Liang Ying-Ying, Xu Fan, Guo Yuan, Wang Jin
Department of Radiology, Guangzhou First People's Hospital, Guangzhou Medical University; The Second Affiliated Hospital, South China University of Technology; 1Panfu Road Guangzhou, Guangdong Province 510180, China.
Department of Radiology, Guangzhou Red Cross Hospital, Medical College, Jinan University, 396 Tongfu Road Guangzhou, Guangdong Province 510220, China.
Clin Imaging. 2018 Nov-Dec;52:36-43. doi: 10.1016/j.clinimag.2018.05.026. Epub 2018 Jun 7.
To assess the added benefit of combining different MRI techniques for preoperative diagnosis of parotid tumors when compared to conventional MRI and advanced MRI techniques alone with meta-analysis.
A comprehensive PubMed electronic database search was performed for original diagnostic studies up to July 2017. The methodologic quality of each study was evaluated by two independent reviewers who used the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Statistical analysis included pooling of sensitivity and specificity with 95% confidence intervals (CI). All analyses were conducted using STATA (version 12.0), RevMan (version 5.2), and Meta-Disc 1.4 software programs.
Pooled sensitivity and specificity of conventional MRI, diffusion weighted imaging (DWI), dynamic contrast enhanced (DCE) and the above combination were 76% (95%CI)/91% (95%CI)/80% (95%CI)/86% (95%CI) and 83% (95%CI)/56% (95%CI)/90% (95%CI)/90% (95%CI).
Conventional MRI combined with DWI and DCE showed higher diagnostic accuracy than conventional or advanced MRI alone, supporting their use in parotid tumors diagnosis.
通过荟萃分析，评估与单独使用传统MRI和先进MRI技术相比，联合不同MRI技术用于腮腺肿瘤术前诊断的附加益处。
对截至2017年7月的原始诊断研究进行全面的PubMed电子数据库检索。由两名独立审阅者使用诊断准确性研究质量评估2（QUADAS - 2）工具评估每项研究的方法学质量。统计分析包括合并敏感性和特异性以及95%置信区间（CI）。所有分析均使用STATA（版本12.0）、RevMan（版本5.2）和Meta - Disc 1.4软件程序进行。
传统MRI、扩散加权成像（DWI）、动态对比增强（DCE）及上述组合的合并敏感性和特异性分别为76%（95%CI）/91%（95%CI）/80%（95%CI）/86%（95%CI）和83%（95%CI）/56%（95%CI）/90%（95%CI）/90%（95%CI）。
传统MRI联合DWI和DCE显示出比单独使用传统或先进MRI更高的诊断准确性，支持其在腮腺肿瘤诊断中的应用。
