Literature DB >> 30327280

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

Nicholas A Pickersgill1, Joel M Vetter1, Gerald L Andriole1, Anup S Shetty2, Kathryn J Fowler2, Aaron J Mintz2, Cary L Siegel2, Eric H Kim3.   

Abstract

BACKGROUND: Multiparametric (mp) magnetic resonance imaging (MRI) has become an important tool for the detection of clinically significant prostate cancer. However, diagnostic accuracy is affected by variability between radiologists.
OBJECTIVE: To determine the accuracy and variability in prostate mpMRI interpretation among radiologists, both individually and in teams, in a blinded fashion. DESIGN, SETTING, AND PARTICIPANTS: A study cohort (n=32) was created from our prospective registry of patients who received prostate mpMRI with subsequent biopsy. The cohort was then independently reviewed by four radiologists of varying levels of experience, who assigned a Prostate Imaging Reporting and Data System (PI-RADS) classification, blinded to all clinical information. Consensus interpretation by teams of two radiologists was evaluated after a 12-wk wash-out period. Interpretive accuracy was calculated with various cutoffs for PI-RADS classification and Gleason score. Variability among individual radiologists and teams was calculated using the Fleiss kappa and intraclass correlation coefficient (ICC). RESULTS AND LIMITATIONS: Using PI-RADS 3+/Gleason 7+ (p<0.01) and PI-RADS 4+/Gleason 6+ (p=0.02) as cutoffs, significant differences in accuracy among the four radiologists were noted. At no cutoff for PI-RADS classification or Gleason score did a team read achieve higher accuracy than the most accurate radiologist. The kappa and ICC ranged from 0.22 to 0.29 for the individuals and from 0.16 to 0.21 for the teams (poor agreement). A larger sample size may be needed to adequately power differences in accuracy among individual radiologists.
CONCLUSIONS: At various cutoffs for PI-RADS classification and Gleason score, we find significant differences in individual radiologist accuracy, as well as a poor agreement among individual radiologists. Consensus interpretations-as teams of two radiologists-did not improve accuracy or reduce variability. PATIENT
SUMMARY: This study investigated radiologist variability and differences in accuracy using multiparametric magnetic resonance imaging for the diagnosis of prostate cancer. Despite attempts to standardize interpretation within the field, we found substantial variability and significant differences in accuracy among individual radiologists.
Copyright © 2018 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Accuracy; Biopsy; Diagnosis; Magnetic resonance imaging; Prostate cancer; Radiologist variability

Mesh:

Year:  2018        PMID: 30327280     DOI: 10.1016/j.euf.2018.10.008

Source DB:  PubMed          Journal:  Eur Urol Focus        ISSN: 2405-4569


  6 in total

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Journal:  Med Image Anal       Date:  2021-01-23       Impact factor: 8.545

Review 2.  Role of Multiparametric Magnetic Resonance Imaging in Predicting Pathologic Outcomes in Prostate Cancer.

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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

4.  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

5.  Use of the MyProstateScore Test to Rule Out Clinically Significant Cancer: Validation of a Straightforward Clinical Testing Approach.

Authors:  Jeffrey J Tosoian; Bruce J Trock; Todd M Morgan; Simpa S Salami; Scott A Tomlins; Daniel E Spratt; Javed Siddiqui; Lakshmi P Kunju; Rachel Botbyl; Zoey Chopra; Balaji Pandian; Nicholas W Eyrich; Gary Longton; Yingye Zheng; Ganesh S Palapattu; John T Wei; Yashar S Niknafs; Arul M Chinnaiyan
Journal:  J Urol       Date:  2020-10-20       Impact factor: 7.450

6.  Clinical utility and cost modelling of the phi test to triage referrals into image-based diagnostic services for suspected prostate cancer: the PRIM (Phi to RefIne Mri) study.

Authors:  Lois Kim; Nicholas Boxall; Anne George; Keith Burling; Pete Acher; Jonathan Aning; Stuart McCracken; Toby Page; Vincent J Gnanapragasam
Journal:  BMC Med       Date:  2020-04-17       Impact factor: 8.775

  6 in total

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