Diagnostic value of the flare sign in predicting extracapsular extension in metastatic axillary lymph nodes and nodal status on breast magnetic resonance imaging

This study aimed to evaluate the diagnostic performance of breast magnetic resonance imaging (MRI) in predicting extracapsular extension (ECE) and axillary nodal status in the axillary metastatic lymph nodes of patients with breast cancer. The preoperative MRI scans of 92 patients with breast cancer and axillary metastases who did not receive neoadjuvant treatment between January 2018 and January 2024 were retrospectively examined. The presence of an increased signal in the axillary fatty tissue surrounding the lymph node (flare sign) on T2-weighted images, irregular nodal contour (shaggy margin), axillary asymmetry (difference in the number and size of lymph nodes compared with the unaffected axilla), loss of the fatty hilum in the most suspicious lymph node, and morphological features on T1-weighted images were assessed. Each dissected axillary lymph node was examined for ECE, and the histopathological results were recorded. Axillary flare sign was significantly associated with the presence of ECE ( < 0.001), number of lymph nodes with ECE ( < 0.001), the presence of ≥4 axillary metastatic lymph nodes ( < 0.001), size of the primary tumor ( = 0.033), lymphovascular invasion in the primary tumor ( < 0.001), and presence of perineural invasion ( = 0.001). The flare sign exhibited 65.7% sensitivity, 96% specificity, 97.8% positive predictive value, 51.1% negative predictive value, and 73.9% accuracy in predicting ECE. Additionally, the receiver operating characteristic curve analysis revealed an area under the curve of 0.808 (95% confidence interval: 0.719-0.898). The flare sign has high performance in predicting ECE and axillary nodal status and is associated with primary tumor aggressiveness, indicating its potential utility in preoperative evaluation. The flare sign on breast MRI may play a crucial role in preoperative planning, surgical decision-making, and axillary status assessment by accurately predicting ECE.