Abstract

Purpose: To investigate the value of radiomics method based on the fat-suppressed T2 sequence for preoperative predicting axillary lymph node (ALN) metastasis in breast carcinoma. Methods: The data of 329 invasive breast cancer patients were divided into the primary cohort (n=269) and validation cohort (n=60). Radiomics features were extracted from the fat-suppressed T2-weighted images on breast MRI, and ALN metastasis-related radiomics feature selection was performed using Mann Whitney U-test and support vector machines with recursive feature elimination(SVM-RFE); then a radiomics signature was constructed by linear SVM. The predictive models were constructed using a linear regression model based on the clinicopathologic factors and radiomics signature, and nomogram was used for a visual prediction of the combined model. The predictive performances are evaluated with the sensitivity, specificity, accuracy and area under the receiver operating characteristic (ROC) curve (AUC). Results: A total of 647 radiomics features were extracted from each patient. 23 ALN metastasis-related radiomics features were selected to construct the radiomics signature, including 17 texture features, 5 first-order statistical features and one shape feature; patient age, tumor size, HER2 status and vascular cancer thrombus accompanied or not were selected to construct the cilinicopathologic feature model. The sensitivity, specificity, accuracy and AUC value of radiomics signature, clinicopathologic feature model and the nomogram were 65.22%, 81.08%, 75.00% and 0.819 (95% confidence interval [CI]: 0.776-0.861), 30.44%, 81.08%,61.67% and 0.605 (95% CI: 0.571-0.624) and 60.87%, 89.19%, 78.33% and 0.810 (95%CI: 0.761-0.855), respectively. Conclusion: Radiomics methods based on the fat-suppressed T2 sequence and the nomogram are helpful for preoperative accurate predicting ALN metastasis.

Acknowledgements

The authors thank the patients for their willingness to cooperate with our study, and the pathological and surgical doctors who helped us to evaluate the status of axillary lymph nodes in breast cancer.

References

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