Sensitivity analysis refers to the reanalysis of data after excluding a single study. We evaluated the effect of a single study on the pooled results by excluding each study. The pooled weighted mean deviation did not alter when a single study was excluded. The presence of publication bias was visually evaluated by Egger's funnel plot. Results of Egger's funnel plot test (P = .703) did not yield strong evidence for publication bias (Fig. 5). Actually, the actual pooled effect size was almost equal to the theoretical pooled effect size.
To date, an evidence-based approach to evaluate the accuracy of APT-weighted MRI in characterization of gliomas has been unreported. This result could provide us with clues to investigate the diagnostic value of preclinical tumor grading via APT measurements. It has been demonstrated that APT was capable of effectively differentiating primary central nervous system lymphomas and high-grade gliomas, benign and atypical meningioma; but also malignant gliomas from benign tumor. However, studies on the efficacy of APT-based grading of brain tumor have challenged. Choi et al reported that SI for grades II and IV was significantly different (P = .002), while the SI for grades II and III showed no significant difference (P = .059). In contrast, compared with grade II gliomas, Zou et al reported that SI derived from APT of grade III and IV gliomas with larger SI (P < .05), whereas there was no statistically significant differences for all measured parameters within WHO grade III and IV gliomas (P > .05). It was possible that inhomogeneous of the results among included studies, may influence by study design and parameters examined. Thus, in order to address the variations from studies, meta-analysis can improve accuracy of APT by increasing sample size.
According to the forest map, there is a possibility that significant heterogeneity in this meta-analysis could have arisen from differences in MRI scanners, data acquisition, patients examined among the 6 chosen studies. Since the technology was first introduced in 2003, only 6 studies have been included in this project, which was uncontrollable. While publication bias did not exist in this meta-analysis, we cannot rule out that some biases possible source of unreported papers.
Although our findings indicate that APT was useful for predicting the grading of brain gliomas, some inherent limitations existed in our study and should be considered when interpreting our results. First, all included studies in our meta-analysis originate from Asia (Japan, Korea, and China), which may represent one source of heterogeneity. Second, since the pathological results of the included studies were based on the 2007 WHO standard, the updated 2017 WHO standard believes that genes provide more valuable information. Third, there was a notable heterogeneity in our meta-analyses. Subgroup analysis was not implemented, since 6 papers have been included in this meta-analysis, which was uncontrollable. The sensitivity and specificity of the measure could not be evaluated currently. Future high-quality and large-scale randomized studies were warranted.
To date, we have not found any articles using the APT technique as a preclinical diagnostic marker for distinguishing HGGs from LGGs. Although the limitations of our meta-analysis, all currently evidence indicated that APT was an accurate and noninvasive imaging technique for distinguishing HGGs from LGGs. In the future, large-scale randomized trials were necessary to evaluate the clinical value of APT and to establish standards of scanning parameters.
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