PI-RADS V2 Score Research Articles

How Often is the Dynamic Contrast Enhanced Score Needed in PI-RADS Version 2?

BackgroundProstate imaging reporting and data system version 2 (PI-RADS v2) relegates dynamic contrast enhanced (DCE) imaging to a minor role. We sought to determine how often DCE is used in PI-RADS v2 scoring. Materials and MethodsWe retrospectively reviewed data from 388 patients who underwent prostate magnetic resonance imaging and subsequent biopsy from January 2016 through December 2017. In accordance with PI-RADS v2, DCE was deemed necessary if a peripheral-zone lesion had a diffusion-weighted imaging score of 3, or if a transition-zone lesion had a T2 score of 3 and diffusion-weighted imaging experienced technical failure. Receiver operating characteristic curve analysis assessed the accuracy of prostate-specific antigen density (PSAD) at different threshold values for differentiating lesions that would be equivocal with noncontrast technique. Accuracy of PSAD was compared to DCE using McNemar's test. ResultsSixty-nine lesions in 62 patients (16%) required DCE for PI-RADS scoring. Biopsy of 10 (14%) of these lesions showed clinically significant cancer (Gleason score ≥7). In the subgroup of patients with equivocal lesions, those with clinically significant cancer had significantly higher PSADs than those with clinically insignificant lesions (means of 0.18 and 0.13 ng/mL/mL, respectively; P= 0.038). In this subgroup, there was no statistical difference in accuracy in determining clinically significant cancer between a PSAD threshold value of 0.13 and DCE (P= 0.25). ConclusionsOnly 16% of our patients needed DCE to generate the PI-RADS version 2 score, raising the possibility of limiting the initial screening prostate MRI to a noncontrast exam. PSAD may also be used to further decrease the need for or to replace DCE altogether.

Extracapsular extension on MRI indicates a more aggressive cell cycle progression genotype of prostate cancer.

To explore associations between magnetic resonance imaging (MRI) features of prostate cancer and expression levels of cell cycle genes, as assessed by the Prolaris® test. Retrospective analysis of 118 PCa patients with genetic testing of biopsy specimen and prostate MRI from 08/2013 to 11/2015. Associations between the cell cycle risk (CCR) score and MRI features [i.e., PI-RADSv2 score, extracapsular extension (ECE), quantitative metrics] were analyzed with Fisher's exact test, nonparametric tests, and Spearman's correlation coefficient. In 41 patients (34.7%), test results were compared to unfavorable features on prostatectomy specimen (i.e., Gleason group ≥ 3, ECE, lymph node metastases). Fifty-four (45.8%), 60 (50.8%), and 4 (3.4%) patients had low-, intermediate-, and high-risk cancers according to American Urological Association scoring system. Patients with ECE on MRI had significantly higher mean CCR scores (reader 1: 3.9 vs. 3.2, p = 0.015; reader 2: 3.6 vs. 3.2, p = 0.045). PI-RADSv2 scores and quantitative MRI features were not associated with CCR scores. In the prostatectomy subset, ECE on MRI (p = < 0.001-0.001) and CCR scores (p = 0.049) were significantly associated with unfavorable histopathologic features. The phenotypic trait of ECE on MRI indicates a more aggressive genotype of prostate cancer.

Combination of prostate imaging reporting and data system with the apparent diffusion coefficient map for the diagnosis of peripheral zone prostate cancer

To explore the value of prostate imaging reporting and data system version 2 (PI-RADS V2) combined with quantitative parameters derived from apparent diffusion coefficient (ADC) map in the diagnosis of peripheral zone prostate cancer. Methods: A total of 50 patients who underwent prostate multiparametric MRI (mpMRI) with suspicious peripheral nodules were retrospectively enrolled, and all patients were biopsy-proven histologically. Two radiologists analyzed the position and category of peripheral zone lesions based on PI-RADS V2. Then 12 ADC quantitative parameters were calculated regarding each lesion on the ADC map by post-processing software. The lesions were divided into malignant group and benign group according to histopathological findings. The ADC quantitative parameters between groups were compared, and stepwise logistic regression analysis was used to build a discriminative model. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were performed to evaluate the diagnostic power and clinical benefit. Results: Twenty-eight peripheral zone prostate malignant lesions and 25 benign lesions were obtained finally. The area under the ROC curve, sensitivity and specificity to differentiate peripheral zone prostate malignant from benign lesions were as follows: 0.803, 60.71%, 92.00% (PI-RADS V2 score), 0.857, 89.29%, 76.00% (ADC model), and 0.891, 71.43%, 92.00% (combined model), respectively. The discriminative power of the combined model was significantly improved compared with PI-RADS V2 score (P=0.012). The combined model had relatively optimal overall net benefit, which outperformed the PI-RADS V2 score when threshold probability varied in the range of 0.05-0.27 and 0.46-0.81. Conclusion: PI-RADS V2 combined with quantitative analysis of ADC map improve the power in discriminating peripheral zone prostate cancer from benign lesions, and the clinical benefit as well.

Correlation between MRI phenotypes and a genomic classifier of prostate cancer: preliminary findings.

We sought to evaluate the correlation between MRI phenotypes of prostate cancer as defined by PI-RADS v2 and the Decipher Genomic Classifier (used to estimate the risk of early metastases). This single-center, retrospective study included 72 nonconsecutive men with prostate cancer who underwent MRI before radical prostatectomy performed between April 2014 and August 2017 and whose MRI registered lesions were microdissected from radical prostatectomy specimens and then profiled using Decipher (89 lesions; 23 MRI invisible [PI-RADS v2 scores ≤ 2] and 66 MRI visible [PI-RADS v2 scores ≥ 3]). Linear regression analysis was used to assess clinicopathologic and MRI predictors of Decipher results; correlation coefficients (r) were used to quantify these associations. AUC was used to determine whether PI-RADS v2 could accurately distinguish between low-risk (Decipher score < 0.45) and intermediate-/high-risk (Decipher score ≥ 0.45) lesions. MRI-visible lesions had higher Decipher scores than MRI-invisible lesions (mean difference 0.22; 95% CI 0.13, 0.32; p < 0.0001); most MRI-invisible lesions (82.6%) were low risk. PI-RADS v2 had moderate correlation with Decipher (r = 0.54) and had higher accuracy (AUC 0.863) than prostate cancer grade groups (AUC 0.780) in peripheral zone lesions (95% CI for difference 0.01, 0.15; p = 0.018). MRI phenotypes of prostate cancer are positively correlated with Decipher risk groups. Although PI-RADS v2 can accurately distinguish between lesions classified by Decipher as low or intermediate/high risk, some lesions classified as intermediate/high risk by Decipher are invisible on MRI. • MRI phenotypes of prostate cancer as defined by PI-RADS v2 positively correlated with a genomic classifier that estimates the risk of early metastases. • Most but not all MRI-invisible lesions had a low risk for early metastases according to the genomic classifier. • MRI could be used in conjunction with genomic assays to identify lesions that may carry biological potential for early metastases.

586 - PI-RADSv2 score

586 - PI-RADSv2 score <5 associates with a very low risk of pelvic lymph node invasion in prostate cancer, even among high-risk population

Establishing a prediction model for prostate cancer bone metastasis.

We collected clinical data from 308 prostate cancer (PCa) patients to investigate the clinical characteristics and independent risk factors of bone metastasis (BM) and to establish a prediction model for BM of PCa and determine the necessity of bone scans. Univariate and multivariate analyses were performed based on age, biopsy Gleason score (BGS), clinical tumor stage (cTx), total prostate specific antigen (tPSA), free prostate specific antigen (fPSA), fPSA/tPSA, prostate volume, alkaline phosphatase (ALP), serum calcium and serum phosphorus. Moreover, 80 of the 308 PCa patients had a PI-RADS v2 score and were analysed retrospectively. The univariate analysis showed that the BGS, cTx, tPSA, fPSA, prostate volume and ALP were significant. The multivariate logistic regression analysis showed significant differences among the BGS, cTx, tPSA and ALP. Four cases should be highly suspected with BM: (i) cTl-cT2, BGS ≤7, ALP >120 U/L and tPSA >90.64 ng/ml; (ii) cTl-cT2, BGS ≥8, and ALP >120 U/L; (iii) cT3-cT4, BGS ≤7, and ALP >120 U/L; and (iv) cT3-cT4 and BGS ≥8. After the PI-RADS v2 score was included in the model, the AUC of the prediction model rose from 0.884 (95% CI: 0.813-0.996) to 0.934 (95% CI: 0.883-0.986). This model may help determine the necessity of bone scans to diagnose BM for PCa patients.

Differences in negative predictive value of prostate MRI based in men with suspected or known cancer.

ObjectiveTo compare the negative predictive value (NPV) of multiparametric MRI for Gleason score (GS) ≥ 3+4 cancer and evaluate predictors of these tumors in men with suspected disease and under active surveillance (AS).Materials and MethodsThis retrospective study included 38 men with suspected prostate cancer and 38 under AS with scans assigned PI-RADS v2 scores 1 or 2 between May 2016 and September 2017. Biopsy results were no cancer, GS = 3+3, or GS ≥ 3+4. Pre-MRI PSA, gland volume, and PSA density were recorded. Chi-square, equality of proportions, and logistic regressions were used to analyze the data.ResultsIntermediate to high-grade cancer was found in 12.8% (95% CI = 2.3-23.3) and 35.9% (95% CI = 20.8-50.9) of men with suspected cancer, and under AS (p = 0.02), respectively. The NPV for GS ≥ 3+4 were 87.2% (suspected cancer; 76.7-97.7) and 64.1% (AS; 49.0-79.2). In neither group PSA significantly predicted cancer grade (p = 0.75 and 0.63). Although it did not reach conventional statistical significance, PSA density was a good predictor of cancer grade in men with suspected disease (p = 0.06), but not under AS (p = 0.62).ConclusionThe NPV of multiparametric MRI for GS ≥ 3+4 is higher in men with suspected prostate cancer than in men under AS. PSA density ≤ 0.15 improved the prediction of intermediate to high-grade disease in patients without known cancer.

Intraductal carcinoma of the prostate (IDC-P) lowers apparent diffusion coefficient (ADC) values among intermediate risk prostate cancers.

Prostatic intraductal carcinoma (IDC-P) is an aggressive variant of prostate cancer (PCa) characterized by proliferation of malignant cells within prostatic ducts/acini and nucleomegaly. To compare apparent diffusion coefficient (ADC) values and Prostate Imaging and Data Reporting System (PI-RADS) v. 2 scores in intermediate risk (International Society of Urological Pathology [ISUP] Grade Group [GG] 2 and 3) PCa with/without IDC-P to determine if IDC-P alters the MRI appearance of PCa. Retrospective, case-control. Fifteen consecutive men with ISUP GG 2/3 (Gleason score 3+4 = 7 [N = 4], 4+3 = 7 [N = 11]) PCa with IDC-P diagnosed at radical prostatectomy were compared with: 1) ISUP GG 2/3 PCa without IDC-P (matched for percentage Gleason pattern 4), and 2) ISUP GG 4 and 5 (Gleason score 8/9) PCa without IDC-P. 3T multiparametric MRI. Two blinded radiologists (R1/R2) measured mean ADC, ADC.ratio (ADC.tumor/ADC.normal peripheral zone) and assigned PI-RADS v2 scores. Statistical Tests: Chi-square and analysis of variance (ANOVA). There were no differences in age, prostate serum antigen, tumor size, or stage between groups (P = 0.063-0.912). Tumors with IDC-P had lower mean ADC and ADC.ratio (0.741 ± 0.152 mm2 /sec and 0.44 ± 0.07) compared with ISUP GG 2/3 tumors without IDC-P (0.888 ± 0.167 mm2 /sec and 0.62 ± 0.14), P = 0.012 and <0.001; and did not differ compared with ISUP GG 4/5 tumors (0.705 ± 0.141 mm2 /sec and 0.44 ± 0.08), P = 0.509 and 0.868. Tumors with IDC-P were nearly all PI-RADS v2 score 5 (14/15) compared with ISUP GG 2/3 tumors without IDC-P (10/15 R1, 8/15 R2) and GG 4/5 tumors (9/15), (P = 0.040 = 0.092). Agreement in PI-RADS v2 scoring was moderate (K = 0.68). ISUP GG 2 and 3 (intermediate risk, Gleason score 7) PCa with IDC-P have lower ADC compared with tumors without IDC-P with a similar percentage of Gleason pattern 4 and resemble ISUP GG 4 and 5 high risk tumors on MRI. IDC-P lowers ADC values among intermediate risk prostate cancers. 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:279-287.

Deep transfer learning-based prostate cancer classification using 3 Tesla multi-parametric MRI.

The purpose of the study was to propose a deep transfer learning (DTL)-based model to distinguish indolent from clinically significant prostate cancer (PCa) lesions and to compare the DTL-based model with a deep learning (DL) model without transfer learning and PIRADS v2 score on 3 Tesla multi-parametric MRI (3T mp-MRI) with whole-mount histopathology (WMHP) validation. With IRB approval, 140 patients with 3T mp-MRI and WMHP comprised the study cohort. The DTL-based model was trained on 169 lesions in 110 arbitrarily selected patients and tested on the remaining 47 lesions in 30 patients. We compared the DTL-based model with the same DL model architecture trained from scratch and the classification based on PIRADS v2 score with a threshold of 4 using accuracy, sensitivity, specificity, and area under curve (AUC). Bootstrapping with 2000 resamples was performed to estimate the 95% confidence interval (CI) for AUC. After training on 169 lesions in 110 patients, the AUC of discriminating indolent from clinically significant PCa lesions of the DTL-based model, DL model without transfer learning and PIRADS v2 score ≥ 4 were 0.726 (CI [0.575, 0.876]), 0.687 (CI [0.532, 0.843]), and 0.711 (CI [0.575, 0.847]), respectively, in the testing set. The DTL-based model achieved higher AUC compared to the DL model without transfer learning and PIRADS v2 score ≥ 4 in discriminating clinically significant lesions in the testing set. The DeLong test indicated that the DTL-based model achieved comparable AUC compared to the classification based on PIRADS v2 score (p = 0.89).

Characteristics of missed prostate cancer lesions on 3T multiparametric-MRI in 518 patients: based on PI-RADSv2 and using whole-mount histopathology reference.

To determine the characteristics of missed prostate cancer (PCa) lesions on 3T multiparametric-MRI (mpMRI) based on PI-RADSv2 with whole-mount histopathology (WMHP) correlation. This IRB-approved, HIPAA-compliant study, included 614 consecutive men with 3T mpMRI prior to prostatectomy at a single tertiary center between 12/2009 and 4/2017. Clinical, mpMRI, and pathologic features were obtained. PI-RADSv2-based MRI detected lesions were matched with previously finalized WMHP by a genitourinary (GU) radiologist and a GU pathologist. Patients with no mpMRI detected PCa lesion, but with at least one lesion ≥ 1cm on WMHP, were reviewed retrospectively and assigned a PI-RADSv2 score. Tumor characteristics were compared between missed and detected lesions. The final cohort included 518 patients with 1085 WMHP lesions. 51.9% (563/1085) of lesions were missed on 3T mpMRI. 71.4% (402/563), 21.7% (122/563), 4.4% (25/563), and 2.5% (14/563) of the missed lesions were Gleason scores (GS) 3 + 3, 3 + 4, 4 + 3, and 8 - 10, respectively. Missed PCa lesions had significantly lower proportion of GS ≥ 7 (p < 0.001) and smaller size for overall (p < 0.001) and index subcohorts (p < 0.001), as compared to detected lesions. 34.5% (194) of overall and 71.2% (79) index missed lesions were larger than 1cm. In 13.7% (71/518) of patients without MR detected PCa, 149 lesions were detected on WMHP, with 70 (47%) lesions ≥ 1cm. In retrospective review of these lesions, 42.9% (30), 18.6% (13), 21.5% (15), 10% (7), and 7% (5) were PI-RADSv2 1, 2, 3, 4, and 5, respectively. 3T mpMRI has an excellent per patients diagnostic performance for PCa and majority of missed lesions are clinically nonsignificant.

A Prospective Accuracy Study of Prostate Imaging Reporting and Data System Version 2 on Multiparametric Magnetic Resonance Imaging in Detecting Clinically Significant Prostate Cancer With Whole-mount Pathology

ObjectiveTo assess the accuracy of Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) in detecting clinically significant prostate cancer (csPCa) on multiparametric magnetic resonance imaging (mpMRI) using whole-mount sections after radical prostatectomy (RP) as reference standard. MethodsForty-eight patients undergoing mpMRI before RP were prospectively enrolled. Two experienced radiologists independently scored and mapped imaging findings according to PI-RADS v2. One experienced uropathologist mapped cancers detected on whole-mount sections using the PI-RADS v2 sector scheme. Per-lesion and per-patient analyses were run. Primary outcomes were sensitivity and false discovery rate (FDR) in detecting csPCa using PI-RADS v2 score ≥3 and ≥4 as thresholds. Secondary outcome was inter-reader agreement. ResultsOn the per-lesion analysis, sensitivity and FDR at the PI-RADS v2 threshold score ≥3 were 0.75 and 0.17 for Reader 1, and 0.67 and 0.13 for Reader 2, respectively. At the PI-RADS v2 threshold score ≥4, sensitivity was slightly lower, and FDR nearly halved for both readers. On the per-patient analysis, sensitivity for csPCa at the PI-RADS v2 threshold score ≥3 was 0.85 for Reader 1, and 0.78 for Reader 2. At the PI-RADS v2 threshold score ≥4, sensitivity was slightly lower for both readers. Inter-reader agreement was substantial (k 0.72 and 0.65 for PI-RADS v2 threshold score ≥3 and ≥4, respectively). ConclusionIn our prospective study with pathology after RP as standard of reference, PI-RADS v2 showed good sensitivity in detecting csPCa on mpMRI with substantial agreement between 2 experienced readers. Threshold score ≥4 had lower FDR.

Assessment of PI-RADS v2 categories ≥ 3 for diagnosis of clinically significant prostate cancer.

To assess the diagnostic accuracy of PI-RADS v2 categories ≥ 3 to detect clinically significant prostate cancer (csPCa) against histopathology of Transperineal Mapping Biopsy (TPMB). IRB-approved retrospective cohort study included 47 men who had 3.0 T multi-parametric MRI (mpMRI) and TPMB of prostate. Two radiologists independently evaluated T2, DWI, ADC map, and DCE images using PI-RADS v2 categories. A third radiologist served as tie-breaker. PI-RADS v2 score (PS) ≥ 3 lesions were correlated with 3D model of TPMB (3DTPMB) results based on prostate sectors. Two groups of csPCa status were separately analyzed for accuracy measures at lesion and person levels: Group 1 with GS (Gleason Score) ≥ 7 and group 2 with tumor volume ≥ 0.5cc. Inter-rater reliability for PS and MR lexicon was calculated. Forty-seven patients with 3DTPMB had at least one lesion with PS ≥ 3 on mpMRI. PS of 5 had high PPV and high specificity of 100% at the lesion and person levels. Sensitivity of a PS ≥ 3 was 68.27% for group 1 and was 48.39% for group 2. Specificity was 93.56% for group 1 and was 95.53% for group 2. At the person level, sensitivity of PS ≥ 3 was 81.25% for group 1 and was 82.35% for group 2. Specificity was 32.26% for group 1 and was 53.85% for group 2. PI-RADS v2 category of 5 had high PPV and specificity; however, combined PS ≥ 3 had mixed performance in detection of csPCa.

Predictive role of PI-RADSv2 and ADC parameters in differentiating Gleason pattern 3 + 4 and 4 + 3 prostate cancer.

To compare the predictive roles of qualitative (PI-RADSv2) and quantitative assessment (ADC metrics), in differentiating Gleason pattern (GP) 3 + 4 from the more aggressive GP 4 + 3 prostate cancer (PCa) using radical prostatectomy (RP) specimen as the reference standard. We retrospectively identified treatment-naïve peripheral (PZ) and transitional zone (TZ) Gleason Score 7 PCa patients who underwent multiparametric 3T prostate MRI (DWI with b value of 0,1400 and where unavailable, 0,500) and subsequent RP from 2011 to 2015. For each lesion identified on MRI, a PI-RADSv2 score was assigned by a radiologist blinded to pathology data. A PI-RADSv2 score ≤ 3 was defined as "low risk," a PI-RADSv2 score ≥ 4 as "high risk" for clinically significant PCa. Mean tumor ADC (ADCT), ADC of adjacent normal tissue (ADCN), and ADCratio (ADCT/ADCN) were calculated. Stepwise regression analysis using tumor location, ADCT and ADCratio, b value, low vs. high PI-RADSv2 score was performed to differentiate GP 3 + 4 from 4 + 3. 119 out of 645 cases initially identified met eligibility requirements. 76 lesions were GP 3 + 4, 43 were 4 + 3. ADCratio was significantly different between the two GP groups (p = 0.001). PI-RADSv2 score ("low" vs. "high") was not significantly different between the two GP groups (p = 0.17). Regression analysis selected ADCT (p = 0.03) and ADCratio (p = 0.0007) as best predictors to differentiate GP 4 + 3 from 3 + 4. Estimated sensitivity, specificity, and accuracy of the predictive model in differentiating GP 4 + 3 from 3 + 4 were 37, 82, and 66%, respectively. ADC metrics could differentiate GP 3 + 4 from 4 + 3 PCa with high specificity and moderate accuracy while PI-RADSv2, did not differentiate between these patterns.

Multiparametric magnetic resonance imaging - Transrectal ultrasound-guided cognitive fusion biopsy of the prostate: Clinically significant cancer detection rates stratified by the Prostate Imaging and Data Reporting System version 2 assessment category.

We aimed to report the clinically significant prostate cancer (PCa) detection rate in men undergoing magnetic resonance imaging-transrectal ultrasound (MRI-TRUS)-cognitive fusion (CF) targeted biopsies stratified by the Prostate Imaging and Data Reporting System (PI-RADS) version 2 (v2) scores. With a quality assurance waiver from the IRB, we identified a cohort of men who underwent MRI-TRUS-CF and synchronous template biopsy from 2015-2017. MRI (PI-RADS v2 score, lesion size, lesion location [peripheral or transition zone (PZ/TZ)]), and CF-TRUS biopsy (operator experience, TRUS visibility, and number of biopsies) features were extracted. The primary outcome was diagnosis of clinically significant (Gleason score ≥3+4=7 or International Society of Urological Pathology (ISUP) grade group ≥2) PCa. During the study period, 131 men (with 142 PIRADS v2 score ≥3 lesions) met inclusion criteria; 98 men had previously negative template biopsy and 33 were on active surveillance for previously detected low-grade PCa. In total, 41.9% (55/131) men had clinically significant PCa - 17.6% (23/131) detected on targeted biopsy only, 8.4% (11/131) on template biopsy only, and 16.0% (21/131) on both targeted and template biopsy. Clinically significant PCa detection stratified by PI-RADS v2 scores were: 11.1% (3/27) for score 3 (indeterminate), 42.9% (24/56) for score 4 (significant cancer likely), and 35.6% (21/59) for score 5 (significant cancer very likely). Clinically significant PCa detection rates in targeted biopsies were better among PZ (41.8% [33/79]) compared to TZ (23.8% [15/63]) lesions (p=0.025) in TRUS visible lesions (p=0.033) and in the most experienced radiologists (p=0.05), with no difference by lesion size or number of additional core biopsies performed (all p&gt;0.05). Cognitive fusion MRI-TRUS-guided targeted biopsy yielded substantially lower rates of clinically significant cancer in PI-RADS v2 score 4 and 5 lesions when compared to published results using in-bore MR-guided or automated MRI-TRUS fusion guidance systems. Cancer detection was worst for TZ lesions.

Development and internal validation of PI-RADs v2-based model for clinically significant prostate cancer

BackgroundOur objective is to build a model based on Prostate Imaging Reporting and Data System version 2 (PI-RADs v2) and assess its accuracy by internal validation.MethodsPatients who took prostate biopsy from 2014 to 2015 were retrospectively collected to compose training cohort according to the inclusion criteria and patients in 2016 composing validation cohort. Diagnostic performance was evaluated by analyzing the area under the curve (AUC), calibration curves, and decision curves.ResultsOf the 441 patients involved, the clinically significant prostate cancer (csPCa) detection rate were 40.6% (114/281) and 43.8% (70/160) in the training and validation cohort, respectively. Meanwhile, PCa detection rate were 50.2% (141/281) and 53.8% (86/160). Age, prostate-specific antigen density (PSAD)*10 and PI-RADs v2 score composed the model for PCa (model 1) and csPCa (model 2). The area under the curve of models 1 and 2 was 0.870 (95% CI 0.827–0.912) and 0.753 (95% CI 0.717–0.828) in the training cohort, while 0.845 (95% CI 0.786–0.904) and 0.834 (95% CI 0.787–0.882) in the validation cohort. Both models illustrated good calibration, and decision curve analyses showed good performance in predicting PCa or csPCa when the threshold was 0.35 or above.ConclusionsThe model based on age, PSAD*10 and PI-RADs v2 score showed internally validated high predictive value for both PCa and csPCa. It could be used to improve the diagnostic performance of suspicious PCa.

PD23-04 ADDED VALUE OF SYSTEMATIC BIOPSIES IN MEN WITH ABNORMAL MULTIPARAMETRIC MRI UNDERGOING MRI-TRUS FUSION PROSTATE BIOPSY

You have accessJournal of UrologyProstate Cancer: Detection & Screening II1 Apr 2018PD23-04 ADDED VALUE OF SYSTEMATIC BIOPSIES IN MEN WITH ABNORMAL MULTIPARAMETRIC MRI UNDERGOING MRI-TRUS FUSION PROSTATE BIOPSY Yuval Freifeld, Yin Xi, Claus Roehrborn, Franto Francis, Niccolo Passoni, Yair Lotan, Kenneth Goldberg, Brad Hornberger, Vitaly Margulis, Ivan Pedrosa, Ganesh Raj, Jeffrey Cadeddu, and Daniel Costa Yuval FreifeldYuval Freifeld More articles by this author , Yin XiYin Xi More articles by this author , Claus RoehrbornClaus Roehrborn More articles by this author , Franto FrancisFranto Francis More articles by this author , Niccolo PassoniNiccolo Passoni More articles by this author , Yair LotanYair Lotan More articles by this author , Kenneth GoldbergKenneth Goldberg More articles by this author , Brad HornbergerBrad Hornberger More articles by this author , Vitaly MargulisVitaly Margulis More articles by this author , Ivan PedrosaIvan Pedrosa More articles by this author , Ganesh RajGanesh Raj More articles by this author , Jeffrey CadedduJeffrey Cadeddu More articles by this author , and Daniel CostaDaniel Costa More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.1185AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Targeted prostate biopsy (TBx) using MRI-TRUS fusion has emerged as the most common approach for sampling suspicious lesions identified on multiparametric MRI (mpMRI). Concurrent systematic biopsies (SBx) are usually performed as the standard of care. To minimize over-diagnosis of indolent tumors, patient discomfort, duration of the biopsy procedure and, potentially, decrease the risk of bleeding and infection, some groups have advocated for replacing the 12-core scheme with either a targeted only or a targeted plus modified systematic approach. The goal of our study was to determine the incremental diagnostic value of systematic cores obtained from the same (ipsi-SBx) and contralateral (contra-SBx) side for the diagnosis of clinically significant prostate cancer (csPCa) in men with abnormal mpMRI. METHODS Using a prospectively maintained database, we identified all men with abnormal 3T endorectal coil mpMRI examinations (single lesion, PIRADS v2 score ≥3) between Jan/14-Jun/17, without prior treatment, who subsequently had a concurrent systematic and targeted biopsy using a MRI-TRUS fusion system (UroStation, Koelis, or UroNav, DynaCAD). TBx usually consisted of 2 cores from the suspicious area and SBx included the usual 12-core template. csPCa was defined as ISUP grade group 2 (i.e., Gleason 3+4) or greater tumors. Combined TBx and SBx were used as the standard of reference. Sensitivity and 95% confidence intervals for detection of csPCa using TBx only, TBx plus ipsi-SBx and TBx plus contra-SBx were calculated. RESULTS Combined, SBx and TBx detected csPCa in 47% (55/117) of the 117 eligible men. TBx alone, TBx plus ipsi-SBx and TBx plus contra-SBx would have missed csPCa in 6.8% (8/117), 1.7% (2/117) and 3.4% (4/117), respectively. TBx alone, TBx plus ipsi-SBx, TBx plus contra-SBx, and SBx alone would have exclusively diagnosed non-csPCa in 7.7% (9/117), 15.4% (18/117), 13% (15/117), and 12.8% (15/117) of the men, respectively. Of the 36 men who underwent radical prostatectomy (RP), index lesion on whole-mount radical prostatectomy specimen was site-concordant with the MRI lesion in 91.7% (33/36) of the cases. CONCLUSIONS Most of the csPCa missed by TBx seem related to imperfections of the MRI-TRUS image registration and, in most men, may be overcome by obtaining ipsi-SBx. By not performing contra-SBx, the number of cores obtained can be decreased nearly by half, with a potential small number of missed csPCa, decrease in detection of indolent tumors, and improved patient experience. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e481-e482 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Yuval Freifeld More articles by this author Yin Xi More articles by this author Claus Roehrborn More articles by this author Franto Francis More articles by this author Niccolo Passoni More articles by this author Yair Lotan More articles by this author Kenneth Goldberg More articles by this author Brad Hornberger More articles by this author Vitaly Margulis More articles by this author Ivan Pedrosa More articles by this author Ganesh Raj More articles by this author Jeffrey Cadeddu More articles by this author Daniel Costa More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

MP57-04 THE GERMAN RISK-ADAPTED PROSTATE CANCER SCREENING TRIAL (PROBASE) – FIRST RESULTS AFTER RECRUITMENT OF 30.000 MEN

You have accessJournal of UrologyProstate Cancer: Detection & Screening V1 Apr 2018MP57-04 THE GERMAN RISK-ADAPTED PROSTATE CANCER SCREENING TRIAL (PROBASE) – FIRST RESULTS AFTER RECRUITMENT OF 30.000 MEN Christian Arsov, Nikolaus Becker, Kathleen Herkommer, Jürgen Gschwend, Florian Imkamp, Markus Kuczyk, Boris Hadaschik, Markus Hohenfellner, Roswitha Siener, Glen Kristiansen, Lars Schimmöller, Gerald Antoch, and Peter Albers Christian ArsovChristian Arsov More articles by this author , Nikolaus BeckerNikolaus Becker More articles by this author , Kathleen HerkommerKathleen Herkommer More articles by this author , Jürgen GschwendJürgen Gschwend More articles by this author , Florian ImkampFlorian Imkamp More articles by this author , Markus KuczykMarkus Kuczyk More articles by this author , Boris HadaschikBoris Hadaschik More articles by this author , Markus HohenfellnerMarkus Hohenfellner More articles by this author , Roswitha SienerRoswitha Siener More articles by this author , Glen KristiansenGlen Kristiansen More articles by this author , Lars SchimmöllerLars Schimmöller More articles by this author , Gerald AntochGerald Antoch More articles by this author , and Peter AlbersPeter Albers More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.1816AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Population-based PSA screening still is controversially discussed. A risk-adapted approach using a baseline PSA value at age 45 may improve the number needed to screen and to treat. The German risk-adapted PCa screening trial PROBASE is currently the largest ongoing screening trial and aims to accrue 50,000 men within 5 yrs in a prospective and randomized fashion. The trial opened in April 2014. METHODS The PROBASE trial is powered for superiority in terms of specificity of risk-adapted PSA screening starting at age 50 (arm B) as compared to 45 yrs (arm A) with non-inferiority in terms of metastasis from PCa. 45 yrs old men are randomly assigned to risk-adapted screening beginning at age 45 or five years later at age 50. Both groups receive risk-adapted PSA screening based on baseline PSA values: < 1.5 ng/ml (low risk) - 5-yearly PSA (expected 90%), 1.5-2.99 ng/ml (intermediate risk) - 2-yearly PSA (expected 7.5%), >=3.0 ng/ml (high risk) MRI and combined systematic and MRI/TRUS fusion-guided biopsy recommended (expected 2.5%). Screening ends at age 60. RESULTS Overall 30,298 men have been enrolled until October 2017 of which 15,152 were randomized into trial arm A. The majority of the PSA values of trial arm A were < 1.5 ng/ml (n=13,506, 89.1%), few in the range of 1.5 to 2.99 ng/ml (n=1,427, 9.4%) and at 3.0 ng/ml or above (n=219, 1.5%). In the latter group, a PSA value >=3.0 ng/ml was confirmed by a second test in 115/219 subjects (52.5%, 0.8% of all trial arm A participants). Median PSA of these participants was 4.1 ng/ml (range 3.0-28.1).Subsequently, 81 subjects out of the 115 PSA-suspicious men underwent MRI (70.4%). PI-RADS v2 scores were as follows: PI-RADS 1 n=2 (2.5%) PI-RADS 2 n=32 (39.6%), PI-RADS 3 n=23 (28.4%), PI-RADS 4 n=16 (19.8%), PI-RADS 5 n=3 (3.7%).Until now, 81.5% (66/81) also underwent combined biopsy with a PCa detection rate of 33.3% (22/66). Thus, the overall PCa incidence in trial arm A at the first screening round is 0.15%. The rate of cancers with a Gleason score of at least 3+4=7 was 68.2% (15/22). So far, 561 participants initially assigned to the intermediate risk group underwent a second screening round two years later. Altogether, 6.6% (37/561) had a confirmed PSA increase >=3.0 ng/ml (median 3.9, range 3.1-15.7). During this workup, 24 out of these 37 participants had an MRI with combined biopsy. PCa detection rate was 37.5% (9/24) with 5 PCa having a Gleason pattern 4. CONCLUSIONS PROBASE started with a rapid recruitment and the expected distribution of risk-groups could be confirmed. The overall PCa incidence in 45 yrs old men is very low (<1%). Increased PSA levels should be confirmed before performing prostate biopsy. However, men with a confirmed baseline PSA >=3.0 ng/ml or those initially assigned to the intermediate risk group and exceeding the biopsy cut off two years later have a high risk of harbouring significant PCa. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e765 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Christian Arsov More articles by this author Nikolaus Becker More articles by this author Kathleen Herkommer More articles by this author Jürgen Gschwend More articles by this author Florian Imkamp More articles by this author Markus Kuczyk More articles by this author Boris Hadaschik More articles by this author Markus Hohenfellner More articles by this author Roswitha Siener More articles by this author Glen Kristiansen More articles by this author Lars Schimmöller More articles by this author Gerald Antoch More articles by this author Peter Albers More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

PD06-07 AGGRESSIVENESS OF PROSTATE CANCER: CORRELATION BETWEEN PROSPECTIVELY ASSIGNED APPARENT DIFFUSION COEFFICIENT VALUES AND ISUP GRADE GROUP

You have accessJournal of UrologyProstate Cancer: Detection & Screening I1 Apr 2018PD06-07 AGGRESSIVENESS OF PROSTATE CANCER: CORRELATION BETWEEN PROSPECTIVELY ASSIGNED APPARENT DIFFUSION COEFFICIENT VALUES AND ISUP GRADE GROUP Daniel Costa, Yin Xi, Muhammad Aziz, Franto Francis, Claus Roehrborn, Kenneth Goldberg, Niccolo Passoni, Nabeel Shakir, Alberto Diaz de Leon, and Ivan Pedrosa Daniel CostaDaniel Costa More articles by this author , Yin XiYin Xi More articles by this author , Muhammad AzizMuhammad Aziz More articles by this author , Franto FrancisFranto Francis More articles by this author , Claus RoehrbornClaus Roehrborn More articles by this author , Kenneth GoldbergKenneth Goldberg More articles by this author , Niccolo PassoniNiccolo Passoni More articles by this author , Nabeel ShakirNabeel Shakir More articles by this author , Alberto Diaz de LeonAlberto Diaz de Leon More articles by this author , and Ivan PedrosaIvan Pedrosa More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.427AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Non-invasive quantitative markers of prostate cancer (PCa) aggressiveness have the potential to improve pre-treatment risk stratification. Previous investigations have shown an inverse correlation between Gleason score and apparent diffusion coefficient (ADC) values derived from diffusion-weighted MRI. Most of these investigations, however, were retrospective. The goal of this study was to determine the ability to use prospectively assigned mean ADC values to discriminate between ISUP grade groups. METHODS Using a prospectively maintained database, we identified all men with abnormal 3T endorectal coil mpMRI examinations (PIRADS v2 score ≥3) between Nov/16-Jul/17, without prior treatment, who subsequently had a positive targeted biopsy or radical prostatectomy. One of 9 radiologists prospectively assigned a mean ADC value for each lesion during clinical image interpretation. The index lesion on MRI - one per patient - was correlated with the site-concordant lesion on biopsy or whole-mount histopathology. Fusion or in-bore targeted biopsy and 3D-printed whole-mount histopathology enabled strict imaging-histology correlation. Logistic regression was used to evaluate the association between mean ADC values in discriminating International Society of Urological Pathology (ISUP) group 1 vs. grade group 2-5. Impact of lesion location (PZ vs. TZ) was also evaluated by stratification. Interquartile ranges (IQRs) were calculated. Diagnostic performances were determined using ROC curve and area under the curve (AUC) with 95% confidence intervals (CIs). Youden′s J statistic was used to determine optimal cutoff values. RESULTS Among the 218 eligible men, 41% underwent surgery and 59% had targeted biopsies. Mean PSA, age, prostate volume and lesion size were 10.2 ng/mL, 65y, 43 cc and 15 mm, respectively. ISUP grade groups 1-5 accounted for, respectively, 21%, 48%, 19%, 7% and 5% of cases. Overall and per-zone mean ADC values were lower for ISUP 2-5 than ISUP 1 (p<0.001,Fig.1). AUCs for the discrimination between ISUP group 1 vs. 2 or higher using mean ADC values were 0.85 (PZ+TZ), 0.91 (PZ) and 0.70 (TZ). Optimal cutoff values were 0.682 for PZ and 0.638 for TZ, resulting in a sensitivity and specificity of 78% and 94% for PZ, 72% and 67% for TZ, respectively. CONCLUSIONS ADC values can be used to predict ISUP grade groups, particularly in PZ lesions, facilitating pre-treatment risk stratification in men undergoing mpMRI and targeted prostate biopsies. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e153 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Daniel Costa More articles by this author Yin Xi More articles by this author Muhammad Aziz More articles by this author Franto Francis More articles by this author Claus Roehrborn More articles by this author Kenneth Goldberg More articles by this author Niccolo Passoni More articles by this author Nabeel Shakir More articles by this author Alberto Diaz de Leon More articles by this author Ivan Pedrosa More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Prediction of adverse pathology after radical prostatectomy on MPMRI in the PIRADS v2 era.

121 Background: As the use of MRI in the diagnosis of prostate cancer (PCa) becomes more established, knowledge of its utility as a prognostic tool is needed to better counsel patients. Here, we aim to assess the ability of mpMRI to predict adverse pathologic factors, such as extraprostatic extension (EPE), seminal vesicle invasion (SVI) or lymph node involvement (LNI) on final pathology after radical prostatectomy (RP). Methods: A prospectively maintained database was queried for all men who underwent mpMRI with current PI-RADS v2 scoring system, MRI/TRUS fusion biopsy (FBx), and RP at our institution (n = 112). Patient demographics, clinical data, imaging and pathology were recorded. Patients were stratified by presence of adverse pathology (AP), defined as EPE, SVI or LNI. Statistical analyses were used to identify mpMRI characteristics predictive of AP using STATA 13. Results: Patients with adverse pathology were middle aged, predominantly caucasian, and significantly higher PSA at baseline (Table 1). Having a PI-RADS 5 lesion was positively associated with AP (adjusted OR = 4.37, 95% CI = 1.20-15.87, p = 0.02). Mean lesion diameter on mpMRI was greater in patients with AP (p &lt; 0.01). However, number of lesions (p = 0.12) and prostate volume on mpMRI (p = 0.88) were not associated with AP. Conclusions: The results of this study demonstrate that features on mpMRI, particularly a PI-RADS score of 5 and large lesion diameter, are predictive of adverse pathology. This information will prove valuable in developing an imaging-based prognostic model in the era of MRI and FBx. This research was supported by the Intramural Research Program of the National Cancer Institute, NIH and NIH Medical Research Scholars Program[Table: see text]

Comparison of likert and PI-RADS v2 scoring in the diagnosis of prostate cancer

Aim: We aimed to compare the inter- and intra-observer variability and diagnostic performance of PI-RADS v2 and Likert scoring in the evaluation of prostate cancer on multiparametric prostate MR imaging. Material and Methods: MRI findings of 53 patients who had histopathologic diagnosis of prostate cancer and 51 patients who had one or more negative transrectal ultrasound guided prostate biopsy were evaluated retrospectively. The images were assessed by three independent observers blinded to histopathologic results of the patients. Intra-observer and inter-observer variability were evaluated by CohenÂ’s Kappa coefficient for all possible pairs of observers. ROC curve analysis was used to determine AUC to evaluate diagnostic performance of Likert and PI-RADS v2 scoring with a 1.5T MR in the diagnosis of prostate cancer. Results: Kappa values for 4 or higher PI-RADS v2 scores were calculated and κ=0.59-0.71 for intra-observer and κ=0.48-0.67 for inter-observer variability were obtained. κ=0.54-0.69 for intra-observer and κ=0.42-0.75 for inter-observer reliability were obtained for 4 or higher Likert scoring. AUC was 72% for PI-RADS v2 scores and was 75.9% for Likert scores for determining Gleason 6 or higher prostate cancers. There was not a statistically significant difference in the comparison of Likert and PI-RADS v2 ROC curves. Conclusion: PI-RADS v2 has no significant superiority compared to Likert scoring in intra-observer and inter-observer reliability. Likert and PI-RADS v2 scoring has no difference in the terms of diagnostic capability of prostate cancers.