The integrated random forest model using perfusion features for hot spots and texture features at SSF 0 had the best performance, and the AUC values for predicting each histological factor were 0.76 for ER status, 0.86 for HER2 status, and 0.79 for the molecular subtype of breast cancer. This evidence concerns the gene ERBB2 and breast carcinoma.