Multimodal ultrasound imaging: a method to improve the accuracy of sentinel lymph node diagnosis in breast cancer

Front Oncol. 2024 Mar 25:14:1366876. doi: 10.3389/fonc.2024.1366876. eCollection 2024.

Abstract

Aim: This study assessed the utility of multimodal ultrasound in enhancing the accuracy of breast cancer sentinel lymph node (SLN) assessment and compared it with single-modality ultrasound.

Methods: Preoperative examinations, including two-dimensional ultrasound (2D US), intradermal contrast-enhanced ultrasound (CEUS), intravenous CEUS, shear-wave elastography (SWE), and surface localization, were conducted on 86 SLNs from breast cancer patients. The diagnostic performance of single and multimodal approaches for detecting metastatic SLNs was compared to postoperative pathological results.

Results: Among the 86 SLNs, 29 were pathologically diagnosed as metastatic, and 57 as non-metastatic. Single-modality ultrasounds had AUC values of 0.826 (intradermal CEUS), 0.705 (intravenous CEUS), 0.678 (2D US), and 0.677 (SWE), respectively. Intradermal CEUS significantly outperformed the other methods (p<0.05), while the remaining three methods had no statistically significant differences (p>0.05). Multimodal ultrasound, combining intradermal CEUS, intravenous CEUS, 2D US, and SWE, achieved an AUC of 0.893, with 86.21% sensitivity and 84.21% specificity. The DeLong test confirmed that multimodal ultrasound was significantly better than the four single-modal ultrasound methods (p<0.05). Decision curve analysis and clinical impact curves demonstrated the superior performance of multimodal ultrasound in identifying high-risk SLN patients.

Conclusion: Multimodal ultrasound improves breast cancer SLN identification and diagnostic accuracy.

Keywords: breast cancer; contrast enhanced ultrasound; multimodal ultrasound imaging; sentinel lymph node; shear wave elastography.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by the Fujian Province Young and middle-aged Teacher Education Research Program (JAT210112) of China.