turk J Urol       Date:  2018-05-01

Review 4.  Quality checkpoints in the MRI-directed prostate cancer diagnostic pathway.

Authors:  Tristan Barrett; Maarten de Rooij; Francesco Giganti; Clare Allen; Jelle O Barentsz; Anwar R Padhani
Journal:  Nat Rev Urol       Date:  2022-09-27       Impact factor: 16.430

5.  Automatic zonal segmentation of the prostate from 2D and 3D T2-weighted MRI and evaluation for clinical use.

Authors:  Dimitri Hamzaoui; Sarah Montagne; Raphaële Renard-Penna; Nicholas Ayache; Hervé Delingette
Journal:  J Med Imaging (Bellingham)       Date:  2022-03-14

Review 6.  PI-RADSv2.1: Current status.

Authors:  Stephanie M Walker; Barış Türkbey
Journal:  Turk J Urol       Date:  2020-10-09

7.  Prospective Evaluation of PI-RADS Version 2.1 for Prostate Cancer Detection.

Authors:  Stephanie M Walker; Sherif Mehralivand; Stephanie A Harmon; Thomas Sanford; Maria J Merino; Bradford J Wood; Joanna H Shih; Peter A Pinto; Peter L Choyke; Baris Turkbey
Journal:  AJR Am J Roentgenol       Date:  2020-09-02       Impact factor: 3.959

Review 8.  Quality in MR reporting (include improvements in acquisition using AI).

Authors:  Liang Wang; Daniel J Margolis; Min Chen; Xinming Zhao; Qiubai Li; Zhenghan Yang; Jie Tian; Zhenchang Wang
Journal:  Br J Radiol       Date:  2022-02-04       Impact factor: 3.039

9.  Deep-Learning-Based Artificial Intelligence for PI-RADS Classification to Assist Multiparametric Prostate MRI Interpretation: A Development Study.

Authors:  Thomas Sanford; Stephanie A Harmon; Evrim B Turkbey; Deepak Kesani; Sena Tuncer; Manuel Madariaga; Chris Yang; Jonathan Sackett; Sherif Mehralivand; Pingkun Yan; Sheng Xu; Bradford J Wood; Maria J Merino; Peter A Pinto; Peter L Choyke; Baris Turkbey
Journal:  J Magn Reson Imaging       Date:  2020-06-01       Impact factor: 5.119

Review 10.  Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review.

Authors:  Michael Roberts; Leonardo Rundo; Nikita Sushentsev; Nadia Moreira Da Silva; Michael Yeung; Tristan Barrett; Evis Sala
Journal:  Insights Imaging       Date:  2022-03-28
  10 in total

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