Score 3 prostate lesions: a gray zone for PI-RADS v2

Combination of prostate volume and apparent diffusion coefficient can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies

BACKGROUND

Nowadays, there are many patients who undergo unnecessary prostate biopsies after receiving a prostate imaging reporting and data system (PI-RADS) score of 3. Our purpose is to identify cutoff values of the prostate volume (PV) and minimum apparent diffusion coefficient (ADCmin) to stratify those patients to reduce unnecessary prostate biopsies.

METHODS

Data from 224 qualified patients who received prostate biopsies from January 2019 to June 2023 were collected. The Mann-Whitney U test was used to compare non-normal distributed continuous variables, which were recorded as median (interquartile ranges). The correlation coefficients were calculated using Spearman's rank correlation analysis. Categorical variables are recorded by numbers (percentages) and compared by χ2 test. Both univariate and multivariate logistic regression analysis were used to determine the independent predictors. The receiver-operating characteristic curve and the area under the curve (AUC) were used to evaluate the diagnostic performance of clinical variables.

RESULTS

Out of a total of 224 patients, 36 patients (16.07%) were diagnosed with clinically significant prostate cancer (csPCa), whereas 72 patients (32.14%) were diagnosed with any grade prostate cancer. The result of multivariate analysis demonstrated that the PV (p < 0.001, odds ratio [OR]: 0.952, 95% confidence interval [95% CI]: 0.927-0.978) and ADCmin (p < 0.01, OR: 0.993, 95% CI: 0.989-0.998) were the independent factors for predicting csPCa. The AUC values of the PV and ADCmin were 0.779 (95% CI: 0.718-0.831) and 0.799 (95% CI: 0.740-0.849), respectively, for diagnosing csPCa. After stratifying patients by PV and ADCmin, 24 patients (47.06%) with "PV < 55 mL and ADCmin < 685 μm2/s" were diagnosed with csPCa. However, only one patient (1.25%) with PV ≥ 55 mL and ADCmin ≥ 685 μm2/s were diagnosed with csPCa.

CONCLUSIONS

In this study, we found the combination of PV and ADCmin can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies. These patients with "PV ≥ 55 mL and ADCmin ≥ 685 μm2/s" may safely avoid prostate biopsies.

Based on PI-RADS v2.1 combining PHI and ADC values to guide prostate biopsy in patients with PSA 4-20 ng/mL

PURPOSE

The study aimed to investigate the diagnostic accuracy of prostate health index (PHI) and apparent diffusion coefficient (ADC) values in predicting prostate cancer (PCa) and construct a nomogram for the prediction of PCa and clinically significant PCa (CSPCa) in Prostate Imaging-Reporting and Data System (PI-RADS) three lesions cohort.

METHODS

This study prospectively enrolled 301 patients who underwent multiparametric magnetic resonance (mpMRI) and were scheduled for prostate biopsy. The receiver operating characteristic curve (ROC) was performed to estimate the diagnostic accuracy of each predictor. Univariable and multivariable logistic regression analysis was conducted to ascertain hidden risk factors and constructed nomograms in PI-RADS three lesions cohort.

RESULTS

In the whole cohort, the area under the ROC curve (AUC) of PHI is relatively high, which is 0.779. As radiographic parameters, the AUC of PI-RADS and ADC values was 0.702 and 0.756, respectively. The utilization of PHI and ADC values either individually or in combination significantly improved the diagnostic accuracy of the basic model. In PI-RADS three lesions cohort, the AUC for PCa was 0.817 in the training cohort and 0.904 in the validation cohort. The AUC for CSPCa was 0.856 in the training cohort and 0.871 in the validation cohort. When applying the nomogram for predicting PCa, 50.0% of biopsies could be saved, supplemented by 6.9% of CSPCa being missed.

CONCLUSION

PHI and ADC values can be used as predictors of CSPCa. The nomogram included PHI, ADC values and other clinical predictors demonstrated an enhanced capability in detecting PCa and CSPCa within PI-RADS three lesions cohort.

PI-RADS upgrading as the strongest predictor for the presence of clinically significant prostate cancer in patients with initial PI-RADS-3 lesions

PURPOSE

Unclear lesions on multiparametric magnetic resonance tomography (mpMRI) are challenging for the indication of biopsy in patients with clinical suspicion of prostate cancer (PCa). The aim of this study is the validation of the detection rate of clinically significant PCa (csPCa) in patients with PI-RADS 3 findings and to determine the appropriate follow-up strategy.

METHODS

In this retrospective single-center study, patients with maximum PI-RADS 3 lesions underwent targeted MRI/ultrasound-fusion biopsy (tPbx) combined with systematic 12-core biopsy (sPbx) and follow-up mpMRI with further control biopsy. We assessed the evolution of MRI findings (PI-RADS, volume of the lesion), clinical parameters and histopathology in follow-up MRI and biopsies. The primary objective is the detection rate of csPCa, defined as ISUP ≥ 2 findings.

RESULTS

A total of 126 patients (median PSA 6.65 ng/ml; median PSA-density (PSAD) 0.13 ng/ml2) were included. The initial biopsy identified low-risk PCa in 24 cases (19%). During follow-up biopsy, 22.2% of patients showed PI-RADS upgrading (PI-RADS > 3), and 29 patients (23%) exhibited a tumor upgrading. Patients with PI-RADS upgrading had a higher risk of csPCa compared to those without PI-RADS upgrading (42.9% vs. 9.18%, p < 0.05). PI-RADS upgrading was identified as an independent predictor for csPCa in follow-up biopsy (OR 16.20; 95% CI 1.17-224.60; p = 0.038).

CONCLUSION

Patients with stable PI-RADS 3 findings may not require a follow-up biopsy. Instead, it is advisable to schedule an MRI, considering that PI-RADS upgrading serves as an independent predictor for csPCa.

Prostate health index can stratify patients with Prostate Imaging Reporting and Data System score 3 lesions on magnetic resonance imaging to reduce prostate biopsies

We aim to evaluate prostate health index as an additional risk-stratification tool in patients with Prostate Imaging Reporting and Data System score 3 lesions on multiparametric magnetic resonance imaging. Men with biochemical or clinical suspicion of having prostate cancer who underwent multiparametric magnetic resonance imaging in two tertiary centers (Queen Mary Hospital and Princess Margaret Hospital, Hong Kong, China) between January 2017 and June 2022 were included. Ultrasound-magnetic resonance imaging fusion biopsies were performed after prostate health index testing. Those who only had Prostate Imaging Reporting and Data System score 3 lesions were further stratified into four prostate health index risk groups and the cancer detection rates were analyzed. Out of the 747 patients, 47.3% had Prostate Imaging Reporting and Data System score 3 lesions only. The detection rate of clinically significant prostate cancer in this group was 15.0%. The cancer detection rates of clinically significant prostate cancer had statistically significant differences 5.3% in prostate health index <25.0, 7.4% in prostate health index 25.0-34.9, 17.9% in prostate health index 35.0-54.9, and 52.6% in prostate health index ≥55.0 (P < 0.01). Among the patients, 26.9% could have avoided a biopsy with a prostate health index <25.0, at the expense of a 5.3% risk of missing clinically significant prostate cancer. Prostate health index could be used as an additional risk stratification tool for patients with Prostate Imaging Reporting and Data System score 3 lesions. Biopsies could be avoided in patients with low prostate health index, with a small risk of missing clinically significant prostate cancer.

Management Strategy for Prostate Imaging Reporting and Data System Category 3 Lesions

PURPOSE OF REVIEW

Prostate Imaging Reporting and Data System (PI-RADS) category 3 lesions present a clinical dilemma due to their uncertain nature, which complicates the development of a definitive management strategy. These lesions have an incidence rate of approximately 22-32%, with clinically significant prostate cancer (csPCa) accounting for about 10-30%. Therefore, a thorough evaluation is warranted.

RECENT FINDINGS

This review highlights the need for radiology peer review, including the confirmation of dynamic contrast-enhanced (DCE) compliance, as the initial step. Additional MRI models such as VERDICT or Tofts need to be verified. Current evidence shows that imaging and clinical indicators can be used for risk stratification of PI-RADS 3 lesions. For low-risk lesions, a safety net monitoring approach involving annual repeat MRI can be employed. In contrast, lesions deemed potentially risky based on prostate-specific antigen density (PSAD), 68 Ga-PSMA PET/CT, MPS, Proclarix, or AI/machine learning models should undergo biopsy. It is recommended to establish a multidisciplinary team that takes into account factors such as age, PSAD, prostate, and lesion size, as well as previous biopsy pathological findings. Combining expert opinions, clinical-imaging indicators, and emerging methods will contribute to the development of management strategies for PI-RADS 3 lesions.

Results of fusion prostate biopsy comparing with cognitive and systematic biopsy

PURPOSE

Our study aims to determine whether there are differences in the degree of detection of prostate cancer (PCa) and CsPCa between fusion prostate biopsy (FPB), cognitive biopsy (PCB), and randomized, systematic biopsy (SB).

METHODS

A retrospective analysis was carried out of 195 patients with suspected PCa at the San Cecilio University Clinical Hospital in Granada who underwent a prostate biopsy between January and December 2021. Patients were divided into three groups: group 1, patients undergoing FPB transperineally with ultrasound BK 3000 (N = 87); group 2, PCB (N = 59) transperineally; and group 3, transrectal SB (N = 49), the latter two, with an ultrasound BK Specto.

RESULTS

We found differences in favor of image-directed biopsies (FPB and PCB) with a percentage of positive biopsies of 52.8% and 50%, respectively, compared to 41.4% with SB, but without these differences being significant. Given the controversy in performing prostate biopsies in PI-RADS 3 lesions reported in the literature, a subanalysis was performed excluding the FPB performed for PI-RADS 3 lesions (PI-RADS 4 and 5 are included), finding significant differences when comparing FPB with PCB and SB (group 1, 64% vs group 2, 45.8%; p = 0.05) (group 1, 64% vs group 3, 42.9%; p = 0.035).

CONCLUSION

With the results obtained in our series, we conclude that the finding of a PI-RADS 3 lesion in mpMRI should not be an absolute criterion to indicate prostate biopsy. On the other hand, for PI-RADS 4 and 5 lesions, FPB is recommended, which in this case turns out to be superior to PCB and SB.

PI-RADS 3 lesions: a critical review and discussion of how to improve management

Since the publication of PI-RADS v1 in 2012, the debate regarding the question of how to manage PI-RADS 3 lesions has been mostly unsolved. However, based on our review of the current literature we discuss possible solutions and improvements to the original classification, factors such as PSAD (Prostate Specific Antigen Density), age, and tumor volume, in the decision of whether to proceed with a biopsy or not.

Study of iron metabolism based on T2* mapping sequences in PI-RADS 3 prostate lesions

Introduction

Prostate cancer is one of the most common malignant tumors in Chinese men, which is rich in iron metabolic activity and is closely related to all stages of prostate cancer progression. Since the current diagnostic methods are insufficient, we aimed to evaluate the value of quantitative T2 star values from the T2* mapping sequences in multiparametric magnetic resonance imaging (mpMRI) in the diagnosis and grading of PI-RADS 3 prostate cancer (PCa).

Methods

We prospectively enrolled patients with PCa or benign prostatic hyperplasia (BPH) admitted to our hospital from January 2021 to November 2022. Imaging indicators, including the T2* value and apparent diffusion coefficient (ADC) value, were collected, and enzyme-linked immunosorbent assays (ELISAs) were used to measure the levels of proteins involved in iron metabolism in the patients. ROC curves were drawn to explore whether the T2* value could be used for the diagnosis and grading of PCa.

Results

We found that three iron metabolism indexes, ferritin, hepcidin, and the ferric ion (Fe), and the T2* value were significantly different between the PCa group and BPH group and between the low International Society of Urology Pathology (ISUP) group (ISUP ≤ 2) and the high ISUP group (ISUP>2). Additionally, there was a significant correlation between the levels of these three indicators and the T2* value. Further ROC analysis showed that the levels of iron metabolism-related indexes and T2* values performed well in diagnosing and grading PCa.

Discussion

The T2* value has good value in detecting and predicting the grade of prostate cancer and can reflect the iron metabolism of the tumor, which could provide a foundation for the diagnosis and grading of PCa in the future.

The function of Prostate Health Index in detecting clinically significant prostate cancer in the PI-RADS 3 population: a multicenter prospective study

PURPOSE

The purpose of this study is to identify patients in the prostate imaging reporting and data system (PI-RADS) 3 population who need biopsy by using prostate health index (PHI) and other clinical parameters in order to avoid unnecessary biopsies.

METHODS

A total of 302 patients from four hospital were enrolled, and 92 patients with PI-RADS 3 were included finally. All patients were biopsy-naïve and had suspicion of prostate cancer (PCa) with PSA level in 4-20 ng/ml and a normal digital rectal exam. Univariable and stepwise forward multivariable logistic regression analyses were used to evaluated the risk factors. The sensitivity, specificity, and positive and negative predictive values of different cut-off value of PHI were calculated for the diagnosis of clinically significant prostate cancer (CSPCa).

RESULTS

The overall patient's mean age was 65.65 ± 9.55 years, median PSA was 7.68 (5.28-12.07) ng/ml and median PHI was 43.80 (33.09-64.69). PCa was identified in 32.61% (30/92) of PI-RADS 3 and CSPCa was identified in 28.26% (26/92) of PI-RADS 3. The risk factors for detecting PCa and CSPCa in multivariable regression analysis were age and PHI. When the biopsy was restricted to those PHI ≥ 43.5, 42.39% unnecessary biopsied could avoid. The sensitivity, specificity, positive predictive value and negative predictive value for the detection of CSPCa in the PHI ≥ 43.5 were 92.31%, 63.64%, 50% and 95.45% respectively.

CONCLUSION

The inclusion of PHI in the diagnosis of the PI-RADS 3 population may avoid many unnecessary biopsies. The multivariable models could increase the detection of cancer.

Development and external validation of a novel nomogram to predict prostate cancer in biopsy-naïve patients with PSA <10 ng/ml and PI-RADS v2.1 = 3 lesions

OBJECTIVE

To develop and externally validate a novel nomogram in biopsy-naïve patients with prostate-specific antigen (PSA) <10 ng/ml and PI-RADS v2.1 = 3 lesions.

METHODS

We retrospectively collected 307 men that underwent initial biopsy from October 2015 to January 2022 in Cohort 1 (The First Affiliated Hospital of Soochow University). External cohort (Cohort 2, Kunshan Hospital) included 109 men that met our criteria from July 2016 to June 2021. By Slicer-3D Software, the volume of all lesions was divided into two subgroups (PI-RADS v2.1 = 3a and 3b). Logistic regression analysis was performed to screen for variables and construct nomogram by analyzing clinical data from Cohort 1. Receiver operating characteristics curve analysis, calibration plot and decision curve analysis (DCA) were plotted to validate the nomogram in external cohort.

RESULTS

A total of 70 (22.8%) patients was diagnosed with prostate cancer in Institution 1. Among them, 34 (11.1%) had clinically significant prostate cancer (csPCa). Age, prostate-specific antigen density, digital rectal examination, PI-RADS v2.1 = 3 subgroups (3a and 3b) and apparent diffusion coefficient (ADC, <750 mm² /s) were predictive factors for prostate cancer (PCa) and csPCa. High area under the curve of the nomogram was found in Cohort 1 and Cohort 2 for PCa (0.857 vs. 0.850) and for csPCa (0.896 vs. 0.893). Calibration curves showed excellent agreement between the predicted probability and actual risk for the models in internal and external validation. The DCA demonstrated net benefit of our nomogram.

CONCLUSION

Until now, this is the first nomogram that predicts PCa and csPCa in biopsy-naïve patients with PSA <10 ng/ml and PI-RADS v2.1 = 3 lesions. Furthermore, PI-RADS v2.1 = 3 subgroups were considered to be an independent risk factor in our model. Our nomogram may assist urologists in biopsy decision making for these so-called "double gray zone" patients.

New Diagnostic Model for Clinically Significant Prostate Cancer in Biopsy-Naïve Men With PIRADS 3

Purpose

The aim of this study was to explore a new model of clinical decision-making to predict the occurrence of clinically significant prostate cancer (csPCa).

Patients and Methods

The demographic and clinical characteristics of 152 patients were recorded. Prostate-specific antigen (PSA), PSA density (PSAD), adjusted PSAD of peripheral zone (aPSADPZ), and peripheral zone volume ratio (PZ ratio) were calculated and subjected to receiver operating characteristic (ROC) curve analysis. The calibration and discrimination abilities of new nomograms were verified with calibration curve and area under the ROC curve (AUC). The clinical benefits of these models were evaluated by decision curve analysis and clinical impact curves.

Results

The AUCs of PSA, PSAD, aPSADPZ, and PZ ratio were 0.521, 0.645, 0.745, and 0.717 for prostate cancer (PCa) diagnosis, while the corresponding values were 0.590, 0.678, 0.780, and 0.731 for csPCa diagnosis, respectively. All nomograms displayed higher net benefit and better overall calibration than the scenarios for predicting the occurrence of csPCa. The new model significantly improved the diagnostic accuracy of csPCa (0.865 vs. 0.741, p = 0.0284) compared with the base model. In addition, the new model was better than the base model for predicting csPCa in the low or medium probability while the number of patients with csPCa predicted by the new model was in good agreement with the actual number of patients with csPCa in the high-risk threshold.

Conclusions

This study demonstrates that aPSADPZ has a higher predictive accuracy for csPCa diagnosis than the conventional indicators. Including aPSADPZ, PZ ratio, and age can improve csPCa diagnosis and avoid unnecessary biopsies.

Considering Predictive Factors in the Diagnosis of Clinically Significant Prostate Cancer in Patients with PI-RADS 3 Lesions

The use of multi-parametric magnetic resonance imaging (mpMRI) in conjunction with the Prostate Imaging Reporting and Data System (PI-RADS) is standard practice in the diagnosis, surveillance, and staging of prostate cancer. The risk associated with lesions graded at a PI-RADS score of 3 is ambiguous. Further characterization of the risk associated with PI-RADS 3 lesions would be useful in guiding further work-up and intervention. This study aims to better characterize the utility of PI-RADS 3 and associated risk factors in detecting clinically significant prostate cancer. From a prospectively maintained IRB-approved dataset of all veterans undergoing mpMRI fusion biopsy at the Southeastern Louisiana Veterans Healthcare System, we identified a cohort of 230 PI-RADS 3 lesions from a dataset of 283 consecutive UroNav-guided biopsies in 263 patients from October 2017 to July 2020. Clinically significant prostate cancer (Gleason Grade ≥ 2) was detected in 18 of the biopsied PI-RADS 3 lesions, representing 7.8% of the overall sample. Based on binomial analysis, PSA densities of 0.15 or greater were predictive of clinically significant disease, as was PSA. The location of the lesion within the prostate was not shown to be a statistically significant predictor of prostate cancer overall (p = 0.87), or of clinically significant disease (p = 0.16). The majority of PI-RADS 3 lesions do not represent clinically significant disease; therefore, it is possible to reduce morbidity through biopsy. PSA density is a potential adjunctive factor in deciding which patients with PI-RADS 3 lesions require biopsy. Furthermore, while the risk of prostate cancer for African-American men has been debated in the literature, our findings indicate that race is not predictive of identifying prostate cancer, with comparable Gleason grade distributions on histology between races.

Pathological features of Prostate Imaging Reporting and Data System (PI-RADS) 3 MRI lesions in biopsy and radical prostatectomy specimens

OBJECTIVE

To assess the whole pathology spectrum of Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions, identified on magnetic resonance imaging, using systematic (SB), targeted biopsy (TB) and radical prostatectomy (RP) specimen analysis.

METHODS

From a prospective database of patients undergoing RP after a combination of SB (median 12 cores) and fusion TB (median 3 cores), we included 150 PI-RADS 3 cases. Clinically significant prostate cancer (csPCa) was defined by a Grade Group 2 or more. The primary endpoints were unfavourable features in RP specimens.

RESULTS

Targeted biopsy was negative in 20.7% of patients. Final Grade Group 3 or more and a pT3 stage was reported in 36.7% and 38.7% of RP specimens. The upgrading rate was 38.2% between biopsy and RP specimens. The concordance rate between Grade Group on TB and RP was only 38.0%. The two independent predictive factors for unfavourable disease (pT3-4 and/or final Grade Group 3-5) were prostate-specific antigen density (PSAD; P = 0.001) and presence of csPCa on TB (odds ratio 3.7; P = 0.001). The risk of unfavourable disease was increased 2.3-fold and 5.8-fold, respectively, for patients with a PSAD between 0.15 and 0.20, and a PSAD >0.20 ng/mL/g. The 5-year biochemical recurrence-free survival rate was 93.2%.

CONCLUSIONS

PI-RADS 3 lesions exhibited aggressive features in almost 40% of cases. PSAD and presence of csPCa on TB are independent predictive factors for high-grade and/or extraprostatic disease. A combination of SB and TB improve grade prediction compared to use of TB alone.

Can high b-value 3.0 T biparametric MRI with the Simplified Prostate Image Reporting and Data System (S-PI-RADS) be used in biopsy-naïve men?

OBJECTIVE

To analyze the clinical value of high b-value 3.0 T biparametric magnetic resonance with the Simplified Prostate Image Reporting and Data System (S-PI-RADS) in biopsy-naïve men.

METHODS

A retrospective analysis of the data of 224 patients who underwent prostate biopsy (cognitive fusion targeted biopsy combined with systematic biopsy) after a high b-value 3.0 T magnetic resonance examination at Haikou Hospital from July 2018 to July 2020 was performed. Two radiologists performed multi-parameter magnetic resonance imaging (mp-MRI) with the prostate imaging report and data system version 2 (PI-RADS v2) and biparametric magnetic resonance imaging (bp-MRI) with the simplified prostate image reporting and data system (S-PI-RADS). The detection efficacy of the two regimens was evaluated by classifying prostate cancer (PCa) and clinically significant prostate cancer (csPCa) according to pathology, and the statistical significance of the differences between the two regimens was determined by Z-test.

RESULTS

The area under the receiver operating curve (AUC) values of mp-MRI based on PI-RADS v2 and bp-MRI based on S-PI-RADS to detect PCa were 0.905 and 0.892, respectively, while the AUC values for the detection of csPCa were 0.919 and 0.906, respectively. There was no statistically significant difference between the two tests (Z values were 0.909 and 1.145, p > 0.05).

CONCLUSION

There was no significant difference in the detection efficacy of high b-value bp-MRI based on the S-PI-RADS score for prostate cancer and clinically significant prostate cancer compared with the standard PI-RADS v2 score with mp-MRI protocols, which can be applied clinically.

The use of 29 MHz transrectal micro-ultrasound to stratify the prostate cancer risk in patients with PI-RADS III lesions at multiparametric MRI: A single institutional analysis

INTRODUCTION

Magnetic Resonance Imaging (MRI) has emerged as the most accurate diagnostic tool, showing a high sensitivity in the diagnosis of clinically significant prostate cancer (csCaP). However only a minority of patients with a PI-RADS 3 lesion at multiparametric magnetic resonance imaging (MRI) are diagnosed with csCaP. The aim of the current study was to assess whether high resolution micro-ultrasound (microUS) could help in sub-stratifying the risk of csCaP in this specific population.

MATERIAL AND METHODS

We retrospectively analyzed the records of 111 consecutive patients scheduled for a prostate biopsy with at least 1 PI-RADS 3 lesions at MRI. We excluded patients with a PIRADS >3 lesion, even if they had a coexisting PIRADS 3 lesions. MicroUS was performed in all patients before prostate biopsy by an operator blind to MRI results. The Prostate Risk Identification using MicroUS (PRI-MUS) protocol was used to assess the risk of CaP and csCaP. All patients received both targeted and systematic biopsies. The primary endpoint was to determine the diagnostic accuracy of microUS in detection of csCaP in patients with a PI-RADS 3 lesion at MRI. Specifically, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of microUS were determined. Multivariable logistic regression models (MLRMs) were fitted to identify predictors of CaP. The diagnostic accuracy was reported as area under the receiver operator characteristic (ROC) curve.

RESULTS

Overall, 43 patients (38.7%) harboured CaP and 22 (20%) csCaP. MicroUS showed a high sensitivity and negative predictive value (100%), while its specificity and positive predictive value were 33.7% and 27.2%, respectively. Among patients without lesions at microUS, 25 (83.3%) did not harbour CaP, while 5 (16.7%) patients were diagnosed with a Gleason score 6 CaP, with no patients harbouring csCaP. Using microUS, the csCaP detection would have remained 100%, while reducing the detection of insignificant CaP of a 23.8% extent (n = 5). In MLRMs, lesion identified at microUS and continuously-coded PSAd were independent predictors of CaP. The accuracy of a model including PRI-MUS score, digital rectal examination (DRE), PSA density, age and family history was 0.744 (95% CI: 0.645 - 0.843).

CONCLUSION

In our single-institutional retrospective study, microUS was potentially capable to stratify the presence of CaP in patients with an equivocal MRI. Further prospective studies on larger populations are needed to validate our results.

Simplified PI-RADS (S-PI-RADS) for biparametric MRI to detect and manage prostate cancer: What urologists need to know

Biparametric magnetic resonance imaging (bpMRI) of the prostate has emerged as an alternative to multiparametric MRI (mpMRI) for the detection of clinically significant prostate cancer (csPCa). However, while the Prostate Imaging Reporting and Data System (PI-RADS) is widely known for mpMRI, a proper PI-RADS for bpMRI has not yet been adopted. In this review, we report the current status and the future directions of bpMRI, and propose a simplified PI-RADS (S-PI-RADS) that could help radiologists and urologists in the detection and management of PCa.

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.

Equivocal PI-RADS Three Lesions on Prostate Magnetic Resonance Imaging: Risk Stratification Strategies to Avoid MRI-Targeted Biopsies

We aimed to investigate the relation between largest lesion diameter, prostate-specific antigen density (PSA-D), age, and the detection of clinically significant prostate cancer (csPCa) using first-time targeted biopsy (TBx) in men with Prostate Imaging-Reporting and Data System (PI-RADS) 3 index lesions. A total of 292 men (2013-2019) from two referral centers were included. A multivariable logistic regression analysis was performed. The discrimination and clinical utility of the built model was assessed by the area under the receiver operation curve (AUC) and decision curve analysis, respectively. A higher PSA-D and higher age were significantly related to a higher risk of detecting csPCa, while the largest index lesion diameter was not. The discrimination of the model was 0.80 (95% CI 0.73-0.87). When compared to a biopsy-all strategy, decision curve analysis showed a higher net benefit at threshold probabilities of ≥2%. Accepting a missing ≤5% of csPCa diagnoses, a risk-based approach would result in 34% of TBx sessions and 23% of low-risk PCa diagnoses being avoided. In men with PI-RADS 3 index lesions scheduled for first-time TBx, the balance between the number of TBx sessions, the detection of low-risk PCa, and the detection of csPCa does not warrant a biopsy-all strategy. To minimize the risk of missing the diagnosis of csPCa but acknowledging the need of avoiding unnecessary TBx sessions and overdiagnosis, a risk-based approach is advisable.

A radiomics machine learning-based redefining score robustly identifies clinically significant prostate cancer in equivocal PI-RADS score 3 lesions

PURPOSE

PI-RADS score 3 is recognized as equivocal likelihood of clinically significant prostate cancer (csPCa) occurrence. We aimed to develop a Radiomics machine learning (RML)-based redefining score to screen out csPCa in equivocal PI-RADS score 3 category.

METHODS

Total of 263 patients with the dominant index lesion scored PI-RADS 3 who underwent biopsy and/or follow-up formed the primary cohort. One-step RML (RML-i) model integrated radiomic features of T2WI, DWI, and ADC images all together, and two-step RML (RML-ii) model integrated the three independent radiomic signatures from T2WI (T2WI_RS), DWI (DWI_RS), and ADC (ADC_RS) separately into a regression model. The two RML models, as well as T2WI_RS, DWI_RS, and ADC_RS, were compared using the receiver operating characteristic-derived area under the curve (AUC), calibration plot, and decision-curve analysis (DCA). Two radiologists were asked to give a subjective binary assessment, and Cohen's kappa statistics were calculated.

RESULTS

A total of 59/263 (22.4%) csPCa were identified. Inter-reader agreement was moderate (Kappa = 0.435). The AUC of RML-i (0.89; 95% CI 0.88-0.90) is higher (p = 0.003) than that of RML-ii (0.87; 95% CI 0.86-0.88). The DCA demonstrated that the RML-i and RML-ii significantly improved risk prediction at threshold probabilities of csPCa at 20% to 80% compared with doing-none or doing-all by PI-RADS score 3 or stratifying by separated DWI_RS, ADC_RS, or T2WI_RS.

CONCLUSION

Our RML models have the potential to predict csPCa in PI-RADS score 3 lesions, thus can inform the decision making process of biopsy.

Round table: arguments in supporting abbreviated or biparametric MRI of the prostate protocol

Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 update, in the attempt to improve clinical guidelines for multiparametric magnetic resonance imaging (mpMRI) of the prostate, has clear limitations. The role of dynamic contrast-enhanced sequences is not defined, precise guidance on the clinical management (biopsy or clinical surveillance) for score 3 lesions [equivocal for clinical significant prostate cancer (sPCa)] is not offered and criteria for lesions interpretation remain difficult and subjective. We report criteria and arguments in supporting the use of abbreviated or biparametric prostate MRI protocol in clinical practice for detection and management of PCa.

PI-RADS 3 lesions: Does the association of the lesion volume with the prostate-specific antigen density matter in the diagnosis of clinically significant prostate cancer?

INTRODUCTION

Currently, a new subclassification of the Pi-RADS 3 lesions and subgroups is being used: 3a (indolent or low-risk lesions with volume <0.5 ml) and 3b (significant or high-risk lesions with volume ≥0.5 ml). The prostate-specific antigen density (PSAd) has been identified as a diagnostic tool that helps to predict clinically significant prostate cancer (csCaP). The aim of this study is to evaluate the association of the volume of the Pi-RADS 3 lesions and the PSAd in the diagnosis of csCaP.

MATERIAL AND METHODS

We conducted a retrospective study that included prostate biopsies performed using a transperineal approach and guided by ultrasound between 2015 and 2020. csCaP was defined as Gleason score ≥3 + 4. The population was divided into groups according to the Pi-RADS 3 subclassification and the PSAd value. We calculated sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV) of 3b lesions for the detection of high-grade prostate cancer, alone and combined with PSAD groups.

RESULTS

In total, 99 patients with Pi-RADS 3 lesions were included. Forty-three patients were in group 3a and 56, in 3b. Mean PSA was 7.28 ± 2.6 ng/ml. Pi-RADS 3a lesion did not present csCaP but 17.8% of Pi-RADS 3b lesion did. In group 3b with PSAd > 0.15, 62.5% presented csCaP. In those Pi-RADS 3b with PSAd ≤ 0.15, all biopsies were insignificant prostate cancer (isCaP) and 40 biopsies could have been avoided. Considering 3b as positive for csCaP detection, sensitivity was 100%, specificity 48.3%, NPV 17.8%, and PPV 100%. When adding PSAd to group 3b, sensitivity was 100%, specificity was 86.9%, NPV was 62.5%, PPV was 100%. In total, only the subgroup 3b with PSAd > 0.15 presented csCaP and 83.8% biopsies could be avoided.

CONCLUSIONS

In this series, the association of the volume of PIRADS 3 lesion and the PSAd improves specificity and PPV contributing to improve the management of csCaP.

Value of prostate-specific antigen density in negative or equivocal lesions on multiparametric magnetic resonance imaging

OBJECTIVE

The prostate-specific antigen density (PSAD) is an accessory tool when suspecting prostate cancer. Multiparametric magnetic resonance imaging (mpMRI) of the prostate has a high rate of false negatives. The aim of this study is to evaluate the sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) when adding the PSAD and negative or equivocal mpMRI.

MATERIAL AND METHODS

A retrospective study that included prostate biopsies performed using a transperineal approach and guided by ultrasound between 2015 and 2019 was conducted. Clinically significant prostate cancer (csPCa) was defined as Gleason score ≥3+4. The population was divided into groups according to the PSAD level-≤0.15 and >0.15. Sensitivity, specificity, NPV, and PPV of mpMRI were calculated.

RESULTS

A total of 292 patients were included; 12.1% (4/33 patients) of the negative mpMRI group presented csPCa, and only 7 in the equivocal mpMRI group presented csPCa. NPV and sensitivity were 91.15% and 90.5%, respectively. In the positive mpMRI group, 53.7% (96/179) had csPCa, with a PPV of 53.6% and specificity of 55.3%. Of the patients with PSAD ≤0.15, 23 (16.54%) presented csPCa. All of them presented a positive mpMRI. All patients with a negative or equivocal mpMRI and a PSAD ≤0.15 presented a clinically non-significant tumor or benign result. The addition of this tool to mpMRI resulted in 100% sensitivity, 69% specificity, and 34.8% PPV.

CONCLUSION

In our series, PSAD ≤0.15 increased the NPV in negative or equivocal mpMRI, and through this unnecessary prostate biopsies could be avoided.

Role of multiparametric prostate MRI in the management of prostate cancer

INTRODUCTION

Prostate cancer has traditionally been diagnosed by an elevation in PSA or abnormal exam leading to a systematic transrectal ultrasound (TRUS)-guided biopsy. This diagnostic pathway underdiagnoses clinically significant disease while over diagnosing clinically insignificant disease. In this review, we aim to provide an overview of the recent literature regarding the role of multiparametric MRI (mpMRI) in the management of prostate cancer.

MATERIALS AND METHODS

A thorough literature review was performed using PubMed to identify articles discussing use of mpMRI of the prostate in management of prostate cancer.

CONCLUSION

The incorporation of mpMRI of the prostate addresses the shortcomings of the prostate biopsy while providing several other advantages. mpMRI allows some men to avoid an immediate biopsy and permits visualization of areas likely to harbor clinically significant cancer prior to biopsy to facilitate use of MR-targeted prostate biopsies. This allows for reduction in diagnosis of clinically insignificant disease as well as improved detection and better characterization of higher risk cancers, as well as the improved selection of patients for active surveillance. In addition, mpMRI can be used for selection and monitoring of patients for active surveillance and treatment planning during surgery and focal therapy.

Multicenter analysis of clinical and MRI characteristics associated with detecting clinically significant prostate cancer in PI-RADS (v2.0) category 3 lesions

OBJECTIVES

We sought to identify clinical and magnetic resonance imaging (MRI) characteristics in men with the Prostate Imaging - Reporting and Data System (PI-RADS) category 3 index lesions that predict clinically significant prostate cancer (CaP) on MRI targeted biopsy.

MATERIALS AND METHODS

Multicenter study of prospectively collected data for biopsy-naive men (n = 247) who underwent MRI-targeted and systematic biopsies for PI-RADS 3 index lesions. The primary endpoint was diagnosis of clinically significant CaP (Grade Group ≥2). Multivariable logistic regression models assessed for factors associated with clinically significant CaP. The probability distributions of clinically significant CaP based on different levels of predictors of multivariable models were plotted in a heatmap.

RESULTS

Men with clinically significant CaP had smaller prostate volume (39.20 vs. 55.10 ml, P < 0.001) and lower apparent diffusion coefficient (ADC) values (973 vs. 1068 μm²/s, P = 0.013), but higher prostate-specific antigen (PSA) density (0.21 vs. 0.13 ng/ml², P = 0.027). On multivariable analyses, lower prostate volume (odds ratio [OR]: 0.95, 95% confidence interval [CI]: 0.92-0.97), lower ADC value (OR: 0.99, 95% CI: 0.99-1.00), and Prostate-specific antigen density >0.15 ng/ml² (OR: 3.51, 95% CI 1.61-7.68) were independently associated with significant CaP.

CONCLUSION

Higher PSA density, lower prostate volume and ADC values are associated with clinically significant CaP in biopsy-naïve men with PI-RADS 3 lesions. We present regression-derived probabilities of detecting clinically significant CaP based on various clinical and imaging values that can be used in decision-making. Our findings demonstrate an opportunity for MRI refinement or biomarker discovery to improve risk stratification for PI-RADS 3 lesions.

Is it worth carrying out ultrasound-magnetic resonance imaging fusion targeted biopsy on Prostate Imaging Reporting and Data System score 3 prostate lesions?

OBJECTIVES

To evaluate the use of ultrasound-magnetic resonance imaging fusion targeted biopsy for Prostate Imaging Reporting and Data System 3 prostate lesions.

METHODS

We identified 227 patients with prostate-specific antigen levels ≥4 ng/mL who underwent concurrent transrectal ultrasound-guided systemic biopsy and fusion biopsy. Suspicious prostatic lesions were assessed in accordance with Prostate Imaging Reporting and Data System version 2.0. We compared ultrasound-magnetic resonance imaging fusion targeted biopsy and ultrasound-guided biopsy cancer detection rates in Prostate Imaging Reporting and Data System 3 lesions with those in other Prostate Imaging Reporting and Data System score lesions. In Prostate Imaging Reporting and Data System 3 patients, we identified clinically significant prostate cancer risk factors by logistic regression analysis.

RESULTS

In total, 2770 transrectal ultrasound-guided and 867 fusion biopsy cores were obtained; where 332 (12.0%) and 194 (22.4%) cores were prostate cancer-positive, respectively (P < 0.001). The fusion biopsy cancer detection rate (8.0%) in Prostate Imaging Reporting and Data System 3 lesions was similar to that in Prostate Imaging Reporting and Data System 1-2 lesions, but was lower than that of Prostate Imaging Reporting and Data System 4 (30.0%; P < 0.001) and 5 lesions (65.2%; P < 0.001), and ultrasound-guided biopsy (12.0%; P = 0.023). For clinically significant prostate cancer detection, fusion biopsy in Prostate Imaging Reporting and Data System 3 lesions was inferior to that in Prostate Imaging Reporting and Data System 4 and 5 lesions, and non-superior to ultrasound-guided biopsy. Cancer detection rate trends were similar in biopsy-naïve patients. In Prostate Imaging Reporting and Data System 3 patients, prostate-specific antigen density was the only significant predictor of clinically significant prostate cancer.

CONCLUSIONS

The present findings do not support the use of ultrasound-magnetic resonance imaging fusion targeted biopsy for Prostate Imaging Reporting and Data System 3 lesions. Thus, we recommend the use of transrectal ultrasound-guided systemic biopsy for patients with Prostate Imaging Reporting and Data System 3 index lesions.

Diagnostic accuracy of biparametric versus multiparametric prostate MRI: assessment of contrast benefit in clinical practice

PURPOSE

To assess the added value of dynamic contrast-enhanced (DCE) in prostate MR in clinical practice.

METHODS

Two hundred sixty-four patients underwent prostate MRI, with T2 and DWI sequences initially interpreted, prior to full multiparametric magnetic resonance imaging (mpMRI) interpretation using a Likert 1-5 scale. A prospective opinion was given on likely benefit of contrast prior to review of the DCE sequence, and retrospectively following full mpMRI review. The final histology result following targeted and/or systematic biopsy of the prostate was used for outcome purposes.

RESULTS

Biparametric magnetic resonance imaging (bpMRI) and mpMRI were assigned the same score in 86% of cases; when dichotomising to a negative or positive MRI (Likert score ≥ 3), concordance increased to 92.8%. At Likert score ≥ 3 bpMRI detected 89.9% of all cancers and 93.5% clinically significant prostate cancers (csPCa) and mpMRI 90.7% and 94.6%, respectively. mpMRI had fewer false positives than bpMRI (11.4% vs 18.9%) and a lower Likert 3 rate (8.3% vs 17%), conferring higher specificity (74% vs 67%), but similar sensitivity (95% versus 94%) and ROC-AUC (90% vs 89%). At a positive MRI threshold of Likert ≥ 4, mpMRI had a higher sensitivity than bpMRI (89% versus 80%) and detected more csPCa (89.2% versus 79.6%). DCE was prospectively considered of potential benefit in 27.3%, but readers would only recall 11% of patients for DCE sequences, mainly to assess score 3 peripheral zone lesions. Following full mpMRI review, DCE was considered helpful in 28.4% of cases; in 23/75 (30.6%) of these cases this only became apparent after reviewing the sequence, reasons included increased confidence, presence of "safety-net" lesions or inflammatory lesions.

CONCLUSION

BpMRI has equivalent cancer detection rates to mpMRI; however, mpMRI had fewer Likert 3 call rates and increased specificity and was subjectively considered of benefit by readers in 28.4% of cases.

KEY POINTS

• bpMRI has similar cancer detection rates to the full mpMRI protocol at a positive MRI threshold of Likert 3. • mpMRI had fewer intermediate category 3 calls (8.3%) than bpMRI (17%) and fewer false positives than bpMRI (11.4% vs 18.9%), conferring higher specificity (74% vs 67%). • Readers considered DCE beneficial in 28.4% of cases, but in a relatively high number (30.6%) this only became apparent after reviewing the sequence.

The role of gadolinium in magnetic resonance imaging for early prostate cancer diagnosis: A diagnostic accuracy study

Objective

Prostate lesions detected with multiparametric magnetic resonance imaging (mpMRI) are classified for their malignant potential according to the Prostate Imaging-Reporting And Data System (PI-RADS™2). In this study, we evaluate the diagnostic accuracy of the mpMRI with and without gadolinium, with emphasis on the added diagnostic value of the dynamic contrast enhancement (DCE).

Materials and methods

The study was retrospective for 286 prostate lesions / 213 eligible patients, n = 116/170, and 49/59% malignant for the peripheral (Pz) and transitional zone (Tz), respectively. A stereotactic MRI-guided prostate biopsy served as the histological ground truth. All patients received a mpMRI with DCE. The influence of DCE in the prediction of malignancy was analyzed by blinded assessment of the imaging protocol without DCE and the DCE separately.

Results

Significant (CSPca) and insignificant (IPca) prostate cancers were evaluated separately to enhance the potential effects of the DCE in the detection of CSPca. The Receiver Operating Characteristics Area Under Curve (ROC-AUC), sensitivity (Se) and specificity (Spe) of PIRADS-without-DCE in the Pz was 0.70/0.47/0.86 for all cancers (IPca and CSPca merged) and 0.73/0.54/0.82 for CSPca. PIRADS-with-DCE for the same patients showed ROC-AUC/Se/Spe of 0.70/0.49/0.86 for all Pz cancers and 0.69/0.54/0.81 for CSPca in the Pz, respectively, p>0.05 chi-squared test. Similar results for the Tz, AUC/Se/Spe for PIRADS-without-DCE was 0.75/0.61/0.79 all cancers and 0.67/0.54/0.71 for CSPca, not influenced by DCE (0.66/0.47/0.81 for all Tz cancers and 0.61/0.39/0.75 for CSPca in Tz). The added Se and Spe of DCE for the detection of CSPca was 88/34% and 78/33% in the Pz and Tz, respectively.

Conclusion

DCE showed no significant added diagnostic value and lower specificity for the prediction of CSPca compared to the non-enhanced sequences. Our results support that gadolinium might be omitted without mitigating the diagnostic accuracy of the mpMRI for prostate cancer.

Biparametric MRI and 41 sector map for MRI/Transrectal ultrasound fusion biopsy to increase diagnostic accuracy of prostate cancer

Optimizing the number of prostate biopsy (PB) cores in the initial diagnosis of prostate cancer is still an open question. Increasing the number of cores can expectedly lead to a higher cancer detection rate but more frequent, and greater number of adverse effects should be considered. It is necessary to limit the number of PBs, obtained from tumor areas and areas with a high suspect of malignancy. Simplified Prostate Imaging Reporting and Data System (PIRADS) using biparametric MR imaging (bpMRI) protocol identifies 4 categories indicating the management for each one. We suggest targeted biopsy for category 3b [lesion with a volume ≥0.5 cc, homogeneous or inhomogeneous, mild/moderately or markedly hypointense on T2-weighted, hyperintense on high b value diffusion-weighted (DW) imaging and moderately hypointense on apparent diffusion coefficient (ADC) map] and category 4 (homogeneous or heterogeneous lesion intra- or extraglandular, mild/moderately or markedly hypointense on T2-weighted, hyperintense on high b value DW imaging and markedly hypointense on ADC map). For a precise localization of the suspected prostate lesions we used a model of 41 sectors/regions map. BpMRI/Transrectal ultrasound fusion-targeted biopsy and the 41 sectors map represent a valid alternative model to the core biopsy of 10-12 systematic transrectal or transperineal peripheral zone biopsies.

Prostate Imaging Reporting and Data System 3 Category Cases at Multiparametric Magnetic Resonance for Prostate Cancer: A Systematic Review and Meta-analysis

CONTEXT

The Prostate Imaging Reporting and Data System (PI-RADS) 3 score represents a "grey zone" that need to be further investigated to solve the issue of whether to biopsy these equivocal cases or not.

OBJECTIVE

To critically analyze the current evidence on PI-RADS 3 cases. We evaluated the prevalence of PI-RADS 3 cases in the literature and detection rate of prostate cancer (PC) and clinically significant PC (csPC) at biopsy with regard to factors determining these rates.

EVIDENCE ACQUISITION

We searched in the Medline and Cochrane Library database from the literature from January 2009 to January 2019, following the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines.

EVIDENCE SYNTHESIS

A total of 28 studies were included in our analysis (total number of PI-RADS 3 cases: 1759, range 20-187). The prevalence of PI-RADS 3 cases reported in available studies was 17.3% (range 6.4-45.7%). The PC detection rate was 36% (95% confidence interval [CI] 33.8-37.4; range 10.3-55.8%), whereas that of csPC was 18.5% (95% CI 16.6-20.3; range 3.4-46.5%). Detection rates of PC and csPC were found to be similar in men who underwent a target biopsy versus those with a systematic biopsy (23.5% vs 23.9% and 11.4% vs 12.3%, respectively) and lower than the rates achieved with the combined strategy (36.9% and 19.6%, respectively). A prostate-specific antigen density (PSAD) of ≥0.15ng/ml/ml may represent an index to decide whether to submit a PI-RADS 3 case to biopsy.

CONCLUSIONS

In most investigations, PI-RADS 3 cases were not evaluated separately. A PI-RADS 3 lesion remains an equivocal lesion. Evaluation of clinical predictive factors in terms of csPC risk is a main aspect of helping clinicians in the biopsy decision process.

PATIENT SUMMARY

Management of Prostate Imaging Reporting and Data System 3 cases remains an unmet need, and the detection rate of clinically significant prostate cancer (csPC) among this population varies widely. Performing a combined target plus a systematic biopsy yields the highest detection of csPC. A prostate-specific antigen density of lower than 0.15ng/ml/ml may select patients for a follow-up strategy.

Prostate MRI and transperineal TRUS/MRI fusion biopsy for prostate cancer detection: clinical practice updates

This narrative review summarizes the current knowledge about multiparametric and biparametric magnetic resonance imaging of the prostate. This is provided from both a radiological and a urological point of view analyzing the technical aspects of fusion-targeted biopsy using the transperineal approach. We report practical considerations concerning pure cognitive and software-assisted settings, discuss the principal transperineal fusion software now available, and debate the pros and cons of choosing one approach over the other.

Optimizing prostate cancer accumulating model: combined PI-RADS v2 with prostate specific antigen and its derivative data

BACKGROUND

To establish a new accumulating model to enhance the accuracy of prostate cancer (PCa) diagnosis by incorporating prostate-specific antigen (PSA) and its derivative data into the Prostate Imaging-Reporting and Data System version 2 (PI-RADS v2).

METHODS

A total of 357 patients who underwent prostate biopsy between January 2014 and December 2017 were included in this study. All patients had 3.0 T multiparametric magnetic resonance imaging (MRI) and complete laboratory examinations. PI-RADS v2 was used to assess the imaging. PSA, PSA density (PSAD), the free/total PSA ratio (f/t PSA) and the Gleason score (GS) were classified into four-tiered levels, and optimal weights were pursued on these managed levels to build a PCa accumulating model. A receiver operating characteristic curve was generated.

RESULTS

In all, 174 patients (48.7%) had benign prostatic hyperplasia, and 183 (51.3%) had PCa, among whom 149 (81.4%, 149/183) had clinically significant PCa. The established model 6 (PI-RADS v2 + level of PSAD + level of f/t PSA+ level of PSA) had a sensitivity and specificity of 81.4 and 84.5%, respectively, at the cut-off point of 11 in PCa diagnosis. Correspondingly, at the 12 cut-off point, the sensitivity and specificity were 87.7 and 83.0%, respectively, in diagnosing clinically significant PCa. The score of the new accumulating system was significantly different among the defined GS groups (p < 0.001). The mean values and 95% confidence intervals for GS 1-4 groups were 10.20 (9.63-10.40), 12.03 (11.19-12.87), 14.12 (13.60-14.64) and 15.44 (15.09-15.79).

CONCLUSIONS

A new PCa accumulating model may be useful in improving the accuracy of the primary diagnosis of PCa and helpful in the clinical decision to perform a biopsy when MRI results are negative.

A review of optimal prostate biopsy: indications and techniques

Prostate biopsy is the gold standard diagnostic technique for the detection of prostate cancer. Patient selection for prostate biopsy is complex and is influenced by emerging use of prebiopsy imaging. The introduction of the magnetic resonance imaging (MRI)-transrectal ultrasound (TRUS) fusion prostate biopsy has clear advantages over the historical standard of care. There are several biopsy techniques currently utilized with unique advantages and disadvantages. We review and summarize the current body of literature pertaining to when and how a prostate biopsy should be performed. We discuss current recommendations regarding patient selection for biopsy and discuss future directions regarding prebiopsy imaging. We offer a description of the MRI-TRUS fusion biopsy technique and a comparison of many of the currently available fusion software platforms. Articles pertaining to the title were obtained via PubMed index search with relevant keywords supplemented with personal collection of related publications. Prostate biopsy should be considered for patients with gross digital rectal exam (DRE) abnormality, patients with a prostate-specific antigen (PSA) greater than 4 ng/ml, and concomitant risk factors for prostate cancer or patients with lesions identified on multiparametric MRI (mpMRI) with Prostate Imaging Reporting and Data System 2 (PI-RADS2) score of 4 or 5. MRI-TRUS fusion biopsy has demonstrated advantages in cancer detection when compared with TRUS-guided biopsy. There are currently several fusion software platforms available with a variety of biopsy approaches. Future efforts should detail the role of prebiopsy imaging as a triage tool for prostate biopsy. Consensus should be sought regarding the preferred modality of fusion biopsy. Additional data describing each fusion software platform would enable a more rigorous comparison of platform sensitivities.

Effectiveness of the «cognitive» biopsy in the diagnosis of prostate cancer in patients with a previous negative biopsy

INTRODUCTION

Evaluation of the effectiveness of cognitive biopsy (CB) in patients with clinical suspicion of prostate cancer (PC), and at least one negative biopsy (TRB).

MATERIAL AND METHOD

Retrospective study of 144 patients with at least one previous TRB and magnetic resonance imaging (MRI). The MRI nodules were classified based on PI-RADS v2 grouping pZa, pZpl and pZpm as the peripheral zone(PZ), Tza, Tzp and CZ as the transitional zone (TZ), and the AS zones as the anterior zone (AZ). A biopsy was indicated for nodules ≥PI-RADS 3. Uni and multivariate analysis was undertaken (logistic regression) to identify variables relating to a PI-RADS 3 tumour on biopsy.

RESULTS

The median age was 67 (IQR: 62-72) years, the median PSA was 8.2 (IQR: 6.2-12) ng/ml. A nodule was identified on MRI in the PZ in 97 (67.4%) cases, in the TZ in 29 (20.1%), and in the AZ in 41 (28.5%). PC was diagnosed on biopsy in 64 (44%) patients. The cancer rate in the PI-RADS 3 lesions was 17.5% (7/40), in the PI-RADS 4 47.3% (35/73), and in the PI-RADS 5 lesions it was 73.3% (22/29) (p=.0001). Multivariable analysis with variables that could influence the biopsy result in patients with PI-RADS 3: None (age, PSA, number of previous biopsies, rectal examination, PSAD, prostate volume or number of extracted cylinders) behaved as an independent tumour predictor.

CONCLUSIONS

The diagnostic performance of CB in patients with at least one previous negative biopsy was 44%, increasing according to the PI-RADS grade, and low in PI-RADS 3. No clinical variable predictive of cancer was found in patients with PI-RADS 3.

MRI in early prostate cancer detection: how to manage indeterminate or equivocal PI-RADS 3 lesions?

This review focuses on indeterminate lesions on prostate magnetic resonance imaging (MRI), assigned as PI-RADS category 3. The prevalence of PI-RADS 3 index lesion in the diagnostic work-up is significant, varying between one in three (32%) to one in five (22%) men, depending on patient cohort of first biopsies, previously negative biopsies, and active surveillance biopsies. A management strategy must be developed for this group of men with an indeterminate suspicion of having clinically significant prostate cancer (csPCa). Currently available data show that the actual prevalence of csPCa after targeted biopsy in PI-RADS 3 lesions vary between patients groups from one in five (21%) to one in six (16%), depending on previous biopsy status. Although this prevalence is lower in comparison to PI-RADS 4 and PI-RADS 5 lesions, still a considerable proportion of men harbor significant disease. Men with such a PI-RADS 3 lesion should therefore be adequately managed. In general, the clinical approach of using a threshold of PI-RADS ≥4 instead of PI-RADS ≥3 to select MRI for targeted biopsies is not supported by data from our explorative literature search using current definitions of csPCa. A possible adaptation to the threshold of PI-RADS ≥4 in combination with other clinical markers could be considered within an active surveillance protocol, where the balance between the individual risk of missing csPCa and the constant process of repeating prostate biopsies is crucial. In the future, improvements in MR imaging and interpretation, combined with molecular biomarkers and multivariate risk models will all be employed in prostate cancer detection and monitoring. These combinations will aid decision-making in challenging circumstances, such as unclear and diagnostic equivocal results for csPCa at early detection.

Retrospective analysis of the development of PIRADS 3 lesions over time: when is a follow-up MRI reasonable?

PURPOSE

Often PIRADS 3 findings are usually followed up with further MRIs of the prostate. Current guidelines do not state an optimal interval between the initial MRI and the follow-up MRI. The aim of this study was to find out if PIRADS 3 lesions evolve over time and to determine how long the optimal interval between initial MRI and follow-ups should be.

METHODS

In this retrospective study, 141 consecutive patients were included who underwent at least one follow-up MRI after an initial PIRADS 3 finding. Changes in PIRADS score and the interval between the first and the follow-up MRI were recorded. An optimal duration was calculated.

RESULTS

Of all patients, 76.6% had a change from PIRADS 3 to either 2 or 4 in the first follow-up MRI. Reclassifications to PIRADS 4 happened earlier than reclassifications to PIRADS 2 (after 366.5 ± 217.9 days and after 534.2 ± 253.0 days, respectively). An optimal point of time for a follow-up to distinguish between changes to PIRADS 2 versus PIRADS 4 turned out to be 379 days (12.4 months, AUC 0.734, p = 0.0001). Of all patients with a PIRADS 3 lesion 14.8% harboured a prostate carcinoma.

CONCLUSION

Performing follow-up mpMRI rather than immediate biopsy may be beneficial for patients with PIRADS 3, as most lesions can be reclassified after a manageable period of time. Upgrades to PIRADS 4 seem to happen earlier and within fewer follow-ups than downgrades to PIRADS 2. The optimal interval for follow-up MRIs seems to be 12.4 months.

Biparametric MRI of the prostate

Biparametric Magnetic Resonance Imaging (bpMRI) of the prostate combining both morphologic T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) is emerging as an alternative to multiparametric MRI (mpMRI) to detect, to localize and to guide prostatic targeted biopsy in patients with suspicious prostate cancer (PCa). BpMRI overcomes some limitations of mpMRI such as the costs, the time required to perform the study, the use of gadolinium-based contrast agents and the lack of a guidance for management of score 3 lesions equivocal for significant PCa. In our experience the optimal and similar clinical results of the bpMRI in comparison to mpMRI are essentially related to the DWI that we consider the dominant sequence for detection suspicious PCa both in transition and in peripheral zone. In clinical practice, the adoption of bpMRI standardized scoring system, indicating the likelihood to diagnose a clinically significant PCa and establishing the management of each suspicious category (from 1 to 4), could represent the rationale to simplify and to improve the current interpretation of mpMRI based on Prostate Imaging and Reporting Archiving Data System version 2 (PI-RADS v2). In this review article we report and describe the current knowledge about bpMRI in the detection of suspicious PCa and a simplified PI-RADS based on bpMRI for management of each suspicious PCa categories to facilitate the communication between radiologists and urologists.