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Aim and objectives We aim to illustrate the diagnostic performance of diffusional kurtosis imaging (DKI) in the diagnosis of gliomas. Methods and materials A review protocol was developed according to the Preferred Reporting Items for Systematic Review and Meta-analysis Protocols (PRISMA-P), registered in the international prospective register of systematic reviews, PROSPERO and published. Literature search in 4 databases was performed using the keywords “glioma” and “diffusional kurtosis”.After applying a robust inclusion/exclusion criteria, included articles were independently evaluated according to the QUADAS-2 tool.Data extraction was done in a pre-designed pro forma.Reported sensitivities and specificities were used to construct 2x2 tables and paired forest plots using the Review Manager (RevMan®) software.Random-effect model was pursued using the hierarchical summary receiver operator characteristics. Results Initially, 216 hits were retrieved. Considering duplicates and inclusion criteria; 23 articles were eligible for full-text reading. Ultimately, 19 studies were deemed to be eligible for final inclusion. Quality assessment revealed 9 studies with low risk of bias in the 4 domains. Using a bivariate random-effect model for data synthesis; summary ROC curve showed pooled area under the curve (AUC) of 0.92 and estimated sensitivity of 0.87 (95% CI: 0.78 - 0.92) in high/low grade gliomas’ differentiation.A mean difference in Mean Kurtosis (MK) value between HGG and LGG of 0.22 [95% CI: 0.25 - 0.19] was illustrated (p value = 0.0014) and a moderate degree of heterogeneity (I²= 73.8%). Conclusion DKI shows good diagnostic accuracy in high/low grade gliomas’ differentiation; which might qualify it to be part of the routine clinical practice, however; further evidence is deemed for technique standardization.

Role of diffusional kurtosis imaging in grading of brain gliomas: A diagnostic test accuracy systematic review and meta-analysis