Objective: To investigate the application of arterial spin labeling magnetic resonance perfusion imaging (MRI-ASL) combined with magnetic resonance angiography (MRA) for predicting the progress of PCI stroke. Methods: According to whether there was an increase of ≥3 scores of National Institute of Health Stroke Scale(NIHSS) 72 hours after admission, 57 patients with acute posterior circulation ischemic stroke were divided into progressive group (n=29) and control group (n=28). All patients were examined with standard magnetic resonance scans (T1WI、T2WI、T2-FLAIR), MRA, diffusion weighted imaging(DWI) and MRI-ASL. The patients were also evaluated with the posterior circulation Alberta Stroke Program Early CT Score(pc-ASPECTS). Relative cerebral blood flow（rCBF） and degree of main arterial stenosis were recorded. The differences of these parameters between progressive group and control group were measured, and multivariate logistic regression analysis was performed on parameters with significant differences. Results: The rCBF [（1.25±0.37） vs. (0.69±0.19), P<0.05] and pc-ASPECTS [（8.21±0.74） vs. (7.69±0.93), P<0.05] in control group were significantly higher than those in progressive group, however, there was no correlation between rCBF and pc-ASPECTS. The main arterial stenosis rate in progressive group were significantly higher than that in control group (82.76% vs. 35.71%, P<0.05), and rCBF was correlated with main arterial stenosis rate. However, the rCBF of 10 cases with main arterial stenosis was not decreased. Multivariate logistic regression analysis revealed that only rCBF （OR=3.703, 95%CI 1.971-6.956） was the protective factor of progression of PCI stroke. ROC curve analysis indicated that rCBF（≥1.014） predicted good prognosis. Conclusions: High rCBF is a protective factor of progreesion of PCI. For PCI patients, pc-ASPECT score, MRA detected main arterial stenosis rate could not comprehensively reflect the short term progression of the disease; MRI, MRA combined with MRI-ASL detecting the rCBE could more effectively predicting the progression of early stage PCT.