Statistical analysis

The data were analyzed by SPSS version 17.0 statistics software (IBM Corp., Armonk, NY, USA). The measurement data was checked by Student’s t-test, which was expressed as x¯ ±s. The count data were evaluated by the Chi-square test. To investigate inter-observer agreement and intra-observer reliability, we evaluated both Pearson correlation coefficients and Cronbach’s Alpha. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were obtained to evaluate the performance of perfusion parameters to predict early response after NAC. The range of 0.9–1.0 indicates an excellent predictor; 0.8–0.9, a good predictor; 0.7–0.8, a general predictor; and< 0.7, a poor predictor (25). The optimal threshold (cut-off) was chosen according to the Youden index. A p value<0.05 was considered to indicate a statistically significant difference.