Literature DB >> 26724653

Differences in morphological features and minimum apparent diffusion coefficient values among breast cancer subtypes using 3-tesla MRI.

Fumi Kato1, Kohsuke Kudo2, Hiroko Yamashita3, Jeff Wang4, Mitsuchika Hosoda5, Kanako C Hatanaka6, Rie Mimura7, Noriko Oyama-Manabe8, Hiroki Shirato9.   

Abstract

PURPOSE: To compare the morphology and minimum apparent diffusion coefficient (ADC) values among breast cancer subtypes.
METHODS: Ninety-three patients, who underwent breast MRI and collectively had 98 pathologically proven invasive carcinomas, were enrolled. Morphology was evaluated according to BIRADS-MRI. Minimum ADC was measured. Morphology and minimum ADC were compared among subtypes. Multivariate logistic regression analyses were used to identify the characteristics associated with different subtypes.
RESULTS: Oval/round shape was significantly associated with triple-negative (TN) cancer (TN vs. non-TN: 90.9% vs. 45.2%; p=0.0123). Rim enhancement was significantly less frequent in Luminal A (Luminal A vs. non-Luminal A: 34.2% vs. 76.1%; p=0.0003). The minimum ADC of Luminal A was significantly higher than that of Luminal B (HER2-negative) (834 vs. 748×10(-6)mm(2)/s; p<0.025). The minimum ADC of the TN-special type was significantly higher than that of TN-ductal (997 vs. 702×10(-6)mm(2)/s; p<0.025). On the multivariate analysis comparing the characteristics associated with Luminal A vs. Luminal B (HER2-negative), the internal enhancement characteristics of the mass and minimum ADC were significant factors.
CONCLUSION: Morphology and minimum ADC would be useful in distinguishing breast cancer subtypes.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Breast cancer subtypes; Diffusion weighed imaging; Ki-67; Magnetic resonance imaging

Mesh:

Substances:

Year:  2015        PMID: 26724653     DOI: 10.1016/j.ejrad.2015.10.018

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


  13 in total

1.  Differentiation of triple-negative breast cancer from other subtypes through whole-tumor histogram analysis on multiparametric MR imaging.

Authors:  Tianwen Xie; Qiufeng Zhao; Caixia Fu; Qianming Bai; Xiaoyan Zhou; Lihua Li; Robert Grimm; Li Liu; Yajia Gu; Weijun Peng
Journal:  Eur Radiol       Date:  2018-11-06       Impact factor: 5.315

2.  Correlation between minimum apparent diffusion coefficient values and the histological grade of breast invasive ductal carcinoma.

Authors:  Suhong Zhao; Weihua Guo; Ru Tan; Peipei Chen; Zhaohua Li; Fengguo Sun; Guangrui Shao
Journal:  Oncol Lett       Date:  2018-03-23       Impact factor: 2.967

3.  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

4.  Whole-lesion apparent diffusion coefficient (ADC) metrics as a marker of breast tumour characterization-comparison between ADC value and ADC entropy.

Authors:  Haralambos Bougias; Abraham Ghiatas; Dimitrios Priovolos; Konstantia Veliou; Alexandra Christou
Journal:  Br J Radiol       Date:  2016-10-10       Impact factor: 3.039

5.  Associations Between Dynamic Contrast Enhanced Magnetic Resonance Imaging and Clinically Relevant Histopathological Features in Breast Cancer: A Multicenter Analysis.

Authors:  Alexey Surov; Jin You Kim; Marco Aiello; Wei Huang; Thomas E Yankeelov; Andreas Wienke; Maciej Pech
Journal:  In Vivo       Date:  2022 Jan-Feb       Impact factor: 2.155

6.  Diffusion-Weighted Imaging of Different Breast Cancer Molecular Subtypes: A Systematic Review and Meta-Analysis.

Authors:  Hans-Jonas Meyer; Andreas Wienke; Alexey Surov
Journal:  Breast Care (Basel)       Date:  2021-02-23       Impact factor: 2.860

7.  Apparent diffusion coefficient cannot predict molecular subtype and lymph node metastases in invasive breast cancer: a multicenter analysis.

Authors:  Alexey Surov; Yun-Woo Chang; Lihua Li; Laura Martincich; Savannah C Partridge; Jin You Kim; Andreas Wienke
Journal:  BMC Cancer       Date:  2019-11-05       Impact factor: 4.430

8.  The Spatial Relationship between Apparent Diffusion Coefficient and Standardized Uptake Value of 18F-Fluorodeoxyglucose Has a Crucial Influence on the Numeric Correlation of Both Parameters in PET/MRI of Lung Tumors.

Authors:  Alexander W Sauter; Bram Stieltjes; Thomas Weikert; Sergios Gatidis; Mark Wiese; Markus Klarhöfer; Damian Wild; Didier Lardinois; Jens Bremerich; Gregor Sommer
Journal:  Contrast Media Mol Imaging       Date:  2017-12-17       Impact factor: 3.161

9.  Correlation between the dynamic contrast-enhanced MRI features and prognostic factors in breast cancer: A retrospective case-control study.

Authors:  Weijing Tao; Chunhong Hu; Genji Bai; Yan Zhu; Yaning Zhu
Journal:  Medicine (Baltimore)       Date:  2018-07       Impact factor: 1.889

10.  Non-Invasive Assessment of Breast Cancer Molecular Subtypes with Multiparametric Magnetic Resonance Imaging Radiomics.

Authors:  Doris Leithner; Marius E Mayerhoefer; Danny F Martinez; Maxine S Jochelson; Elizabeth A Morris; Sunitha B Thakur; Katja Pinker
Journal:  J Clin Med       Date:  2020-06-14       Impact factor: 4.241

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