Literature DB >> 31151899

Differentiation between Luminal A and B Molecular Subtypes of Breast Cancer Using Pharmacokinetic Quantitative Parameters with Histogram and Texture Features on Preoperative Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

Hong-Bing Luo1, Ming-Ying Du1, Yuan-Yuan Liu1, Min Wang1, Hao-Miao Qing1, Zhi-Peng Wen1, Guo-Hui Xu1, Peng Zhou2, Jing Ren3.   

Abstract

OBJECTIVE: The aim of the present study was to use pharmacokinetic quantitative parameters with histogram and texture features on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to differentiate between the luminal A and luminal B molecular subtypes of breast cancer.
METHODS: We retrospectively reviewed the data of 94 patients with histopathologically proven breast cancer. The pharmacokinetic quantitative parameters (Ktrans, Kep, and Ve) with their corresponding histogram and texture features based on preoperative DCE-MRI were obtained. The parameters were compared using the Mann-Whitney U-test between the luminal A and luminal B groups, the human epidermal growth factor receptor-2 (HER2)-positive luminal B and HER2-negative luminal B groups, and the lymph node metastasis (LNM)-positive and LNM-negative groups. Receiver operating characteristic curves were generated for parameters that presented significant between-group differences.
RESULTS: The maximum values of Ktrans, Kep, and Ve, and the mean and 90th percentile values of Ve were significantly higher in the luminal B group than in the luminal A group. Among the texture features, only skewness of Ktrans significantly differed between the luminal A and B groups. All histogram features of Ktrans were higher in the HER2-positive luminal B group than in the HER2-negative luminal B group. However, no parameter differed between the LNM-positive and LNM-negative groups.
CONCLUSION: Pharmacokinetic quantitative parameters with histogram and texture features obtained from DCE-MRI are associated with the molecular subtypes of breast cancer, and may serve as potential imaging biomarkers to differentiate between the luminal A and luminal B molecular subtypes.
Copyright © 2019 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Biomarkers; Breast cancer; Magnetic resonance imaging; Molecular subtype

Year:  2020        PMID: 31151899     DOI: 10.1016/j.acra.2019.05.002

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


  6 in total

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Authors:  Hao Xu; Jieke Liu; Zhe Chen; Chunhua Wang; Yuanyuan Liu; Min Wang; Peng Zhou; Hongbing Luo; Jing Ren
Journal:  Eur Radiol       Date:  2022-01-25       Impact factor: 5.315

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.  Molecular Mechanism of Secondary Endocrine Resistance in Luminal Breast Cancer.

Authors:  Minhua Wu; Jinhua Ding; Limu Wen; Yuxin Zhou; Weizhu Wu
Journal:  Biomed Res Int       Date:  2021-03-16       Impact factor: 3.411

4.  Radiomic features of axillary lymph nodes based on pharmacokinetic modeling DCE-MRI allow preoperative diagnosis of their metastatic status in breast cancer.

Authors:  Hong-Bing Luo; Yuan-Yuan Liu; Chun-Hua Wang; Hao-Miao Qing; Min Wang; Xin Zhang; Xiao-Yu Chen; Guo-Hui Xu; Peng Zhou; Jing Ren
Journal:  PLoS One       Date:  2021-03-01       Impact factor: 3.240

5.  Development and Internal Validation of a Preoperative Prediction Model for Sentinel Lymph Node Status in Breast Cancer: Combining Radiomics Signature and Clinical Factors.

Authors:  Chunhua Wang; Xiaoyu Chen; Hongbing Luo; Yuanyuan Liu; Ruirui Meng; Min Wang; Siyun Liu; Guohui Xu; Jing Ren; Peng Zhou
Journal:  Front Oncol       Date:  2021-11-08       Impact factor: 6.244

6.  Effect of Neoadjuvant Chemotherapy on Angiogenesis and Cell Proliferation of Breast Cancer Evaluated by Dynamic Enhanced Magnetic Resonance Imaging.

Authors:  Lifang Chang; Honglin Lan
Journal:  Biomed Res Int       Date:  2022-07-23       Impact factor: 3.246

  6 in total

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