Role of PI-RADSv2 with multiparametric MRI in determining who needs active surveillance or definitive treatment according to PRIAS

Non-invasively identifying candidates of active surveillance for prostate cancer using magnetic resonance imaging radiomics

Active surveillance (AS) is the primary strategy for managing patients with low or favorable-intermediate risk prostate cancer (PCa). Identifying patients who may benefit from AS relies on unpleasant prostate biopsies, which entail the risk of bleeding and infection. In the current study, we aimed to develop a radiomics model based on prostate magnetic resonance images to identify AS candidates non-invasively. A total of 956 PCa patients with complete biopsy reports from six hospitals were included in the current multicenter retrospective study. The National Comprehensive Cancer Network (NCCN) guidelines were used as reference standards to determine the AS candidacy. To discriminate between AS and non-AS candidates, five radiomics models (i.e., eXtreme Gradient Boosting (XGBoost) AS classifier (XGB-AS), logistic regression (LR) AS classifier, random forest (RF) AS classifier, adaptive boosting (AdaBoost) AS classifier, and decision tree (DT) AS classifier) were developed and externally validated using a three-fold cross-center validation based on five classifiers: XGBoost, LR, RF, AdaBoost, and DT. Area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE) were calculated to evaluate the performance of these models. XGB-AS exhibited an average of AUC of 0.803, ACC of 0.693, SEN of 0.668, and SPE of 0.841, showing a better comprehensive performance than those of the other included radiomic models. Additionally, the XGB-AS model also presented a promising performance for identifying AS candidates from the intermediate-risk cases and the ambiguous cases with diagnostic discordance between the NCCN guidelines and the Prostate Imaging-Reporting and Data System assessment. These results suggest that the XGB-AS model has the potential to help identify patients who are suitable for AS and allow non-invasive monitoring of patients on AS, thereby reducing the number of annual biopsies and the associated risks of bleeding and infection.

Multiparametric MRI in Active Surveillance of Prostate Cancer: An Overview and a Practical Approach

MRI has become important for the detection of prostate cancer. MRI-guided biopsy is superior to conventional systematic biopsy in patients suspected with prostate cancer. MRI is also increasingly used for monitoring patients with low-risk prostate cancer during active surveillance. It improves patient selection for active surveillance at diagnosis, although its role during follow-up is unclear. We aim to review existing evidence and propose a practical approach for incorporating MRI into active surveillance protocols.

Evaluation of relationships between the final Gleason score, PI-RADS v2 score, ADC value, PSA level, and tumor diameter in patients that underwent radical prostatectomy due to prostate cancer

INTRODUCTION

This study aimed to investigate the relationship between the serum PSA level, Gleason score (GS), PI-RADS v2 score, tumor ADC_min value, and the largest tumor diameter in patients that underwent radical prostatectomy (RP) due to prostate cancer (PCa) and to comparatively evaluate the variables of these parameters in clinically significant and insignificant PCa groups.

MATERIALS AND METHODS

The mpMRI examinations of the patients who underwent RP due to PCa were retrospectively evaluated. According to the final GS, the lesions were divided into two groups as clinically significant (GS ≥ 7) and insignificant (GS ≤ 6). The PSA value, tumor ADC_min value, tumor diameter, and PI-RADS score were compared between the clinically significant and nonsignificant PCa groups using Student's t-test. The correlations between the serum PSA level, GS, PI-RADS v2 score, tumor ADC_min value, and tumor diameter were evaluated separately (Pearson's correlation analysis was used for peripheral gland tumors, and Spearman's correlation analysis for central gland tumors). A ROC analysis was undertaken to evaluate the efficacy of the tumor ADC_min, diameter and PSA values in differentiating clinically significant and nonsignificant tumors.

RESULTS

In both central and peripheral gland tumors, there was a correlation between the PSA level, tumor diameter, PI-RADS score, ADC_min value, and GS at various levels (poor, moderate, and high). In central gland tumors, there was no significant difference between the two groups in terms of the PSA value and PI-RADS scores (p > 0.05), but the ADC_min value and diameter of the tumor significantly differed (p < 0.05). For peripheral gland tumors, significant differences were observed in all parameters (p < 0.05). The cut-off values for the peripheral and central gland tumors are as follows: lesion diameter, 13.5 mm and 19 mm; tumor ADC_min, 0.709 × 10^-3 mm²/s and 0.874 × 10^-3 mm²/s; and PSA level, 8.47 ng/ml and 11.10 ng/ml, respectively.

CONCLUSION

The current PI-RADS v2 scoring system can be inadequate in distinguishing clinically significant and insignificant groups in central gland tumors. A separate cut-off value of the tumor diameter should be determined for central and peripheral gland tumors. Tumor ADC_min values can be used as a predictive parameter. The PSA cut-off value should be kept lower in peripheral gland tumors.

Confirmatory multiparametric magnetic resonance imaging at recruitment confers prolonged stay in active surveillance and decreases the rate of upgrading at follow-up

BACKGROUND

To understand the value of multiparametric magnetic resonance imaging (mpMRI) and targeted biopsies at recruitment on active surveillance (AS) outcomes.

MATERIALS AND METHODS

This retrospective single-center study enrolled two cohorts of 206 and 310 patients in AS. The latter group was submitted to mpMRI and targeted biopsies at recruitment. Kaplan-meier curves quantified progression-free survival (PFS) and Bioptic-PFS (B-PFS: no upgrading or >3 positive cores) in the two cohorts. Cox-regression analyses tested independent predictors of PFS and B-PFS. In patients submitted to radical prostatectomy (RP) after AS, significant cancer (csPCa) was defined as: GS ≥ 4 + 3 and/or pT ≥ 3a and/or pN+ . Logistic-regression analyses predicted csPCa at RP.

RESULTS AND LIMITATIONS

Median time follow-up and median time of persistence in AS were 46 (24-70) and 36 (23-58) months, respectively. Patients submitted to mpMRI at AS begin, showed greater PFS at 1- (98% vs. 91%), 3- (80% vs. 57%), and 5-years (70% vs. 35%) follow-up, respectively (all p < 0.01). At Cox-regression analysis only confirmatory mpMRI± targeted biopsy (HR: 0.3; 95% CI 0.2-0.5; p < 0.01) at AS begin was an independent predictor of PFS. Globally, 50 (16%) vs. 128 (62%) and 26 (8.5%) vs. 64 (31%) [all p < 0.01] men in the two groups experienced any-cause and bioptic AS discontinuation, respectively. Patients submitted to confirmatory mpMRI experienced greater 1-(98% vs. 93%), 3-(90% vs. 75%), and 5-years (83% vs. 56%) B-PFS, respectively (all p < 0.01). At Cox-regression analysis, mpMRI±-targeted biopsy at AS begin was associated with B-PFS (HR: 0.3; 95% CI 0.2-0.6; p < 0.01). No differences were recorded in csPCa rates between the two groups (22% vs. 28%; p = 0.47). Limitations of the study are the single-center retrospective nature and the absence of long-term follow-up.

CONCLUSIONS

Confirmatory mpMRI±-targeted biopsies are associated with higher PFS and B-PFS during AS. However, a non-negligible percentage of patients experience csPCa after switching to active treatment.

PI-RADS version 2: optimal time range for determining positivity of dynamic contrast-enhanced MRI in peripheral zone prostate cancer

AIM

To analyse the optimal time cut-off for determining positivity of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in peripheral zone (PZ) prostate cancer (PCa).

MATERIALS AND METHODS

A consecutive series of 89 patients with PZ PCa who had undergone diffusion-weighted imaging (DWI) and subtraction DCE MRI were included. An experienced reader visually analysed the earliest time after contrast medium injection to visualise the best contrast between an index tumour and normal PZ on DCE MRI (i.e., best contrast time). The best contrast time cut-off for clinically significant cancer (csPCa) according to Epstein criteria or International Society of Urological Pathology (ISUP) grade ≥2 was analysed by an experienced reader, and applied to a less-experienced reader. For the index lesion of DWI category 3, the added value of DCE MRI (increased true positive and negative rates of PI-RADSv2 for csPCa) was evaluated using the cut-off time.

RESULTS

The best contrast time cut-off for csPCa was ≤72 seconds for Epstein criteria and ≤56 seconds for ISUP grade ≥2 by an experienced reader. The weighted kappa to determine positivity of DCE MRI was 0.622 for ≤72 seconds and 0.527 for ≤56 seconds between the two readers. The added value of DCE MRI was 55-75% by an experienced reader and 39.1-69.6% by a less-experienced reader.

CONCLUSION

For interpreting PI-RADSv2, imaging findings within 60-72 seconds following contrast media injection seem to reliably determine positivity of DCE MRI in PZ, and have added value for detecting csPCa.

Low PI-RADS assessment category excludes extraprostatic extension (≥pT3a) of prostate cancer: a histology-validated study including 301 operated patients

OBJECTIVES

To evaluate whether low PI-RADS v2 assessment categories are effective at excluding extraprostatic extension (EPE) of prostate cancer (≥pT3a PCa).

METHODS

The local institutional ethics committee approved this retrospective analysis of 301 consecutive PCa patients. Patients were classified as low- or intermediate/high-risk based on clinical parameters and underwent pre-surgical multiparametric magnetic resonance imaging. A PI-RADS v2 assessment category and ESUR EPE score were assigned for each lesion by two readers working in consensus. Histopathologic analysis of the whole-mount radical prostatectomy specimen was the reference standard. Univariate and multivariate analyses were performed to evaluate the association of PI-RADS v2 assessment category with final histology ≥pT3a PCa.

RESULTS

For a PI-RADS v2 assessment category threshold of 3, the overall performance for ruling out (sensitivity, negative predictive value, negative likelihood ratio) ≥pT3a PCa was 99%/98%/0.04 and was similar in both the low-risk (96%/97%/0.12; N = 137) and the intermediate/high-risk groups (100%/100%/0.0; N = 164). In univariate analysis, all clinical and tumor characteristics except age were significantly associated with ≥pT3a PCa. In multivariate analysis, PI-RADS v2 assessment categories ≤ 3 had a protective effect relative to categories 4 and 5. The inclusion of ESUR EPE score improved the AUC of ≥pT3a PCa prediction (from 0.73 to 0.86, p = 0.04 in the overall cohort). The impact of PI-RADS v2 assessment category is reflected in a nomogram derived on the basis of our cohort.

CONCLUSIONS

In our cohort, low PI-RADS v2 assessment categories of 3 or less confidently ruled out the presence of ≥pT3a PCa irrespective of clinical risk group.

KEY POINTS

• Our analysis of 301 mp-MRI and RARP specimens showed that the addition of PI-RADS v2 assessment categories to clinical parameters improves the exclusion of ≥pT3a (extraprostatic) prostate cancer. • PI-RADS v2 assessment categories of 1 to 3 are useful for excluding ≥pT3a prostate cancer with a NPV of 98%; such patients can be considered as candidates for less invasive approaches. • The ability to exclude ≥pT3a prostate cancer may improve confidence in choosing nerve-sparing surgery or in avoiding pelvic nodal dissections, and similarly for patients undergoing radiotherapy, in adopting short-course adjuvant hormonal therapy or foregoing prophylactic nodal irradiation.

Role of multiparametric magnetic resonance imaging for patients under active surveillance for prostate cancer: a systematic review with diagnostic meta-analysis

BACKGROUND

The use of multiparametric magnetic resonance imaging (mpMRI) in the setting of patients under active surveillance (AS) is promising. In this systematic-review we aimed to analyse the role of mpMRI in patients under AS.

METHODS

A comprehensive literature research for English-language original and review articles, recently published, was carried out using Medline, Scopus and Web of sciences databases until 30 October 2017. The following MeSH terms were used: 'active surveillance', 'prostate cancer', 'multiparametric magnetic resonance imaging'. A diagnostic meta-analysis was performed for 3.0 T mpMRI in predicting disease re-classification.

RESULTS

In total, 226 studies were selected after research and after removal of duplicates. After analysis on inclusion criteria, 43 studies were identified as eligible for this systematic review with a total of 6,605 patients. The timing of MRI during follow-up of AS differed from all studies like criteria for inclusion in the AS protocol. Overall, there was a low risk of bias across all studies. The diagnostic meta-analysis for 1.5 tesla showed a sensitivity of 0.60, negative predictive value (NPV) of 0.75 and a hierarchical summary receiving operating curve (HSROC) of 0.74 while for 3.0 tesla mpMRI a sensitivity of 0.81, a NPV of 0.78 and a HSROC of 0.83.

CONCLUSIONS

Overall, the available evidence suggests that both 1.5 or 3.0 Tesla mpMRI are a valid tool to monitor progression during AS follow-up, showing good accuracy capabilities in detecting PCa re-classification. However, the modality to better define what means 'disease progression' on mpMRI must be further evaluated.

The role of Prostate Imaging Reporting and Data System score in Gleason 3 + 3 active surveillance candidates enrollment: a diagnostic meta-analysis

BACKGROUND

The contemporary active surveillance (AS) criteria may result in an unsatisfactory misclassification rate, which may delay curative treatment for prostate cancer patients. The magnetic resonance imaging (MRI), not included in any AS criteria, provides useful information for prostate cancer diagnosis. Our goal is to evaluate the diagnostic performance of Prostate Imaging Reporting and Data Systems (PI-RADS) score, a standardized MRI reporting system, in AS candidates enrollment.

METHODS

We searched Cochrane CENTRAL, PubMed, and Embase for pertinent studies through June 2018. The standard methods recommended for meta-analyses of diagnostic evaluation were employed. We draw the summary receiver operating characteristic (SROC) curve. Meta-regression analysis was performed to evaluate the effects of confounding factors.

RESULTS

From the resulting 168 studies, 5 provided the diagnostic data on PI-RADS score and pathological results; 834 patients were included. All AS candidates in these studies were defined by Prostate Cancer Research International: Active Surveillance (PRIAS) criterion. The pooled estimates of PI-RADS 4 or 5 on adverse pathological features at radical prostatectomy (RP) among AS candidates were: sensitivity, 0.77 (95% confidence interval (CI), 0.71-0.82); specificity, 0.63 (95% CI, 0.55-0.71); positive predictive value, 0.72 (95% CI, 0.64-0.79); negative predictive value, 0.68 (95% CI, 0.63-0.73); and diagnostic odds ratio, 6 (95% CI, 4-8). The SROC curve was positioned toward the desired upper left corner of the curve, the area under the curve was 0.77 (95% CI, 0.73-0.80). The P-value for heterogeneity was <0.01. The pathological outcomes and endorectal coils contributed to the heterogeneity of sensitivity. The evidences supporting the advantage of PI-RADS v2 over v1 were not sufficient yet.

CONCLUSION

AS candidates with PI-RADS 4 or 5 may be unsuitable for AS even though they fulfill current AS criteria. Those with PI-RADS 3 or less indicated relative safety for AS enrollment.

Combined Analysis of Biparametric MRI and Prostate-Specific Antigen Density: Role in the Prebiopsy Diagnosis of Gleason Score 7 or Greater Prostate Cancer

OBJECTIVE

The objective of our study was to investigate the diagnostic performance of prebiopsy biparametric MRI (bpMRI) and prostate-specific antigen density (PSAD) for Gleason score (GS) 7 or greater prostate cancer (PCa).

MATERIALS AND METHODS

Sixty-eight consecutive patients who underwent prebiopsy bpMRI and biopsy were included. Pathologic results of systemic and targeted biopsies were the reference standard. Qualitative analyses comprised Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) and modified PI-RADSv2 (mPI-RADSv2). Quantitative analyses comprised mean apparent diffusion coefficient (ADC) of tumor, 10th percentile ADC of tumor, mean ADC ratio (ADCR) between benign tissues and PCa, and 10th percentile ADCR between benign tissues and PCa. The AUCs of the following combined models for GS 7 or greater PCa were investigated: model 1, PSAD and PI-RADSv2; model 2, PSAD and mPI-RADSv2; model 3, PSAD and mean ADC; model 4, PSAD and 10th percentile ADC; model 5, PSAD and mean ADCR; and model 6, PSAD and 10th percentile ADCR.

RESULTS

The rate of GS 7 or greater PCa was 45.6% (31/68). AUCs of bpMRI parameters were 0.816 for PI-RADSv2, 0.838 for mPI-RADSv2, 0.820 for mean ADC, 0.823 for 10th percentile ADC, 0.780 for mean ADCR, and 0.763 for 10th percentile ADCR (p > 0.05 in all comparisons), whereas AUCs of prostate-specific antigen (PSA)-based parameters were 0.650 for PSA and 0.745 for PSAD (PSA vs PSAD, p = 0.017). AUCs of the combined models from 1 to 6 were 0.860, 0.880, 0.837, 0.844, 0.811, and 0.806, respectively, for biopsy GS 7 or greater PCa (p > 0.05 in all comparisons).

CONCLUSION

Combined analysis of prebiopsy bpMRI and PSAD is useful for identifying GS 7 or greater PCa.

Multiparametric Magnetic-Resonance to Confirm Eligibility to an Active Surveillance Program for Low-Risk Prostate Cancer: Intermediate Time Results of a Third Referral High Volume Centre Active Surveillance Protocol

BACKGROUND

To evaluate the role of confirmatory multiparametric magnetic resonance imaging (mpMRI) of the prostate at the time of Active Surveillance (AS) enrollment to reduce disease misclassification.

MATERIALS

From 2012 to 2016, 383 patients with low-risk disease respecting Prostate Cancer Research International AS criteria underwent confirmatory 1.5-T mpMRI. AS was proposed to patients with Prostate Imaging and Report and Data System (PI-RADS) score ≤3 and no extraprostatic extension (EPE), whereas patients with PI-RADS score ≥4 and/or EPE were treated actively. Kaplan-Meier analyses quantified progression-free survival (PFS) in patients enrolled in the AS program. Logistic regression analyses tested the association between confirmatory mpMRI and clinically significant prostate cancer (csPCa) at radical prostatectomy (RP). Diagnostic performance of mpMRI was calculated in patients submitted to immediate RP.

RESULTS

PFS rate was 99, 90 and 86% at 1, 2 and 3 years respectively. At multivariable analysis, PI-RADS 3, PI-RADS 4, PI-RADS 5 and EPE increased the probability of having csPCa at immediate RP (PI-RADS 3 [OR] 1.2, p = 0.26; PI-RADS 4 [OR] 5.1, p = 0.02; PI-RADS 5 [OR] 6.7; p = 0.009; EPE [OR] 11.8, p < 0.001). Confirmatory mpMRI showed sensibility, specificity, positive predictive value and negative predictive value of 85, 55, 68 and 76% respectively.

CONCLUSIONS

MpMRI at the time of AS enrollment reduces the misclassification rate of csPCa. We suggest to perform target biopsies in patients with PI-RADS score 3 and 4 lesions.

Magnetic resonance imaging in active surveillance-a modern approach

In recent years, active surveillance has been increasingly adopted as a conservative management approach to low and sometimes intermediate risk prostate cancer, to avoid or delay treatment until there is evidence of higher risk disease. A number of studies have investigated the role of multiparametric magnetic resonance imaging (mpMRI) in this setting. MpMRI refers to the use of multiple MRI sequences (T2-weighted anatomical and functional imaging which can include diffusion-weighted imaging, dynamic contrast enhanced imaging, spectroscopy). Each of the parameters investigates different aspects of the prostate gland (anatomy, cellularity, vascularity, etc.). In addition to a qualitative assessment, the radiologist can also extrapolate quantitative imaging biomarkers from these sequences, for example the apparent diffusion coefficient from diffusion-weighted imaging. There are many different types of articles (e.g., reviews, commentaries, consensus meetings, etc.) that address the use of mpMRI in men on active surveillance for prostate cancer. In this paper, we compare original articles that investigate the role of the different mpMRI sequences in men on active surveillance for prostate cancer, in order to discuss the relative utility of the different sequences, and combinations of sequences. We searched MEDLINE/PubMed for manuscripts published from inception to 1^st December 2017. The search terms used were (prostate cancer or prostate adenocarcinoma or prostatic carcinoma or prostate carcinoma or prostatic adenocarcinoma) and (MRI or NMR or magnetic resonance imaging or mpMRI or multiparametric MRI) and active surveillance. Overall, 425 publications were found. All abstracts were reviewed to identify papers with original data. Twenty-five papers were analysed and summarised. Some papers based their analysis only on one mpMRI sequence, while others assessed two or more. The evidence from this review suggests that qualitative assessments and quantitative data from different mpMRI sequences hold promise in the management of men on active surveillance for prostate cancer. Both qualitative and quantitative approaches should be considered when assessing mpMRI of the prostate. There is a need for robust studies assessing the relative utility of different combinations of sequences in a systematic manner to determine the most efficient use of mpMRI in men on active surveillance.

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.