Literature DB >> 25946597

Comparison of readout segmented echo planar imaging (EPI) and EPI with reduced field-of-VIew diffusion-weighted imaging at 3t in patients with breast cancer.

Jin Young Park1, Hee Jung Shin1, Ki Chang Shin1, Yu Sub Sung1, Woo Jung Choi1, Eun Young Chae1, Joo Hee Cha1, Hak Hee Kim1.   

Abstract

PURPOSE: To qualitatively and quantitatively compare the diagnostic performance of rs-EPI (readout segmented echo planar imaging) and reduced FOV (field-of-view) EPI in patients with biopsy-proven breast cancer at 3T.
MATERIALS AND METHODS: Between November 2013 and July 2014, 96 patients (age range, 30-75 years: mean, 52 years) with breast cancer were retrospectively enrolled in this study. In all patients, rs-EPI and rFOV EPI were performed using a 3T MR scanner. Differences between two sequences were compared quantitatively by measuring the tumor apparent diffusion coefficient (ADC), signal-to-noise ratio (SNR), contrast, and contrast-to-noise ratio (CNR). Two independent readers visually assessed overall image quality, lesion conspicuity, and reader preference. The regions of interest (ROIs) were drawn in the whole tumor and in the normal breast parenchyma. Comparisons of quantitative and qualitative parameters between two sequences were performed using the Mann-Whitney and the paired t-test.
RESULTS: SNR was significantly higher in rFOV EPI than in rs-EPI (51.88 ± 27.68 vs. 76.46 ± 50.20, P < 0.001). Mean tumor ADC value and normal tissue ADC were significantly lower in rFOV EPI (P < 0.001). Absolute tumor mean and minimum ADCs of rFOV EPI were significantly lower than those of rs-EPI (P < 0.001 for both). However, normalized ADC did not show a significant difference between the two sequences (P = 0.737). Lesion conspicuity and overall image quality of rFOV EPI were significantly higher than those of rs-EPI for both readers (P = 0.025 and < 0.001).
CONCLUSION: In breast cancer, rFOV EPI provided significantly higher image quality, lesion conspicuity, and SNR than rs-EPI.
© 2015 Wiley Periodicals, Inc.

Entities:  

Keywords:  breast; diffusion-weighted image; neoplasm

Mesh:

Year:  2015        PMID: 25946597     DOI: 10.1002/jmri.24940

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


  10 in total

1.  Diffusion-weighted MRI for Unenhanced Breast Cancer Screening.

Authors:  Nita Amornsiripanitch; Sebastian Bickelhaupt; Hee Jung Shin; Madeline Dang; Habib Rahbar; Katja Pinker; Savannah C Partridge
Journal:  Radiology       Date:  2019-10-08       Impact factor: 11.105

Review 2.  Diffusion-weighted breast MRI: Clinical applications and emerging techniques.

Authors:  Savannah C Partridge; Noam Nissan; Habib Rahbar; Averi E Kitsch; Eric E Sigmund
Journal:  J Magn Reson Imaging       Date:  2016-09-30       Impact factor: 4.813

3.  Quantitative dynamic contrast-enhanced MRI and readout segmentation of long variable echo-trains diffusion-weighted imaging in differentiating parotid gland tumors.

Authors:  Nan Huang; Zebin Xiao; Yu Chen; Dejun She; Wei Guo; Xiefeng Yang; Qi Chen; Dairong Cao; Tanhui Chen
Journal:  Neuroradiology       Date:  2021-07-09       Impact factor: 2.804

4.  Quantitative T2*-Weighted Imaging and Reduced Field-of-View Diffusion-Weighted Imaging of Rectal Cancer: Correlation of R2* and Apparent Diffusion Coefficient With Histopathological Prognostic Factors.

Authors:  Yang Peng; Yan Luo; Xuemei Hu; Yaqi Shen; Daoyu Hu; Zhen Li; Ihab Kamel
Journal:  Front Oncol       Date:  2021-05-24       Impact factor: 6.244

Review 5.  Image formation in diffusion MRI: A review of recent technical developments.

Authors:  Wenchuan Wu; Karla L Miller
Journal:  J Magn Reson Imaging       Date:  2017-02-14       Impact factor: 4.813

Review 6.  Diffusion-Weighted Magnetic Resonance Imaging of the Breast: Standardization of Image Acquisition and Interpretation.

Authors:  Su Hyun Lee; Hee Jung Shin; Woo Kyung Moon
Journal:  Korean J Radiol       Date:  2020-08-28       Impact factor: 3.500

7.  Image quality and whole-lesion histogram and texture analysis of diffusion-weighted imaging of breast MRI based on advanced ZOOMit and simultaneous multislice readout-segmented echo-planar imaging.

Authors:  Kun Sun; Hong Zhu; Bingqing Xia; Xinyue Li; Weimin Chai; Caixia Fu; Benkert Thomas; Wei Liu; Robert Grimm; Weiland Elisabeth; Fuhua Yan
Journal:  Front Oncol       Date:  2022-08-12       Impact factor: 5.738

Review 8.  [Diffusion-Weighted Imaging as a Stand-Alone Breast Imaging Modality].

Authors:  Hee Jung Shin; Su Hyun Lee; Woo Kyung Moon
Journal:  Taehan Yongsang Uihakhoe Chi       Date:  2021-01-31

9.  Rectal Cancer Invasiveness: Whole-Lesion Diffusion-Weighted Imaging (DWI) Histogram Analysis by Comparison of Reduced Field-of-View and Conventional DWI Techniques.

Authors:  Yang Peng; Hao Tang; Xuemei Hu; Yaqi Shen; Ihab Kamel; Zhen Li; Daoyu Hu
Journal:  Sci Rep       Date:  2019-12-10       Impact factor: 4.379

10.  Special Issue "Advances in Breast MRI".

Authors:  Francesca Galati; Rubina Manuela Trimboli; Federica Pediconi
Journal:  Diagnostics (Basel)       Date:  2021-12-08
  10 in total

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