Prostate cancer is the second most common cancer for men, and it has high leading cause of cancer death among men 1. The purpose of this study was to evaluate the feasibility of the typical parameters of diffusion kurtosis imaging (DKI) , MK, Ka, Kr, FA, MD, Da, Dr, in diagnostic differentiation of prostate cancer from prostatic hyperplasia, and in further the sensitivity, specificity and accuracy of the parameters for the diagnosis. Introduction: WhileAlthough transrectal ultrasonographically guided biopsy and prostate-specific antigen testing have been the primary tools used for tumor detection, these methods have clear limitations of prone to result in missed diagnoses of cancer. Prostate magnetic resonance (MR) imaging was previously ordered used in routine most commonly for disease staging, while the novel multi-parametric MR imaging has facilitated an increased role for imaging in risk stratification and treatment planning2. Among various functional MR imaging techniques, diffusion-weighted imaging (DWI) is well accepted and applied as a clinical marker of tumor aggressiveness, but with one limitation of DWI is an approach assuming Gaussian behavior of water diffusion in human body which however not true, especially for the regions of tumors 3. Diffusional kurtosis imaging (DKI) is a novel DW model that treats water diffusion as non-Gaussian in behavior and can may better reflect the microstructural complexity of tissue from by a multi-direction and multi-b value acquisition. DKI provides a measure of the excess DK of tissue, and quantifies the deviation of tissue diffusion from a Gaussian pattern, as well as a diffusion coefficient corrected to account for this non-Gaussianity4. In previous cross-sectional studies, it has been reported that DKI could supply certain information in purpose that might serve as a sensitive biomarker for a possible detection of prostate3,4. The purpose of this study was to evaluate the feasibility of the typical parameters of DKI in diagnostic differentiation of prostate cancer from prostatic hyperplasia compared to traditional ADC. And in further, the sensitivity, specificity and accuracy of the parameters for the diagnosis were also analyzed.59 patients with the suspicion of prostate disease were recruited in the study. All the patients were performed MRI exams on a 3.0T scanner (GE-Signa HDXT) in a protocol containing the routine T1WI, T2WI, contrast-enhanced MRI, DWI(b=0, 1000s/mm2) and DKI (b =0, 1000 and 2000 s/mm2, in 15 directions). From Based on the following histopathological examination, it was confirmed that prostate carcinoma was in 30 patients and prostatic hyperplasia in 29 patients. MR images were reviewed and analyzed by two experienced radiologist in prostate diagnosis blind to the histopathological results, using a dedicated software in Functool on GE ADW4.4 workstation. For each focus, the mean value of the parameters of DKI (mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da), radial diffusivity (Dr) )(MK, Ka, Kr, FA, MD, Da, Dr) and DWI (ADC) wereas measured (Fig1). ICC test was used to examine the consistency of the measurements, and student’s t-test was executed to compare the obtained parametric values with p< 0.05 concerned statistical significant. The ROC curve of all the parameters were drew and analyzed. The ICC value of the DKI parameters and DWI parameter in the PCa group and BPH group were higher than 0.75(Table 1), exhibiting an amenable consistency. The mean MK, Ka, Kr of PCa were significantly higher (p < 0.01) than the BPH, while the mean MD, Da, Dr of cancerous tissue was found to be significantly lower (p < 0.01) than the hyperplasia tissue(Table 2). No statistically significant difference was observed between FA values of two groups (p >0.05). The area under the ROC curve of all parameters were higher than 0.9 (Table 3). DKI provides a measure of the excess diffusion kurtosis of tissue, and quantifies the deviation of tissue diffusion from a Gaussian pattern, as well as a diffusion coefficient corrected to account for this non-Gaussianity4. DKI demonstrated can supply many meritorious parameters, with most useful in diagnostic differentiation of prostate cancer from prostatic hyperplasia. Combining with the routine prostate MRI, DKI may help in increasing the sensitivity and specificity of cancer detection.