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应用超声和磁共振成像的 Percreta 评分鉴别胎盘植入和胎盘穿透。

Percreta score to differentiate between placenta accreta and placenta percreta with ultrasound and MR imaging.

机构信息

Department of Gynecology & Obstetrics, FHU PREMA, Cochin Hospital, Paris, France.

Faculty of Medicine, Université Paris Centre, Paris, France.

出版信息

Acta Obstet Gynecol Scand. 2022 Oct;101(10):1135-1145. doi: 10.1111/aogs.14420. Epub 2022 Jul 12.

Abstract

INTRODUCTION

The objective of this study was to assess the performance of ultrasound and magnetic resonance imaging (MRI) features in helping to classify the type of placenta accreta spectrum (PAS; accreta/increta vs percreta), alone or combined in a predictive score.

MATERIAL AND METHODS

We conducted a retrospective study in 82 pregnant women with PAS who underwent ultrasound and MRI examination of the pelvis before delivery (from an initial cohort of 185 women with PAS). We estimated the sensitivity, specificity and accuracy of MRI and ultrasound in the diagnosis of the type of PAS. We analyzed cesarean and imaging features using univariable logistic regression analysis. We constructed a nomogram to predict the risk of placenta percreta and validated it with bootstrap resampling, then used receiver operating characteristic curves to assess the performance of the model in distinguishing between placenta percreta and placenta accreta/increta.

RESULTS

Among the 82 patients, 29 (35%) had placenta accreta/increta and 53 (65%) had placenta percreta. The best features to discriminate between placenta accreta/increta and placenta percreta with ultrasound were increased vascularization at the uterine serosa-bladder wall interface (odds ratio [OR] 7.93; 95% confidence interval [CI] 2.78-24.99; p < 0.01) and the number of lacunae without a hyperechogenic halo (OR 1.36; 95% CI 1.14-1.67; p = 0.012). Concerning MRI markers, heterogeneous placenta (OR 12.89; 95% CI 3.05-89.16; p = 0.002), dark intraplacental bands (OR 12.89; 95% CI 3.05-89.16; p = 0.002) and bladder wall interruption (OR 15.89; 95% CI 4.78-73.33; p < 0.001) had a higher OR in discriminating placenta accreta/increta from placenta percreta. The nomogram yielded areas under the curve of 0.841 (95% CI 0.754-0.927) and 0.856 (95% CI 0.767-0.945), after bootstrap resampling, for the accurate prediction of placenta percreta.

CONCLUSIONS

The nomogram we developed to predict the risk of placenta percreta among patients with PAS had good discriminative capabilities. This performance and its impact on maternal morbidity should be confirmed by future prospective studies.

摘要

简介

本研究的目的是评估超声和磁共振成像(MRI)特征在帮助分类胎盘植入谱系(PAS;粘连/植入与穿透性)中的表现,单独或联合预测评分。

材料和方法

我们对 82 名 PAS 孕妇进行了回顾性研究,这些孕妇在分娩前接受了骨盆超声和 MRI 检查(来自最初的 185 名 PAS 女性队列)。我们估计了 MRI 和超声在 PAS 类型诊断中的灵敏度、特异性和准确性。我们使用单变量逻辑回归分析分析了剖宫产和影像学特征。我们构建了一个列线图来预测胎盘穿透的风险,并通过 bootstrap 重采样进行验证,然后使用接收者操作特征曲线来评估该模型在区分胎盘穿透和胎盘粘连/植入中的表现。

结果

在 82 名患者中,29 名(35%)为胎盘粘连/植入,53 名(65%)为胎盘穿透。用于区分胎盘粘连/植入和胎盘穿透的最佳超声特征是子宫浆膜-膀胱壁界面处血管增多(比值比 [OR] 7.93;95%置信区间 [CI] 2.78-24.99;p < 0.01)和无高回声晕的陷窝数量(OR 1.36;95% CI 1.14-1.67;p = 0.012)。关于 MRI 标志物,不均匀胎盘(OR 12.89;95% CI 3.05-89.16;p = 0.002)、暗胎盘内带(OR 12.89;95% CI 3.05-89.16;p = 0.002)和膀胱壁中断(OR 15.89;95% CI 4.78-73.33;p < 0.001)在区分胎盘粘连/植入和胎盘穿透方面具有更高的 OR。列线图在 bootstrap 重采样后对胎盘穿透的准确预测产生了 0.841(95% CI 0.754-0.927)和 0.856(95% CI 0.767-0.945)的曲线下面积。

结论

我们开发的预测 PAS 患者胎盘穿透风险的列线图具有良好的鉴别能力。这种性能及其对产妇发病率的影响应通过未来的前瞻性研究来证实。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6008/9812204/ec7e3b8a56a9/AOGS-101-1135-g004.jpg

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