The aim of this study is to evaluate the role of diffusion kurtosis imaging (DKI) in characterizing clear cell renal cell carcinoma (ccRCC) and to correlate DKI related parameters with tumor cellularity.Fifty-nine patients with pathologically diagnosed ccRCCs were evaluated by DKI performed with 7 b-values ranging from 0 to 2000 s/mm2 on a 3T scanner. Regions of interest were drawn on the maps of mean diffusion coefficient (MD) and mean diffusion kurtosis (MK). All ccRCCs were histologically graded according to Fuhrman classification system. Tumor cellularity was measured by nuclear-to-cytoplasm (N/C) ratio and the number of tumor cell nuclear (NTCN). Parameter of DKI was calculated according to former literature [1]. Region of interest (ROI) analysis was conducted on the DW b1000 (b-value = 1000 s/mm2) images with reference to the T2-weighted images. The renal lesions were delineated and care was taken to avoid region’s cyst and necrosis that were hyperintense on both T2-weighted images and MD maps. Lesion and normal renal parenchymal ROIs were then transferred and used for MD and MK measurements on the MD and MK maps (Figure 1). The result of our study was listed in Table 1 and Table 2. Both MD and MK could readily discriminate normal renal parenchyma from ccRCCs (P < 0.001). Further, MD and MK were significantly different between Grade 1 and Grade 3&4 (P = 0.01, P < 0.001) and between Grade 2 and Grade 3&4 (P = 0.015, P < 0.005), respectively. However, no significant difference was found between Grade 1 and Grade 2 (P > 0.05) for both MD and MK. As for NTCN, no significant difference was found between any two grades (P > 0.05), while N/C ratio changes significantly with grades (P < 0.01, between any two grades). Negative correlations were found between MK and MD (r = -0.56, P < 0.001), and between MD and N/C ratio (r = -0.36, P < 0.005), while MK and N/C ratio was positively correlated (r = 0.45, P = 0.003). Our finding indicated that both water diffusion restriction and its non-Gaussian behavior increase with tumor grade. This is not surprising, because N/C ratio would have an impact on water diffusion restriction and tissue complexity and, more important, it was one of the features to determine histologic grade [2]. However, no statistical significance was found for NTCN between tumor grades, and either MD or MK did not correlate with NTCN. This might be attributed to the fact that NTCN is a tumor-specific index; it remains relatively stable of ccRCC in this study. The nuclear size and morphology of the four-tiered ccRCCs defined by Fuhrman nuclear grading system may partially account for the changes of MD, MK and tumor cellularity in this study. According to Fuhrman grading system, nuclei will have a larger size and contain more irregular appearance with high tumor grades. In addition, accompanied with the changes of nuclei, the presence and the size of nucleoli also increase with tumor grade. All of these changes in tumor cells led to the increase of N/C ratio with tumor grades, suggesting that molecular motion of water becomes more restricted because of decreasing extracellular space as tumor cells proliferate and microstructural complexity in tumor increases. It is worthwhile to note that both MD and MK were not significantly different between G1 and G2. Several factors may be potentially responsible for this. First, Nuclear grading was based on the highest-grade area identified within the tumor, but it is subjected to the extent of tumor sampling of a given tumor. Second, the specimen fixation protocol used also can markedly affect the assignment of nuclear grades. Suboptimal fixation can make nuclear chromatin appear coarser and less hyperchromatic and can alter nucleolar morphology, thereby leading to grade migration. Last, the similar nuclear feature would add the difficulty for MD and MK in discrimination between G1 and G2.DKI could not only quantitatively characterize ccRCC with different grades but also provide valuable information on the diffusion properties related to tumor microenvironment changes or tissue complexity in tumor.