Literature DB >> 27130048

Diffusion-weighted imaging in the assessment of prostate cancer: Comparison of zoomed imaging and conventional technique.

Cornelia Brendle1, Petros Martirosian2, Nina F Schwenzer3, Sascha Kaufmann3, Stephan Kruck4, Ulrich Kramer3, Mike Notohamiprodjo3, Konstantin Nikolaou3, Christina Schraml5.   

Abstract

PURPOSE: To compare reduced field-of-view (zoomed) diffusion-weighted imaging (DWI) and conventional DWI in the evaluation of prostate cancer with respect to lesion detection, image quality and alignment accuracy.
MATERIAL AND METHODS: The study was carried out in accordance with the Declaration of Helsinki and was approved by the institutional review board. Image data of 29 histology-proven prostate cancer lesions in 15 patients were evaluated. All patients underwent both conventional DWI and zoomed DWI at 3T. Zoomed DWI and conventional DWI sequences were analysed qualitatively and quantitatively. Subjective image quality, visual distortion and presence of artefacts were rated on a 5-point Likert scale (1=excellent) by two readers in consensus. Lesion conspicuity, sensitivity and specificity in lesion detection were evaluated and compared for both DWI sequences using ROC curves and area under the curve (AUC). To analyze the geographic distortion in DWI the alignment accuracy of prostate and lesions was measured in three spatial dimensions referring to the T2-weighted anatomical images as reference. In a region of interest (ROI) evaluation, ADC values were measured in prostate tissue and malignant lesions. Comparison of qualitative and quantitative parameters was performed using Wilcoxon test with subsequent Bonferroni correction.
RESULTS: Subjective image quality was rated significantly higher in zoomed DWI compared to conventional DWI (2.1±0.9 vs. 2.7±0.9; p=0.0375). Visual distortion and artefacts were reduced in zoomed DWI without reaching statistical significance (1.8±0.7 vs. 2.4±1.0 and 2.1±1.0 vs. 2.5±1.0). Sensitivity and specificity of zoomed and conventional DWI were not significantly different. Zoomed DWI had a slightly higher AUC compared to conventional DWI without significant difference (0.82 versus 0.78; p=0.0576). Lesion conspicuity did not significantly differ between zoomed DWI and conventional DWI (1.8±0.8 vs. 1.9±1.0; p=0.8523). The alignment accuracy of zoomed DWI was significantly higher regarding both the prostate gland and lesions (deviation of outer contours of lesions in sagittal plane: 3±4mm vs. 5±3mm; p=0.0008). ADC tended to be higher in zoomed DWI without statistical significance (ADCmean in peripheral zone: 1.7±0.2×10(-3)mm(2)/s vs. 1.5±0.4×10(-3)mm(2)/s; ADCmean in lesion: 1.0±0.71×10(-3)mm(2)/s vs. 0.8±0.2×10(-3)mm(2)/s).
CONCLUSIONS: Zoomed technique offers improved image quality for diffusion-weighted imaging of the prostate with reduced image distortion both for the whole gland as well as for cancer lesions and at least comparable diagnostic performance. The zoomed technique could be useful for multiparametric tissue characterization but also for biopsy and radiation therapy planning.
Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Diffusion-weighted imaging; Magnetic resonance imaging; Prostate cancer; Reduced field of view; Zoomed imaging

Mesh:

Year:  2016        PMID: 27130048     DOI: 10.1016/j.ejrad.2016.02.020

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


  11 in total

1.  Quantitative diffusion MRI using reduced field-of-view and multi-shot acquisition techniques: Validation in phantoms and prostate imaging.

Authors:  Yuxin Zhang; James Holmes; Iñaki Rabanillo; Arnaud Guidon; Shane Wells; Diego Hernando
Journal:  Magn Reson Imaging       Date:  2018-04-17       Impact factor: 2.546

Review 2.  Diffusion and quantification of diffusion of prostate cancer.

Authors:  Yoshiko Ueno; Tsutomu Tamada; Keitaro Sofue; Takamichi Murakami
Journal:  Br J Radiol       Date:  2021-09-19       Impact factor: 3.039

3.  Synthesizing High-b-Value Diffusion-weighted Imaging of the Prostate Using Generative Adversarial Networks.

Authors:  Lei Hu; Da-Wei Zhou; Yun-Fei Zha; Liang Li; Huan He; Wen-Hao Xu; Li Qian; Yi-Kun Zhang; Cai-Xia Fu; Hui Hu; Jun-Gong Zhao
Journal:  Radiol Artif Intell       Date:  2021-06-02

Review 4.  Emerging MR methods for improved diagnosis of prostate cancer by multiparametric MRI.

Authors:  Durgesh Kumar Dwivedi; Naranamangalam R Jagannathan
Journal:  MAGMA       Date:  2022-07-22       Impact factor: 2.533

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.  Quantitative diffusion MRI of the abdomen and pelvis.

Authors:  Diego Hernando; Yuxin Zhang; Ali Pirasteh
Journal:  Med Phys       Date:  2021-10-08       Impact factor: 4.506

7.  Reproducibility and feasibility of optic nerve diffusion MRI techniques: single-shot echo-planar imaging (EPI), readout-segmented EPI, and reduced field-of-view diffusion-weighted imaging.

Authors:  Fanglu Zhou; Qing Li; Xiaohui Zhang; Hongli Ma; Ge Zhang; Silin Du; Lijun Zhang; Thomas Benkert; Zhiwei Zhang
Journal:  BMC Med Imaging       Date:  2022-05-24       Impact factor: 2.795

8.  Accelerated Segmented Diffusion-Weighted Prostate Imaging for Higher Resolution, Higher Geometric Fidelity, and Multi-b Perfusion Estimation.

Authors:  Pelin Aksit Ciris; Jr-Yuan George Chiou; Daniel I Glazer; Tzu-Cheng Chao; Clare M Tempany-Afdhal; Bruno Madore; Stephan E Maier
Journal:  Invest Radiol       Date:  2019-04       Impact factor: 6.016

9.  The diagnostic accuracy of high b-value diffusion- and T2-weighted imaging for the detection of prostate cancer: a meta-analysis.

Authors:  Tom J Syer; Keith C Godley; Donnie Cameron; Paul N Malcolm
Journal:  Abdom Radiol (NY)       Date:  2018-07

10.  Differentiation of orbital lymphoma and idiopathic orbital inflammatory pseudotumor: combined diagnostic value of conventional MRI and histogram analysis of ADC maps.

Authors:  Jiliang Ren; Ying Yuan; Yingwei Wu; Xiaofeng Tao
Journal:  BMC Med Imaging       Date:  2018-05-02       Impact factor: 1.930

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