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Intratumoral and peritumoral radiomics for preoperative prediction of neoadjuvant chemotherapy effect in breast cancer based on contrast-enhanced spectral mammography

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Abstract

Objective

To investigative the performance of intratumoral and peritumoral radiomics based on contrast-enhanced spectral mammography (CESM) to preoperatively predict the effect of the neoadjuvant chemotherapy (NAC) of breast cancers.

Materials and methods

A total of 118 patients with breast cancer who underwent preoperative CESM and NAC from July 2017 to June 2020 were retrospectively analyzed, and the patients were grouped into training (n = 81) and test sets (n = 37) according to the CESM examination time. NAC effect for each patient was assessed by pathology. Intratumoral and peritumoral radiomics features were extracted from CESM images, and feature selection was performed through the Mann–Whitney U test and least absolute shrinkage and selection operator regression (LASSO). Five radiomics signatures based on intratumoral regions, 5-mm peritumoral regions, 10-mm peritumoral regions, intratumoral regions + 5-mm peritumoral regions, and intratumoral regions + 10-mm peritumoral regions were calculated through a linear combination of selected features weighted by their respective coefficients. The prediction performance of radiomics signatures was assessed by the area under the receiver operator characteristic (ROC) curve, the precision-recall (P-R) curve, the calibration curve, and decision curve analysis (DCA).

Results

Ten radiomics features were selected to establish the radiomics signature of intratumoral regions + 5-mm peritumoral regions, which yielded a maximum AUC of 0.85 (95% CI, 0.72–0.98) in the test set. The calibration curves, P-R curves, and DCA showed favorable predictive performance of the five radiomics signatures.

Conclusion

The intratumoral and peritumoral radiomics based on CESM exhibited potential for predicting the NAC effect in breast cancer, which could guide treatment decisions.

Key Points

• The intratumoral and peritumoral CESM-based radiomics signatures show good performance in predicting the NAC effect in breast cancer.

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Abbreviations

AUC:

Area under the curve

CC:

Cranial caudal

CESM:

Contrast-enhanced spectral mammography

DCA:

Decision curve analysis

ER:

Estrogen receptor

FFDM:

Full-field digital mammogram

HER2:

Human epidermal growth factor receptor 2

ICC:

Intraclass correlation coefficient

LASSO:

Least absolute shrinkage and selection operator

MLO:

Mediolateral oblique

NAC:

Neoadjuvant chemotherapy

PR:

Progesterone receptor

ROC:

Receiver operator characteristic

ROI:

Region of interest

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Acknowledgements

Thanks to all participants in this study. Especially thanks to Shaofeng Duan, who is an employee of GE Healthcare, and Ran Zhang, who is an employee of Huiying Medical Technology Co. Ltd, for their contribution in guiding the drafting and revision of the manuscript.

Funding

This study was supported by the National Natural Science Foundation of China (82001775, 61773244), and “Taishan Scholar” Project (NO. tsqn202103197).

Author information

Authors and Affiliations

  1. Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, No.20 Yuhuangding East Street, Yantai, Shandong, 264000, People’s Republic of China

    Ning Mao, Yinghong Shi, Zhongyi Wang & Haizhu Xie

  2. Big Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, 264000, People’s Republic of China

    Ning Mao, Kun Zhang & Haicheng Zhang

  3. Department of Radiology, Peking University Shenzhen Hospital, No.1120 Lianhua Road, Shenzhen, Guangdong, 518036, People’s Republic of China

    Chun Lian, Guanxun Cheng & Yi Dai

  4. Department of Breast Surgery, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, 264000, People’s Republic of China

    Kun Zhang

  5. Precision Health Institution, GE Healthcare, Shanghai, 200000, People’s Republic of China

    Qianqian Chen

  6. Physical Examination Center, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, 264000, People’s Republic of China

    Cong Xu

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  1. Ning Mao
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  11. Yi Dai
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Corresponding authors

Correspondence to Cong Xu or Yi Dai.

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Guarantor

The scientific guarantor of this publication is Dr. Yi Dai.

Conflict of interest

One of the authors of this manuscript (Qianqian Chen) is an employee of GE Healthcare. The remaining authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

Qianqian Chen and Haicheng Zhang have significant statistical expertise.

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Written informed consent was waived by the institutional review board.

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Institutional Review Board approval was obtained.

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• retrospective

• diagnostic or prognostic study

• performed at one institution

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Ning Mao and Yinghong Shi are co-first authors on the paper.

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Mao, N., Shi, Y., Lian, C. et al. Intratumoral and peritumoral radiomics for preoperative prediction of neoadjuvant chemotherapy effect in breast cancer based on contrast-enhanced spectral mammography. Eur Radiol 32, 3207–3219 (2022). https://doi.org/10.1007/s00330-021-08414-7

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  • DOI: https://doi.org/10.1007/s00330-021-08414-7

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