Literature DB >> 33434861

Application of bi-planar reduced field-of-view DWI (rFOV DWI) in the assessment of muscle-invasiveness of bladder cancer.

Xiaoyan Meng1, Henglong Hu2, Yanchun Wang1, Daoyu Hu1, Zhen Li1, Cui Feng3.   

Abstract

OBJECTIVES: To compare the image quality of the reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with the full field-of-view (fFOV) DWI in the assessment of bladder cancer (BC); and to explore the possible superiority of bi-planar (axial and sagittal) rFOV DWI over single planar fFOV DWI in predicting muscle-invasiveness of BC.
MATERIALS AND METHODS: This retrospective study analyzed 61 patients with BC who underwent DWI sequences including axial fFOV DWI, axial rFOV DWI, and sagittal rFOV DWI. Qualitative and quantitative image quality assessment were compared between axial fFOV DWI and rFOV DWI sequences. The tumor with its base could be clearly displayed on DWI was defined as the evaluable lesion, and the number of evaluable lesions detected from single axial fFOV DWI, axial rFOV DWI, sagittal rFOV DWI, and bi-planar rFOV DWI sequences was recorded and compared. The apparent diffusion coefficient (ADC) was compared between non-muscular-invasive bladder cancer (NMIBC) and muscular-invasive bladder cancer (MIBC) based on the sequences of axial fFOV DWI and rFOV DWI, respectively. Vesical Imaging-Reporting and Data System (VI-RADS) was introduced to evaluate the overall risk of muscle-invasiveness of BC and receiver operating characteristic (ROC) curve analysis was applied to assess the diagnostic performance.
RESULTS: The contrast-to-noise ratio (CNR) of the rFOV DWI was significantly higher than that of fFOV DWI (p < 0.01), while the signal-to-noise ratio (SNR) was significantly lower than that of fFOV DWI (p < 0.01). The subjective score of rFOV DWI was significantly higher than that of fFOV DWI (p < 0.01). The ADC value of the MIBC group was significantly lower than that of the NMIBC in both rFOV DWI and fFOV DWI (all p < 0.01). The number of evaluable lesions detected from the bi-planar rFOV DWI was significantly higher than that detected from the single axial fFOV DWI, axial rFOV DWI, and sagittal rFOV DWI (all p < 0.01). VI-RADS based on the bi-planar rFOV DWI offered high predictive power (the area under the ROC curve, 0.946) for predicting the presence of muscle-invasiveness of BC.
CONCLUSION: Bi-planar rFOV DWI may provide more diagnostic confidence than the single planar DWI for predicting the presence of muscle-invasiveness in BC, with improved image quality over the fFOV DWI.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Bladder cancer; Diffusion weighted imaging; Histopathology; VI-RADS

Mesh:

Year:  2020        PMID: 33434861     DOI: 10.1016/j.ejrad.2020.109486

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  3 in total

Review 1.  Multiparametric magnetic resonance imaging for bladder cancer: a comprehensive systematic review of the Vesical Imaging-Reporting and Data System (VI-RADS) performance and potential clinical applications.

Authors:  Denis Séguier; Philippe Puech; Ronald Kool; Léa Dernis; Héléna Gabert; Wassim Kassouf; Arnauld Villers; Gautier Marcq
Journal:  Ther Adv Urol       Date:  2021-08-25

Review 2.  The accuracy of Vesical Imaging-Reporting and Data System (VI-RADS): an updated comprehensive multi-institutional, multi-readers systematic review and meta-analysis from diagnostic evidence into future clinical recommendations.

Authors:  Francesco Del Giudice; Rocco Simone Flammia; Martina Pecoraro; Marco Moschini; David D'Andrea; Emanuele Messina; Lucia Martina Pisciotti; Ettore De Berardinis; Alessandro Sciarra; Valeria Panebianco
Journal:  World J Urol       Date:  2022-03-16       Impact factor: 3.661

3.  Comparing the clinical utility of single-shot, readout-segmented and zoomit echo-planar imaging in diffusion-weighted imaging of the kidney at 3 T.

Authors:  Wenguang Liu; Hui Liu; Simin Xie; Ismail Bilal Masokano; Yu Bai; Xiao Wang; Linhui Zhong; Yi Wu; Jilin Nie; Gaofeng Zhou; Yigang Pei; Wenzheng Li
Journal:  Sci Rep       Date:  2022-07-20       Impact factor: 4.996

  3 in total

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