Literature DB >> 22161802

Comparisons of multi b-value DWI signal analysis with pathological specimen of breast cancer.

Takayuki Tamura1, Shuji Usui, Shigeru Murakami, Koji Arihiro, Takashi Fujimoto, Tamaki Yamada, Kumiko Naito, Mitoshi Akiyama.   

Abstract

Previous studies have reported that the signal attenuation of diffusion weighted magnetic resonance imaging for tumor tissues displays a non-monoexponential biexponential decay, and the apparent diffusion coefficients (ADCs) can be divided into a fast and slow diffusion component by using a simple biexponential decay model. The purpose of this study is to examine the non-monoexponential character of the diffusion weighted magnetic resonance imaging signal attenuations of breast cancers, estimate the fast and slow diffusion components, and compare them with the extra- and intracellular component information obtained from the pathological specimens. Twenty-two subjects having breast cancers underwent diffusion weighted magnetic resonance imaging using six b-values up to 3500 s/mm(2) and the signal attenuations were analyzed using the biexponential function. The derived slow component fraction correlated with the cellular fraction and the ADCs converged to 0.2-0.3 × 10(-3) mm(2) /s for the higher cellular fractions. The ADCs of the fast component ranged from 1.3 to 3.9 × 10(-3) mm(2) /s and showed no correlation with the extracellular components. This result suggests that the main reason for the decreasing ADC of a breast tumor is the decreasing fraction of the fast component and the increasing fraction of the slow component having a low ADC rather than the decreasing ADC of the fast component by the restricted water diffusion in the reduced extracellular spaces.
Copyright © 2011 Wiley Periodicals, Inc.

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Year:  2011        PMID: 22161802     DOI: 10.1002/mrm.23277

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  17 in total

1.  Application of the diffusion kurtosis model for the study of breast lesions.

Authors:  Luísa Nogueira; Sofia Brandão; Eduarda Matos; Rita Gouveia Nunes; Joana Loureiro; Isabel Ramos; Hugo Alexandre Ferreira
Journal:  Eur Radiol       Date:  2014-03-22       Impact factor: 5.315

2.  Diffusion-weighted imaging: determination of the best pair of b-values to discriminate breast lesions.

Authors:  L Nogueira; S Brandão; E Matos; R G Nunes; J Loureiro; H A Ferreira; I Ramos
Journal:  Br J Radiol       Date:  2014-05-16       Impact factor: 3.039

3.  Intravoxel incoherent motion MR imaging for breast lesions: comparison and correlation with pharmacokinetic evaluation from dynamic contrast-enhanced MR imaging.

Authors:  Chunling Liu; Kun Wang; Queenie Chan; Zaiyi Liu; Jine Zhang; Hui He; Shuixing Zhang; Changhong Liang
Journal:  Eur Radiol       Date:  2016-02-10       Impact factor: 5.315

4.  Apparent diffusion coefficient value in invasive ductal carcinoma at 3.0 Tesla: is it correlated with prognostic factors?

Authors:  Inanc Guvenc; Sinan Akay; Selami Ince; Ramazan Yildiz; Zafer Kilbas; Fahrettin G Oysul; Mustafa Tasar
Journal:  Br J Radiol       Date:  2016-02-08       Impact factor: 3.039

5.  Feasibility and Diagnostic Performance of Voxelwise Computed Diffusion-Weighted Imaging in Breast Cancer.

Authors:  Jiejie Zhou; Endong Chen; Huazhi Xu; Qiong Ye; Jiance Li; Shuxin Ye; Qinyuan Cheng; Liang Zhao; Min-Ying Su; Meihao Wang
Journal:  J Magn Reson Imaging       Date:  2018-10-16       Impact factor: 4.813

6.  Contribution of IVIM to Conventional Dynamic Contrast-Enhanced and Diffusion-Weighted MRI in Differentiating Benign from Malignant Breast Masses.

Authors:  Qingjun Wang; Yong Guo; Jing Zhang; Zijun Wang; Minhua Huang; Yun Zhang
Journal:  Breast Care (Basel)       Date:  2016-08-19       Impact factor: 2.860

7.  Correlation of tumor characteristics derived from DCE-MRI and DW-MRI with histology in murine models of breast cancer.

Authors:  Stephanie L Barnes; Anna G Sorace; Mary E Loveless; Jennifer G Whisenant; Thomas E Yankeelov
Journal:  NMR Biomed       Date:  2015-08-30       Impact factor: 4.044

8.  q-Space Imaging Yields a Higher Effect Gradient to Assess Cellularity than Conventional Diffusion-weighted Imaging Methods at 3.0 T: A Pilot Study with Freshly Excised Whole-Breast Tumors.

Authors:  Nicholas Senn; Yazan Masannat; Ehab Husain; Bernard Siow; Steven D Heys; Jiabao He
Journal:  Radiol Imaging Cancer       Date:  2019-09-27

9.  Discrimination of Breast Cancer from Healthy Breast Tissue Using a Three-component Diffusion-weighted MRI Model.

Authors:  Maren M Sjaastad Andreassen; Ana E Rodríguez-Soto; Rebecca Rakow-Penner; Anders M Dale; Christopher C Conlin; Igor Vidić; Tyler M Seibert; Anne M Wallace; Somaye Zare; Joshua Kuperman; Boya Abudu; Grace S Ahn; Michael Hahn; Neil P Jerome; Agnes Østlie; Tone F Bathen; Haydee Ojeda-Fournier; Pål Erik Goa
Journal:  Clin Cancer Res       Date:  2020-11-04       Impact factor: 12.531

10.  Analysis of multiple B-value diffusion-weighted imaging in pediatric acute encephalopathy.

Authors:  Yasuhiko Tachibana; Noriko Aida; Tetsu Niwa; Kumiko Nozawa; Kouki Kusagiri; Kana Mori; Kazuo Endo; Takayuki Obata; Tomio Inoue
Journal:  PLoS One       Date:  2013-06-03       Impact factor: 3.240

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