| Objective To explore the predictive value of nomogram (Nomogram) prediction model base on multimodal ultrasound parameters and clinicopathological features for axillary lymph node metastasis (ALNM) of breast cancer (BC). Methods 251 BC patients who were admitted to The Second Affiliated Hospital of Hunan University of Chinese Medicine from March 2020 to December 2023 were selected, and patients were divided into ALNM group (102 cases) and Non-ALNM group (149 cases) according to whether ALNM occurred in BC patients. All patients underwent color Doppler imaging (CDI), strain elastography (SE) and real-time shear wave elastography (SWE), the multimodal ultrasound parameters and clinicopathological features were compared between two groups. The influencing factors of ALNM in BC patients were analyzed by multivariate Logistic regression, and the Nomogram prediction model for ALNM in BC patients was constructed. The predictive value of the Nomogram prediction model for ALNM in BC patients was evaluated by receiver operating characteristic (ROC) curve. Results The lymph node short diameter, lymph node cortical thickness, lymph node short diameter/long diameter, elastic strain rate ratio (SR), maximum elastic modulus (Emax), minimum elastic modulus (Emin), mean elastic modulus (Emean), standard deviation (SD) and color Doppler flow imaging (CDFI) blood flow classification III/IV type ratio of lymph nodes in ALNM group were higher than those in Non-ALNM group (P<0.05). Lymphatic vascular invasion proportion, invasive carcinoma proportion and histological grade III proportion in ALNM group were higher than those in Non-ALNM group (P<0.05). Combined with CDFI blood flow classification III/IV type, lymphatic vascular invasion, histological grade III, higher lymph node short diameter/long diameter, SR and Emax were risk factors for ALNM in BC patients (P<0.05). The prediction curve of the Nomogram prediction model based on multimodal ultrasound parameters and clinicopathological features was in good agreement with the ideal curve, and the consistency index was 0.897. The area under the curve (AUC) of the Nomogram model for predicting ALNM in BC patients was 0.828, which had high predictive efficacy. Conclusion Combined with CDFI blood flow classification, lymphatic vascular invasion, histological grade, lymph node short diameter/long diameter, SR and Emax are the influencing factors of ALNM in BC patients, the Nomogram model base on multimodal ultrasound parameters and clinicopathological features has a high value in predicting the risk of ALNM in BC patients. |
