To explore the value of a radiomics model based on ultrasound imaging in predicting the axillary lymph node status of patients with breast cancer.

A total of 265 patients with early-stage breast cancer were retrospectively analyzed, all of whom underwent preoperative breast ultrasound examination at Sun Yat-sen University Cancer Center from January 2020 to October 2020. According to the order of examination time, the patients were divided into a training group (n=159) and a validation group (n=106). ImageJ software was used to manually delineate the lesion area in the ultrasound image along the tumor boundary. Pyradiomics was used to extract 1130 features from each lesion area, and three statistical methods were used to screen the features. Finally, a logistic regression model was used to construct ultrasound imaging radiomics model. The receive operating characteristic (ROC) curve, calibration curve, and decision curve were used to evaluate the performance and value of the ultrasound imaging radiomics model in predicting axillary lymph node status.

A total of eight key image features were selected to construct the ultrasound imaging radiomics model. The area under the ROC curve values of the model in the training group and the validation group were 0.805 (95% confidence interval [CI]: 0.734-0.876) and 0.793 (95% CI: 0.706-0.880), respectively. The calibration curve showed that the model had a good calibration in both the training and validation groups (P=0.592、0.593); besides, the decision curve analysis confirmed that the model had some clinical practicability.

Ultrasound-based imaging radiomics model is of great value in predicting the axillary lymph node status of patients with breast cancer before surgery, which could guide clinicians in the accurate staging of breast cancer and selection of appropriate therapeutic regimen.