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• CLINICAL ARTICLE •
Radiomics features based on pharmacokinetic dynamic contrast-enhanced magnetic resonance imaging for identifying triple negative breast cancer
WANG Chunhua  LUO Hongbing  LIU Yuanyuan  CHEN Xiaoyu  QING Haomiao  WANG Min  ZHANG Xin  XU Guohui  REN Jing  ZHOU Peng 

Cite this article as: Wang CH, Luo HB, Liu YY, et al. Radiomics features based on pharmacokinetic dynamic contrast-enhanced magnetic resonance imaging for identifying triple negative breast cancer[J]. Chin J Magn Reson Imaging, 2021, 12(2): 29-33. DOI:10.12015/issn.1674-8034.2021.02.007.


[Abstract] Objective To study the evaluation of radiomics features based on pharmacokinetic dynamic contrast-enhanced MRI (DCE-MRI) for differentiating triple negative (TN) breast cancer from other molecular subtype breast cancers. Materials andMethods This retrospective study included 85 patients with breast cancer who underwent pharmacokinetic DCE-MRI before treatment. Breast cancers were classified into four molecular subtypes by immunohistochemistry, including Luminal (n=39), human epidermal growth factor receptor 2 (HER-2) overexpression (n=16) and TN (n=30). Radiomics features of whole breast cancer were extracted from pharmacokinetic quantitative and enhanced images, respectively. Spearman correlation and least absolute shrinkage and selection operator (LASSO) were used for feature selection in R. Logistic model was used for classification of TN vs. luminal, TN vs. HER-2 overexpression, and TN vs. non-TN. Receiver operating characteristics curve and area under curve (AUC) were obtained. Five-fold cross validation was used to verify classification performance.Results For the TN vs. luminal breast cancer, 6 optimal features were selected. Accuracy, and AUC were 0.783 and 0.865, respectively. For the TN vs. HER-2 overexpression breast cancer, 14 optimal features were selected. Accuracy and AUC were 0.870 and 0.923, respectively. For the TN vs. non-TN breast cancer, 17 optimal features were selected. Accuracy and AUC were 0.847 and 0.913, respectively.Conclusions The rediomics features can help to differentiate TN from other molecular subtype breast cancer.
[Keywords] breast tumor；triple negative；magnetic resonance imaging；dynamic enhancement；pharmacokinetics；radiomics

WANG Chunhua1   LUO Hongbing1   LIU Yuanyuan1   CHEN Xiaoyu1   QING Haomiao1   WANG Min1   ZHANG Xin2   XU Guohui1   REN Jing1   ZHOU Peng1*  

1 Department of Radiology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China

2 GE Healthcare, PDx, IPM, Shanghai 201203, China

Zhou P, E-mail: penghyzhou@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS This work was part of National Key Research and Development Program (No. 2017YFC0109405) and the Applied Basic Research Foundation of Science and Technology Department of Sichuan Province (No. 2019YJ0585).
Received  2020-08-07
Accepted  2021-01-12
DOI: 10.12015/issn.1674-8034.2021.02.007
Cite this article as: Wang CH, Luo HB, Liu YY, et al. Radiomics features based on pharmacokinetic dynamic contrast-enhanced magnetic resonance imaging for identifying triple negative breast cancer[J]. Chin J Magn Reson Imaging, 2021, 12(2): 29-33. DOI:10.12015/issn.1674-8034.2021.02.007.

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