Xiao Simin, Zeng Siyuan, Kou Yangbin
Radiology Department, The First Affiliated Hospital of Traditional Chinese Medicine of Chengdu Medical College, XinDu Hospital of Traditional Chinese Medicine, Chengdu, China.
Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, China.
Sci Rep. 2025 May 20;15(1):17521. doi: 10.1038/s41598-025-88315-7.
To evaluate the diagnostic value of magnetic resonance imaging (MRI) radiomics in distinguishing high-grade meningiomas (HGM) from low-grade meningiomas (LGM). A systematic search was conducted in PubMed, EMbase, Web of Science, and The Cochrane Library databases up to December 31, 2023. Two researchers independently screened studies, extracted data, and assessed risk of bias and quality of included studies as well. Meta-analysis was performed using Stata 14 software to calculate pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC). A total of 21 studies with 2253 patients were included (607 HGM, 1646 LGM). Meta-analysis showed an overall SEN of 0.82 (95% CI 0.74-0.88) and SPE of 0.85 (95% CI 0.81-0.89). The PLR and NLR were 5.64 (95% CI 4.17-7.64) and 0.21 (95% CI 0.14-0.31), respectively, with a pooled DOR of 26.66 (95% CI 14.42-49.27) and an AUC of 0.91 (95% CI 0.88-0.93), indicating high diagnostic accuracy. Although additional research is required to validate suitable techniques, MRI radiomics shows strong potential as an accurate tool for meningioma grading. Standardizing radiomics application could enhance diagnostic precision and clinical decision-making for meningioma grading in the future.Trial Registration: CRD42024500086.
评估磁共振成像（MRI）放射组学在鉴别高级别脑膜瘤（HGM）与低级别脑膜瘤（LGM）中的诊断价值。截至2023年12月31日，在PubMed、EMbase、Web of Science和Cochrane图书馆数据库中进行了系统检索。两名研究人员独立筛选研究、提取数据，并评估纳入研究的偏倚风险和质量。使用Stata 14软件进行荟萃分析，以计算合并敏感度（SEN）、特异度（SPE）、阳性似然比（PLR）、阴性似然比（NLR）、诊断比值比（DOR）和曲线下面积（AUC）。共纳入21项研究，涉及2253例患者（607例HGM，1646例LGM）。荟萃分析显示总体SEN为0.82（95%CI 0.74 - 0.88），SPE为0.85（95%CI 0.81 - 0.89）。PLR和NLR分别为5.64（95%CI 4.17 - 7.64）和0.21（95%CI 0.14 - 0.31），合并DOR为26.66（95%CI 14.42 - 49.27），AUC为0.91（95%CI 0.88 - 0.93），表明诊断准确性高。尽管需要进一步研究来验证合适的技术，但MRI放射组学作为脑膜瘤分级的准确工具显示出强大潜力。标准化放射组学应用可提高未来脑膜瘤分级的诊断精度和临床决策。试验注册号：CRD42024500086。
