Evaluating the performance of PI-RADS v2 in the non-academic setting

To evaluate the utility of PI-RADS v2 to diagnose clinically significant prostate cancer (CS-PCa) with magnetic resonance ultrasound (MR/US) fusion-guided prostate biopsies in the non-academic setting.

Retrospective analysis of men whom underwent prostate multiparametric MRI and subsequent MR/US fusion biopsies at a single non-academic center from 11/2014 to 3/2016. Prostate MRIs were performed on a 3-Tesla scanner with a surface body coil. The Prostate Imaging Reporting and Data System (PI-RADS) v2 scoring algorithm was utilized and MR/US fusion biopsies were performed in selected cases. Mixed effect logistic regression analyses and receiver-operating characteristic (ROC) curves were performed on PI-RADS v2 alone and combined with PSA density (PSAD) to predict CS-PCa.

170 patients underwent prostate MRI with 282 PI-RADS lesions. MR/US fusion diagnosed 71 CS-PCa, 33 Gleason score 3+3, and 168 negative. PI-RADS v2 score is a statistically significant predictor of CS-PCa (P < 0.001). For each one-point increase in the overall PI-RADS v2 score, the odds of having CS-PCa increases by 4.2 (95% CI 2.2-8.3). The area under the ROC curve for PI-RADS v2 is 0.69 (95% CI 0.63-0.76) and for PI-RADS v2 + PSAD is 0.76 (95% CI 0.69-0.82), statistically higher than PI-RADS v2 alone (P < 0.001). The rate of CS-PCa was about twice higher in men with high PSAD (≥0.15) compared to men with low PSAD (<0.15) when a PI-RADS 4 or 5 lesion was detected (P = 0.005).

PI-RADS v2 is a strong predictor of CS-PCa in the non-academic setting and can be further strengthened when utilized with PSA density.

Abdominal radiology (New York). 2017 Apr 27 [Epub ahead of print]

Eric J Jordan, Charles Fiske, Ronald J Zagoria, Antonio C Westphalen

Department of Radiology & Biomedical Imaging, University of California San Francisco, 505 Parnasssus Ave. M-391, San Francisco, CA, 94143, USA., RadNet Medical Imaging, Walnut Creek, CA, USA., Department of Radiology & Biomedical Imaging, University of California San Francisco, 505 Parnasssus Ave. M-391, San Francisco, CA, 94143, USA. .