Effects of the addition of quantitative apparent diffusion coefficient data on the diagnostic performance of the PI-RADS v2 scoring system to detect clinically significant prostate cancer.

PURPOSE: To evaluate the impact of the addition of quantitative apparent diffusion coefficient (ADC) data into the diagnostic performance of the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) scoring system to predict clinically significant prostate cancer (CSPCa). METHODS: We retrospectively included 91 consecutive patients who underwent prostate multiparametric magnetic resonance imaging (mp-MRI) and histopathological evaluation. Mp-MRI images were reported by the PI-RADSv2 scoring system and patients were divided into groups considering the likelihood of CSPCa. ADC value and ratio were obtained. Findings were correlated with histopathological data. RESULTS: CSPCa was found in 41.8% of cases (n = 38). PI-RADSv2 score 3-5 yielded a sensitivity of 97.4% (95% confidence intervals 86.5-99.5), a specificity of 50.9% (37.9-63.9), and AUC of 0.74 (0.67-0.81) to predict CSPCa. ADC value < 750 µm2/s and an ADC ratio < 0.62 were the most accurate thresholds for differentiation of CSPCa, with AUC of 0.81 and 0.76, respectively. Combined PI-RADSv2 score 3-5 and ADC value < 750 µm2/s yielded a specificity of 84.9 (72.9-92.2), sensitivity of 70.3 (54.2-82.5), and AUC of 0.77 (0.68-0.86). Combined PI-RADSv2 score 3-5 and ADC ratio < 0.62 yielded a specificity of 86.5 (74.7-93.3), sensitivity of was 64.9 (48.8-78.2), and AUC of 0.75 (0.66-0.84). CONCLUSION: Quantitative ADC data might not be beneficial to be used routinely in mp-MR imaging as criteria to detect clinically significant lesions due to the reduced sensitivity. Instead, when prostate lesions present a PI-RADSv2 score ≥ 3, additional quantitative ADC criteria can be helpful to increase the PI-RADS score specificity.

Validation of PI-RADS v.2 for prostate cancer diagnosis with MRI at 3T using an external phased-array coil.

PURPOSE: To date, few studies have validated the Prostate Imaging Reporting and Data System Version 2 (PI-RADS v. 2) for the diagnosis of prostate cancer. Our aim was to validate PI-RADS v.2 using 3 Tesla (T) MRI. MATERIALS AND METHODS: This is a retrospective study of 54 consecutive patients who underwent 3T MRI with a body-array coil for diagnostic confirmation of prostate cancer or cancer staging between June 2013 and June 2015. Sensitivity, specificity, and agreement were calculated based on a criterion of PI-RADS score = 3. Inter-examiner agreement was determined by the weighted kappa statistic. RESULTS: Histological findings were positive for cancer in 33 patients and negative in 21 patients. Considering a PI-RADS score of 3 as positive for cancer, the accuracy of each reader was 85.20% and 70.40%, respectively, and agreement coefficients were κ = 0.69 and κ = 0.35. Considering PI-RADS 3 as absence of cancer, the accuracy of each reader was 77.80% and 77.80%, respectively, and agreement was κ = 0.55 and κ = 0.54. Inter-reader agreement was moderate/good (weighted κ = 0.53; 95% confidence interval: 0.39-0.66; P = 0.038). CONCLUSION: High accuracy was obtained for the diagnosis of prostate cancer using 3T MRI with a body coil and the PI-RADS v.2 score. J. Magn. Reson. Imaging 2016;44:1354-1359.