Dual-modal Computer-assisted Evaluation of Axillary Lymph Node Metastasis in Breast Cancer Patients on Both Real-time Elastography and B-mode Ultrasound

Purpose: To propose a computer-assisted method for quantifying the hardness of an axillary lymph node on real-time elastography (RTE) and its morphology on B-mode ultrasound; and to combine the dual-modal features for differentiation of metastatic and benign axillary lymph nodes in breast cancer patients.

Materials And Methods: A total of 161 axillary lymph nodes (benign, n=69; metastatic, n=92) from 158 patients with breast cancer were examined with both B-mode ultrasound and RTE. With computer assistance, five morphological features describing the hilum, size, shape, and echogenic uniformity of a lymph node were extracted from B-mode, and three hardness features were extracted from RTE. Single-modal and dual-modal features were used to classify benign and metastatic nodes with two computerized classification approaches, i.e., a scoring approach and a support vector machine (SVM) approach. The computerized approaches were also compared with a visual evaluation approach.

Results: All features exhibited significant differences between benign and metastatic nodes (p<0.001), with the highest area under the receiver operating characteristic curve (AUC) of 0.803 and the highest accuracy (ACC) of 75.2% for a single feature. The SVM on dual-modal features achieved the largest AUC (0.895) and ACC (85.7%) among all methods, exceeding the scoring (AUC=0.881; ACC=83.6%) and the visual evaluation methods (AUC=0.830; ACC=84.5%). With the leave-one-out cross validation, the SVM on dual-modal features still obtained an ACC as high as 84.5%.

Conclusion: Dual-modal features can be extracted from RTE and B-mode ultrasound with computer assistance, which are valuable for discrimination between benign and metastatic lymph nodes. The SVM on dual-modal features outperforms the scoring and visual evaluation methods, as well as all methods using single-modal features. The computer-assisted dual-modal evaluation of lymph nodes could be potentially used in daily clinical practice for assessing axillary metastasis in breast cancer patients.