Literature DB >> 30240296

Head-to-Head Comparison Between Biparametric and Multiparametric MRI for the Diagnosis of Prostate Cancer: A Systematic Review and Meta-Analysis.

Sungmin Woo1,2, Chong Hyun Suh2,3, Sang Youn Kim1, Jeong Yeon Cho1,4, Seung Hyup Kim1,4, Min Hoan Moon5.   

Abstract

OBJECTIVE: The purpose of this study was to perform a systematic review and meta-analysis of a head-to-head comparison between the performance of biparametric MRI (bpMRI; only T2-weighted imaging and DWI) and that of multiparametric MRI (mpMRI; T2-weighted imaging, DWI, dynamic contrast-enhanced MRI) for the diagnosis of prostate cancer.
MATERIALS AND METHODS: The PubMed and Embase databases were searched up to November 11, 2017. The search included diagnostic test accuracy studies that compared bpMRI and mpMRI for prostate cancer diagnosis with histopathologic findings from biopsy or radical prostatectomy as the reference standard. Methodologic quality was evaluated with the revised Quality Assessment of Diagnostic Accuracy Studies tool. Sensitivity and specificity were pooled by means of bivariate and hierarchic summary ROC (HSROC) modeling and graphically presented with HSROC plots. Meta-regression analysis and multiple subgroup analyses were used to compare the diagnostic performances of bpMRI and mpMRI.
RESULTS: Twenty studies (2142 patients) were included. Pooled sensitivity and specificity were 0.74 (95% CI, 0.66-0.81) and 0.90 (95% CI, 0.86-0.93) for bpMRI and 0.76 (95% CI, 0.69-0.82) and 0.89 (95% CI, 0.85-0.93) for mpMRI. MRI protocol (bpMRI vs mpMRI) was not a significant factor in heterogeneity (p = 0.83). In 26 subgroups evaluated on the basis of stratification to clinicopathologic, study, and MRI characteristics, MRI protocol (bpMRI vs mpMRI) was not a significant factor in heterogeneity in any subgroup (p = 0.25-0.97).
CONCLUSION: A head-to-head comparison showed that the performance of bpMRI was similar to that of mpMRI in the diagnosis of prostate cancer. Consistent results were found in multiple subgroup analyses.

Entities:  

Keywords:  MRI; biparametric; contrast media; gadolinium; meta-analysis; multiparametric; prostate cancer

Mesh:

Substances:

Year:  2018        PMID: 30240296     DOI: 10.2214/AJR.18.19880

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  34 in total

1.  Prostate MRI, with or without MRI-targeted biopsy, and systematic biopsy for detecting prostate cancer.

Authors:  Frank-Jan H Drost; Daniël F Osses; Daan Nieboer; Ewout W Steyerberg; Chris H Bangma; Monique J Roobol; Ivo G Schoots
Journal:  Cochrane Database Syst Rev       Date:  2019-04-25

Review 2.  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

3.  Clinical impact of ultra-high b-value (3000 s/mm2) diffusion-weighted magnetic resonance imaging in prostate cancer at 3T: comparison with b-value of 2000 s/mm2.

Authors:  Tsutomu Tamada; Ayumu Kido; Yu Ueda; Mitsuru Takeuchi; Takeshi Fukunaga; Teruki Sone; Akira Yamamoto
Journal:  Br J Radiol       Date:  2021-09-24       Impact factor: 3.039

4.  Simplified PI-RADS (S-PI-RADS) for biparametric MRI to detect and manage prostate cancer: What urologists need to know.

Authors:  Michele Scialpi; Pietro Scialpi; Eugenio Martorana; Riccardo Torre; Antonio Improta; Maria Cristina Aisa; Alfredo D'Andrea; Aldo Di Blasi
Journal:  Turk J Urol       Date:  2021-05

Review 5.  Diffusion-weighted imaging in prostate cancer.

Authors:  Tsutomu Tamada; Yu Ueda; Yoshiko Ueno; Yuichi Kojima; Ayumu Kido; Akira Yamamoto
Journal:  MAGMA       Date:  2021-09-07       Impact factor: 2.533

6.  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

7.  Texture analysis on bi-parametric MRI for evaluation of aggressiveness in patients with prostate cancer.

Authors:  Tae Wook Baek; Seung Ho Kim; Sang Joon Park; Eun Joo Park
Journal:  Abdom Radiol (NY)       Date:  2020-08-01

8.  Interactive, Up-to-date Meta-Analysis of MRI in the Management of Men with Suspected Prostate Cancer.

Authors:  Anton S Becker; Julian Kirchner; Thomas Sartoretti; Soleen Ghafoor; Sungmin Woo; Chong Hyun Suh; Joseph P Erinjeri; Hedvig Hricak; H Alberto Vargas
Journal:  J Digit Imaging       Date:  2020-06       Impact factor: 4.056

Review 9.  Rethinking prostate cancer screening: could MRI be an alternative screening test?

Authors:  David Eldred-Evans; Henry Tam; Heminder Sokhi; Anwar R Padhani; Mathias Winkler; Hashim U Ahmed
Journal:  Nat Rev Urol       Date:  2020-07-21       Impact factor: 14.432

10.  MRI-derived radiomics model for baseline prediction of prostate cancer progression on active surveillance.

Authors:  Nikita Sushentsev; Leonardo Rundo; Oleg Blyuss; Vincent J Gnanapragasam; Evis Sala; Tristan Barrett
Journal:  Sci Rep       Date:  2021-06-21       Impact factor: 4.379

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