Prostate Imaging Reporting And Data System Version 2 Score Research Articles

Performance of a Region of Interest–based Algorithm in Diagnosing International Society of Urological Pathology Grade Group ≥2 Prostate Cancer on the MRI-FIRST Database—CAD-FIRST Study

Background and objectiveProstate multiparametric magnetic resonance imaging (MRI) shows high sensitivity for International Society of Urological Pathology grade group (GG) ≥2 cancers. Many artificial intelligence algorithms have shown promising results in diagnosing clinically significant prostate cancer on MRI. To assess a region-of-interest–based machine-learning algorithm aimed at characterising International Society of Urological Pathology GG ≥2 prostate cancer on multiparametric MRI. MethodsThe lesions targeted at biopsy in the MRI-FIRST dataset were retrospectively delineated and assessed using a previously developed algorithm. The Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) score assigned prospectively before biopsy and the algorithm score calculated retrospectively in the regions of interest were compared for diagnosing GG ≥2 cancer, using the areas under the curve (AUCs), and sensitivities and specificities calculated with predefined thresholds (PIRADSv2 scores ≥3 and ≥4; algorithm scores yielding 90% sensitivity in the training database). Ten predefined biopsy strategies were assessed retrospectively. Key findings and limitationsAfter excluding 19 patients, we analysed 232 patients imaged on 16 different scanners; 85 had GG ≥2 cancer at biopsy. At patient level, AUCs of the algorithm and PI-RADSv2 were 77% (95% confidence interval [CI]: 70–82) and 80% (CI: 74–85; p = 0.36), respectively. The algorithm’s sensitivity and specificity were 86% (CI: 76–93) and 65% (CI: 54–73), respectively. PI-RADSv2 sensitivities and specificities were 95% (CI: 89–100) and 38% (CI: 26–47), and 89% (CI: 79–96) and 47% (CI: 35–57) for thresholds of ≥3 and ≥4, respectively. Using the PI-RADSv2 score to trigger a biopsy would have avoided 26–34% of biopsies while missing 5–11% of GG ≥2 cancers. Combining prostate-specific antigen density, the PI-RADSv2 and algorithm’s scores would have avoided 44–47% of biopsies while missing 6–9% of GG ≥2 cancers. Limitations include the retrospective nature of the study and a lack of PI-RADS version 2.1 assessment. Conclusions and clinical implicationsThe algorithm provided robust results in the multicentre multiscanner MRI-FIRST database and could help select patients for biopsy. Patient summaryAn artificial intelligence–based algorithm aimed at diagnosing aggressive cancers on prostate magnetic resonance imaging showed results similar to expert human assessment in a prospectively acquired multicentre test database.

The Impact of Multiparametric Magnetic Resonance Imaging on Treatment Strategies for Incidental Prostate Cancer after Holmium Laser Enucleation of the Prostate.

To investigate the impact of multiparametric magnetic resonance imaging (mpMRI) on treatment strategies for incidental prostate cancer (iPCa) after holmium enucleation of the prostate (HoLEP); Methods: Data from 1781 men who underwent HoLEP for clinical bladder outlet obstruction between September 2009 and March 2022 were reviewed retrospectively. Among patients with confirmed iPCa, those with prostate-specific antigen (PSA) levels < 10 ng/mL and who underwent mpMRI 3 months after HoLEP were included. Pathologic results, including Gleason grade (GG) and tumor volume, were identified. mpMRI was interpreted using the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2). Treatment strategies for iPCa according to GG alone, or according to a combination of Gleason grade and mpMRI, were analyzed and compared. Of 1764 men with serum PSA levels < 10 ng/mL, iPCa was confirmed in 64 (3.6%) after HoLEP. Of the 62 men who underwent mpMRI, the median (IQR) age at the time of HoLEP was 72.5 (66.5-78.0) years. The median PSA level and prostate volume were 3.49 (1.82-5.03) ng/mL and 49.6 (38.5-85.4) cm3, respectively. The pathologic results of iPCa were as follows: GG1 = 42 (67.7%), GG2 = 13 (21.0%), GG3 = 2 (3.2%), GG4 = 1 (1.6%), and GG5 = 4 (6.5%). Of the patients with GG1 and GG2, 78.6% (33/42) and 53.8% (7/13), respectively, underwent active surveillance (AS). However, of 42 patients with GG1, 27 (64.3%) had a PI-RADSv2 score of 2, and 24 (88.9%) of them underwent AS. Of the 13 patients with GG2, 4 (80%) with a PI-RADSv2 score of 2 underwent AS. All patients with GG 3-5 were clinically expected to have locally advanced PCa and be treated with radiotherapy and/or ADT. For patients with iPCa of GG 1-2 after HoLEP, mpMRI helps to establish a treatment strategy by allowing risk stratification to select those who should be considered for AS or active treatment.

Characterization of high-grade prostate cancer at multiparametric MRI using a radiomic-based computer-aided diagnosis system as standalone and second reader

PurposeThe purpose of this study was to develop and test across various scanners a zone-specific region-of-interest (ROI)-based computer-aided diagnosis system (CAD) aimed at characterizing, on MRI, International Society of Urological Pathology (ISUP) grade≥2 prostate cancers. Materials and methodsROI-based quantitative models were selected in multi-vendor training (265 pre-prostatectomy MRIs) and pre-test (112 pre-biopsy MRIs) datasets. The best peripheral and transition zone models were combined and retrospectively assessed in internal (158 pre-biopsy MRIs) and external (104 pre-biopsy MRIs) test datasets. Two radiologists (R1/R2) retrospectively delineated the lesions targeted at biopsy in test datasets. The CAD area under the receiver operating characteristic curve (AUC) for characterizing ISUP≥2 cancers was compared to that of the Prostate Imaging-Reporting and Data System version2 (PI-RADSv2) score prospectively assigned to targeted lesions. ResultsThe best models used the 25th apparent diffusion coefficient (ADC) percentile in transition zone and the 2nd ADC percentile and normalized wash-in rate in peripheral zone. The PI-RADSv2 AUCs were 82% (95% confidence interval [CI]: 74–87) and 86% (95% CI: 81–91) in the internal and external test datasets respectively. They were not different from the CAD AUCs obtained with R1 and R2 delineations, in the internal (82% [95% CI: 76–89], P = 0.95 and 85% [95% CI: 78–91], P = 0.55) and external (82% [95% CI: 74–91], P = 0.41 and 86% [95% CI:78–95], P = 0.98) test datasets. The CAD yielded sensitivities of 86–89% and 90–91%, and specificities of 64–65% and 69–75% in the internal and external test datasets respectively. ConclusionThe CAD performance for characterizing ISUP grade≥2 prostate cancers on MRI is not different from that of PI-RADSv2 score across two test datasets.

An independent practice validation of the Prostate Imaging Reporting and Data System version 2 scoring system and the introduction of PDP (prostate-specific antigen density × PI-RADSv2) score to assist with further risk assessment.

To provide concise information to clinicians on how to better interpret multiparametric magnetic resonance imaging for prostate cancer risk stratification. We analyzed 2 separate cohorts. For patients receiving a Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) score of 1 or 2, we reviewed the charts of 226 patients who underwent multiparametric magnetic resonance imaging of the prostate ordered from 2015 to 2017 to determine who developed clinically significant prostate cancer (csPCa) by August 27, 2020. For patients receiving PI-RADSv2 a score of 3, 4, or 5, we reviewed the results of 733 fusion biopsies on solitary lesions. Statistical analysis was used to further determine risk factors for csPCa. Ten percent of men with PI-RADSv2 a score of 1 eventually developed csPCa. Seven percent with a score of 2 were eventually diagnosed with csPCa. Only 1 of 226 with a score of 1 or 2 developed metastasis. For PI-RADSv2 scores of 3, 4, and 5, csPCa was detected in 16%, 45%, and 67% of fusion biopsies. Peripheral zone (PZ) PI-RADSv2 score of 4 or 5 and prostate-specific antigen density (PSA-D) were significant predictors of csPCa on multivariable analysis. Using a PSA-D × PI-RADSv2 score of ≤0.39, we identified 38% of men with a PI-RADSv2 score of 3 in the PZ or 3, 4, or 5 in the transition zone who could have avoided a benign biopsy. The vast majority of patients with PI-RADSv2 scores 1 and 2 can be safely monitored with close surveillance. Lesions with PI-RADSv2 scores of 4 and 5 in the PZ should be biopsied. Peripheral zone lesions with a PI-RADSv2 score of 3 and transition zone lesions with 3, 4, or 5 can be risk-stratified using the PSA-D × PI-RADSv2 score to determine who may safely avoid a biopsy and who should proceed to fusion biopsy.

Influence of the Location and Zone of Tumor in Prostate Cancer Detection and Localization on 3-T Multiparametric MRI Based on PI-RADS Version 2.

OBJECTIVE. The objective of our study was to determine the performance of 3-T multiparametric MRI (mpMRI) for prostate cancer (PCa) detection and localization, stratified by anatomic zone and level, using Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) and whole-mount histopathology (WMHP) as reference. MATERIALS AND METHODS. Multiparametric MRI examinations of 415 consecutive men were compared with thin-section WMHP results. A genitourinary radiologist and pathologist collectively determined concordance. Two radiologists assigned PI-RADSv2 scores and sector location to all detected foci by consensus. Tumor detection rates were calculated for clinical and pathologic (tumor location and zone) variables. Both rigid and adjusted sector-matching models were used to account for fixation-related issues. RESULTS. Of 863 PCa foci in 16,185 prostate sectors, the detection of overall and index PCa lesions in the midgland, base, and apex was 54.9% and 83.1%, 42.1% and 64.0% (p = 0.04, p = 0.02), and 41.9% and 71.4% (p = 0.001, p = 0.006), respectively. Tumor localization sensitivity was highest in the midgland compared with the base and apex using an adjusted match compared with a rigid match (index lesions, 71.3% vs 43.7%; all lesions, 70.8% vs 36.0%) and was greater in the peripheral zone (PZ) than in the transition zone. Three-Tesla mpMRI had similarly high specificity (range, 93.8-98.3%) for overall and index tumor localization when using both rigid and adjusted sector-matching approaches. CONCLUSION. For 3-T mpMRI, the highest sensitivity (83.1%) for detection of index PCa lesions was in the midgland, with 98.3% specificity. Multiparametric MRI performance for sectoral localization of PCa within the prostate was moderate and was best for index lesions in the PZ using an adjusted model.

Preoperative PI-RADS Version 2 scores helps improve accuracy of clinical nomograms for predicting pelvic lymph node metastasis at radical prostatectomy.

Lymph node invasion (LNI) is a strong adverse prognostic factor in prostate cancer (PCa). The purpose of this study was to evaluate the role of Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) scores for estimating the risk of LN metastasis. The study also aimed to investigate the additional value of PI-RADSv2 scores when used in combination with clinical nomograms for the prediction of LNI in patients with PCa. We retrospectively identified 308 patients who underwent multiparametric magnetic resonance imaging (mpMRI) and RP with pelvic lymph node dissection (PLND). Clinicopathological parameters and PI-RADSv2 scores were assessed. Univariate and multivariate logistic analyses were performed. The area under the receiver operating characteristic curves (AUCs) and decision curve analysis (DCA) were generated for assessing the incremental value of PI-RADSv2 scores combined with the Briganti and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms. Overall, 20 (6.5%) patients had LNI. At univariate analysis, all clinicopathological characteristics and PI-RADSv2 scores were significantly associated to LNI (p < 0.04). However, multivariate analysis revealed that only PI-RADSv2 scores and percentage of positive cores were independently significant (p ≤ 0.006). The PI-RADSv2 score was the most accurate predictor (AUC, 80.2%). The threshold of PI-RADSv2 score was 5, which provided high sensitivity (18/20, 90.0%) and negative predictive value (203/205, 99.0%). When PI-RADSv2 scores were combined with Briganti and MSKCC nomograms, the AUC value increased from 75.1 to 86.3% and from 79.2 to 87.9%, respectively (p ≤ 0.001). The DCA also demonstrated that the two nomograms plus PI-RADSv2 scores improved clinical risk prediction of LNI. The patients with a PI-RADSv2 score <5 were associated with a very low risk of LNI in PCa. Preoperative PI-RADSv2 scores could help improve the accuracy of clinical nomograms for predicting pelvic LN metastasis at radical prostatectomy.

Computer-aided diagnosis system for characterizing ISUP grade ≥ 2 prostate cancers at multiparametric MRI: A cross-vendor evaluation

PurposeTo assess the performance of a computer-aided diagnosis (CADx) system trained at characterizing International Society of Urological Pathology (ISUP) grade≥2 peripheral zone (PZ) prostate cancers on multiparametric magnetic resonance imaging (mpMRI) examinations from a different institution and acquired on different scanners than those used for the training database. Patients and methodsPreoperative mpMRIs of 74 men (median age, 65.7 years) treated by prostatectomy between 2014 and 2017 were retrospectively selected. One radiologist outlined suspicious lesions and scored them using Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2); their CADx score was calculated using a classifier trained on an independent database of 106 patients treated by prostatectomy in another institution. The lesions’ nature was assessed by comparison with prostatectomy whole-mounts. Diagnostic accuracy was estimated with areas under receiver operating characteristic curves (AUCs). Sensitivity and specificity were calculated using a CADx threshold (≥0.21) that yielded 95% sensitivity in the training database, and a PI-RADSv2≥3 threshold. ResultsA total of 127 lesions (PZ, n=104; transition zone [TZ], n=23) were described. In PZ, CADx and PI-RADSv2 scores had similar AUCs for characterizing ISUP grade≥2 cancers (0.78 [95% confidence interval (CI): 0.69–0.87] vs. 0.74 [95%CI: 0.62–0.82], respectively) (P=0.59). Sensitivity and specificity were respectively 89% (95%CI: 82–97%) and 42% (95%CI: 26–58%) for the CADx score, and 97% (95%CI: 93–100%) and 37% (95%CI: 22–52%) for the PI-RADSv2 score. In TZ, both scores showed poor specificity. ConclusionIn this external cohort, the CADx and PI-RADSv2 scores showed similar performances in characterizing ISUP grade≥2 cancers.

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.

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). 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. 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 < 750µm2/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 < 750µm2/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). 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.

Dynamic Contrast-Enhanced MRI-Upgraded Prostate Imaging Reporting and Data System Version 2 Category 3 Peripheral Zone Observations Stratified by a Size Threshold of 15 mm.

OBJECTIVE. The purpose of this study is to evaluate dynamic contrast-enhanced (DCE) MRI (DCE-MRI)-upgraded Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) peripheral zone (PZ) observations stratified by a size threshold of 15 mm. MATERIALS AND METHODS. Two blinded radiologists independently assessed 301 patients with 326 clinically significant tumors (Gleason score [GS] ≥ 7) using multiparametric MRI performed before radical prostatectomy (RP) between 2012 and 2017 and then assigned PI-RADSv2 scores for the tumors. PI-RADSv2 category 3 PZ observations upgraded on the basis of abnormal DCE-MRI findings were tabulated, agreement was calculated, and discrepancies were resolved by consensus. The rate of detection of clinically significant cancer among upgraded observations was calculated. Size was measured at consensus review and was compared with pathologic outcomes on the basis of the PI-RADSv2 size threshold of 15 mm or more, with the use of chi-square tests. RESULTS. Reader 1 identified 5.2% (17/326) of DCE-MRI-upgraded PZ observations, and reader 2 identified 8.3% (27/326) of such observations. Interobserver agreement for PI-RADSv2 scoring was moderate (κ = 0.42) overall, but it was fair (κ = 0.23) when only DCE-MRI-upgraded observations were considered. Of the upgraded observations, which had a mean (± SD) size of 14 ± 6 mm (range, 6-29 mm), 10.4% (34/326) were agreed on after consensus review. Size smaller than 15 mm was noted for 61.8% (21/34) of observations. Among DCE-MRI-upgraded PZ observations, true- and false-positive detection rates for significant cancer were 91.2% (31/34) and 8.8% (3/34), respectively. Observations 15 mm or larger had no false-positive diagnoses and higher rates of extraprostatic extension (84.6% [11/13] vs 38.1% [8/21]; p = 0.016); however, there was no difference in GS (p = 0.354) compared with observations less than 15 mm in size. CONCLUSION. PZ observations upgraded on the basis of abnormal DCE-MRI findings have a high likelihood of being clinically significant cancer; however, agreement between readers was low. DCE-MRI-upgraded tumors of 15 mm or larger had no false-positive diagnoses and higher rates of extraprostatic extension, suggesting that they could be assigned to PI-RADSv2 assessment category 5.

A Systematic Review of the Existing Prostate Imaging Reporting and Data System Version 2 (PI-RADSv2) Literature and Subset Meta-Analysis of PI-RADSv2 Categories Stratified by Gleason Scores.

The objective of this study was to quantitatively and qualitatively assess the methodologic heterogeneity of the current Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) literature and estimate the proportions of Gleason scores (GSs) diagnosed across PI-RADSv2 categories. This study was a systematic review and meta-analysis and was performed in concordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Only English-language studies and studies published before April 1, 2018, were assessed. The primary outcome of the meta-analysis was the estimated percentage of patients with GS ≥ 3 + 4 within each individual PI-RADSv2 score. We calculated the pooled estimates and 95% CIs on the basis of a random-effects model using the meta-analysis routine of Stata (version 13.1). Our search revealed 434 titles, and 59 of these studies were selected. These studies were remarkable for their technical and terminological diverseness. Thirteen studies had sufficient data to be included in the meta-analysis. The prevalence of ≥ GS 3 + 4 in lesions assigned a PI-RADSv2 score of 3 or higher was approximately 45%. Lesions assigned PI-RADSv2 scores 1 or 2, 3, 4, and 5 represented high-grade disease in approximately 6%, 12%, 48%, and 72% of patients. The data available in the literature are highly heterogeneous and challenging to analyze because of variations in terminology, patient cohort selection, criteria, imaging parameters, and reference standards. In spite of this heterogeneity, our meta-analysis shows that PI-RADSv2 has good sensitivity when a score of ≥ 3 is considered as a positive test.

Intra- and interreader reproducibility of PI-RADSv2: A multireader study.

The Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) has been in use since 2015; while interreader reproducibility has been studied, there has been a paucity of studies investigating the intrareader reproducibility of PI-RADSv2. To evaluate both intra- and interreader reproducibility of PI-RADSv2 in the assessment of intraprostatic lesions using multiparametric magnetic resonance imaging (mpMRI). Retrospective. In all, 102 consecutive biopsy-naïve patients who underwent prostate MRI and subsequent MR/transrectal ultrasonography (MR/TRUS)-guided biopsy. Prostate mpMRI at 3T using endorectal with phased array surface coils (TW MRI, DW MRI with ADC maps and b2000 DW MRI, DCE MRI). Previously detected and biopsied lesions were scored by four readers from four different institutions using PI-RADSv2. Readers scored lesions during two readout rounds with a 4-week washout period. Kappa (κ) statistics and specific agreement (Po ) were calculated to quantify intra- and interreader reproducibility of PI-RADSv2 scoring. Lesion measurement agreement was calculated using the intraclass correlation coefficient (ICC). Overall intrareader reproducibility was moderate to substantial (κ = 0.43-0.67, Po = 0.60-0.77), while overall interreader reproducibility was poor to moderate (κ = 0.24, Po = 46). Readers with more experience showed greater interreader reproducibility than readers with intermediate experience in the whole prostate (P = 0.026) and peripheral zone (P = 0.002). Sequence-specific interreader agreement for all readers was similar to the overall PI-RADSv2 score, with κ = 0.24, 0.24, and 0.23 and Po = 0.47, 0.44, and 0.54 in T2 -weighted, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE), respectively. Overall intrareader and interreader ICC for lesion measurement was 0.82 and 0.71, respectively. PI-RADSv2 provides moderate intrareader reproducibility, poor interreader reproducibility, and moderate interreader lesion measurement reproducibility. These findings suggest a need for more standardized reader training in prostate MRI. 2 Technical Efficacy: Stage 2.

Prostate Cancer Genomic Classifier Relates More Strongly to Gleason Grade Group Than Prostate Imaging Reporting and Data System Score in Multiparametric Prostate Magnetic Resonance Imaging-ultrasound Fusion Targeted Biopsies

ObjectiveTo assess the association between Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) score, the Decipher score, and histologic grade of carcinoma in biopsy tissue among low- to intermediate-risk prostate cancer patients. MethodsMRI-ultrasound targeted biopsy of regions of interest and concurrent 12-core systematic biopsy was performed on men with Gleason grade group (GG) 1 and 2. We compared Decipher score with PI-RADS scores and biopsy Gleason GG. Subgroup analyses were performed to evaluate patients who underwent radical prostatectomy (RP), and men with Decipher testing from a targeted biopsy core. ResultsOne hundred two patients with GG1 and GG2 had biopsy Decipher testing. There was no significant difference in the median Decipher scores among the 3 multiparametric magnetic resonance imaging categories. Patients with GG2 vs GG1 in the setting of PI-RADS 4-5 had higher genomic scores (P = .01), but no significant difference was noted in patients with PI-RADS ≤3. The rate of genomic higher-risk disease on a targeted biopsy from PI-RADS5 was higher in GG2 (75%) vs GG1 (11.1%; P = .01). On multivariable logistic regression analysis, the Decipher score ≥0.45, (odds ratio (OR) 2.71; P = .02), and age (OR 1.11; P = .004) remained significant factors associated with Gleason GG2 on biopsy. ConclusionHigh-risk genomic classification can be seen across all combinations of PI-RADS categories and Gleason GG1 and GG2, confirming a potential utility for Decipher testing in men with low- to favorable intermediate-risk prostate cancer. The Decipher biopsy genomic test related to Gleason GG independent of PI-RADSv2 score. Confirmatory genomic testing for patients undergoing active surveillance appears more valuable than PI-RADSv2 score.

Genomic Prostate Score, PI-RADSv2, and Progression in Men with Prostate Cancer on Active Surveillance

PurposeOncotypeDx Genomic Prostate Score (GPS) is a 17-gene RNA expression assay intended to help guide treatment decisions for men diagnosed with prostate cancer. The Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2) was developed to standardize the risk stratification of lesions identified on multiparametric prostate MRI. We sought to determine whether these tests are associated with increased risk of biopsy upgrade in men on active surveillance (AS). Materials and MethodsAll AS patients at University of California San Francisco (UCSF) were identified who had low/intermediate-risk PCa (PSA≤20, clinical stage T1/T2), Gleason Score (GS) 6 disease, underwent multiple biopsies, and had a GPS, mpMRI with PI-RADSv2 score, or both. The primary outcome was biopsy upgrade (an increase in GS from 3+3 to ≥ 3+4) analyzed by Cox proportional hazards regression. Results140 men had only a GPS test, 169 men had only PI-RADSv2 score, and 131 men had both tests. Each 5-unit increase in GPS was associated with increased risk of biopsy upgrade (Hazard ratio [HR]: 1.28; 95% confidence interval [CI]: [1.19, 1.39]; p<0.01). PI-RADS 5 vs. 1-2 (HR: 4.38; CI: [2.36, 8.16]; p<0.01) and 4 vs. PI-RADS 1-2 (HR: 2.62; CI [1.45, 4.76]; p<0.01) were also associated with increased risk of biopsy upgrade. In a sub-analysis of patients with both GPS and PI-RADSv2 scores, GPS was associated with biopsy upgrade, adding value to clinical covariates (partial likelihood ratio p=0.01). ConclusionsA higher GPS or PI-RADSv2 score of 4 or 5 is associated with increased risk of biopsy upgrade.

Is Prostate Imaging Reporting and Data System Version 2 Sufficiently Discovering Clinically Significant Prostate Cancer? Per-Lesion Radiology-Pathology Correlation Study.

The objective of our study was to evaluate the performance of multiparametric MRI with Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) for detecting prostate cancer (PCA) and clinically significant PCA through this per-lesion one-to-one correlation study between pathologically proven lesions and MRI-visible lesions. A total of 93 PCA lesions from 44 patients who underwent radical prostatectomy were included in this retrospective study. Two radiologists scored every visible lesion with a PI-RADSv2 score of 3, 4, or 5 in each patient's multiparametric MRI examination using PI-RADSv2. A per-lesion one-to-one correlation between MRI-visible lesions and pathologically confirmed PCA lesions was conducted during regular radiology-pathology meetings at our center. The detection rates of clinically significant PCA and the proportions of clinically significant PCAs from MRI-visible and MRI-invisible PCAs were calculated. The performance of PI-RADSv2 for detecting clinically significant PCA was evaluated using the positive predictive value (PPV), negative predictive value (NPV), and area under the ROC curve (AUC) value. Using a PI-RADSv2 score of 3, 4, or 5 as an MRI-visible lesion, 46.88% of clinically significant PCA lesions were detected. The PPV, NPV, and AUC were 96.77%, 45.16%, and 0.72, respectively. Tumor volume and secondary Gleason grade showed a statistically significant difference between MRI-visible and MRI-invisible clinically significant PCAs. Multiparametric MRI with PI-RADSv2 missed a considerable number of clinically significant PCA lesions in this per-lesion analysis, causing a relatively low NPV and diagnostic performance compared with previous per-patient studies. However, the high PPV indicates that multiparametric MRI with PI-RADSv2 may be useful for follow-up of active surveillance and planning focal therapy.

Role of PI-RADS Version 2 for Prediction of Upgrading in Biopsy-Proven Prostate Cancer With Gleason Score 6

The objective of this study was to investigate the effect of Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) on prediction of postoperative Gleason score (GS) upgrading for patients with biopsy GS 6 prostate cancer. We retrospectively reviewed 443 patients who underwent magnetic resonance imaging (MRI) and radical prostatectomy for biopsy-proven GS 6 prostate cancer between January 2011 and December 2013. Preoperative clinical variables and pathologic GS were examined, and all MRI findings were assessed with PI-RADSv2. Receiver operating characteristic curves were used to compare predictive accuracies of multivariate logistic regression models with or without PI-RADSv2. Of the total 443 patients, 297 (67.0%) experienced GS upgrading postoperatively. PI-RADSv2 scores 1 to 3 and 4 to 5 were identified in 157 (25.4%) and 286 (64.6%) patients, respectively, and the rate of GS upgrading was 54.1% and 74.1%, respectively (P< .001). In multivariate analysis, prostate-specific antigen density > 0.16 ng/mL2, number of positive cores≥ 2, maximum percentage ofcancer per core > 20, and PI-RADSv2 score 4 to 5 were independent predictors influencing GS upgrading (each P<.05). When predictive accuracies of multivariate models with or without PI-RADSv2 were compared, the model including PI-RADSv2 was shown to have significantly higher accuracy (area under the curve, 0.729 vs. 0.703; P=.041). Use of PI-RADSv2 is an independent predictor of postoperative GS upgrading and increases the predictive accuracy of GS upgrading. PI-RADSv2 might be used as a preoperative imaging tool to determine risk classification and to help counsel patients with regard to treatment decision and prognosis of disease.

PI-RADSv2 Score &amp;lt; 5 Associates with a Very Low Risk of Pelvic Lymph Node Invasion in Prostate Cancer, Even Among High-Risk Population

Purpose: To evaluate the role of Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) scores for estimating the risk of lymph node invasion (LNI) in prostate cancer (PCa). Materials and Methods: We retrospectively identified 308 patients who underwent multiparametric magnetic resonance imaging (mpMRI) and RP with pelvic lymph node dissection (PLND). Univariate and multivariate logistic analyses were performed. The area under the receiver operating characteristic curves (AUC) and decision curve analysis (DCA) were generated for assessing the incremental value of PI-RADSv2 scores combined with the Briganti and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms. Results: Overall, 20 (6.5%) patients had LNI. According to D'Amico classification, 22 (7.1%) patients were at low, 75 (24.4%) at intermediate, 211 (68.5%) at high risk. In the multivariate analysis, PIRADSv2 scores and percentage of positive cores were independently significant predictors of LNI (p ≤ 0.006). The AUC of PI-RADSv2 score was 80.2%. The threshold of PI-RADSv2 score was 5, which provided high sensitivity (18/20, 90.0%) and negative predictive value (203/205, 99.0%). When PI-RADSv2 scores were combined with Briganti and MSKCC nomograms, the AUC value increased from 75.1% to 86.3% and from 79.2% to 87.9%, respectively (p ≤ 0.001). The DCA also demonstrated the two nomograms plus PI-RADSv2 scores improved clinical risk prediction of LNI. Conclusion: PI-RADSv2 scores alone or combined with clinical nomograms provide significant incremental value for predicting LNI in PCa. Patients with a PI-RADSv2 score < 5 were associated with a very low risk of LNI, even among a relatively high-risk population. Funding Statement: The authors state: none. Declaration of Interests: The authors declare that they have no competing interests. Ethics Approval Statement: The review board at the authors institution approved this retrospective study.

Clinical Application of Biparametric MRI Texture Analysis for Detection and Evaluation of High-Grade Prostate Cancer in Zone-Specific Regions.

The purpose of this study was to investigate the performance of biparametric MRI texture analysis (TA) in detecting and evaluating high-grade prostate cancer in zone-specific regions. A retrospective study included 184 consecutively registered biopsy-naive patients in whom prostate cancer was suspected who were undergoing multiparametric prostate MRI. MR images were scored and evaluated by two readers using the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) and biparametric MRI TA in separate sessions. Interobserver agreement on PI-RADSv2 score and textural parameters of biparametric MRI was evaluated. The logistic regression model based on TA was built for different zones of the prostate. ROC analysis was used to compare the TA-based model with other parameters alone. The correlation of each parameter with Gleason score of high-grade prostate cancer was also assessed. Reader reliability ranged from moderate to good for PI-RADSv2 (Cohen κ = 0.525-0.616) and from good to excellent for textural metrics (intraclass correlation coefficient, 0.745-0.925). Diagnostic performance was significantly improved by use of the TA-based model (transition zone AUC, 0.87; peripheral zone AUC, 0.89) in comparison with PI-RADSv2 and other texture parameters alone. For the transition zone, entropy had moderate to good correlation with the Gleason score of high-grade prostate cancer (r = 0.562, p = 0.004). In the peripheral zone, entropy (r = 0.614, p = 0.003) and inertia (r = 0.663, p = 0.002) had moderate to good correlations with Gleason score. The results of this clinical study indicate that a TA-based model that includes biparametric MRI can be used for identifying high-grade prostate cancer and that specific parameters extracted from TA may be additional tools for assessing tumor aggressiveness.

Validation of Prostate Imaging-Reporting and Data System Version 2: A Retrospective Analysis

Use of magnetic resonance imaging (MRI)/transrectal ultrasound fusion biopsies to determine the accuracy of multiparametric MRI (mpMRI), using Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2), for detecting clinically significant prostate cancer in the overall gland and specifically the peripheral zone (PZ) and transitional zone (TZ). A retrospective analysis of patients who underwent fusion biopsy identified 137 men with 231 prostate lesions was approved by the Institutional Review Board. Subjects initially classified under PI-RADSv1 criteria were regraded using PI-RADSv2 by a radiologist blinded to PI-RADSv1 score and biopsy results. Spearman correlation, chi-squared, and logistic regression analysis were performed. There was positive correlation between PI-RADSv2 and Gleason scores (P < 0.001). In the PZ, mpMRI demonstrated 100% sensitivity, 100% negative predictive value, and 35.9% positive predictive value, compared to 100%, 100%, and 27.1%, respectively, for TZ lesions. When predicting clinically significant prostate cancer, the PI-RADSv2 area under the curve for TZ lesions was 0.844 (95% CI: 0.753-0.935, P < 0.001) and 0.769 (95% CI: 0.684-0.854, P < 0.001) for PZ lesions. Combining PI-RADSv2 with additional risk factors (body mass index, prostate-specific antigen density, digital rectal examination) improved the area under curve. PI-RADSv2 achieves excellent sensitivity and negative predictive value for both PZ and TZ lesions.

Interreader Agreement of Prostate Imaging Reporting and Data System Version 2 Using an In-Bore MRI-Guided Prostate Biopsy Cohort: A Single Institution's Initial Experience.

The purpose of this study is to determine the interobserver agreement of the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) for diagnosing prostate cancer using in-bore MRI-guided prostate biopsy as the reference standard. Fifty-nine patients underwent in-bore MRI-guided prostate biopsy between January 21, 2010, and August 21, 2013, and underwent diagnostic multiparametric MRI 6 months or less before biopsy. A single index lesion per patient was selected after retrospective review of MR images. Three fellowship-trained abdominal radiologists (with 1-11 years' experience) blinded to clinical information interpreted all studies according to PI-RADSv2. Interobserver agreement was assessed using Cohen kappa statistics. Thirty-eight lesions were in the peripheral zone and 21 were in the transition zone. Cancer was diagnosed in 26 patients (44%). Overall PI-RADS scores were higher for all biopsy-positive lesions (mean ± SD, 3.9 ± 1.1) than for biopsy-negative lesions (3.1 ± 1.0; p < 0.0001) and for clinically significant lesions (4.2 ± 1.0) than for clinically insignificant lesions (3.1 ± 1.0; p < 0.0001). Overall suspicion score interobserver agreement was moderate (κ = 0.45). There was moderate interobserver agreement among overall PI-RADS scores in the peripheral zone (κ = 0.46) and fair agreement in the transition zone (κ = 0.36). PI-RADSv2 scores were higher in the biopsy-positive group. PI-RADSv2 showed moderate interobserver agreement among abdominal radiologists with no prior experience using the scoring system.

PI-RADS Version 2: Detection of Clinically Significant Cancer in Patients With Biopsy Gleason Score 6 Prostate Cancer.

The purpose of this study was to analyze the utility of the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) in the detection of a clinically significant cancers in patients with prostate cancers with a biopsy Gleason score of 6. A group of 182 consecutively registered patients with biopsy-proven prostate cancer with a Gleason score of 6 underwent MRI and radical prostatectomy. Clinically significant cancer was surgically defined as Gleason score of 7 or greater, tumor volume of 0.5 cm3 or greater, or tumor category T3 or greater. Clinical parameters (prostate-specific antigen level, greatest percentage of biopsy core, and percentage of positive cores) and the PI-RADSv2 ratings by three independent readers (experienced readers 1 and 2, inexperienced reader 3) were investigated. Cutoffs and the diagnostic performance of PI-RADSv2 for clinically significant cancer were analyzed. Clinically significant cancer was found in 87.4% (159/182) of patients. The cutoff PI-RADSv2 score for clinically significant cancer was 4 for readers 1 and 2 and 5 for reader 3. The AUCs were 0.829 and 0.853 for readers 1 and 2 (p < 0.001) and 0.602 for reader 3 (p = 0.067). For reader 1, sensitivity was 89.9% (143/159); specificity, 69.6% (16/23); positive predictive value, 95.3% (143/150); negative predictive value, 50.0% (16/32); and accuracy, 87.4% (159/182). The corresponding values for reader 2 were 81.1% (129/159), 82.6% (19/23), 97.0% (129/133), 38.8% (19/49), and 81.3% (148/182). For the experienced readers, 66.7-81.3% of patients with false-negative results had clinically significant cancers with tumor volume less than 1 cm3. PI-RADSv2 may help experienced readers identify clinically significant prostate cancers in patients with a biopsy Gleason score of 6. However, some small (< 1 cm3) clinically significant cancers can be missed when PI-RADSv2 is used.