Literature DB >> 32192942

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

Armando Stabile1, Francesco Giganti2, Veeru Kasivisvanathan3, Gianluca Giannarini4, Caroline M Moore3, Anwar R Padhani5, Valeria Panebianco6, Andrew B Rosenkrantz7, Georg Salomon8, Baris Turkbey9, Geert Villeirs10, Jelle O Barentsz11.   

Abstract

CONTEXT: There is a lack of comprehensive data regarding the factors that influence the diagnostic accuracy of multiparametric magnetic resonance imaging (mpMRI) to detect and localize clinically significant prostate cancer (csPCa).
OBJECTIVE: To systematically review the current literature assessing the factors influencing the variability of mpMRI performance in csPCa diagnosis. EVIDENCE ACQUISITION: A computerized bibliographic search of Medline/PubMed database was performed for all studies assessing magnetic field strength, use of an endorectal coil, assessment system used by radiologists and inter-reader variability, experience of radiologists and urologists, use of a contrast agent, and use of computer-aided diagnosis (CAD) tools in relation to mpMRI diagnostic accuracy. EVIDENCE SYNTHESIS: A total of 77 articles were included. Both radiologists' reading experience and urologists'/radiologists' biopsy experience were the main factors that influenced diagnostic accuracy. Therefore, it is mandatory to indicate the experience of the interpreting radiologists and biopsy-performing urologists to support the reliability of the findings. The most recent Prostate Imaging Reporting and Data System (PI-RADS) guidelines are recommended for use as the main assessment system for csPCa, given the simplified and standardized approach as well as its particular added value for less experienced radiologists. Biparametric MRI had similar accuracy to mpMRI; however, biparametric MRI performed better with experienced readers. The limited data available suggest that the combination of CAD and radiologist readings may influence diagnostic accuracy positively.
CONCLUSIONS: Multiple factors affect the accuracy of mpMRI and MRI-targeted biopsy to detect and localize csPCa. The high heterogeneity across the studies underlines the need to define the experience of radiologists and urologists, implement quality control, and adhere to the most recent PI-RADS assessment guidelines. Further research is needed to clarify which factors impact the accuracy of the MRI pathway and how. PATIENT
SUMMARY: We systematically reported the factors influencing the accuracy of multiparametric magnetic resonance imaging (mpMRI) in detecting clinically significant prostate cancer (csPCa). These factors are significantly related to each other, with the experience of the radiologists being the dominating factor. In order to deliver the benefits of mpMRI to diagnose csPCa, it is necessary to develop expertise for both radiologists and urologists, implement quality control, and adhere to the most recent Prostate Imaging Reporting and Data System assessment guidelines.
Copyright © 2020 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Diagnosis, Multiparametric magnetic resonance imaging; Magnetic resonance imaging; Prostate cancer; Targeted biopsy

Mesh:

Year:  2020        PMID: 32192942      PMCID: PMC8942295          DOI: 10.1016/j.euo.2020.02.005

Source DB:  PubMed          Journal:  Eur Urol Oncol        ISSN: 2588-9311


  109 in total

1.  Computer-aided diagnosis prior to conventional interpretation of prostate mpMRI: an international multi-reader study.

Authors:  Matthew D Greer; Nathan Lay; Joanna H Shih; Tristan Barrett; Leonardo Kayat Bittencourt; Samuel Borofsky; Ismail Kabakus; Yan Mee Law; Jamie Marko; Haytham Shebel; Francesca V Mertan; Maria J Merino; Bradford J Wood; Peter A Pinto; Ronald M Summers; Peter L Choyke; Baris Turkbey
Journal:  Eur Radiol       Date:  2018-04-12       Impact factor: 5.315

2.  Biparametric versus Multiparametric MRI with Non-endorectal Coil at 3T in the Detection and Localization of Prostate Cancer.

Authors:  Michele Scialpi; Enrico Prosperi; Alfredo D'Andrea; Eugenio Martorana; Corrado Malaspina; Barbara Palumbo; Agostino Orlandi; Giuseppe Falcone; Michele Milizia; Luigi Mearini; Maria Cristina Aisa; Pietro Scialpi; Carlo DE Dominicis; Giampaolo Bianchi; Angelo Sidoni
Journal:  Anticancer Res       Date:  2017-03       Impact factor: 2.480

Review 3.  Biparametric vs multiparametric prostate magnetic resonance imaging for the detection of prostate cancer in treatment-naïve patients: a diagnostic test accuracy systematic review and meta-analysis.

Authors:  Mostafa Alabousi; Jean-Paul Salameh; Kaela Gusenbauer; Lucy Samoilov; Ali Jafri; Hang Yu; Abdullah Alabousi
Journal:  BJU Int       Date:  2019-04-25       Impact factor: 5.588

Review 4.  Image-guided prostate biopsy using magnetic resonance imaging-derived targets: a systematic review.

Authors:  Caroline M Moore; Nicola L Robertson; Nasr Arsanious; Thomas Middleton; Arnauld Villers; Laurence Klotz; Samir S Taneja; Mark Emberton
Journal:  Eur Urol       Date:  2012-06-13       Impact factor: 20.096

5.  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

6.  Accuracy and Variability of Prostate Multiparametric Magnetic Resonance Imaging Interpretation Using the Prostate Imaging Reporting and Data System: A Blinded Comparison of Radiologists.

Authors:  Nicholas A Pickersgill; Joel M Vetter; Gerald L Andriole; Anup S Shetty; Kathryn J Fowler; Aaron J Mintz; Cary L Siegel; Eric H Kim
Journal:  Eur Urol Focus       Date:  2018-10-14

7.  The Learning Curve in Prostate MRI Interpretation: Self-Directed Learning Versus Continual Reader Feedback.

Authors:  Andrew B Rosenkrantz; Abimbola Ayoola; David Hoffman; Anunita Khasgiwala; Vinay Prabhu; Paul Smereka; Molly Somberg; Samir S Taneja
Journal:  AJR Am J Roentgenol       Date:  2016-12-27       Impact factor: 3.959

8.  Comparison of prostate cancer detection at 3-T MRI with and without an endorectal coil: A prospective, paired-patient study.

Authors:  Daniel N Costa; Qing Yuan; Yin Xi; Neil M Rofsky; Robert E Lenkinski; Yair Lotan; Claus G Roehrborn; Franto Francis; Debbie Travalini; Ivan Pedrosa
Journal:  Urol Oncol       Date:  2016-03-09       Impact factor: 3.498

9.  Interreader agreement of PI-RADS v. 2 in assessing prostate cancer with multiparametric MRI: A study using whole-mount histology as the standard of reference.

Authors:  Rossano Girometti; Gianluca Giannarini; Franco Greco; Miriam Isola; Lorenzo Cereser; Giuseppe Como; Stefano Sioletic; Stefano Pizzolitto; Alessandro Crestani; Vincenzo Ficarra; Chiara Zuiani
Journal:  J Magn Reson Imaging       Date:  2018-09-05       Impact factor: 4.813

10.  Multi-parametric MRI zone-specific diagnostic model performance compared with experienced radiologists for detection of prostate cancer.

Authors:  Nikolaos Dikaios; Francesco Giganti; Harbir S Sidhu; Edward W Johnston; Mrishta B Appayya; Lucy Simmons; Alex Freeman; Hashim U Ahmed; David Atkinson; Shonit Punwani
Journal:  Eur Radiol       Date:  2018-11-19       Impact factor: 5.315

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  23 in total

1.  A multifaceted approach to quality in the MRI-directed biopsy pathway for prostate cancer diagnosis.

Authors:  Anwar R Padhani; Ivo G Schoots; Baris Turkbey; Gianluca Giannarini; Jelle O Barentsz
Journal:  Eur Radiol       Date:  2020-11-25       Impact factor: 5.315

Review 2.  The role of radiomics in prostate cancer radiotherapy.

Authors:  Rodrigo Delgadillo; John C Ford; Matthew C Abramowitz; Alan Dal Pra; Alan Pollack; Radka Stoyanova
Journal:  Strahlenther Onkol       Date:  2020-08-21       Impact factor: 3.621

3.  Evidence-based guideline recommendations on multiparametric magnetic resonance imaging in the diagnosis of clinically significant prostate cancer: A Cancer Care Ontario updated clinical practice guideline.

Authors:  Masoom A Haider; Judy Brown; Jospeh L K Chin; Nauthan Perlis; Nicola Schieda; Andrew Loblaw
Journal:  Can Urol Assoc J       Date:  2022-02       Impact factor: 1.862

Review 4.  Deep learning-based artificial intelligence applications in prostate MRI: brief summary.

Authors:  Baris Turkbey; Masoom A Haider
Journal:  Br J Radiol       Date:  2021-12-03       Impact factor: 3.039

Review 5.  Emerging MR methods for improved diagnosis of prostate cancer by multiparametric MRI.

Authors:  Durgesh Kumar Dwivedi; Naranamangalam R Jagannathan
Journal:  MAGMA       Date:  2022-07-22       Impact factor: 2.533

Review 6.  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

7.  Prostate biopsy in the era of MRI-targeting: towards a judicious use of additional systematic biopsy.

Authors:  Dominik Deniffel; Nathan Perlis; Sangeet Ghai; Stephanie Girgis; Gerard M Healy; Neil Fleshner; Robert Hamilton; Girish Kulkarni; Ants Toi; Theodorus van der Kwast; Alexandre Zlotta; Antonio Finelli; Masoom A Haider
Journal:  Eur Radiol       Date:  2022-05-04       Impact factor: 7.034

8.  The comparative effectiveness of mpMRI and MRI-guided biopsy vs regular biopsy in a population-based PSA testing: a modeling study.

Authors:  Abraham M Getaneh; Eveline A M Heijnsdijk; Harry J de Koning
Journal:  Sci Rep       Date:  2021-01-19       Impact factor: 4.379

9.  Evaluation of PSA and PSA Density in a Multiparametric Magnetic Resonance Imaging-Directed Diagnostic Pathway for Suspected Prostate Cancer: The INNOVATE Trial.

Authors:  Hayley Pye; Saurabh Singh; Joseph M Norris; Lina M Carmona Echeverria; Vasilis Stavrinides; Alistair Grey; Eoin Dinneen; Elly Pilavachi; Joey Clemente; Susan Heavey; Urszula Stopka-Farooqui; Benjamin S Simpson; Elisenda Bonet-Carne; Dominic Patel; Peter Barker; Keith Burling; Nicola Stevens; Tony Ng; Eleftheria Panagiotaki; David Hawkes; Daniel C Alexander; Manuel Rodriguez-Justo; Aiman Haider; Alex Freeman; Alex Kirkham; David Atkinson; Clare Allen; Greg Shaw; Teresita Beeston; Mrishta Brizmohun Appayya; Arash Latifoltojar; Edward W Johnston; Mark Emberton; Caroline M Moore; Hashim U Ahmed; Shonit Punwani; Hayley C Whitaker
Journal:  Cancers (Basel)       Date:  2021-04-20       Impact factor: 6.575

10.  Tumour blood flow for prediction of human prostate cancer aggressiveness: a study with Rubidium-82 PET, MRI and Na+/K+-ATPase-density.

Authors:  Mads Ryø Jochumsen; Jens Sörensen; Bodil Ginnerup Pedersen; Jens Randel Nyengaard; Søren Rasmus Palmelund Krag; Jørgen Frøkiær; Michael Borre; Kirsten Bouchelouche; Lars Poulsen Tolbod
Journal:  Eur J Nucl Med Mol Imaging       Date:  2020-08-18       Impact factor: 9.236

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