Wang Qiang-Ping, Lei De-Qiang, Yuan Ye, Xiong Nan-Xiang
Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Medicine (Baltimore). 2020 Feb;99(8):e19254. doi: 10.1097/MD.0000000000019254.
Quantitative apparent diffusion coefficient (ADC) values of diffusion weighted imaging (DWI) could be applied to grade gliomas. This meta-analysis was conducted to assess the accuracy of ADC analysis in differentiating high-grade (HGGs) from low-grade gliomas (LGGs).
PubMed, Cochrane library, Science Direct, and Embase were searched to identify suitable studies up to September 1, 2018. The quality of studies was evaluated by the quality assessment of diagnostic accuracy studies (QUADAS 2). We estimated the pooled sensitivity, specificity, positive and negative likelihood ratios (LR), diagnostic accuracy ratio (DOR) with 95% confidence intervals (CI), and determined the accuracy of the data by using the summary receiver operating characteristic (SROC) and calculating the area under the curve (AUC) to identity the accuracy of ADC analysis in grading gliomas.
Eighteen studies including 1172 patients were included and analyzed. The pooled sensitivity, specificity, PLR, NLR, DOR, and AUC with 95% CIs of DWI with b values of 1000 s/mm for separating HGGs from LGGs were 0.81 (95% CI 0.75-0.86), 0.87 (95% CI 0.81-0.91), 6.1 (95% CI 4.2-8.9), 0.22 (95% CI 0.17-0.29), 28 (95% CI 17-45), and 0.91 (95% CI 0.88-0.93), respectively. DWI with b values of 3000 s/mm showed slightly higher accuracy than that of 1000 (sensitivity 0.80, specificity 0.90 and AUC 0.92). Meta-regression analyses showed that field strengths and b values had significant impacts on diagnostic efficacy. Deeks testing confirmed no significant publication bias in all studies.
This meta-analysis suggested that ADC analysis of DWI have high accuracy in differentiating HGGs from LGGs. Standardized methodology is warranted to guide the use of this technique for clinical decision-making.
扩散加权成像(DWI)的定量表观扩散系数(ADC)值可用于胶质瘤分级。本荟萃分析旨在评估ADC分析在区分高级别胶质瘤(HGGs)和低级别胶质瘤(LGGs)方面的准确性。
检索了PubMed、Cochrane图书馆、Science Direct和Embase,以确定截至2018年9月1日的合适研究。采用诊断准确性研究的质量评估(QUADAS 2)对研究质量进行评估。我们估计了合并敏感度、特异度、阳性和阴性似然比(LR)、诊断准确性比值(DOR)及其95%置信区间(CI),并通过使用汇总接收器操作特征(SROC)和计算曲线下面积(AUC)来确定数据的准确性,以确定ADC分析在胶质瘤分级中的准确性。
纳入并分析了18项研究,共1172例患者。对于将HGGs与LGGs区分开来,b值为1000 s/mm²的DWI的合并敏感度、特异度、阳性似然比、阴性似然比、DOR和AUC及其95%CI分别为0.81(95%CI 0.75 - 0.86)、0.87(95%CI 0.81 - 0.91)、6.1(95%CI 4.2 - 8.9)、0.22(95%CI 0.17 - 0.29)、28(95%CI 17 - 45)和0.91(95%CI 0.88 - 0.93)。b值为3000 s/mm²的DWI显示出比b值为1000 s/mm²时略高的准确性(敏感度0.80,特异度0.90,AUC 0.92)。Meta回归分析表明,场强和b值对诊断效能有显著影响。Deeks检验证实所有研究中均无显著的发表偏倚。
本荟萃分析表明,DWI的ADC分析在区分HGGs和LGGs方面具有较高的准确性。需要标准化的方法来指导该技术在临床决策中的应用。