Prostate Imaging Reporting And Data System V2 Score Research Articles

Establishing a novel prediction model for improving the positive rate of prostate biopsy.

BackgroundAt present, prostate-specific antigen (PSA) is the primary evaluation index for judging the necessity of prostate cancer (PCa) biopsy. However, there is a high false-positive rate and a low predictive value due to many interference factors. In this study, we tried to find a novel prediction model that could improve the positive rate of prostate biopsy and reduce unnecessary biopsy.MethodsWe retrospectively studied 237 patients, including their age, body mass index (BMI), PSA, prostate volume (PV), prostate imaging-reporting and data system (PI-RADS) v2 score, neutrophil-lymphocyte ratio (NLR), biopsy Gleason score (BGS), and other information. The univariate and multivariate logistic analyses were used to screen out indicators related to PCa. After establishing a prediction formula model, we used receiver operating characteristic (ROC) curves to assess its prediction performance.ResultsOur study found that age, PSA, PI-RADS v2 score, and diabetes significantly correlated with PCa. Based on multivariate logistic regression analysis results, we created the following prediction formula: Y = 2.599 × PI-RADS v2 score + 1.766 × diabetes + 0.052 × age + 1.005 × PSAD – 9.119. ROC curves showed the formula’s threshold was 0.3543. The composite formula had an excellent capacity to detect PCa with the area under the curve (AUC) of 0.91. In addition, the composite formula also achieved significantly better sensitivity, specificity, and diagnostic accuracy than PSA, PSA density (PSAD), and PI-RADS v2 score alone.ConclusionsOur predictive formula predicted performance better than PSA, PSAD, and PI-RADS v2 score. It can thus contribute to the diagnosis of PCa and be used as an indicator for prostate biopsy, thereby reducing unnecessary biopsy.

Detection of prostate cancer using prostate imaging reporting and data system score and prostate-specific antigen density in biopsy-naive and prior biopsy-negative patients.

BackgroundFew studies report on indications for prostate biopsy using Prostate Imaging–Reporting and Data System (PI-RADS) score and prostate-specific antigen density (PSAD). No study to date has included biopsy-naïve and prior biopsy-negative patients. Therefore, we evaluated the predictive values of the PI-RADS, version 2 (v2) score combined with PSAD to decrease unnecessary biopsies in biopsy-naïve and prior biopsy-negative patients.Materials and methodsA total of 1,098 patients who underwent multiparametric magnetic resonance imaging at our hospital before a prostate biopsy and who underwent their second prostate biopsy with an initial benign negative prostatic biopsy were included. We found factors associated with clinically significant prostate cancer (csPca). We assessed negative predictive values by stratifying biopsy outcomes by prior biopsy history and PI-RADS score combined with PSAD.ResultsThe median age was 65 years (interquartile range: 59-70), and the median PSA was 5.1 ng/mL (interquartile range: 3.8-7.1). Multivariate logistic regression analysis revealed that age, prostate volume, PSAD, and PI-RADS score were independent predictors of csPca. In a biopsy-naïve group, 4% with PI-RADS score 1 or 2 had csPca; in a prior biopsy-negative group, 3% with PI-RADS score 1 or 2 had csPca. The csPca detection rate was 2.0% for PSA density <0.15 ng/mL/mL and 4.0% for PSA density 0.15-0.3 ng/mL/mL among patients with PI-RADS score 3 in a biopsy-naïve group. The csPca detection rate was 1.8% for PSA density <0.15 ng/mL/mL and 0.15-0.3 ng/mL/mL among patients with PI-RADS score 3 in a prior biopsy-negative group.ConclusionPatients with PI-RADS v2 score ≤2, regardless of PSA density, may avoid unnecessary biopsy. Patients with PI-RADS score 3 may avoid unnecessary biopsy through PSA density results.

PI-RADS v2 and periprostatic fat measured on multiparametric magnetic resonance imaging can predict upgrading in radical prostatectomy pathology amongst patients with biopsy Gleason score 3 + 3 prostate cancer

Purpose: An underestimated biopsy Gleason score 3 + 3 can result in unfounded optimism amongst patients and cause physicians to miss the window for prostate cancer (PCa) cure. This study aims to evaluate the effectiveness of Prostate Imaging Reporting and Data System (PI-RADS) version 2 as well as periprostatic fat (PPF) measured on multiparametric magnetic resonance imaging (mp-MRI) at predicting pathological upgrading amongst patients with biopsy Gleason score 3 + 3 disease.Patients and methods: A retrospective analysis of 56 patients with biopsy Gleason score 6 PCa who underwent prebiopsy mp-MRI and radical prostatectomy (RP) between November 2013 and March 2018 was conducted. Two radiologists performed PI-RADS v2 score evaluation and different fat measurements on mp-MRI. The associations amongst clinical information, PI-RADS v2 score, different fat parameters and pathologic findings were analyzed. A nomogram predicting upgrading was established based on the results of logistic regression analysis.Results: A total of 38 (67.9%) patients were upgraded to Gleason ≥7 disease on RP specimens. Prostate-specific antigen density (PSAD) (p < .001), positive core (p < .001), single-core positivity (p = .039), PI-RADS score (p < .001), front PPF area (p = .007) and front-to-total ratio (the ratio of front PPF area to total contour area) (p < .001) were risk factors for upgrading. On multivariate analysis, Epstein criteria (p = .02), PI-RADS score >3 (p = .024), and front-to-total ratio (p = .006) were independent risk factors for pathologic upgrading. The AUC value of the nomogram was 0.893 (95% CI, 0.787–0.999).Conclusion: The combination of PI-RADS v2 and periprostatic fat measured on mp-MRI can help predict pathologic upgrading amongst patients with biopsy Gleason score 3 + 3 PCa.

Prognostic Significance for Long-Term Outcomes Following Radical Prostatectomy in Men with Prostate Cancer: Evaluation with Prostate Imaging Reporting and Data System Version 2.

ObjectiveTo retrospectively determine whether the use of the Prostate Imaging Reporting and Data System (PI-RADS) version 2 (v2) helps predict long-term outcomes for prostate cancer (PCa) patients following radical prostatectomy (RP).Materials and MethodsA total of 166 patients with localized PCa evaluated with multiparametric magnetic resonance imaging (mpMRI) at 3T before RP were enrolled. Three groups were created based on PI-RADS v2 score used to predict clinical outcomes: group A, ≥ 3; group B, ≥ 4; group C, 5. We calculated biochemical recurrence-free survival (RFS) and progression-free survival (PFS). Cox proportion hazards models were used to identify variables predictive of biochemical recurrence and disease progression.ResultsDuring a median follow-up of 9.1 years, biochemical recurrence occurred in 67 patients (40.4%) and disease progression occurred in 55 patients (33.1%). In all groups, 10-year RFS and 10-year PFS were significantly lower for PI-RADS scores ≥ 3, ≥ 4 and 5 than for score < 3, < 4 and < 5 (p <0.05), respectively. In multivariate analysis, PI-RADS score ≥ 3 and score 5 were significant independent risk marker for biochemical recurrence (hazard ratio [HR] = 5.58, p = 0.018; HR = 1.75, p = 0.033) and disease progression (HR = 3.99, p = 0.047; HR = 2.31, p = 0.040). Moderate inter-observer agreement was seen for PI-RADS scoring.ConclusionPI-RADS v2 may be used to predict long-term outcomes following RP in PCa.

Does the Prostate Imaging-Reporting and Data System (PI-RADS) version 2 improve accuracy in reporting anterior lesions on multiparametric magnetic resonance imaging (mpMRI)?

Multiparametric MRI (mpMRI) is useful in detecting anterior prostate tumours. Due to the location of anterior tumours, they are often diagnosed with a large size and may be suspicious for extra-prostatic extension (EPE). We aim to evaluate whether PI-RADS v2 is more accurate in assessing anterior prostate lesions identified on mpMRI compared to PI-RADS v1. Patients with anterior prostate lesions diagnosed on mpMRI who proceeded to a cognitive fusion transperineal prostate biopsy were identified. Each mpMRI was blinded and read by two experienced prostate MRI radiologists and assigned a PI-RADS v1 and PI-RADS v2 score, and the presence of EPE was estimated. Correlation was made with transperineal histopathology and, where relevant, radical prostatectomy histopathology. Concordance measures between PI-RADS v1 and PI-RADS v2, and between examiners of the same PI-RADS score were calculated using a weighted kappa. Fifty-eight consecutive men were identified. Concordance between the examiners for PI-RADS v1 and for v2 showed substantial agreement (version 1: weighted kappa 0.71; version 2: weighted kappa 0.69). There was no difference in accuracy when using PI-RADS v1 or PI-RADS v2 to predict clinically significant cancer. There was poor correlation between EPE measured on mpMRI compared with EPE in radical prostatectomy histopathology. PI-RADS v2 is reproducible between radiologists but does not have improved accuracy for diagnosing anterior tumours of the prostate when compared to PI-RADS v1. Multiparametric MRI is accurate at detecting anterior tumours with a sensitivity of 86-88%.

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.

Differentiation of prostatitis and prostate cancer using the Prostate Imaging—Reporting and Data System (PI-RADS)

PurposeTo determine if prostate cancer (PCa) and prostatitis can be differentiated by using PI-RADS. Materials and methods3T MR images of 68 patients with 85 cancer suspicious lesions were analyzed. The findings were correlated with histopathology. T2w imaging (T2WI), diffusion weighted imaging (DWI), dynamic contrast enhancement (DCE), and MR-Spectroscopy (MRS) were acquired. Every lesion was given a single PI-RADS score for each parameter, as well as a sum score and a PI-RADS v2 score. Furthermore, T2-morphology, ADC-value, perfusion type, citrate/choline-level, and localization were evaluated. Results44 of 85 lesions showed PCa (51.8%), 21 chronic prostatitis (24.7%), and 20 other benign tissue such as hyperplasia or fibromuscular tissue (23.5%). The single PI-RADS score for T2WI, DWI, DCE, as well as the aggregated score including and not including MRS, and the PI-RADS v2-score were all significantly higher for PCa than for prostatitis or other tissue (p<0.001). The single PI-RADS score for MRS and the PI-RADS sum score including MRS were significantly higher for prostatitis than for other tissue (p=0.029 and p=0.020), whereas the other parameters were not different. Prostatitis usually presented borderline pathological PI-RADS scores, showed restricted diffusion with ADC≥900mm2/s in 100% of cases, was more often indistinctly hypointense on T2WI (66.7%), and localized in the transitional zone (57.1%). An ADC≥900mm2/s achieved the highest predictive value for prostatitis (AUC=0.859). ConclusionProstatitis can be differentiated from PCa using PI-RADS, since all available parameters are more distinct in cases of cancer. However, there is significant overlap between prostatitis and other benign findings, thus PI-RADS is only suitable to a limited extent for the primary assessment of prostatitis. Restricted diffusion with ADC≥900mm2/s is believed to be a good indicator for prostatitis. MRS can help to distinguish between prostatitis and other tissue.