OBJECTIVES: This study was designed to develop and validate models based on delta intratumoral and peritumoral radiomics features from breast masses on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for the prediction of axillary lymph node (ALN) pathological complete response (pCR) after neoadjuvant therapy (NAT) in patients with breast cancer (BC). METHODS: We retrospectively collected data from 187 BC patients with ALN metastases. Radiomics features were extracted from the intratumoral and 3 mm-peritumoral regions on DCE-MRI at baseline and after the 2nd course of NAT to calculate delta intratumoral and peritumoral radiomics features, respectively. After feature selection, the delta intratumoral radiomics (DIR) model and delta peritumoral radiomics (DPR) model were built using the retained features. An ultrasound model was constructed on the basis of preoperative axillary ultrasound results. All variables were screened by univariate and multivariate logistic regression to construct the combined model. The above models were evaluated and compared. RESULTS: In the validation set, the ultrasound model had the lowest AUC, which was lower than those of the DIR, DPR and combined models (0.627 vs 0.825, 0.687, 0.846, respectively). The combined model constructed by delta dual-region radiomics and ultrasound dianogsis was significantly better than the ultrasound model in terms of the Delong test and integrated discrimination improvement (all p <
0.05). CONCLUSIONS: Delta intratumoral and peritumoral radiomics based on DCE-MRI have the potential to predict ALN status after NAT. The combined model based on delta dual-region radiomics of breast mass can accurately diagnose ALN-pCR and provide assistance in the selection of axillary surgical approaches for patients.