Evaluation of prostate imaging reporting and data system classification in the prediction of tumor aggressiveness in targeted magnetic resonance imaging/ultrasound-fusion biopsy

Abstract

Objectives: The study aimed to evaluate the prediction of Prostate Imaging Reporting and Data System (PI-RADS) with respect to the prostate cancer (PCa) detection rate and tumor aggressiveness in magnetic resonance imaging (MRI)/ultrasound-fusion-biopsy (fusPbx) and in systematic biopsy (sysPbx). Materials and Methods: Six hundred and twenty five patients undergoing multiparametric MRI were investigated. MRI findings were classified using PI-RADS v1 or v2. All patients underwent fusPbx combined with sysPbx (comPbx). The lesion with the highest PI-RADS was defined as maximum PI-RADS (maxPI-RADS). Gleason Score ≥7 (3 + 4) was defined as significant PCa. Results: The overall PCa detection rate was 51% (n = 321; 39% significant PCa). The detection rate was 43% in fusPbx (n = 267; 34% significant PCa) and 36% in sysPbx (n = 223; 27% significant PCa). Nine percentage of significant PCa were detected by sysPbx alone. A total of 1,162 lesions were investigated. The detection rate of significant PCa in lesions with PI-RADS 2, 3, 4, and 5 were 9% (18/206), 12% (56/450), 27% (98/358), and 61% (90/148) respectively. maxPI-RADS ≥4 was the strongest predictor for the detection of significant PCa in comPbx (OR 2.77; 95% CI 1.81-4.24; p < 0.005). Conclusions: maxPI-RADS is the strongest predictor for the detection of significant PCa in comPbx. Due to a high detection rate of additional significant PCa in sysPbx, fusPbx should still be combined with sysPbx.