Diagnostic Performance of DWI for Differentiating High- From Low-Grade Clear Cell Renal Cell Carcinoma: A Systematic Review and Meta-Analysis

Abstract

Objective: The purpose of our study was to review the diagnostic performance of DWI for differentiating high- from low-grade clear cell renal cell carcinoma (RCC).

Materials and methods: MEDLINE, EMBASE, and Cochrane library databases were searched up to March 15, 2017. We included diagnostic accuracy studies that used DWI for differentiating high- from low-grade clear cell RCC compared with histopathologic results of Fuhrman grade based on nephrectomy or biopsy specimens in original research articles. Two independent reviewers assessed methodologic quality using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Sensitivity and specificity of the included studies were pooled and graphically presented using a hierarchic summary ROC plot. For heterogeneity exploration, we assessed the presence of a threshold effect and performed meta-regression analyses.

Results: Eight retrospective studies (394 patients with 397 clear cell RCCs) were included. Pooled sensitivity was 0.78 (95% CI, 0.68-0.85) with a specificity of 0.86 (95% CI, 0.70-0.94). A considerable threshold effect was observed with a correlation coefficient of 0.811 (95% CI, 0.248-0.964) between the sensitivity and false-positive rate. At meta-regression analysis, apparent diffusion coefficient (× 10 mm²/s) cutoff value (< 1.57 vs ≥ 1.57; p = 0.03) and location of ROI (solid portion vs whole tumor; p = 0.04) were significant factors affecting heterogeneity. Other factors with regard to patients and tumors, study, and MRI characteristics were not significant (p = 0.17-0.91).

Conclusion: DWI shows moderate diagnostic performance for differentiating high-from low-grade clear cell RCC. Substantial heterogeneity was observed because of a threshold effect. Further prospective studies may be needed; all included studies were retrospective.

Keywords: DWI; Fuhrman grade; MRI; clear cell renal cell carcinoma; meta-analysis.