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磁共振成像诊断胎盘植入的准确性:系统评价和荟萃分析。

Accuracy of Magnetic Resonance Imaging in Diagnosing Placenta Accreta: A Systematic Review and Meta-Analysis.

机构信息

Department of Medical Imaging, Haikou Maternal and Child Health Hospital, Haikou 570203, China.

Department of Imaging, Hainan Women and Children's Medical Center, Haikou 570216, China.

出版信息

Comput Math Methods Med. 2022 Aug 26;2022:2751559. doi: 10.1155/2022/2751559. eCollection 2022.

DOI:10.1155/2022/2751559
PMID:36060665
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9439908/
Abstract

BACKGROUND

The disease burden and incidence of placenta accreta are increasing worldwide. The morbidity and mortality associated with undiagnosed placenta accreta are both high, highlighting the important of early diagnosis and intervention. In recent years, increasing studies are exploring the diagnostic value of magnetic resonance imaging (MRI) for placenta accreta. Compared with traditional ultrasound, MRI has the advantages of high-resolution, multiangle imaging, and less influence by amniotic fluid and intestinal gas. However, the reported diagnostic accuracy among studies was inconsistent. Therefore, this study is aimed at exploring the diagnostic value of MRI for placenta accreta by systematic review and meta-analysis.

METHODS

Relevant literature were systematically searched in PubMed, Ovid, Embase, ScienceDirect database, CNKI, and Wanfang database by using medical subject headings and relevant diagnostic terminologies such as sensitivity, specificity, likelihood ratio, receiver-operating characteristic curve, and area under the curve. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and area under the curve of the included literature were analyzed using stata 17.0 software. Publication bias of the included studies was assessed by Deek's funnel plot. Cochrane statistics and statistics were used to test the heterogeneity.

RESULTS

A total of 10 primary publications, comprising 4 retrospective studies and 6 prospective studies, were included in this meta-analysis. The gestational weeks of pregnant women ranged from 32 to 35 weeks, and the sample size ranged from 37 cases to 575 cases. Only 4 studies used the blind method in the process of clinical diagnosis by MRI. The combined sensitivity, specificity, and area of curve under summary receiver-operating characteristic for the diagnosis of placenta accreta by MRI were 0.88 (95% CI, 0.79-0.93), 0.79 (95% CI, 0.68-0.87), and 0.91 (95% CI, 0.88.-0.93), respectively. The combined positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and diagnostic score were 4.17 (95% CI, 2.62-6.66), 0.16 (95% CI, 0.09-0.29), 26.61 (95% CI, 10.22-69.28), and 3.28 (95% CI, 2.32-4.24), respectively. No publication bias was noted.

CONCLUSION

Diagnosis of placenta accreta by MRI has good accuracy and predictive value that warrants clinical promotion.

摘要

背景

胎盘植入的疾病负担和发病率在全球范围内呈上升趋势。未诊断的胎盘植入相关的发病率和死亡率都很高,这凸显了早期诊断和干预的重要性。近年来,越来越多的研究探讨了磁共振成像(MRI)在胎盘植入诊断中的价值。与传统超声相比,MRI 具有高分辨率、多角度成像和较少受羊水和肠气影响的优点。然而,不同研究报道的诊断准确性并不一致。因此,本研究旨在通过系统评价和荟萃分析探讨 MRI 对胎盘植入的诊断价值。

方法

使用 PubMed、Ovid、Embase、ScienceDirect 数据库、CNKI 和万方数据库,通过医学主题词和相关诊断术语(如灵敏度、特异度、似然比、受试者工作特征曲线和曲线下面积)系统地检索相关文献。使用 stata 17.0 软件分析纳入文献的灵敏度、特异度、阳性似然比、阴性似然比和曲线下面积。采用 Deek's 漏斗图评估纳入研究的发表偏倚。使用 Cochrane Q 统计量和 统计量检验异质性。

结果

本荟萃分析共纳入 10 篇原始文献,包括 4 项回顾性研究和 6 项前瞻性研究。纳入研究的孕妇孕周为 32-35 周,样本量为 37-575 例。只有 4 项研究在 MRI 临床诊断过程中采用了盲法。MRI 诊断胎盘植入的汇总受试者工作特征曲线下面积的合并灵敏度、特异度和曲线下面积分别为 0.88(95%CI,0.79-0.93)、0.79(95%CI,0.68-0.87)和 0.91(95%CI,0.88-0.93)。合并阳性似然比、阴性似然比、诊断优势比和诊断评分分别为 4.17(95%CI,2.62-6.66)、0.16(95%CI,0.09-0.29)、26.61(95%CI,10.22-69.28)和 3.28(95%CI,2.32-4.24)。未发现发表偏倚。

结论

MRI 诊断胎盘植入具有良好的准确性和预测价值,值得临床推广。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cd9/9439908/35ae970cb749/CMMM2022-2751559.009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cd9/9439908/2bf00ca60a64/CMMM2022-2751559.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cd9/9439908/e747e84ce983/CMMM2022-2751559.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cd9/9439908/35ae970cb749/CMMM2022-2751559.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cd9/9439908/4a861aa97b17/CMMM2022-2751559.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cd9/9439908/c9325a98954a/CMMM2022-2751559.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cd9/9439908/927c0069b8b6/CMMM2022-2751559.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cd9/9439908/0fc7d83f2c91/CMMM2022-2751559.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cd9/9439908/cb562ff6c480/CMMM2022-2751559.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cd9/9439908/9ad0801e88dd/CMMM2022-2751559.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cd9/9439908/2bf00ca60a64/CMMM2022-2751559.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cd9/9439908/e747e84ce983/CMMM2022-2751559.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cd9/9439908/35ae970cb749/CMMM2022-2751559.009.jpg

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