Accuracy of shear wave elastography in diagnosing axillary lymph node metastasis in patients with suspicious axillary
Wethaka Kritcharoen1, Varanatjaa Pradaranon2, Patteera Rohitopakarn2
1Department of Diagnostic and Interventional Radiology, Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok, Thailand. wethaka.kri@cra.ac.th.
Purpose:
This study aimed to evaluate shear wave elastography [SWE] for predicting axillary lymph node metastasis in breast cancer patients.
Methods:
Thirty-nine patients with suspicious axillary lymph nodes (BI-RADS ≥ 4 and abnormal B-mode ultrasound features) underwent B-mode ultrasound, strain elastography, and shear wave elastography (SWE) prior to ultrasound-guided core needle biopsy. Two experienced radiologists independently assessed lymph node appearance, cortical thickness, vascularity, as well as shear wave and strain elastography using the Siemens ACUSON Sequoia system. Statistical analysis compared imaging parameters between benign and malignant nodes using the Wilcoxon rank-sum test. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curves. A predictive nomogram incorporating B-mode, strain elastography, and SWE findings was developed to improve diagnostic accuracy.
Results:
Malignant nodes showed significantly higher stiffness and velocity [p < 0.05]. Cut points for diagnostic accuracy were determined by using the Youden index. Combining B-Mode and elastography improved sensitivity and specificity. A predictive nomogram incorporating SWE, strain elastography, and B-Mode appearance achieved high diagnostic efficacy [sensitivity = 0.96, specificity = 0.77, PPV = 0.89, NPV = 0.91].
Conclusions:
SWE demonstrates potential as a non-invasive tool for axillary nodal assessment in breast cancer patients. It effectively distinguishes between benign and malignant axillary lymph nodes, offering promise for optimizing management. The predictive nomogram, incorporating SWE, strain elastography, and B-Mode appearance, provides a practical tool for pre-operative decision-making, enhancing the diagnostic process and potentially improving the management of breast cancer patients.
