Abstract
Purpose
This study aimed to establish a radiomics nomogram model based on digital breast tomosynthesis (DBT) images, to predict the status of axillary lymph nodes (ALN) in patients with breast carcinoma.
Methods
The data of 120 patients with confirmed breast carcinoma, including 49 cases with axillary lymph node metastasis (ALNM), were retrospectively analyzed in this study. The dataset was randomly divided into a training group consisting of 84 patients (37 with ALNM) and a validation group comprising 36 patients (12 with ALNM). Clinical information was collected for all cases, and radiomics features were extracted from DBT images. Feature selection was performed to develop the Radscore model. Univariate and multivariate logistic regression analysis were employed to identify independent risk factors for constructing both the clinical model and nomogram model. To evaluate the performance of these models, receiver operating characteristic (ROC) curve analysis, calibration curve, decision curve analysis (DCA), net reclassification improvement (NRI), and integrated discriminatory improvement (IDI) were conducted.
Results
The clinical model identified tumor margin and DBT_reported_LNM as independent risk factors, while the Radscore model was constructed using 9 selected radiomics features. Incorporating tumor margin, DBT_reported_LNM, and Radscore, the radiomics nomogram model exhibited superior performance with AUC values of 0.933 and 0.920 in both datasets, respectively. The NRI and IDI showed a significant improvement, suggesting that the Radscore may serve as a useful biomarker for predicting ALN status.
Conclusion
The radiomics nomogram based on DBT demonstrated effective preoperative prediction performance for ALNM in patients with breast cancer.
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Data availability
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
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Acknowledgements
We thank Fang Li for assistance in the study.
Funding
This study was financially supported by Wu Jieping Medical Foundation (Project No. 320.6750.19089–40; 320.6750.2022–11-50); Jilin Province Science and Technology Development Plan (Project No. 20220203113SF); National Natural Science Foundation of China (Project No. 52275006); State Key Laboratory of Electroanalytical Chemistry Open Project Fund (Project No. SKLEAC202101); Jilin provincial financial department Project (Project No. JLSWSRCZX2020-069).
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MX, SY and GL: Conceptional design of the manuscript. MX, HY, QY, PT, HH, CL, and GL: Experimental design of the manuscript, data collection and manuscript writing. MX, HY, QY, SY and GL: Clinical design of the manuscript, data management and manuscript writing. All authors read and approved the final manuscript.
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This retrospective study was approved by the Institutional Ethics Committee of our hospital, which waived the requirement for written informed consent.
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Xu, M., Yang, H., Yang, Q. et al. Radiomics nomogram based on digital breast tomosynthesis: preoperative evaluation of axillary lymph node metastasis in breast carcinoma. J Cancer Res Clin Oncol 149, 9317–9328 (2023). https://doi.org/10.1007/s00432-023-04859-z
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DOI: https://doi.org/10.1007/s00432-023-04859-z