Wang Jiefang, Chen Zhichao, Chen Jieyun
Department of Radiology, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, Fujian 362000, P.R. China.
Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian 362000, P.R. China.
Oncol Lett. 2023 Aug 23;26(4):436. doi: 10.3892/ol.2023.14023. eCollection 2023 Oct.
No clear conclusions have yet been reached regarding the accuracy of magnetic resonance imaging (MRI) radiomics in distinguishing high-grade glioma (HGG) from low-grade glioma (LGG). In the present study, a meta-analysis was conducted to determine the diagnostic value of MRI radiomics in differentiating between HGG and LGG, in order to guide their clinical diagnosis. PubMed, Embase and the Cochrane Library databases were searched up to November 2022. The search included studies in which true positive, false positive, true negative and false negative values for the differentiation of HGG from LGG were reported or could be calculated by retrograde extrapolation. Duplicate publications, research without full text, studies with incomplete information or unextractable data, animal studies, reviews and systematic reviews were excluded. STATA 15.1 was used to analyze the data. The meta-analysis included 15 studies, which comprised a total of 1,124 patients, of which 701 had HGG and 423 had LGG. The pooled sensitivity and specificity of the studies overall were 0.92 (95% CI: 0.89-0.95) and 0.89 (95% CI: 0.85-0.92), respectively. The positive and negative likelihood ratios of the studies overall were 7.89 (95% CI: 6.01-10.37) and 0.09 (95% CI: 0.07-0.12), respectively. The pooled diagnostic odds ratio of the studies was 85.20 (95% CI: 54.52-133.14). The area under the summary receiver operating characteristic curve was 0.91. These findings indicate that radiomics may be an accurate tool for the differentiation of glioma grades. However, further research is needed to verify the most appropriate of these technologies.
关于磁共振成像(MRI)放射组学在区分高级别胶质瘤(HGG)和低级别胶质瘤(LGG)方面的准确性,目前尚未得出明确结论。在本研究中,进行了一项荟萃分析,以确定MRI放射组学在鉴别HGG和LGG方面的诊断价值,从而指导其临床诊断。检索了截至2022年11月的PubMed、Embase和Cochrane图书馆数据库。检索纳入了报告了或可通过逆向推断计算出HGG与LGG鉴别诊断的真阳性、假阳性、真阴性和假阴性值的研究。排除重复发表的文献、无全文的研究、信息不完整或数据无法提取的研究、动物研究、综述和系统评价。使用STATA 15.1分析数据。该荟萃分析纳入了15项研究,共1124例患者,其中701例为HGG,423例为LGG。这些研究的总体合并敏感性和特异性分别为0.92(95%CI:0.89 - 0.95)和0.89(95%CI:0.85 - 0.92)。这些研究的总体阳性和阴性似然比分别为7.89(95%CI:6.01 - 10.37)和0.09(95%CI:0.07 - 0.12)。这些研究的合并诊断比值比为85.20(95%CI:54.52 - 133.14)。汇总的受试者工作特征曲线下面积为0.91。这些结果表明,放射组学可能是一种准确的胶质瘤分级鉴别工具。然而,需要进一步研究以验证这些技术中最合适的技术。