Literature DB >> 32614123

Comparison of Biparametric and Multiparametric MRI for Clinically Significant Prostate Cancer Detection With PI-RADS Version 2.1.

Tsutomu Tamada1, Ayumu Kido1, Akira Yamamoto1, Mitsuru Takeuchi2, Yoshiyuki Miyaji3, Takuya Moriya4, Teruki Sone1.   

Abstract

BACKGROUND: Biparametric MRI (bpMRI) without dynamic contrast-enhanced MRI (DCE-MRI) results in an elimination of adverse events, shortened examination time, and reduced costs, compared to multiparametric MRI (mpMRI). The ability of bpMRI to detect clinically significant prostate cancer (csPC) with the Prostate Imaging and Reporting Data System version 2.1 (PI-RADS v2.1) compared to standard mpMRI has not been studied extensively.
PURPOSE: To compare the interobserver reliability and diagnostic performance for detecting csPC of bpMRI and mpMRI using PI-RADS v2.1. STUDY TYPE: Retrospective. POPULATION: In all, 103 patients with elevated prostate-specific antigen (PSA) levels who underwent mpMRI and subsequent MRI-ultrasonography fusion-guided prostate-targeted biopsy (MRGB) with or without prostatectomy. FIELD STRENGTH/SEQUENCES: T2 -weighted imaging (T2 WI), diffusion-weighted imaging (DWI), and DCE-MRI at 3T. ASSESSMENT: Three readers independently assessed each suspected PC lesion, assigning a score of 1-5 for T2 WI, a score of 1-5 for DWI, and positive and negative for DCE-MRI according to PI-RADS v2.1 and determined the overall PI-RADS assessment category of bpMRI (T2 WI and DWI) and mpMRI (T2 WI, DWI, and DCE-MRI). The reference standard was MRGB or prostatectomy-derived histopathology. STATISTICAL TESTING: Statistical analysis was performed using the kappa statistic and McNemar and Delong tests.
RESULTS: Of the 165 suspected PC lesions in 103 patients, 81 were diagnosed with csPC and 84 with benign conditions. Interobserver variability of PI-RADS assessment category showed good agreement for bpMRI (kappa value = 0.642) and mpMRI (kappa value = 0.644). For three readers, the diagnostic sensitivity was significantly higher for mpMRI than for bpMRI (P < 0.001 to P = 0.016, respectively), whereas diagnostic specificity was significantly higher for bpMRI than for mpMRI (P < 0.001 each). For three readers, the area under the receiver operating characteristic curve (AUC) was higher for bpMRI than for mpMRI; however, the difference was significant only for Reader 1 and Reader 3 (Reader 1: 0.823 vs. 0.785, P = 0.035; Reader 2: 0.852 vs. 0.829, P = 0.099; and Reader 3: 0.828 vs. 0.773, P = 0.002). DATA
CONCLUSION: For detecting csPC using PI-RADS v2.1, the interobserver reliability and diagnostic performance of bpMRI was comparable with those of mpMRI. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 2.
© 2020 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  magnetic resonance imaging; multiparametric magnetic resonance imaging; prostate neoplasms

Mesh:

Year:  2020        PMID: 32614123     DOI: 10.1002/jmri.27283

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


  17 in total

Review 1.  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

2.  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 3.  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

4.  Evaluation of the Efficiency of MRI-Based Radiomics Classifiers in the Diagnosis of Prostate Lesions.

Authors:  Linghao Li; Lili Gu; Bin Kang; Jiaojiao Yang; Ying Wu; Hao Liu; Shasha Lai; Xueting Wu; Jian Jiang
Journal:  Front Oncol       Date:  2022-07-05       Impact factor: 5.738

Review 5.  PI-RADSv2.1: Current status.

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

6.  Diagnostic value of integrated 18F-PSMA-1007 PET/MRI compared with that of biparametric MRI for the detection of prostate cancer.

Authors:  Yuping Zeng; Xiaoming Leng; Hengbin Liao; Guihua Jiang; Ping Chen
Journal:  Prostate Int       Date:  2022-03-28

7.  Autosegmentation of Prostate Zones and Cancer Regions from Biparametric Magnetic Resonance Images by Using Deep-Learning-Based Neural Networks.

Authors:  Chih-Ching Lai; Hsin-Kai Wang; Fu-Nien Wang; Yu-Ching Peng; Tzu-Ping Lin; Hsu-Hsia Peng; Shu-Huei Shen
Journal:  Sensors (Basel)       Date:  2021-04-12       Impact factor: 3.576

8.  Deep Learning in Prostate Cancer Diagnosis Using Multiparametric Magnetic Resonance Imaging With Whole-Mount Histopathology Referenced Delineations.

Authors:  Danyan Li; Xiaowei Han; Jie Gao; Qing Zhang; Haibo Yang; Shu Liao; Hongqian Guo; Bing Zhang
Journal:  Front Med (Lausanne)       Date:  2022-01-13

9.  A risk model for detecting clinically significant prostate cancer based on bi-parametric magnetic resonance imaging in a Japanese cohort.

Authors:  Kazushige Sakaguchi; Michikata Hayashida; Naoto Tanaka; Suguru Oka; Shinji Urakami
Journal:  Sci Rep       Date:  2021-09-22       Impact factor: 4.379

10.  Synthetic magnetic resonance imaging for primary prostate cancer evaluation: Diagnostic potential of a non-contrast-enhanced bi-parametric approach enhanced with relaxometry measurements.

Authors:  Yuki Arita; Hirotaka Akita; Hirokazu Fujiwara; Masahiro Hashimoto; Keisuke Shigeta; Thomas C Kwee; Soichiro Yoshida; Takeo Kosaka; Shigeo Okuda; Mototsugu Oya; Masahiro Jinzaki
Journal:  Eur J Radiol Open       Date:  2022-02-15
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