https://orcid.org/0000-0003-3010-7629
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Abstract
Background
Axillary lymph node dissection (ALND) can be safely avoided in women with T1 or T2 primary invasive breast cancer (BC) and one to two metastatic sentinel lymph nodes (SLNs). However, cancellation of ALND based solely on SLN biopsy (SLNB) may lead to adverse outcomes. Therefore, preoperative assessment of LN tumor burden becomes a new focus for ALN status.
Objective
This study aimed to develop and validate a nomogram incorporating the radiomics score (rad-score) based on automated breast ultrasound system (ABUS) and other clinicopathological features for evaluating the ALN status in patients with early-stage BC preoperatively.
Methods
Totally 354 and 163 patients constituted the training and validation cohorts. They were divided into ALN low burden (<3 metastatic LNs) and high burden (≥3 metastatic LNs) based on the histopathological diagnosis. The radiomics features of the segmented breast tumor in ABUS images were extracted and selected to generate the rad-score of each patient. These rad-scores, along with the ALN burden predictors identified from the clinicopathologic characteristics, were included in the multivariate analysis to establish a nomogram. It was further evaluated in the training and validation cohorts.
Results
High ALN burdens accounted for 11.2% and 10.8% in the training and validation cohorts. The rad-score for each patient was developed based on 7 radiomics features extracted from the ABUS images. The radiomics nomogram was built with the rad-score, tumor size, US-reported LN status, and ABUS retraction phenomenon. It achieved better predictive efficacy than the nomogram without the rad-score and exhibited favorable discrimination, calibration and clinical utility in both cohorts.
Conclusion
We developed an ABUS-based radiomics nomogram for the preoperative prediction of ALN burden in BC patients. It would be utilized for the identification of patients with low ALN burden if further validated, which contributed to appropriate axillary treatment and might avoid unnecessary ALND.
Data Sharing Statement
The data during the current study are available from the corresponding author on reasonable request.
Ethical Approval
Ethical approvals for the study were obtained from the Institutional Review Boards at Yunnan Cancer Hospital (KYLX2022181) and Anning First People’s Hospital (2022-034-01).
Informed Consent
Informed consents were waived due to the retrospective nature of this study. We declared that patient data was maintained with confidentiality.
Acknowledgments
The authors wish to thank all the study participants, research staff and students who participated in this work.
Author Contributions
All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
Study design: Ning Li, Chao Song, Hongjiang Zhang, and Xian Huang.
Data collection and analysis: Ning Li, Chao Song, Hongjiang Zhang, Xian Huang, Juhua He, Juan Su, Lichun Yang, and Guihua Cui.
Supervision: Chao Song and Hongjiang Zhang.
Statistics: Ning Li, Juhua He, Chao Song, Xian Huang, and Hongjiang Zhang.
Manuscript writing: Ning Li, Chao Song, Hongjiang Zhang, and Xian Huang.
Manuscript revision: Ning Li, Chao Song, Hongjiang Zhang, and Xian Huang.
Approval of the manuscript: all authors.
Disclosure
The authors declare that they have no conflict of interest.