The Diagnostic Value Of Biparametric Magnetic Resonance Imaging Based On PI-RADS V2.1 Combined With PSAD In Prostate Cancer

Objective:To evaluate the diagnostic value of biparametric magnetic resonance imaging(bp-MRI)based on PI-RADS V2.1 combined with prostate specific antigen density(PSAD)for prostate cancer(PCa).Methods : Patients who underwent MRI examinations and were diagnosed with prostate cancer(PCa)and prostatic hyperplasia(BPH)by needle biopsy at JIANGSU TAIZHOU PEOPLE’S HOSPITAL from January 2018 to October 2020 was collected retrospectively,and a total of 268 patients were finally included following the strict criteria,including 137 with PCa and 131 with BPH.All MRI images were analyzed,and those for prostate were scored according to the PI-RADS v2.1(1-5 scores).Clinical indicators of patients were recorded,including age,total prostate-specific antigen(t PSA),prostatic volume(PV)and prostate-specific antigen density(PSAD).Statistical analysis was performed using SPSS20.0 statistical software and Med Calc software(De Long’s method).The PI-RADS v2.1 score,age,t PSA,PV and PSAD were tested for normality.Independent-sample T test was used to conduct univariate analysis for the indicators conforming to normal distribution,expressed as x±s,and Mann-Whitney U test was for those not conforming to normal distribution,expressed as median(upper and lower quartiles).Differences of each indicator between the PCA group and the BPH group were evaluated,and binary logistic regression analysis was performed on the diagnostic indicators with statistical significance(P <0.05),so as to determine the independent predictors of PCa.The diagnostic value of PI-RADS v2.1 score,t PSA,PSAD and PV to PCa was analyzed through ROC curves.Patients with PI-RADS v2.1score of 3 were divided into 2 groups based on pathological results,the clinical significant prostate cancer(cs PCa)group and non-cs PCa group.Univariate analysis was performed on the clinical indicators of patients,and then binary logistic regression analysis was performed to explore the diagnostic value of PSAD,age,t PSA and PV for cs PCa.Results : The PI-RADS v2.1 score,t PSA and PSAD of the PCa group were significantly higher than those of the BPH group(Z values were-10.30,-10.84,-11.62,p<0.05).The PV of the PCa group was significantly lower than that of the BPH group(Z=-5.00,p<0.05).There was no significant difference in age between PCa group and BPH group(t=1.92,P>0.05).The PI-RADS v2.1 score,t PSA,PV,and PSAD of patients are helpful for the diagnosis of PCa.The diagnostic efficiency is in descending order of PI-RADS v2.1 score,PSAD,t PSA,PV.The optimal threshold of PI-RADS v2.1 score is3,and its sensitivity,specificity,positive predictive value,and negative predictive value for diagnosing PCa are 89.05%,64.12%,72.2%,and 84.8%,respectively.The optimal threshold of PSAD is 0.216,and its sensitivity,specificity,positive predictive value,and negative predictive value for diagnosing PCa are 67.88%,75.57%,74.2%,68.7%,respectively.The optimal threshold of t PSA is 24.003,and the sensitivity,specificity,positive predictive value,and negative predictive value of PCa are 55.47%,79.39%,73.5%,62.7%,respectively.The optimal threshold for PV is 58.8,and the sensitivity,specificity,positive predictive value,and negative predictive value of PCa are 67.88%,60.31%,64.1%,and 64.2%,respectively.The PI-RADS v2.1 score,t PSA,PV,PSAD were used as single-factor indicators for binary logistic regression analysis.The independent predictors of PCa were PI-RADS v2.1 score(OR=0.375,95%CI:0.233-0.604,P<0.05),t PSA(OR=0.928,95%CI:0.885-0.974,P<0.05),PV(OR=1.025,95%CI:1.004-1.047,P<0.05),PSAD(OR=0.087,95%CI:0.008-0.920,P<0.05).The efficacy of PI-RADS v2.1 score combined with t PSA,PV,PSAD in diagnosing PCa is as follows: PI-RADS v2.1 score combined with t PSA in the diagnosis of PCa has a AUC of 0.765,a sensitivity of 63.5%,and a specificity of 91.6%,positive The predictive value is 88.8%,and the negative predictive value is 70.6%.The AUC of the PI-RADS v2.1 score combined with PV to diagnose PCa is 0.759,the sensitivity is54.01%,the specificity is 96.95%,the positive predictive value is 94.9%,and the negative predictive value is 66.8%.The PI-RADS v2.1 score combined with PSAD in the diagnosis of PCa has an AUC of 0.885,a sensitivity of 71.5%,a specificity of90.84%,a positive predictive value of 89.1%,and a negative predictive value of75.3%.For patients with a PI-RADS v2.1 score of 3,after univariate analysis,the t PSA and PSAD of the cs PCa group were higher than those of the non-cs PCa group,and the difference was statistically significant(Z=-4.367、-5.056,P<0.05).The PV of the cs PCa group was lower than that of the non-cs PCa group,and the difference was statistically significant(Z=-3.01,P<0.05).There was no significant difference in age between the two groups(t=0.058,P>0.05).The area under the ROC curve(AUC)corresponding to the t PSA,PV,and PSAD of patients with a PI-RADS v2.1 score of 3 to diagnose cs PCa are 0.805,0.710,and 0.853.Binary logistic regression of t PSA,PV and PSAD Analysis shows that the independent predictor of cs PCa is PSAD(OR=0.020,95%CI:0-0.824,P<0.05).When the optimal threshold of PSAD is 0.256 and the Youden index is the largest,the sensitivity,specificity,positive predictive value,and negative predictive value of cs PCa are 84.62%,88.46%,77.8%,and 90.2%.Conclusion:(1)PI-RADS v2.1 score,t PSA,PV,PSAD can be used as indicators and independent predictors for the diagnosis of PCa,and the biparametric PI-RADS v2.1 score shows the highest diagnostic efficiency.(2)The PI-RADS v2.1 score combined with PSAD has a higher diagnostic efficiency than either of them alone in the diagnosis of prostate cancer.(3)For patients with a PI-RADS v2.1 score of 3,the probability of developing cs PCa is very low when PSAD is less than 0.256,and unnecessary biopsy can be avoided in this case.