摘要目的:探讨门控心肌灌注显像(GMPI)相位分析预测冠状动脉粥样硬化性心脏病(简称冠心病)主要心脏不良事件(MACE)的价值。方法:回顾性分析自2012年9月至2014年1月于北京医院核医学科行两日法静息－负荷GMPI的627例受检者，收集一般临床资料、GMPI影像及相关参数[相位标准差(PSD)、相位直方图带宽(PBW)、熵、左心室射血分数(LVEF)、总负荷积分(SSS)、高峰射血率(PER)、高峰充盈率(PFR)]分析结果。随访至出现MACE(即心源性死亡、非致死性心肌梗死、GMPI检查后60 d内行晚期血运重建术)。组间比较采用 χ2检验、两独立样本 t检验或Wilcoxon秩和检验；应用多因素Cox比例风险回归模型分析MACE的独立危险因素，用Kaplan－Meier生存曲线分析累积无MACE生存率。 结果:纳入成功完成随访的受检者共505例，其中男235例，女270例，中位年龄73岁。中位随访时间为55.6(52.0，60.5)个月，发生MACE者54例(10.7%)，其中心源性死亡6例、非致死性心肌梗死27例、晚期冠脉血运重建术21例。MACE组的高血压和高脂血症发生率高于无MACE组( χ2值：4.126、6.021，均 P<0.05)，LVEF、PFR和PER绝对值低于无MACE组( t或 z值：6.261、5.683、－4.246，均 P<0.05)，SSS、PSD、PBW及熵高于无MACE组( t或 z值：5.024、5.874、7.119、－6.405，均 P<0.05)。Cox回归分析显示，PBW异常(>80°)、熵异常(>58 J·mol －1·K －1)及SSS ≥12分为MACE的独立危险因素[比值比( OR)值分别为2.795(95% CI：1.259～6.201)、3.213(95% CI：1.468～7.029)、3.640(95% CI：1.999～6.628)，均 P<0.05]。PSD异常(>26.7°)组、PBW异常组、熵异常组的5年累积无MACE生存率分别为51.2%、63.2%和46.7%，明显低于PSD正常组(92.3%)、PBW正常组(94.2%)和熵正常组(92.8%), χ2值分别为77.768、77.741、117.437，均 P<0.05。PBW异常且SSS≥12分的患者5年累积无MACE生存率为31.7%，低于PBW正常或PBW异常且SSS<12分的患者的相应指标(80.1%～94.4%; χ2＝185.4， P<0.01)；熵和SSS联合分析也有类似结果。 结论:GMPI相位分析获得的左心室PBW及熵是预测冠心病MACE的独立危险因素，GMPI相位分析有很好的冠心病危险度分层价值。

abstractsObjective:To evaluate the value of phase analysis of gated myocardial perfusion imaging (GMPI) in predicting major adverse cardiac events (MACE) in patients with coronary atherosclerotic heart disease.Methods:Patients who underwent two-day rest-stress GMPI in the Department of Nuclear Medicine of Beijing Hospital from September 2012 to January 2014 were selected as observed subjects and analyzed retrospectively. The general clinical information, GMPI images and related parameters including phase standard deviation (PSD), phase histogram bandwidth (PBW), entropy, left ventricular ejection fraction (LVEF), summed stress score (SSS), peak ejection rate (PER), peak filling rate (PFR) were noted. Patients were followed up until the onset of MACE (cardiac death, nonfatal myocardial infarction, and late revascularization within 60 d after GMPI). χ2 test, independent-sample t test or Wilcoxon rank sum test were used to compare data between different groups. The independent risk factors of MACE were obtained by Cox proportional risk regression model. Kaplan-Meier survival curve analysis was used to analyze the cumulative survival rate without MACE. Results:A total of 505 patients (235 males, 270 females, median age: 73 years) were followed up successfully, with a median follow-up period of 55.6(52.0, 60.5) months. There were 54 cases (10.7%) with MACE: 6 patients with cardiac death, 27 patients with non-fatal myocardial infarction, and 21 patients with late revascularization. The incidence of hypertension and hyperlipidemia in patients with MACE was significantly higher than that in patients without MACE ( χ2 values: 4.126, 6.021, both P<0.05); LVEF, PFR and absolute value of PER of patients with MACE were significantly lower ( t/ z values: 6.261, 5.683, -4.246, all P<0.05), while SSS, PSD, PBW and entropy were significantly higher ( t/ z values: 5.024, 5.874, 7.119, -6.405, all P<0.05). Cox proportional risk regression model showed that abnormal PBW(>80°), abnormal entropy(>58 J·mol -1·K -1) and SSS≥12 were independent risk factors for MACE (odds ratio( OR) values: 2.795(95% CI: 1.259-6.201), 3.213(95% CI: 1.468-7.029), 3.640 (95% CI: 1.999-6.628), all P<0.05). The 5-year cumulative MACE-free survival rates of abnormal PSD group(>26.7°), abnormal PBW group and abnormal entropy group were 51.2%, 63.2% and 46.7%, which were significantly lower than those of normal PSD group (92.3%; χ2=77.768, P<0.05), normal PBW group (94.2%; χ2=77.741, P<0.05) and normal entropy group (92.8%; χ2=117.437, P<0.05). The 5-year cumulative MACE-free survival rate (31.7%) of patients with abnormal PBW and SSS≥12 was significantly lower than that of patients with normal PBW or patients with abnormal PBW and SSS<12 (80.1%-94.4%; χ2=185.4, P<0.01). The combination analysis of entropy and SSS showed similar results. Conclusions:PBW and entropy obtained by GMPI phase analysis are independent risk factors for predicting MACE in coronary artery disease. GMPI phase analysis is useful for coronary artery disease risk stratification.