It remains unclear what kind of morphologic and biochemical features best predict plaque rupture in patients with angina pectoris (AP). This study aimed to investigate whether combined high-frequency vascular ultrasound imaging and measurements of serum inflammatory biomarkers can predict coronary plaque ruptures in patients with AP. The study population consisted of 20 patients with stable AP and 40 patients with unstable AP. High-frequency vascular ultrasound imaging was performed in the 2 groups to measure intima-media thickness, the plaque acoustic density of the common carotid arteries, and the flow-mediated dilation of the brachial arteries. Serum lipid profile and inflammatory biomarkers were measured in all patients. Using intravascular ultrasound, a list of coronary imaging parameters was obtained. A multivariate logistic regression model was applied to calculate the odds ratio of each parameter to predict coronary plaque ruptures detected by intravascular ultrasound. Of 139 coronary artery plaques identified by intravascular ultrasound, 48 plaques (9 in stable AP and 39 in unstable AP) developed ruptures. Among measured parameters, the values of carotid intima-media thickness, coronary external elastic membrane area, plaque area, plaque burden, plaque eccentric index and remodeling index, serum high-sensitivity C-reactive protein, soluble intercellular adhesion molecule-1, and soluble vascular cell adhesion molecule-1 were significantly higher in unstable AP than in stable AP (p <0.05 to 0.01). Of these parameters, carotid intima-media thickness, serum high-sensitivity C-reactive protein, and the coronary remodeling index were found to be significant predictors of coronary plaque rupture, with odds ratios of 9.51 (95% confidence interval 1.29 to 21.81), 3.02 (95% confidence interval 1.01 to 7.65), and 0.01 (95% confidence interval 0.00 to 0.34), respectively. In conclusion, combined high-frequency ultrasound imaging of coronary and carotid arteries and measurements of serum inflammatory markers are able to predict coronary plaque ruptures in patients with AP.