Predictive role of PI-RADSv2 and ADC parameters in differentiating Gleason pattern 3+4 and 4+3 prostate cancer

PurposeTo compare the predictive roles of qualitative (PI-RADSv2) and quantitative assessment (ADC metrics), in differentiating Gleason pattern (GP) 3+4 from the more aggressive GP 4+3 prostate cancer (PCa) using radical prostatectomy (RP) specimen as the reference standard.MethodsWe retrospectively identified treatment-naive peripheral (PZ) and transitional zone (TZ) Gleason Score 7 PCa patients who underwent multiparametric 3T prostate MRI (DWI with b value of 0,1400 and where unavailable, 0,500) and subsequent RP from 2011 to 2015. For each lesion identified on MRI, a PI-RADSv2 score was assigned by a radiologist blinded to pathology data. A PI-RADSv2 score3 was defined as low risk, a PI-RADSv2 score4 as high risk for clinically significant PCa. Mean tumor ADC (ADC(T)), ADC of adjacent normal tissue (ADC(N)), and ADC(ratio) (ADC(T)/ADC(N)) were calculated. Stepwise regression analysis using tumor location, ADC(T) and ADC(ratio), b value, low vs. high PI-RADSv2 score was performed to differentiate GP 3+4 from 4+3.Results119 out of 645 cases initially identified met eligibility requirements. 76 lesions were GP 3+4, 43 were 4+3. ADC(ratio) was significantly different between the two GP groups (p=0.001). PI-RADSv2 score (low vs. high) was not significantly different between the two GP groups (p=0.17). Regression analysis selected ADC(T) (p=0.03) and ADC(ratio) (p=0.0007) as best predictors to differentiate GP 4+3 from 3+4. Estimated sensitivity, specificity, and accuracy of the predictive model in differentiating GP 4+3 from 3+4 were 37, 82, and 66%, respectively.ConclusionsADC metrics could differentiate GP 3+4 from 4+3 PCa with high specificity and moderate accuracy while PI-RADSv2, did not differentiate between these patterns.