Abstract: Objective To analyze the value of multi-parameter magnetic resonance imaging （Mp-MRI） based on Prostate Imaging Reporting and Data System version 2 （PI-RADS v2） score combined with prostate specific antigen density （PSAD） for middlehigh grade prostate cancer（MHGPCa）.
MethodsThis retrospective study analyzed the datas of 227 patients of suspicious prostate disease， including 70 cases of MHGPCa， 23 cases of LGPCa and non-cancer of 134 cases who were all confirmed pathologically by puncture biopsies and underwent the high-resolution axial T2WI combined with DWI and DCE-MRI. The MRI images of the 227 patients were scored according to the PI-RADS v2 and the prostate volume and PSAD value were calculated. The univariate and multivariate analysis were performed for the observed indicators， including age， prostate volume， total prostate specific antigen （tPSA）， free-to-total PSA ratio （f／tPSA） and PI-RADS v2 score， to determine the independent predictors for MHGPCa. Then， the Logistic regression model was established using the independent predictors to jointly predict MHGPCa. The receiver operating characteristics （ROC） curves of the independent predictors and the model to diagnose MHGPCa were drew respectively to get the best threshold， and the differences of AUC values were compared to evaluate the diagnostic performance for MHGPCa. Results Among all the observed indicators， PI-RADS v2 score and PSAD were independent predictors for MHGPCa （P＜0.05）. The Logistic regression model established by PI-RADS v2 score combined with the PSAD to predict MHGPCa was as follows： Logit（P）=-5.514+0.7×PSAD+1.219×PI-RADS v2 score. The area under curve （AUC） value of the model （0.916） was higher than those of the PI-RADS v2 score and PSAD（0.882 and 0.892） and the differences between the model and PIRADS v2 score was statistically significant （P＜0.05）；but the difference of the AUC value between the model and PSAD was not statistically significant （P＞0.05） and the difference between PI-RADS v2 score and PSAD was not statistically significant （P＞0.05）. Conclusion The diagnositic performance of MpMRI based on PI-RADS v2 score combined with PSAD for MHGPCa is superior to that of PIRADS v2 score alone. Combined application of PI-RADS v2 score and PSAD can be popularized in clinical practice.