Literature DB >> 28778511

Differentiation Between Luminal-A and Luminal-B Breast Cancer Using Intravoxel Incoherent Motion and Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

Hiroko Kawashima1, Tosiaki Miyati2, Naoki Ohno2, Masako Ohno3, Masafumi Inokuchi4, Hiroko Ikeda5, Toshifumi Gabata6.   

Abstract

RATIONALE AND
OBJECTIVES: The study aimed to investigate whether intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) can differentiate luminal-B from luminal-A breast cancer
MATERIALS AND METHODS: Biexponential analyses of IVIM and DCE MRI were performed using a 3.0-T MRI scanner, involving 134 patients with 137 pathologically confirmed luminal-type invasive breast cancers. Luminal-type breast cancer was categorized as luminal-B breast cancer (LBBC, Ki-67 ≧ 14%) or luminal-A breast cancer (LABC, Ki-67 < 14%). Quantitative parameters from IVIM (pure diffusion coefficient [D], perfusion-related diffusion coefficient [D*], and fraction [f]) and DCE MRI (initial percentage of enhancement and signal enhancement ratio [SER]) were calculated. The apparent diffusion coefficient (ADC) was also calculated using monoexponential fitting. We correlated these data with the Ki-67 status.
RESULTS: The D and ADC values of LBBC were significantly lower than those of LABC (P = 0.028, P = 0.037). The SER of LBBC was significantly higher than that of LABC (P = 0.004). A univariate analysis showed that a significantly lower D (<0.847 x 10-3 mm2/s), lower ADC (<0.960 × 10-3 mm2/s), and higher SER (>1.071) values were associated with LBBC (all P values <0.01), compared to LABC. In a multivariate analysis, a higher SER (>1.071; odds ratio: 3.0099, 95% confidence interval: 1.4246-6.3593; P = 0.003) value and a lower D (<0.847 × 10-3 mm2/s; odds ratio: 2.6878, 95% confidence interval: 1.0445-6.9162; P = 0.040) value were significantly associated with LBBC, compared to LABC.
CONCLUSION: The SER derived from DCE MRI and the D derived from IVIM are associated independently with the Ki-67 status in patients with luminal-type breast cancer.
Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Ki-67 labeling index; Luminal-type breast cancer; dynamic contrast-enhanced MR imaging; intravoxel incoherent motion; magnetic resonance imaging

Mesh:

Substances:

Year:  2017        PMID: 28778511     DOI: 10.1016/j.acra.2017.06.016

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  11 in total

1.  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

2.  Sigmoid model analysis of breast dynamic contrast-enhanced MRI: Distinguishing between benign and malignant breast masses and breast cancer subtype prediction.

Authors:  Norikazu Koori; Tosiaki Miyati; Naoki Ohno; Hiroko Kawashima; Hiroko Nishikawa
Journal:  J Appl Clin Med Phys       Date:  2022-05-20       Impact factor: 2.243

3.  Diagnostic and prognostic values of contrast‑enhanced ultrasound combined with diffusion‑weighted magnetic resonance imaging in different subtypes of breast cancer.

Authors:  Gui-Feng Liu; Zong-Qiang Wang; Shu-Hua Zhang; Xue-Feng Li; Lin Liu; Ying-Ying Miao; Shao-Nan Yu
Journal:  Int J Mol Med       Date:  2018-03-27       Impact factor: 4.101

4.  Can apparent diffusion coefficient (ADC) distinguish breast cancer from benign breast findings? A meta-analysis based on 13 847 lesions.

Authors:  Alexey Surov; Hans Jonas Meyer; Andreas Wienke
Journal:  BMC Cancer       Date:  2019-10-15       Impact factor: 4.430

5.  Dynamic contrast-enhanced perfusion parameters in ovarian cancer: Good accuracy in identifying high HIF-1α expression.

Authors:  Auni Lindgren; Maarit Anttila; Suvi Rautiainen; Otso Arponen; Kirsi Hämäläinen; Mervi Könönen; Ritva Vanninen; Hanna Sallinen
Journal:  PLoS One       Date:  2019-08-22       Impact factor: 3.240

6.  Quantitative Multiparametric MRI as an Imaging Biomarker for the Prediction of Breast Cancer Receptor Status and Molecular Subtypes.

Authors:  Zhiqi Yang; Xiaofeng Chen; Tianhui Zhang; Fengyan Cheng; Yuting Liao; Xiangguan Chen; Zhuozhi Dai; Weixiong Fan
Journal:  Front Oncol       Date:  2021-09-16       Impact factor: 6.244

7.  Prediction of Prognostic Factors and Genotypes in Patients With Breast Cancer Using Multiple Mathematical Models of MR Diffusion Imaging.

Authors:  Weiwei Wang; Xindong Zhang; Laimin Zhu; Yueqin Chen; Weiqiang Dou; Fan Zhao; Zhe Zhou; Zhanguo Sun
Journal:  Front Oncol       Date:  2022-01-31       Impact factor: 6.244

Review 8.  Breast Cancer Subtypes and Quantitative Magnetic Resonance Imaging: A Systemic Review.

Authors:  Toshiki Kazama; Taro Takahara; Jun Hashimoto
Journal:  Life (Basel)       Date:  2022-03-28

Review 9.  Perfusion-driven Intravoxel Incoherent Motion (IVIM) MRI in Oncology: Applications, Challenges, and Future Trends.

Authors:  Mami Iima
Journal:  Magn Reson Med Sci       Date:  2020-06-15       Impact factor: 2.471

10.  Intravoxel Incoherent Motion Diffusion-Weighted Imaging for Quantitative Differentiation of Breast Tumors: A Meta-Analysis.

Authors:  Jianye Liang; Sihui Zeng; Zhipeng Li; Yanan Kong; Tiebao Meng; Chunyan Zhou; Jieting Chen; YaoPan Wu; Ni He
Journal:  Front Oncol       Date:  2020-10-20       Impact factor: 6.244

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.