【摘要】 目的 探讨三维能量多普勒超声（3D-PDU）胎盘及子宫动脉血流动力学参数与胎盘植入的相关性。方法 回顾性分析2021年3月—2022年3月贵州省人民医院收治的70例胎盘植入孕妇的临床资料，将其作为胎盘植入组，另选取同期该院无胎盘植入的70例孕妇作为无胎盘植入组。比较两组孕妇的一般资料，测量胎盘血管参数指标[血管化指数（VI）、流量指数（FI）、血管流量指数（VFI）]及子宫动脉血流动力学参数[搏动指数（PI）、阻力指数（RI）、收缩期峰值/舒张末期流速（S/D）]。多因素Logistic逐步回归性分析明确胎盘植入发生的危险因素；绘制受试者工作特征（ROC）曲线分析胎盘植入预测模型预测胎盘植入发生的价值。结果 胎盘植入组与无胎盘植入组孕妇的年龄、流产史、前置胎盘、剖宫产史、VI、FI、VFI、PI、RI、S/D比较，差异均有统计学意义（P <0.05）；胎盘植入组中年龄≥35岁、有流产史、前置胎盘、剖宫产史的孕妇占比高于无胎盘植入组，VI、FI、VFI、S/D高于无胎盘植入组，PI、RI低于无胎盘植入组。ROC曲线分析结果显示：VI、FI、VFI、PI、RI、S/D预测胎盘植入发生的曲线下面积分别为0.853（95%CI:0.789,0.917）、0.756（95%CI:0.674,0.837）、0.771（95%CI:0.690,0.852）、0.850（95%CI:0.786,0.914）、0.765（95%CI:0.686,0.844）、0.747（95%CI:0.666,0.827）（P <0.05），敏感性分别为70.0%（95%CI:0.643,0.858）、75.7%（95%CI:0.691,0.866）、65.7%（95%CI:0.582,0.771）、81.4%（95%CI:0.745,0.861）、64.3%（95%CI:0.573,0.716）、61.4%（95%CI:0.532,0.698），特异性分别为90.0%（95%CI:0.832,0.957）、68.6%（95%CI:0.603,0.757）、84.3%（95%CI:0.779,0.904）、75.7%（95%CI:0.689,0.812）、84.3%（95%CI:0.767,0.915）、78.6%（95%CI:0.703,0.849）。多因素Logistic逐步回归分析结果显示，年龄≥35岁[■=3.459（95%CI:1.721,6.952）]、流产史[■=3.023（95%CI:1.511,6.048）]、前置胎盘[■=4.878（95%CI:2.215,10.743）]、剖宫产史[■=3.436（95%CI:1.517,7.783）]、VI≥21.315[■=3.244（95%CI:1.624,6.480）]、FI≥35.575[=■3.105（95%CI:1.347,7.157）]、VFI≥11.475[■=2.994（95%CI:1.471,6.094）]、PI≤0.735[=■3.843（95%CI:1.678,8.801）]、RI≤0.605[■=3.111（95%CI:1.319,7.338）]、S/D≥3.405[=■3.486（95%CI:1.677,7.246）]是胎盘植入发生的危险因素（P <0.05）。根据多因素Logistic回归分析建立胎盘植入预测模型，Logit（P）=-35.687+1.177X_VI+1.133X_FI+1.097X_VFI+1.346X_PI+1.135X_RI+1.249X_S/D,ROC曲线分析结果显示，胎盘植入预测模型预测胎盘植入发生的曲线下面积为94.9%（95%CI:0.913,0.984），敏感性为90.0%（95%CI:0.829,0.962），特异为88.6%（95%CI:0.819,0.923）（P <0.05）。结论 3D-PDU胎盘血管化指数及子宫动脉血流动力学参数与胎盘植入具有相关性，可辅助用于胎盘植入的诊断。更多还原

【Abstract】 Objective To investigate the relationship between the hemodynamics parameters of placenta and uterine artery and placenta accreta by three-dimensional energy Doppler ultrasound（3D-PDU）. Methods The clinical data of 70 pregnant women with placenta accreta admitted to our hospital from March 2021 to March 2022were retrospectively analyzed. They were selected as the placenta accreta group, and another 70 pregnant women without placenta accreta during the same period were selected as the non-placenta accreta group. The general data of pregnant women in the two groups were compared, and the parameters of placental vascular parameters [vascularization index（VI）, flow index（FI）, vascular flow index（VFI） ] and the mechanical parameters of uterine arterial blood flow [pulsatile index（PI）, resistance index（RI）, peak systolic/end diastolic flow rate（S/D）] were measured. Multivariate Logistic regression analysis was used to determine the risk factors of placenta accreta. The value of predicting placenta accreta by ROC analysis and placenta accreta prediction model. Results The differences in age, abortion history, placenta previa history, cesarean section history, VI, FI, VFI, PI, RI, S/D between the placenta accreta group and the non-placenta accreta group were statistically significant by χ² or t test（P < 0.05）.The proportion of pregnant women aged ≥ 35 years, with history of abortion, placenta previa and cesarean section was higher than that in the group without placenta accreta, VI, FI, VFI, S/D was higher than that in the group without placenta accreta, and PI and RI were lower than that in the group without placenta accreta. According to ROC analysis, the areas under the curve predicted by VI, FI, VFI, PI, RI and S/D were 0.853（95% CI: 0.789, 0.917）,0.756（95% CI: 0.674, 0.837）, 0.771（95% CI: 0.690, 0.852）, 0.850（95% CI: 0.786, 0.914）, 0.765（95% CI: 0.686,0.844）, 0.747（95% CI: 0.666, 0.827）, respectively（P < 0.05）; and the sensitivity were 70.0%（95% CI: 0.643,0.858）, 75.7%（95% CI: 0.691, 0.866）, 65.7%（95% CI: 0.582, 0.771）, 81.4%（95% CI: 0.745, 0.861）, 64.3%（95%CI: 0.573, 0.716）, 61.4%（95% CI: 0.532, 0.698）, respectively; specificity were 90.0%（95% CI: 0.832, 0.957）,68.6%（95% CI: 0.603, 0.757）, 84.3%（95% CI: 0.779, 0.904）, 75.7%（95% CI: 0.689, 0.812）, 84.3%（95% CI:0.767, 0.915）, and 78.6%（95% CI: 0.703, 0.849）, respectively. Multivariate Logistic regression analysis showed that age ≥ 35 years old [■= 3.459（95% CI: 1.721, 6.952） ], abortion history [ ■= 3.023（95% CI: 1.511, 6.048）,placenta previa [■ = 4.878（95% CI: 2.215, 10.743）, cesarean section history [ ■= 3.436（95% CI: 1.517,7.783） ], VI ≥ 21.315 [■ = 3.244（95% CI: 1.624, 6.480） ], FI ≥ 35.575 [ ■= 3.105（95% CI: 1.347, 7.157） ],VFI ≥ 11.475 [ ■= 2.994（95% CI: 1.471, 6.094） ], PI ≤ 0.735 [ ■= 3.843（95% CI: 1.678, 8.801）, RI ≤ 0.605[ ■= 3.111（95% CI: 1.319, 7.338） ], S/D ≥ 3.405 [ ■ = 3.486（95% CI: 1.677, 7.246） ] were risk factors for placenta accreta（P < 0.05）. The prediction model of placenta accreta was established based on Logistic regression analysis, Logit（P） =-35.687 + 1.177X_VI + 1.133X_FI + 1.097X_VFI + 1.346X_PI + 1.135X_RI + 1.249_XS/D, ROC analysis showed that the area under the curve of placenta accreta prediction model was 94.9%（95% CI: 0.913, 0.984）,sensitivity: 90.0%（95% CI: 0.829, 0.962）, specificity: 88.6%（95% CI: 0.819, 0.923）（P < 0.05）. Conclusion 3DPDU placental vascularization index and uterine artery perfusion parameters are correlated with placenta accreta,which can assist in the diagnosis of placental implantation.更多还原