Literature DB >> 29501957

ADC at 3.0 T as a noninvasive biomarker for preoperative prediction of Ki67 expression in invasive ductal carcinoma of breast.

Lu Shen1, Guoxing Zhou1, Tong Tong2, Fei Tang1, Yi Lin1, Jie Zhou1, Yibin Wang1, Genlin Zong1, Lei Zhang3.   

Abstract

PURPOSE: To investigate the role of apparent diffusion coefficient (ADC) as an imaging biomarker for invasive ductal carcinoma (IDC) in the breast.
METHODS: Seventy-one patients undergoing 3.0 Tesla DWI were retrospectively enrolled. Correlations between the ADC values and prognostic factors were evaluated.
RESULTS: Multivariate regression analyses showed that Ki67 expression and molecular subtype were independently associated with the ADC. Discriminant analysis excluded the ADC as a good biomarker for subtype, but the mean ADC significantly distinguished Ki67-positive (low ADC) from Ki67-negative (high ADC) lesions, as observed in the in ROC curves, with a diagnostic sensitivity of 1.00 and a cut-off value of 0.97 × 10-3 mm2/s.
CONCLUSION: The ADC may be helpful for predicting Ki67 expression in IDC preoperatively.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Diffusion weighted imaging; Invasive ductal carcinoma; Ki67; Magnetic resonance imaging

Mesh:

Substances:

Year:  2018        PMID: 29501957     DOI: 10.1016/j.clinimag.2018.02.010

Source DB:  PubMed          Journal:  Clin Imaging        ISSN: 0899-7071            Impact factor:   1.605


  8 in total

1.  Apparent Diffusion Coefficient Histogram Analysis for Assessing Tumor Staging and Detection of Lymph Node Metastasis in Epithelial Ovarian Cancer: Correlation with p53 and Ki-67 Expression.

Authors:  Feng Wang; Yuxiang Wang; Yan Zhou; Congrong Liu; Dong Liang; Lizhi Xie; Zhihang Yao; Jianyu Liu
Journal:  Mol Imaging Biol       Date:  2019-08       Impact factor: 3.488

2.  DWI and IVIM are predictors of Ki67 proliferation index: direct comparison of MRI images and pathological slices in a murine model of rhabdomyosarcoma.

Authors:  Yuan Yuan; Dewei Zeng; Yajie Liu; Juan Tao; Yu Zhang; Jie Yang; Tsendjav Lkhagvadorj; Zhenzhen Yin; Shaowu Wang
Journal:  Eur Radiol       Date:  2019-11-08       Impact factor: 5.315

3.  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

4.  An analysis of Ki-67 expression in stage 1 invasive ductal breast carcinoma using apparent diffusion coefficient histograms.

Authors:  Maolin Xu; Qi Tang; Manxiu Li; Yulin Liu; Fang Li
Journal:  Quant Imaging Med Surg       Date:  2021-04

5.  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

6.  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 7.  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 8.  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

  8 in total

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