论文部分内容阅读
目的采用Meta分析方法综合定量评价扩散峰度成像在脑胶质瘤分级中的应用价值。方法检索Cochrane协作网、Cochrane图书馆、Pubmed、OVID、中文科技期刊全文数据库(CNKI)、万方数据知识服务平台、维普中文科技期刊数据库(VIP)、中国生物医学文献数据库(CBM)自建库以来至2016年5月国内外公开发表的关于扩散峰度成像在脑胶质瘤分级中应用的中英文文献。按照Cochrane协作网推荐的诊断试验纳入标准筛选文献,采用QUADAS条目评价纳入研究的质量,提取纳入研究的相关数据信息。采用Meta-Disc 1.4软件进行数据分析,通过Meta分析合并诊断效应量及绘制汇总受试者工作特征曲线(SROC曲线),计算曲线下面积(AUC)。结果共纳入5篇文献,研究病灶共265个,汇总加权敏感度、特异度、诊断比值比、阳性似然比、阴性似然比及95%可信区间分别为0.88(95%CI 0.81~0.93)、0.87(95%CI 0.81~0.91)、52.49(95%CI17.36~158.67)、6.25(95%CI 3.17~12.32)、0.16(95%CI 0.08~0.36);SROC曲线AUC为0.9439。结论扩散峰度成像在脑胶质瘤分级中具有很高的应用价值。
Objective To evaluate the value of diffusion kurtosis imaging in the classification of glioma using Meta analysis. Methods Cochrane Collaboration, Cochrane Library, Pubmed, OVID, CNKI, Wanfang Data Knowledge Service Platform, Vip Database of Chinese Science and Technology, and CBM Library Since May 2016, both Chinese and English literatures published at home and abroad have been widely used in glioma grading. According to the diagnostic tests recommended by the Cochrane Collaboration, standard screening literature was included, QUADAS entries were used to assess the quality of the studies included, and information about the data included in the study was extracted. Meta-Disc 1.4 software was used to analyze the data. Meta-analysis was used to calculate the amount of diagnostic effect and to draw a summary of the receiver operating characteristic curve (SROC curve) to calculate the area under the curve (AUC). Results A total of 5 articles were included and 265 were studied. The weighted weighted sensitivity, specificity, diagnostic odds ratio, positive likelihood ratio, negative likelihood ratio and 95% confidence interval were 0.88 (95% CI 0.81-0.93 ), 0.87 (95% CI 0.81-0.91), 52.49 (95% CI 17.36-158.67), 6.25 (95% CI 3.17-12.32) and 0.16 (95% CI 0.08-0.36). The AUC of SROC curve was 0.9439. Conclusion diffusion kurtosis imaging in glioma grading has a high value.