Research Article

Department of Radiology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, 200072, China

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Xiaolian Su

Department of Radiology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, 200072, China

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Tingting Xu

Department of Radiology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, 200072, China

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Qifeng Luo

Department of General Surgery, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, 200072, China

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Lin Zhang

Department of Radiology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, 200072, China

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Guangyu Tang

*Author for correspondence:

E-mail Address: tgy17@tongji.edu.cn

Department of Radiology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, 200072, China

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Published Online:10 Feb 2022https://doi.org/10.2217/fon-2021-1559

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Abstract

Aims: To develop a model based on breast MRI to stratify axillary lymph node metastasis (ALNM) in breast cancer. Patients & methods: A total of 134 eligible patients were used to build a predicting model, which was validated with an independent group of 57 patients and evaluated for accuracy and sensitivity. Results: A model based on breast MRI was developed and yielded total accuracy of 82.5% and sensitivities of 94.3, 64.3 and 62.5% to predict patients with no, low and heavy ALNM burden, respectively, in the validation group. Conclusion: A noninvasive model based on breast MRI was developed to preoperatively stratify ALNM in breast cancer; its performance needs to be validated and improved in future research.

Plain language summary

Assessment of axillary lymph node metastasis burden before surgery in breast cancer patients is warranted for axillary management. This study tried to develop a simple model based on breast MRI to differentiate patients with no, low or heavy axillary metastasis burden. By providing the probability of different axillary metastasis burdens, this model would help patients and clinicians to make more rational decisions when choosing to omit intervention, undergo sentinel lymph node biopsy or axillary lymph node dissection for axilla management.

Keywords:

Papers of special note have been highlighted as: • of interest; •• of considerable interest

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Vol. 18, No. 15

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History

Received 6 December 2021

Accepted 28 January 2022

Published online 10 February 2022

Published in print May 2022

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Keywords

Supplementary data

To view the supplementary data that accompany this paper please visit the journal website at: www.futuremedicine.com/doi/suppl/10.2217/fon-2021-1559

Author contributions

J Chen, L Zhang and G Tang were responsible for study design; X Su was responsible for data collection; T Xu conducted statistical analysis; Q Luo was responsible for data interpretation; all authors were responsible for manuscript preparation and approval.

Financial & competing interests disclosure

This study was funded by the National Natural Science Foundation of China (grant no. 81871325, 81801656). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Ethical conduct of research

This study was approved by the Ethics Committee of our hospital (IRB no. SHSY-IEC-4.1/21-95/01). Informed consent was waived due to its retrospective design and no identifiable information was disclosed in this study. The authors state that they have obtained appropriate institutional review board approval or have followed the principles outlined in the Declaration of Helsinki for all human or animal experimental investigations. In addition, for investigations involving human subjects, informed consent has been obtained from the participants involved.

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Stratification of axillary lymph node metastasis risk with breast MRI in breast cancer

Abstract

Plain language summary

References