Department of Radiology, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huaian, Jiangsu, PR China.
Acta Radiol. 2021 Jul;62(7):966-978. doi: 10.1177/0284185120944916. Epub 2020 Aug 2.
Accurate preoperative diagnosis of malignant ovarian tumors (MOTs) is particularly important for selecting the optimal treatment strategy and avoiding overtreatment.
To evaluate the diagnostic efficacy of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for MOTs.
A systematic search was performed in PubMed, Embase, the Cochrane Library, and Web of Science databases to find relevant original articles up to October 2019. The included studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Studies on the diagnosis of MOTs with quantitative or semi-quantitative DCE-MRI were analyzed separately. The bivariate random-effects model was used to assess the diagnostic authenticity. Meta-regression analyses were performed to analyze the potential heterogeneity.
For semi-quantitative DCE-MRI, the pooled sensitivity, specificity, positive likelihood ratio (LR), negative LR, diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristic curves (AUC) were 85% (95% confidence interval [CI] 0.75-0.92), 85% (95% CI 0.77-0.91), 5.8 (95% CI 3.8-8.8), 0.17 (95% CI 0.10-0.30), 33 (95% CI 18-61), and 0.92 (95% CI 0.89-0.94), respectively. For quantitative DCE-MRI, the pooled sensitivity, specificity, positive LR, negative LR, DOR, and AUC were 88% (95% CI 0.65-0.96), 93% (95% CI 0.78-0.98), 12.3 (95% CI 3.4-43.9), 0.13 (95% CI 0.04-0.45), 91 (95% CI 10-857), and 0.96 (95% CI 0.94-0.98), respectively.
DCE-MRI has great diagnostic value for MOTs. Semi-quantitative DCE-MRI may be a relatively mature approach; however, quantitative DCE-MRI appears to be more promising than semi-quantitative DCE-MRI.
准确的术前诊断卵巢恶性肿瘤（MOTs）对于选择最佳治疗策略和避免过度治疗尤为重要。
评估动态对比增强磁共振成像（DCE-MRI）对 MOTs 的诊断效能。
系统检索 PubMed、Embase、Cochrane 图书馆和 Web of Science 数据库，查找截至 2019 年 10 月的相关原始研究。使用诊断准确性研究质量评估工具 2 对纳入的研究进行评估。分别分析 MOTs 定量或半定量 DCE-MRI 的研究。使用双变量随机效应模型评估诊断真实性。进行 Meta 回归分析以分析潜在的异质性。
对于半定量 DCE-MRI，汇总的敏感性、特异性、阳性似然比（LR）、阴性 LR、诊断比值比（DOR）和汇总受试者工作特征曲线下面积（AUC）分别为 85%（95%置信区间 [CI] 0.75-0.92）、85%（95% CI 0.77-0.91）、5.8（95% CI 3.8-8.8）、0.17（95% CI 0.10-0.30）、33（95% CI 18-61）和 0.92（95% CI 0.89-0.94）。对于定量 DCE-MRI，汇总的敏感性、特异性、阳性 LR、阴性 LR、DOR 和 AUC 分别为 88%（95% CI 0.65-0.96）、93%（95% CI 0.78-0.98）、12.3（95% CI 3.4-43.9）、0.13（95% CI 0.04-0.45）、91（95% CI 10-857）和 0.96（95% CI 0.94-0.98）。
DCE-MRI 对 MOTs 具有很大的诊断价值。半定量 DCE-MRI 可能是一种相对成熟的方法；然而，定量 DCE-MRI 似乎比半定量 DCE-MRI 更有前途。
