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目的:探讨基于MRI征象的评分模型对侵袭性胎盘植入及不良临床结局的预测价值。方法:采用回顾性队列研究设计，纳入2015年1月至2018年12月在北京大学第三医院分娩、超声检查同时存在2种及以上胎盘植入征象并行MRI检查的260例孕产妇。通过术中所见或病理结果诊断胎盘植入并分型。不良临床结局定义为术中出血≥1 500 ml和/或行子宫切除术。定量及定性判读胎盘内T2加权像低信号带面积、胎盘内增生血管面积、子宫膀胱交界面增生血管、子宫外突、宫颈受侵等5个MRI征象，采用n χ2检验和n t检验对上述5个MRI征象进行单因素分析，并绘制各MRI征象预测侵袭性胎盘植入的受试者工作特性（receiver operating characteristic, ROC）曲线。以约登指数最大时预测值为界值，≥界值则赋值为1，反之为0，建立基于上述MRI征象的评分模型，绘制MRI征象的评分模型预测侵袭性胎盘植入及不良临床结局的ROC曲线，并计算曲线下面积（area under curve, AUC）、灵敏度、特异度和约登指数。n 结果:（1）单因素分析显示5个MRI征象均与侵袭性胎盘植入和不良临床结局显著相关；除宫颈受侵外，其余4个征象预测侵袭性胎盘植入和不良临床结局的AUC值均大于0.5。（2）取约登指数最大时胎盘内增生血管面积、胎盘内T2加权像低信号带面积、宫颈受侵、子宫外突以及子宫膀胱交界面增生血管5个征象单项预测界值，分别为2.0 cmn 2、0.6 cmn 2、1.0、1.0、1.0。基于MRI征象的评分模型预测侵袭性胎盘植入的AUC值为0.863，当分值≥2分，灵敏度为0.836，特异度为0.726。基于MRI征象的评分模型预测不良临床结局的AUC值为0.841，当分值≥3分时预测灵敏度为0.707，特异度为0.818。n 结论:基于MRI征象的评分模型对于侵袭性胎盘植入的诊断及不良临床结局的预测有一定价值。“,”Objective:To explore the predictive value of a scoring model based on MRI images for diagnosing invasive placenta accreta and associated adverse clinical outcomes.Methods:This retrospective cohort study involved 260 patients delivered at Peking University Third Hospital from January 2015 to December 2018, who were suspected to be placenta accreta with two or more ultrasound image findings and underwent MRI examination. Placenta accreta was finally diagnosed and classified based on the intraoperative clinical findings or pathological examination. Adverse clinical outcomes were defined as intraoperative bleeding ≥1 500 ml and/or having hysterectomy. Quantitative and qualitative interpretation of five MRI signs were performed, including intraplacental low-intensity band on T2 weighted imaging, abnormal intraplacental vascularization, vascularization of uterovesical interface, uterine bulging and cervical involvement. n Chi-square and n t test were used for univariate analysis of the five MRI signs and the receiver operating characteristics (ROC) curve of each MRI sign for predicting invasive placenta accreta and adverse clinical outcomes were drawn. The predictive value was assigned as 1 when ≥ the cutoffs that matched to the maximum Yoden index values, and was assigned as 0 when below the cutoffs. A scoring model based on the five MRI signs was established, ROC curves of the model for predicting invasive placenta accreta and adverse clinical outcomes were drawn and the area under the curve (AUC), sensitivity, specificity and Youden index were calculated.n Results:(1) Univariate analysis showed that all five MRI signs were significantly associated with invasive placenta accreta and adverse clinical outcomes. Except for cervical involvement, the other four signs had an AUC value of greater than 0.5 in predicting invasive placenta accreta and adverse clinical outcomes. (2) The predictive cut-off values of abnormal intraplacental vascularization image and intraplacental dark band area on T2 weighted imaging were 2.0 cmn 2 and 0.6 cmn 2, respectively, and were all 1.0 for the other three signs. The AUC value of MRI signs-based scoring model for predicting invasive placenta accreta was 0.863. When the score was ≥ 2 points, the diagnostic sensitivity was 0.836 and the specificity was 0.726. The scoring model predicted adverse clinical outcomes with an AUC of 0.841. When the score was ≥3 points, the predictive sensitivity was 0.707 and the specificity was 0.818.n Conclusions:The scoring model based on MRI signs is of good value for the diagnosis of invasive placenta accreta and the prediction of adverse clinical outcomes.