Noninvasive Prediction of Axillary Sentinel Lymph Node Metastasis via Contrast-Enhanced Ultrasound to Guide Omission of SLNB in Breast Cancer.

BACKGROUND

The evaluation of axillary sentinel lymph node (SLN) is integral to the treatment of breast cancer. This study aims to build a noninvasive prediction model of SLN metastasis based on percutaneous contrast-enhanced ultrasound (p-CEUS) for low-risk patients.

MATERIALS AND

METHODS

Patients with breast cancer were enrolled in this study at Wenzhou Central Hospital between June 2023 and October 2024. The patients were divided into a modeling group and a validation group in a 2:1 ratio. Clinical and pathological features were assessed with univariate analysis and multivariate logistic regression. A nomogram based on p-CEUS enhancement patterns and other independent predictors for the SLN metastasis identified by multivariate logistic regression was constructed.

RESULTS

A total of 120 patients were included, comprising 80 in the modeling group (mean age, 55.01 ± 9.91 years) and 40 in the validation group (mean age, 55.20 ± 8.35 years). Independent predictors of SLN metastasis by the multivariate logistic regression analysis included tumor size, Ki-67 status and p-CEUS enhancement pattern. The areas under the receiver operating characteristic (ROC) curve of the modeling group and the validation group were 0.855 and 0.873, respectively. At a ≤ 20% probability threshold, the false-negative rate was 6.5%.

CONCLUSIONS

The p-CEUS-based nomogram can accurately predict the risk of SLN metastasis in early breast cancer patients with negative-node status. Patients with predicted metastasis probability ≤ 20%, especially those with tumor size ≤ 2 cm, Ki-67 ≤ 20%, and p-CEUS Type I enhancement, can safely omit SLNB.