AbstractObjective To analyze the diagnostic value of diffusion tensor imaging (DTI) for early radiation-induced brain injury.Methods We searched CNKI and PubMed and included articles according to the PRISMA statement. FA value, λ||, and λ丄 were pooled, and Forest plot generation, cumulative analysis, sensitivity analysis, and regression analysis were performed. We also used the funnel plot to analyze publication bias. Results A total 11 studies were included for meta-analysis. The results of FA value heterogeneity test were as follows:P=0.000, I2=93.6% in China;P=0.004, I2=82.2% in other countries and regions;P=0.000, I2=91.5% in all regions. The regression analysis of time-dose dependence and study design showed significant and non-significant associations, respectively, with the heterogeneity of these studies (adjusted P=0.026, P=0.005;adjusted P=0.859, P=0.908). The results of λ|| and λ丄 heterogeneity tests were as follows:P=0.908, I2=0.0%;P=0.100, I2=56.6%. There was a sign of publication bias by Egger’s test (coefficient:-6.26, 95% CI:-9.31 to -3.20, P=0.001) and Begg’s test (P=0.004). Conclusions DTI-derived metrics are sensitive and reliable in the diagnosis of early radiation-induced brain injury.
Li Junchen,Li Guohua,Hu Chunhong. A meta-analysis of diffusion tensor imaging for diagnosis of early radiation-induced brain injury[J]. Chinese Journal of Radiation Oncology, 2017, 26(5): 508-512.
Li Junchen,Li Guohua,Hu Chunhong. A meta-analysis of diffusion tensor imaging for diagnosis of early radiation-induced brain injury[J]. Chinese Journal of Radiation Oncology, 2017, 26(5): 508-512.
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