Keywords: Prostate, ProstateIt’s still a challenge to accurately diagnose prostate cancer through MRI before operation. PI-RADS was capable of assessing the value of risk, but it did not combine clinical characteristics. we combined clinical characteristics and mpMRI parameters for the prediction of the risk of prostate cancer and compared them with PI-RADS. We found that the model was significantly better than PI-RADS (P=0.01976). The AUC of the model is higher than that of PI-RADS (0.99＞0.90, p=0.019). This study demonstrated the feasibility of the model to predict the risk of prostate cancers early so that low-risk patients can avoid unnecessary needle biopsies.
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