Association between US features of primary tumor and axillary lymph node metastasis in patients with clinical T1–T2N0 breast cancer

Abstract

Background Most patients with early-stage breast cancer have clinically negative lymph nodes (LNs). However, 15-20% of patients have axillary nodal metastasis based on the sentinel LN biopsy. Purpose To assess whether ultrasound (US) features of a primary tumor are associated with axillary LN metastasis in patients with clinical T1-T2N0 breast cancer. Material and Methods This retrospective study included 138 consecutive patients (median age = 51 years; age range = 27-78 years) who underwent breast surgery with axillary LN evaluation for clinically node-negative T1-T2 breast cancer. Three radiologists blinded to the axillary surgery results independently reviewed the US images. Tumor distance from the skin and distance from the nipple were determined based on the US report. Association between US features of a breast tumor and axillary LN metastasis was assessed using a multivariate logistic regression model after controlling for clinicopathologic variables. Results Of the 138 patients, 28 (20.3%) had nodal metastasis. At univariate analysis, tumor distance from the skin ( P = 0.019), tumor size on US ( P = 0.023), calcifications ( P = 0.036), architectural distortion ( P = 0.001), and lymphovascular invasion ( P = 0.049) were associated with axillary LN metastasis. At multivariate analysis, shorter skin-to-tumor distance (odds ratio [OR] = 4.15; 95% confidence interval [CI] = 1.01-16.19; P = 0.040) and masses with associated architectural distortion (OR = 3.80; 95% CI = 1.57-9.19; P = 0.003) were independent predictors of axillary LN metastasis. Conclusion US features of breast cancer can be promising factors associated with axillary LN metastasis in patients with clinically node-negative early-stage breast cancer.

Correlation of Conventional Ultrasound Characteristics of Breast Tumors With Axillary Lymph Node Metastasis and Ki‐67 Expression in Patients With Breast Cancer

“…Clinically, negative lymph nodes do not imply the absence of sentinel lymph node metastasis . Recent studies have shown that several US features are associated with ALNM, such as the tumor size, architectural distortion in the tumor, skin‐to‐tumor distance, nipple‐to tumor distance, and tumor stiffness, with a larger number of unfavorable US features indicating a higher risk of lymph node metastasis . In this study, the maximum tumor diameter and margin and internal echo of the tumor on breast US images were significantly associated with ALNM; thus, these characteristics of the primary tumor may aid in the identification of metastatic ALNs in patients with breast cancer.…”

“…Although early and accurate diagnosis of breast cancer is very important, modern medicine has mostly focused on the prognosis. Thus far, few studies have assessed the association of US characteristics of breast tumors with ALNM and explored the association of US characteristics of breast tumors with Ki‐67 expression. To predict the prognosis of breast cancer and help clinicians in making individualized treatment plans, we designed this study to investigate whether the US features of the breast tumor are associated with ALNM and Ki‐67 expression.…”

Predictive performance of ultrasonography-based radiomics for axillary lymph node metastasis in the preoperative evaluation of breast cancer

“…As combination with the US-based radiomics model significantly improved the predictive performance of the clinicopathologic model, the radiomics model can be said to provide additional value in the prediction of axillary lymph node metastasis. This result implies that US-based intratumoral characteristics of primary breast cancer, represented by radiomic features, are associated with axillary lymph node metastasis, although this has not been clearly identified in the context of US features such as shape, margin, echogenicity, or orientation [10]. In the future, this model may help identify patients who need sentinel lymph node biopsy or axillary dissection before surgery, and it could even potentially indicate which patients require aspiration or core-needle biopsy of lymph nodes at the staging workup.…”

“…In our preoperative clinicopathologic model, multivariable logistic regression was used to identify tumor size, tumor location, tumor type, and multiplicity as predictors of axillary lymph node metastasis; these factors have similarly been shown to be predictive factors in previous studies [19]. Based on previous reports, we also added skin-to-tumor distance and the distance from the nipple in the analysis; however, these were not found to be predictive factors in our study [10,20]. Our preoperative clinicopathologic model did not include histologic grade or lymphovascular invasion of the tumor, since this information is obtained after surgery.…”

“…These include clinical factors and post-biopsy information, such as patient age, tumor size, tumor location, multiplicity, tumor type, and receptor status. Previous studies have also associated several US features of primary tumors with axillary lymph node metastasis [10,11]. Recently, magnetic resonance imaging-based radiomics features extracted from primary tumors showed high predictive performance for axillary lymph node metastasis [12][13][14][15].…”