Wang Haoda, Xu Haidong, Fan Junsheng, Liu Jie, Li Liangfu, Kong Zailiang, Zhao Hui
Department of Radiology, The First Hospital of Huhhot, Huhhot, China.
Department of Radiotherapy, Affiliated Hospital of Inner Mongolia Medical University, Huhhot, China.
Front Neurosci. 2024 Oct 9;18:1474780. doi: 10.3389/fnins.2024.1474780. eCollection 2024.
To systematically review the literature on radiomics for predicting intracranial aneurysm rupture and conduct a meta-analysis to obtain evidence confirming the value of radiomics in this prediction.
A systematic literature search was conducted in PubMed, Web of Science, Embase, and The Cochrane Library databases up to March 2024. The QUADAS-2 tool was used to assess study quality. Stata 15.0 and Review Manager 5.4.1 were used for statistical analysis. Outcomes included combined sensitivity (Sen), specificity (Spe), positive likelihood ratio (+LR), negative likelihood ratio (-LR), diagnostic odds ratio (DOR), and their 95% confidence intervals (CI), as well as pre-test and post-test probabilities. The SROC curve was plotted, and the area under the curve (AUC) was calculated. Publication bias and small-study effects were assessed using the Deeks' funnel plot.
The 9 included studies reported 4,284 patients, with 1,411 patients with intracranial aneurysm rupture (prevalence 32.9%). The overall performance of radiomics for predicting intracranial aneurysm rupture showed a combined Sen of 0.78 (95% CI: 0.74-0.82), Spe of 0.74 (95% CI: 0.70-0.78), +LR of 3.0 (95% CI: 2.7-3.4), -LR of 0.29 (95% CI: 0.25-0.35), DOR of 10 (95% CI: 9-12), and AUC of 0.83 (95% CI: 0.79-0.86). Significant heterogeneity was observed in both Sen (I = 90.93, 95% CI: 89.00-92.87%) and Spe (I = 94.28, 95% CI: 93.21-95.34%).
Radiomics can improve the diagnostic efficacy of intracranial aneurysm rupture. More large-sample, prospective, multicenter clinical studies are needed to further evaluate its predictive value.
系统回顾关于放射组学预测颅内动脉瘤破裂的文献,并进行荟萃分析以获得证实放射组学在该预测中价值的证据。
截至2024年3月,在PubMed、Web of Science、Embase和Cochrane图书馆数据库中进行了系统的文献检索。使用QUADAS - 2工具评估研究质量。使用Stata 15.0和Review Manager 5.4.1进行统计分析。结果包括合并敏感度(Sen)、特异度(Spe)、阳性似然比(+LR)、阴性似然比(-LR)、诊断比值比(DOR)及其95%置信区间(CI),以及检验前和检验后概率。绘制SROC曲线并计算曲线下面积(AUC)。使用Deeks漏斗图评估发表偏倚和小研究效应。
纳入的9项研究报告了4284例患者,其中1411例颅内动脉瘤破裂患者(患病率32.9%)。放射组学预测颅内动脉瘤破裂的总体表现为合并Sen为0.78(95%CI:0.74 - 0.82),Spe为0.74(95%CI:0.70 - 0.78),+LR为3.0(95%CI:2.7 - 3.4),-LR为0.29(95%CI:0.25 - 0.35),DOR为10(95%CI:9 - 12),AUC为0.83(95%CI:0.79 - 0.86)。在Sen(I = 90.93,95%CI:89.00 - 92.87%)和Spe(I = 94.28,95%CI:93.21 - 95.34%)中均观察到显著异质性。
放射组学可提高颅内动脉瘤破裂的诊断效能。需要更多大样本、前瞻性、多中心临床研究来进一步评估其预测价值。