Literature DB >> 30788558

Prostate cancer detection with biparametric magnetic resonance imaging (bpMRI) by readers with different experience: performance and comparison with multiparametric (mpMRI).

Marco Gatti1, Riccardo Faletti2, Giorgio Calleris3, Jacopo Giglio2, Claudio Berzovini2, Francesco Gentile2, Giancarlo Marra3, Francesca Misischi2, Luca Molinaro4, Laura Bergamasco5, Paolo Gontero3, Mauro Papotti4, Paolo Fonio2.   

Abstract

PURPOSE: To study the detection of clinically significant prostate cancer (PCa) by readers with different experience, comparing performance with biparametric magnetic resonance imaging (bmMRI) and with the reference multiparametric (mpMRI).
METHODS: Retrospective analysis of 68 patients with mpMRI of the prostate at 1.5 Tesla using a 32 phased-array coil. Forty-five patients (cases) underwent radical prostatectomy, whereas 23 (controls) had a negative prostate biopsy and ≥ 2.5 years of negative follow-up. Six observers (two with 1000 cases interpreted, two with 300, two with 100) performed the analysis first with bpMRI including diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) maps and T2-weighted (T2W) imaging in three planes and, after 1 month, with mpMRI, adding dynamic contrast enhancement (DCE). The performance was quantified by sensitivity (SNS), specificity (SPC) and area under the curve (AUC) of the ROC (Receiver Operating Characteristics) procedure.
RESULTS: Concordance within observers of equivalent experience was good (weighted Cohen's k ≈ 0.7). The two expert readers performed as well in bpMRI as in mpMRI (SNS = 0.91-0.96, AUC = 0.86-0.93; p ≥ 0.10); readers with 300 cases performed well in mpMRI, but significantly worse in bpMR: SNS = 0.58 versus 0.91 (p < 0.0001) and AUC = 0.73 versus 0.86 (p = 0.01); the limited experience of readers with 100 cases showed in mpMRI (SNS = 0.71; AUC = 0.77) and even more in bpMRI (SNS = 0.50; AUC = 0.68).
CONCLUSION: The study revealed the impact of the readers' experience when using bpMRI. The bpMRI without contrast media was a valid alternative for expert readers, whereas less experienced ones needed DCE to significantly boost SNS and AUC. Results indicate 700-800 cases as threshold for reliable interpretation with bpMRI.

Entities:  

Keywords:  Biparametric magnetic resonance imaging (bpMRI); Diffusion-weighted imaging; Dynamic contrast-enhanced imaging (DCE); Prostate cancer (PCa); Prostate imaging reporting and data system version 2 (PI-RADS v2)

Mesh:

Substances:

Year:  2019        PMID: 30788558     DOI: 10.1007/s00261-019-01934-3

Source DB:  PubMed          Journal:  Abdom Radiol (NY)


  22 in total

1.  Multivariate use of MRI biomarkers to classify histologically confirmed necrosis in symptomatic total hip arthroplasty.

Authors:  Mohammad Sherafati; Thomas W Bauer; Hollis G Potter; Matthew F Koff; Kevin M Koch
Journal:  J Orthop Res       Date:  2020-03-23       Impact factor: 3.494

2.  [Importance of magnetic resonance imaging/ultrasound-guided fusion biopsy for the detection and monitoring of prostate cancer].

Authors:  R Ganzer; W Brummeisl; F S Siokou; R Scheck; T Franz; P Ho-Thi; A Mangold
Journal:  Urologe A       Date:  2019-12       Impact factor: 0.639

3.  Detecting Prostate Cancer with Deep Learning for MRI: A Small Step Forward.

Authors:  Anwar R Padhani; Baris Turkbey
Journal:  Radiology       Date:  2019-10-08       Impact factor: 11.105

Review 4.  Is perfect the enemy of good? Weighing the evidence for biparametric MRI in prostate cancer.

Authors:  Alexander P Cole; Bjoern J Langbein; Francesco Giganti; Fiona M Fennessy; Clare M Tempany; Mark Emberton
Journal:  Br J Radiol       Date:  2021-12-16       Impact factor: 3.039

5.  Biparametric prostate MRI: impact of a deep learning-based software and of quantitative ADC values on the inter-reader agreement of experienced and inexperienced readers.

Authors:  Stefano Cipollari; Martina Pecoraro; Alì Forookhi; Ludovica Laschena; Marco Bicchetti; Emanuele Messina; Sara Lucciola; Carlo Catalano; Valeria Panebianco
Journal:  Radiol Med       Date:  2022-09-17       Impact factor: 6.313

6.  Analysis of Apparent Diffusion Coefficient Value and Dynamic Contrast-Enhanced Magnetic Resonance Imaging Parameters of Prostate Cancer Patients after Diagnosis and Treatment with Magnetic Resonance Imaging.

Authors:  Peng Gu
Journal:  Comput Math Methods Med       Date:  2022-06-23       Impact factor: 2.809

7.  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 8.  PI-RADSv2.1: Current status.

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

Review 9.  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

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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