Predictive value of combining clinicopathological, multimodal ultrasonic characteristics in axillary lymph nodal metastasis burden of patients with cT1-2N0 breast cancer.

Objective: To improving diagnosis of axillary lymph node metastasis (ALNM), we assessed the value of combining clinicopathological, conventional ultrasound, SWE features in the cT1-2N0 breast cancer patients.

Methods: Retrospective analysis of 285 patients with cT1-2N0 breast cancer who underwent preoperative ultrasound examination of the lesion and axillary, with shear wave elastography (SWE) of the lesions. According to the postoperative pathological results, they were divided into ≤2 metastatic ALNs group (low nodal burden, LNB) and > 2 metastatic ALNs group (high nodal burden, HNB). Binary logistic regression analysis was used to screen independent risk factors and establish prediction models. The best cut-off value of continuous variables is determined by the receiver operating characteristic curve, and the performance of the prediction model is evaluated.

Results: Presence of lymphovascular invasion (OR = 7.966, P = 0.010), tumor size (OR = 2.485, P = 0.019), Emean of intratumor (OR = 0.939, P = 0.002) and cortical thickness of lymph node (OR = 9.277, P < 0.001) were independent risk predictors for HNB of cT1-2N0 Group. The predictive model of combined method had better performance in predicting HNB of cT1-2N0 compared with models based on SWE and conventional ultrasound alone (area under the curve: 0.824 vs 0.658, P < 0.001; 0.824 vs 0.789, P = 0.035).

Conclusions: The predictive models of combined method obtained from significant clinicopathological and ultrasonographic features can potentially improve the diagnosis and individual treatment of ALNM in patients with cT1-2N0 breast cancer.