Literature DB >> 30187600

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.

Rossano Girometti1, Gianluca Giannarini1, Franco Greco1, Miriam Isola1, Lorenzo Cereser1, Giuseppe Como1, Stefano Sioletic1, Stefano Pizzolitto1, Alessandro Crestani1, Vincenzo Ficarra1, Chiara Zuiani1.   

Abstract

BACKGROUND: Most studies assessing interreader agreement of Prostate Imaging Reporting and Data System v. 2 (PI-RADS v2) have used biopsy as the standard of reference, thus carrying the risk of not definitively noting all existent cancers.
PURPOSE: To evaluate the interreader agreement in assessing prostate cancer (PCa) of PI-RADS v2, using whole-mount histology as the standard of reference. STUDY TYPE: Monocentric prospective cohort study. POPULATION: In all, 48 patients with biopsy-proven PCa referred for radical prostatectomy, undergoing staging multiparametric magnetic resonance imaging (mpMRI) between May 2016 to February 2017. FIELD STRENGTH/SEQUENCE: 3.0T system using high-resolution T2 -weighted imaging, diffusion-weighted imaging (echo-planar imaging with maximum b-value 2000 sec/mm2 ), and dynamic contrast-enhanced imaging (T1 -weighted high resolution isotropic volume examination; THRIVE) ASSESSMENT: Three radiologists blinded to final histology (2-8 years of experience) analyzed mpMRI images independently, scoring imaging findings in accordance with PI-RADS v2. On a per-lesion basis, we calculated overall and pairwise interreader agreement in assigning PI-RADS categories, as well as assessing malignancy with categories ≥3 or ≥4, and stage ≥pT3. STATISTICAL TESTS: Cohen's kappa analysis of agreement.
RESULTS: On 71 lesions found on histology, there was moderate agreement in assigning PI-RADS categories to all cancers (k = 0.53) and clinically significant cancers (csPCa) (k = 0.47). Assessing csPCa with PI-RADS ≥4 cutoff provided higher agreement than PI-RADS ≥3 cutoff (k = 0.63 vs. 0.57). Interreader agreement was higher between more experienced readers, with the most experienced one achieving the highest cancer detection rate (0.73 for csPCa using category ≥4). There was substantial agreement in assessing stage ≥pT3 (k = 0.72). DATA
CONCLUSION: We found moderate to substantial agreement in assigning the PI-RADS v2 categories and assessing the spectrum of cancers found on whole-mount histology, with category 4 as the most reproducible cutoff for csPCa. Readers' experience influenced interreader agreement and cancer detection rate. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:546-555.
© 2018 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  interobserver variability; magnetic resonance imaging; prostatic neoplasms

Mesh:

Year:  2018        PMID: 30187600     DOI: 10.1002/jmri.26220

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


  11 in total

Review 1.  Diagnostic and prognostic significance of extracellular vesicles in prostate cancer drug resistance: A systematic review of the literature.

Authors:  Anna Maria Grimaldi; Marco Salvatore; Carlo Cavaliere
Journal:  Prostate Cancer Prostatic Dis       Date:  2022-03-09       Impact factor: 5.455

2.  The diagnostic accuracy of multiparametric MRI for detection and localization of prostate cancer depends on the affected region.

Authors:  Martina Martins; Stefano Regusci; Stephane Rohner; Ildiko Szalay-Quinodoz; Georges-Antoine De Boccard; Louise Strom; Gerjon Hannink; Sonia Ramos-Pascual; Charles Henry Rochat
Journal:  BJUI Compass       Date:  2020-11-28

3.  Detection and staging of radio-recurrent prostate cancer using multiparametric MRI.

Authors:  Jie-Ying Kowa; Neil Soneji; S Aslam Sohaib; Erik Mayer; Stephen Hazell; Nicholas Butterfield; Joshua Shur; Derfel Ap Dafydd
Journal:  Br J Radiol       Date:  2021-02-15       Impact factor: 3.039

4.  ESUR/ESUI consensus statements on multi-parametric MRI for the detection of clinically significant prostate cancer: quality requirements for image acquisition, interpretation and radiologists' training.

Authors:  Maarten de Rooij; Bas Israël; Marcia Tummers; Hashim U Ahmed; Tristan Barrett; Francesco Giganti; Bernd Hamm; Vibeke Løgager; Anwar Padhani; Valeria Panebianco; Philippe Puech; Jonathan Richenberg; Olivier Rouvière; Georg Salomon; Ivo Schoots; Jeroen Veltman; Geert Villeirs; Jochen Walz; Jelle O Barentsz
Journal:  Eur Radiol       Date:  2020-05-19       Impact factor: 5.315

Review 5.  Evolution of prostate MRI: from multiparametric standard to less-is-better and different-is better strategies.

Authors:  Rossano Girometti; Lorenzo Cereser; Filippo Bonato; Chiara Zuiani
Journal:  Eur Radiol Exp       Date:  2019-01-28

6.  Interobserver reproducibility of the PRECISE scoring system for prostate MRI on active surveillance: results from a two-centre pilot study.

Authors:  Francesco Giganti; Martina Pecoraro; Vasilis Stavrinides; Armando Stabile; Stefano Cipollari; Alessandro Sciarra; Alex Kirkham; Clare Allen; Shonit Punwani; Mark Emberton; Carlo Catalano; Caroline M Moore; Valeria Panebianco
Journal:  Eur Radiol       Date:  2019-12-16       Impact factor: 5.315

7.  Expected impact of MRI-related interreader variability on ProScreen prostate cancer screening trial: a pre-trial validation study.

Authors:  Ronja Hietikko; Tuomas P Kilpeläinen; Anu Kenttämies; Johanna Ronkainen; Kirsty Ijäs; Kati Lind; Suvi Marjasuo; Juha Oksala; Outi Oksanen; Tuomas Saarinen; Ritja Savolainen; Kimmo Taari; Teuvo L J Tammela; Tuomas Mirtti; Kari Natunen; Anssi Auvinen; Antti Rannikko
Journal:  Cancer Imaging       Date:  2020-10-09       Impact factor: 3.909

8.  Textured-Based Deep Learning in Prostate Cancer Classification with 3T Multiparametric MRI: Comparison with PI-RADS-Based Classification.

Authors:  Yongkai Liu; Haoxin Zheng; Zhengrong Liang; Qi Miao; Wayne G Brisbane; Leonard S Marks; Steven S Raman; Robert E Reiter; Guang Yang; Kyunghyun Sung
Journal:  Diagnostics (Basel)       Date:  2021-09-28

9.  The Prognostic Value of PI-RADS Score in CyberKnife Ultra-Hypofractionated Radiotherapy for Localized Prostate Cancer.

Authors:  Marcin Miszczyk; Justyna Rembak-Szynkiewicz; Łukasz Magrowski; Konrad Stawiski; Agnieszka Namysł-Kaletka; Aleksandra Napieralska; Małgorzata Kraszkiewicz; Grzegorz Woźniak; Małgorzata Stąpór-Fudzińska; Grzegorz Głowacki; Benjamin Pradere; Ekaterina Laukhtina; Paweł Rajwa; Wojciech Majewski
Journal:  Cancers (Basel)       Date:  2022-03-23       Impact factor: 6.639

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
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