Diagnostic Performance of Monoexponential DWI Versus Diffusion Kurtosis Imaging in Prostate Cancer: A Systematic Review and Meta-Analysis

We aimed to compare the diagnostic performance of monoexponential DWI and diffusion kurtosis imaging (DKI) for the detection of prostate cancer (PCa). A systematic literature search was conducted for studies evaluating the diagnostic value of monoexponential DWI and DKI for PCa in the same patient cohorts with sufficient data to construct 2 × 2 contingency tables. Qualities of the included studies were assessed by the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Data were extracted to calculate pooled sensitivities and specificities. We constructed summary ROC curves and calculated AUCs to determine the performances of DKI parameters (diffusion coefficient and kurtosis characterizing the deviation from the monoexponential decay) and apparent diffusion coefficient (ADC) values in diagnosing PCa. Five studies (463 patients) were included, with eight, nine, and 10 subsets of data available for analysis of ADC, diffusion, and kurtosis, respectively. Pooled sensitivities were 89% (95% CI, 80-94%) for ADC, 91% (95% CI, 84-95%) for diffusion, and 87% (95% CI, 83-91%) for kurtosis. Pooled specificities were 86% (95% CI, 80-90%) for ADC, 78% (95% CI, 71-84%) for diffusion, and 85% (95% CI, 81-89%) for kurtosis. According to the summary ROC analyses, the AUC was 0.93 (95% CI, 0.90-0.95) for ADC, 0.89 (95% CI, 0.86-0.92) for diffusion, and 0.93 (95% CI, 0.90-0.95) for kurtosis. There was no notable publication bias, but significant heterogeneity was observed. Monoexponential DWI and DKI showed comparable diagnostic accuracies for PCa. DKI is a potentially helpful method for the diagnosis of PCa. Therefore, on the basis of current evidence, we do not recommend including DKI in routine clinical assessment of PCa for the moment.