Meta-analysis of the Diagnostic Performance of Diffusion Magnetic Resonance Imaging with Apparent Diffusion Coefficient Measurements for Differentiating Glioma Recurrence from Pseudoprogression

Objective: The accurate differentiation of glioma recurrence from pseudoprogression (PSP) after therapy remains a considerable clinical challenge. Several studies have shown that diffusion magnetic resonance imaging (MRI) has potential value in distinguishing these 2 outcomes. The current meta-analysis examined the diagnostic accuracy of diffusion MRI with the apparent diffusion coefficient (ADC) in the differentiation of glioma recurrence from PSP.

Method: PubMed, Embase, Cochrane Library, and Chinese Biomedical databases were reviewed to identify studies that fulfilled our inclusion/exclusion criteria and were published on or before May 5, 2019. Threshold effects; heterogeneity; pooled sensitivity (SENS), specificity, positive likelihood ratio, and negative likelihood ratio; and diagnostic odds ratio were calculated. The overall diagnostic usefulness of diffusion MRI-derived ADC values was assessed by calculating the area under the curve (AUC) following summary receiver operating characteristic (SROC) analysis.

Results: Six eligible studies examined a total of 214 patients. Calculation of pooled values indicated the SENS was 0.95 (95% confidence interval [CI] = 0.89-0.98), specificity was 0.83 (95% CI = 0.72-0.91), positive likelihood ratio was 4.82 (95% CI = 2.93-7.93), negative likelihood ratio was 0.08 (95% CI = 0.04-0.17), and diagnostic odds ratio was 59.63 (95% CI = 22.63-157.37). The SROC AUC was 0.9322. Publication bias was not significant, and SENS analysis indicated the results were relatively stable.

Conclusions: Our meta-analysis indicated that diffusion MRI with quantitative ADC is an effective approach for differentiation of glioma recurrence from PSP, and can be used as an auxiliary tool to diagnose glioma progression.