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Intratumoral and peritumoral radiomics based on dynamic contrast-enhanced MRI for preoperative prediction of intraductal component in invasive breast cancer

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Abstract

Objectives

To develop and validate radiomic models for preoperative prediction of intraductal component in invasive breast cancer (IBC-IC) using the intratumoral and peritumoral features derived from dynamic contrast-enhanced MRI (DCE-MRI).

Methods

The prediction models were developed in a primary cohort of 183 consecutive patients from September 2017 to December 2018, consisting of 45 IBC-IC and 138 invasive breast cancers (IBC). The validation cohort of 111 patients (27 IBC-IC and 84 IBC) from February 2019 to January 2020 was enrolled to test the prediction models. A total of 208 radiomic features were extracted from the intratumoral and peritumoral regions of MRI-visible tumors. Then the radiomic features were selected and combined with clinical characteristics to construct predicting models using the least absolute shrinkage and selection operator. The area under the curve (AUC) of receiver operating characteristic, sensitivity, and specificity were used to evaluate the performance of radiomic models.

Results

Four radiomic models for prediction of IBC-IC were built including intratumoral radiomic signature, peritumoral radiomic signature, peritumoral radiomic nomogram, and combined intratumoral and peritumoral radiomic signature. The combined intratumoral and peritumoral radiomic signature had the optimal diagnostic performance, with the AUC, sensitivity, and specificity of 0.821 (0.758–0.874), 0.822 (0.680–0.920), and 0.739 (0.658–0.810) in the primary cohort and 0.815 (0.730–0.882), 0.778 (0.577–0.914), and 0.738 (0.631–0.828) in the validation cohort.

Conclusions

The radiomic model based on the combined intratumoral and peritumoral features from DCE-MRI showed a good ability to preoperatively predict IBC-IC, which might facilitate the individualized surgical planning for patients with breast cancer before breast-conserving surgery.

Key Points

•·Preoperative prediction of intraductal component in invasive breast cancer is crucial for breast-conserving surgery planning.

• Peritumoral radiomic features of invasive breast cancer contain useful information to predict intraductal components.

•·Radiomics is a promising non-invasive method to facilitate individualized surgical planning for patients with breast cancer before breast-conserving surgery.

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Abbreviations

ACR BI-RADS:

American College of Radiology Breast Imaging Reporting and Data System

AUC:

Area under the curve

BCS:

Breast-conserving surgery

CI:

Confidence interval

DCE-MRI:

Dynamic contrast-enhanced MRI

DCIS:

Ductal carcinoma in situ

ER:

Estrogen receptor

ETL:

Echo train length

FOV:

Field of view

HER2:

Human epidermal growth factor receptor 2

IBC:

Invasive breast cancer

IBC-IC:

Intraductal component in invasive breast cancer

IBSI:

Image biomarker standardization initiative

ICC:

Intraclass correlation coefficient

LASSO:

Least absolute shrinkage and selection operator

NEX:

Number of excitations

NME:

Non-mass enhancement

ROC:

Receiver operating characteristic

ROI:

Region of interest

PR:

Progesterone receptor

TA:

Total acquisition time

TE:

Echo time

TR:

Repetition time

TRIPOD:

Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis statement

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Acknowledgements

The authors would like to thank Juan Ji (JJ) and Qiong Liao (QL) for the pathological work and consultation in the study.

Funding

This study has received funding from Sichuan Science and Technology Program (grant numbers 2021YFG0125, 2021YFS0075, and 2021YFS0225).

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Author notes

  1. Hao Xu and Jieke Liu contributed equally to this work.

Authors and Affiliations

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

    Hao Xu, Jieke Liu, Zhe Chen, Chunhua Wang, Yuanyuan Liu, Min Wang, Peng Zhou, Hongbing Luo & **g Ren

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  1. Hao Xu
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  2. Jieke Liu
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Correspondence to Hongbing Luo or **g Ren.

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The scientific guarantor of this publication is Hongbing Luo and **g Ren.

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The 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

One of the authors has significant statistical expertise.

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The requirement for informed consent was waived and patient data are anonymized.

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• Retrospective

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• Performed at one institution

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Xu, H., Liu, J., Chen, Z. et al. Intratumoral and peritumoral radiomics based on dynamic contrast-enhanced MRI for preoperative prediction of intraductal component in invasive breast cancer. Eur Radiol 32, 4845–4856 (2022). https://doi.org/10.1007/s00330-022-08539-3

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