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Immunohistochemical index prediction of breast tumor based on multi-dimension features in contrast-enhanced ultrasound

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Abstract

Breast cancer is the leading killer of Chinese women. Immunohistochemistry index has great significance in the treatment strategy selection and prognosis analysis for breast cancer patients. Currently, histopathological examination of the tumor tissue through surgical biopsy is the gold standard to determine immunohistochemistry index. However, this examination is invasive and commonly causes discomfort in patients. There has been a lack of noninvasive method capable of predicting immunohistochemistry index for breast cancer patients. This paper proposes a machine learning method to predict the immunohistochemical index of breast cancer patients by using noninvasive contrast-enhanced ultrasound. A total of 119 breast cancer patients were included in this retrospective study. Each patient implemented the pathological examination of immunohistochemical expression and underwent contrast-enhanced ultrasound imaging of breast tumor. The multi-dimension features including 266 three-dimension features and 837 two-dimension dynamic features were extracted from the contrast-enhanced ultrasound sequences. Using the machine learning prediction method, 21 selected multi-dimension features were integrated to generate a model for predicting the immunohistochemistry index noninvasively. The immunohistochemical index of human epidermal growth factor receptor-2 (HER2) was predicted based on multi-dimension features in contrast-enhanced ultrasound sequence with the sensitivity of 71%, and the specificity of 79% in the testing cohort. Therefore, the noninvasive contrast-enhanced ultrasound can be used to predict the immunohistochemical index. To our best knowledge, no studies have been reported about predicting immunohistochemical index by using contrast-enhanced ultrasound sequences for breast cancer patients. Our proposed method is noninvasive and can predict immunohistochemical index by using contrast-enhanced ultrasound in several minutes, instead of relying totally on the invasive and biopsy-based histopathological examination.

Immunohistochemical index prediction of breast tumor based on multi-dimension features in contrast-enhanced ultrasound.

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Abbreviations

HER2:

Human epidermal growth factor receptor-2

CEUS:

Contrast-enhanced ultrasound

ROI:

Region of interest

3D:

Three-dimension

2D:

Two-dimension

AUC:

Area under the receiver operating characteristic curve

ER:

Estrogen receptor

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Acknowledgments

We would like to thank Doctor Baojie Wen for his assistance in re-evaluating the histopathological slices.

Funding

This work was supported by the National Nature Science Foundation of China grants (61901214, 81771940), the Fundamental Research Funds for the Central Universities (NJ2019010), and the National Key Research and Development Program of China (2018YFC2001600, 2018YFC2001602, 2017YFC0108000).

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China

    Fang Chen & Peng Wan

  2. Baidu Online Network Technology, AI innovation business, Beijing, China

    Jia Liu

  3. Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China

    Hongen Liao

  4. Ultrasonography Department, Nanjing Drum Tower Hospital, Nanjing, 210000, China

    Wentao Kong

Authors
  1. Fang Chen
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  2. Jia Liu
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  3. Peng Wan
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  4. Hongen Liao
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  5. Wentao Kong
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Correspondence to Fang Chen.

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Electronic supplementary material

Supplementary Table 1

Demographic, clinical and pathological characteristics of patients. (DOCX 17 kb)

Supplementary Table 2

The detailed information of the multi-dimension features (2D and 3D features). (XLSX 24 kb)

Supplementary Table 3

The detailed information of the 2D dynamic feature for each wave pattern, including 14 time-domain wave features and 17 frequency-domain wave features. (XLSX 35 kb)

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Chen, F., Liu, J., Wan, P. et al. Immunohistochemical index prediction of breast tumor based on multi-dimension features in contrast-enhanced ultrasound. Med Biol Eng Comput 58, 1285–1295 (2020). https://doi.org/10.1007/s11517-020-02164-2

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  • DOI: https://doi.org/10.1007/s11517-020-02164-2

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