Reduction of MRI-targeted biopsies in men with low-risk prostate cancer on active surveillance by stratifying to PI-RADS and PSA-density, with different thresholds for significant disease

Management of Patients With a Negative Multiparametric Prostate MRI Examination: AJR Expert Panel Narrative Review

Multiparametric MRI (mpMRI) of the prostate aids risk stratification of patients with elevated PSA levels. Although most clinically significant prostate cancers are detected by mpMRI, insignificant cancers are less evident. Thus, multiple international prostate cancer guidelines now endorse routine use of prostate MRI as a secondary screening test before prostate biopsy. Nonetheless, management of patients with negative mpMRI results (defined as PI-RADS category 1 or 2) remains unclear. This AJR Expert Panel Narrative Review summarizes the available literature on patients with an elevated screening PSA level and a negative prostate mpMRI result and provides guidance for these patients' management. Systematic biopsy should not be routinely performed after a negative mpMRI examination in patients at average risk but should be considered in patients at high risk. In patients who undergo PSA screening rather than systematic biopsy after negative mpMRI, clear triggers should be established for when to perform a repeat MRI examination. Patients with a negative MRI result followed by negative biopsy should follow their health care practitioners' preferred guidelines concerning subsequent PSA screening for the patient's risk level. Insufficient high-level data exist to support routine use of adjunctive serum or urine biomarkers, artificial intelligence, or PSMA PET to determine the need for prostate biopsy after a negative mpMRI examination.

Evaluation of blood and urine based biomarkers for detection of clinically-significant prostate cancer

BACKGROUND

Recognizing the limitations of prostate-specific antigen (PSA) screening and the morbidity of prostate biopsies, several blood- and urine-based biomarkers have been proposed for pre-biopsy risk stratification. These assays aim to reduce the frequency of unnecessary biopsies (i.e., negative or Grade Group 1 [GG1]) while maintaining highly sensitive detection of clinically significant cancer (GG ≥ 2) prostate cancer.

METHODS

We reviewed the literature describing the use of currently available blood- and urine-based biomarkers for detection of GG ≥ 2 cancer, including the Prostate Health Index (PHI), 4Kscore, MyProstateScore (MPS), SelectMDx, ExoDx Prostate Intelliscore (EPI), and IsoPSA. To facilitate clinical application, we focused on the use of biomarkers as a post-PSA secondary test prior to biopsy, as proposed in clinical guidelines. Our outcomes included test performance measures-sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV)-as well as clinical outcomes resulting from biomarker use (i.e., unnecessary biopsies avoided, GG ≥ 2 cancers missed).

RESULTS

Contemporary validation data (2015-2023) reveal that currently available biomarkers provide ~15-50% specificity at a sensitivity of 90-95% for GG ≥ 2 PCa. Clinically, this indicates that secondary use of biomarker testing in men with elevated PSA could allow for avoidance of up to 15-50% of unnecessary prostate biopsies, while preserving detection of 90-95% of GG ≥ 2 cancers that would be detected under the traditional "biopsy all" approach.

CONCLUSIONS

The contemporary literature further supports the proposed role of post-PSA biomarker testing to reduce the use of invasive biopsy while maintaining highly sensitive detection of GG ≥ 2 cancer. Questions remain regarding the optimal application of biomarkers in combination or in sequence with mpMRI.

Cancer Detection Rate and Abnormal Interpretation Rate of Prostate MRI in Patients With Low-Grade Cancer

PURPOSE

The aim of this study was to evaluate the utility of cancer detection rate (CDR) and abnormal interpretation rate (AIR) in prostate MRI for patients with low-grade prostate cancer (PCa).

METHODS

This three-center retrospective study included patients who underwent prostate MRI from 2017 to 2021 with known low-grade PCa (Gleason score 6) without prior treatment. Patient-level highest Prostate Imaging Reporting & Data System (PI-RADS®) score and pathologic diagnosis within 1 year after MRI were used to evaluate the diagnostic performance of prostate MRI in detecting clinically significant PCa (csPCa; Gleason score ≥ 7). The metrics AIR, CDR, and CDR adjusted for pathologic confirmation rate were calculated. Radiologist-level AIR-CDR plots were shown. Simulation AIR-CDR lines were created to assess the effects of different diagnostic performances of prostate MRI and the prevalence of csPCa.

RESULTS

A total of 3,207 examinations were interpreted by 33 radiologists. Overall AIR, CDR, and CDR adjusted for pathologic confirmation rate at PI-RADS 3 to 5 (PI-RADS 4 and 5) were 51.7% (36.5%), 22.1% (18.8%), and 30.7% (24.6%), respectively. Radiologist-level AIR and CDR at PI-RADS 3 to 5 (PI-RADS 4 and 5) were in the 36.8% to 75.6% (21.9%-57.5%) range and the 16.3%-28.7% (10.9%-26.5%) range, respectively. In the simulation, changing parameters of diagnostic performance or csPCa prevalence shifted the AIR-CDR line.

CONCLUSIONS

The authors propose CDR and AIR as performance metrics in prostate MRI and report reference performance values in patients with known low-grade PCa. There was variability in radiologist-level AIR and CDR. Combined use of AIR and CDR could provide meaningful feedback for radiologists to improve their performance by showing relative performance to other radiologists.

Evaluation of Proclarix in the diagnostic work-up of prostate cancer

Objectives

The use of multiparametric magnetic resonance imaging (mpMRI) has been widely adopted in the diagnostic work-up for suspicious prostate cancer (PCa) and is recommended in most current guidelines. However, mpMRI lesions are often indeterminate and/or turn out to be false-positive on prostate biopsy. The aim of this work was to evaluate Proclarix, a biomarker test for the detection of relevant PCa, regarding its diagnostic value in all men before biopsy and in men with indeterminate lesions on mpMRI (PI-RADS 3) during work-up for PCa.

Materials and Methods

Men undergoing mpMRI-targeted and systematic biopsy of the prostate were prospectively enrolled. The Proclarix test was evaluated for the detection accuracy of clinically significant PCa (csPCa) defined as Grade Group ≥ 2 and its association to mpMRI results. Further, Proclarix's performance was also tested when adapted to prostate volume (Proclarix density) and performance compared to PSA density (PSAD).

Results

A total of 150 men with a median age of 65 years and median PSA of 5.8 ng/mL were included in this study. CsPCa was diagnosed in 65 (43%) men. Proclarix was significantly associated with csPCa and higher PI-RADS score (p < 0.001). At the pre-defined cut-off of 10%, Proclarix's sensitivity for csPCa was 94%, specificity 19%, negative predictive value 80% and positive predictive value 47%. Proclarix density showed the highest AUC for the detection of csPCa of 0.77 (95%CI: 0.69-0.85) compared to PSA, PSAD and Proclarix alone. Proclarix was able to identify all six csPCa in men with PI-RADS 3 lesions (n = 28), whereas PSAD missed two out of six. At optimized cut-offs, Proclarix density outperformed PSAD by potentially avoiding 41% of unnecessary biopsies.

Conclusion

Proclarix demonstrates high sensitivity in detecting csPCa but may still result in unnecessary biopsies. However, Proclarix density was able to outperform PSAD and Proclarix and was found to be useful in men with PI-RADS 3 findings by safely avoiding unnecessary biopsies without missing 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.

Clinical and prostate multiparametric magnetic resonance imaging findings as predictors of general and clinically significant prostate cancer risk: A retrospective single-center study

Background

To evaluate the predictive values of Prostate Imaging Reporting and Data System version 2 (PI-RADS v2), prostate-specific antigen (PSA) level, PSA density (PSAD), digital rectal examination findings, and prostate volume, individually and in combination, for the detection of prostate cancer (PCa) in biopsy-naive patients.

Methods

We retrospectively analyzed 630 patients who underwent transrectal systematic prostate biopsy following prostate multiparametric magnetic resonance imaging. A standard 12-core biopsy procedure was performed. Univariate and multivariate analyses were performed to determine the significant predictors of clinically significant cancer but not PCa.

Results

The median age, PSA level, and PSAD were 70 years, 8.6 ng/mL, and 0.18 ng/mL/mL, respectively. A total of 374 (59.4%) of 630 patients were biopsy-positive for PCa, and 241 (64.4%) of 374 were diagnosed with clinically significant PCa (csPCa). The PI-RADS v2 score and PSAD were independent predictors of PCa and csPCa. The PI-RADS v2 score of 5 regardless of the PSAD value, or PI-RADS v2 score of 4 plus a PSAD of <0.3 ng/mL/mL, was associated with the highest csPCa detection rate (36.1%-82.1%). Instead, the PI-RADS v2 score of <3 and PSAD of <0.3 ng/mL/mL yielded the lowest risk of csPCa.

Conclusion

The combination of the PI-RADS v2 score and PSAD could prove to be a helpful and reliable diagnostic tool before performing prostate biopsies. Patients with a PI-RADS v2 score of <3 and PSAD of <0.3 ng/mL/mL could potentially avoid a prostate biopsy.

Evaluating the Utility of Prostate-Specific Antigen Density in Risk Stratification of PI-RADS 3 Peripheral Zone Lesions on Non-Contrast-Enhanced Prostate MRI: An Exploratory Single-Institution Study

Objective This study aimed to explore the potential of prostate-specific antigen density (PSAD) as a supplementary tool for defining high-risk Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions in the peripheral zone on non-contrast-enhanced MRI. This additional stratification tool could supplement the decision-making process for biopsy, potentially helping in identifying higher-risk patients more accurately, minimizing unnecessary procedures in lower-risk patients, and limiting the need for dynamic contrast-enhanced (DCE) scans. Materials and methods Between January 2019 and April 2023, 30 patients with PI-RADS 3 lesions underwent MRI-ultrasound fusion biopsies at our institution. Age and PSAD values were investigated using logistic regression and chi-square automatic interaction detection (CHAID) analysis to discern their predictive value for malignancy. Results The mean patient age was 64.7 years, and the mean PSAD was 0.13 ng/mL2. Logistic regression demonstrated PSAD to be a significant predictor of cancer (p=0.012), but not age (p=0.855). CHAID analysis further identified a PSAD cut-off value of 0.12, below which the cancer detection rate was 23.1% and above which the rate increased to 76.5%. Conclusions This exploratory study suggests that PSAD might be utilized to enhance the stratification of high-risk PI-RADS 3 lesions in the peripheral zone on non-contrast-enhanced MRI, aiding in decision-making for biopsy. While biopsy remains the gold standard for definitive diagnosis, a high PSAD value may suggest a greater need for biopsy in this specific group. Although further validation in larger cohorts is required, our findings contribute to the ongoing discourse on optimizing PI-RADS 3 lesion management. Limitations include a small sample size, the retrospective nature of the study, and the single-center setting, which may impact the generalizability of our results.

Conditional survival of patients with low-risk prostate cancer: Temporal changes in active surveillance permanence over time

PURPOSE

To determine risk categories for patients with prostate cancer (PCa) in active surveillance (AS) and to test the conditional survival (CS) that examined the effect of event-free survival since AS-entrance.

MATERIALS AND METHODS

From January 2012 to December 2020 we analyzed 606 patients with PCa enrolled in our AS program. Kaplan-Meier (KM) plots depicted AS-exit rate. Multivariable Cox regression models (MCRMs) tested for AS-exit rate independent predictors to determine risk categories. CS estimates were used to calculate overall AS-exit rate after event-free survival intervals of 1, 2, 3, and 5 years, and after stratification according to risk categories.

RESULTS

At MCRMs PSAd ≥ 0.15 (HR: 1.43; P-value 0.04), PI-RADS 4-5 (HR: 2.56; P-value <0.001) and number of biopsy positive cores ≥ 2 (HR: 1.75; P-value <0.001) were independent predictors of AS-exit. These variables were used to determine risk categories: low-, intermediate- and high-risk. Overall, according to CS-analyses, 5-year AS-exit free rate increased from 59.7% at baseline, to 67.3%, 74.7%, and 89.4% in patients who remained in AS respectively ≥1, ≥2, ≥3 and ≥5 years. After stratification according to risk categories, in those patients who remained in AS ≥ 5 years, 5-year AS-exit free rates increased from 76.3% to 100% in patients with a low-risk, from 62.7% to 83.7% in patients with an intermediate-risk and from 42.3% to 87.5% in patients with a high-risk.

CONCLUSIONS

CS models showed a direct relationship between event-free survival duration and subsequent AS permanence in overall PCa patients and after stratification according to risk categories.

Urinary MyProstateScore (MPS) to Rule out Clinically-Significant Cancer in Men with Equivocal (PI-RADS 3) Multiparametric MRI: Addressing an Unmet Clinical Need

OBJECTIVE

To evaluate the complementary value of urinary MyProstateScore (MPS) testing and multiparametric MRI (mpMRI) and assess outcomes in patients with equivocal mpMRI.

MATERIALS AND METHODS

Included patients underwent mpMRI followed by urine collection and prostate biopsy at the University of Michigan between 2015 -2019. MPS values were calculated from urine specimens using the validated model based on serum PSA, urinary PCA3, and urinary TMPRSS2:ERG. In the PI-RADS 3 population, the discriminative accuracy of PSA, PSAD, and MPS for GG≥2 cancer was quantified by the AUC curve. Decision curve analysis was used to assess net benefit of MPS relative to PSAD.

RESULTS

There were 540 patients that underwent mpMRI and biopsy with MPS available. The prevalence of GG≥2 cancer was 13% for PI-RADS 3, 56% for PI-RADS 4, and 87% for PI-RADS 5. MPS was significantly higher in men with GG≥2 cancer [median 44.9, IQR (29.4 -57.5)] than those with negative or GG1 biopsy [median 29.2, IQR (14.8 -44.2); P <.001] in the overall population and when stratified by PI-RADS score. In the PI-RADS 3 population (n = 121), the AUC for predicting GG≥2 cancer was 0.55 for PSA, 0.62 for PSAD, and 0.73 for MPS. MPS provided the highest net clinical benefit across all pertinent threshold probabilities.

CONCLUSION

In patients that underwent mpMRI and biopsy, MPS was significantly associated with GG≥2 cancer across all PI-RADS scores. In the PI-RADS 3 population, MPS significantly outperformed PSAD in ruling out GG≥2 cancer. These findings suggest a complementary role of MPS testing in patients that have undergone mpMRI.

Magnetic Resonance Imaging–guided Active Surveillance of Prostate Cancer: Time to Say Goodbye to Protocol-based Biopsies

Traditional protocols for active surveillance (AS) are commonly based on digital rectal examination, prostate-specific antigen (PSA), and standard transrectal biopsy, meaning that initial classification errors and inaccurate lesion monitoring can occur. Protocol-based biopsies are performed to assess changes in cancer grade and extent at prespecified intervals, but this approach represents a barrier to AS adherence and tolerability. There is evidence to support the use of magnetic resonance imaging (MRI) during AS, as this technique (associated with favourable PSA kinetics) offers an opportunity to follow patients on AS without the need for routine, protocol-based biopsies in the absence of signs of radiological progression provided that image quality, interpretation, and reporting of serial imaging are of the highest standards.

Patient summary

In this report we looked at the role of magnetic resonance imaging (MRI) scans in avoiding unnecessary prostate biopsies for patients being monitored for low- or intermediate-risk prostate cancer. We conclude that patients on active surveillance can be monitored with MRI scans over time and that biopsies could be used only when there are changes on MRI or a rising prostate-specific antigen (PSA) not explained by an increase in prostate size.

Classification of Clinically Significant Prostate Cancer on Multi-Parametric MRI: A Validation Study Comparing Deep Learning and Radiomics

The computer-aided analysis of prostate multiparametric MRI (mpMRI) could improve significant-prostate-cancer (PCa) detection. Various deep-learning- and radiomics-based methods for significant-PCa segmentation or classification have been reported in the literature. To be able to assess the generalizability of the performance of these methods, using various external data sets is crucial. While both deep-learning and radiomics approaches have been compared based on the same data set of one center, the comparison of the performances of both approaches on various data sets from different centers and different scanners is lacking. The goal of this study was to compare the performance of a deep-learning model with the performance of a radiomics model for the significant-PCa diagnosis of the cohorts of various patients. We included the data from two consecutive patient cohorts from our own center (n = 371 patients), and two external sets of which one was a publicly available patient cohort (n = 195 patients) and the other contained data from patients from two hospitals (n = 79 patients). Using multiparametric MRI (mpMRI), the radiologist tumor delineations and pathology reports were collected for all patients. During training, one of our patient cohorts (n = 271 patients) was used for both the deep-learning- and radiomics-model development, and the three remaining cohorts (n = 374 patients) were kept as unseen test sets. The performances of the models were assessed in terms of their area under the receiver-operating-characteristic curve (AUC). Whereas the internal cross-validation showed a higher AUC for the deep-learning approach, the radiomics model obtained AUCs of 0.88, 0.91 and 0.65 on the independent test sets compared to AUCs of 0.70, 0.73 and 0.44 for the deep-learning model. Our radiomics model that was based on delineated regions resulted in a more accurate tool for significant-PCa classification in the three unseen test sets when compared to a fully automated deep-learning model.

Repeat MRI during active surveillance: natural history of prostatic lesions and upgrading rates

OBJECTIVES

To assess upgrading rates in patients on active surveillance (AS) for prostate cancer (PCa) after serial multiparametric magnetic resonance imaging (mpMRI).

METHODS

We conducted a retrospective analysis of 558 patients. Five different criteria for mpMRI progression were used: 1) a Prostate Imaging Reporting and Data System (PI-RADS) score increase; 2) a lesion size increase; 3) an extraprostatic extension score increase; 4) overall mpMRI progression; and 5) the number of criteria met for mpMRI progression (0 vs 1 vs 2-3). In addition, two definitions of PCa upgrading were evaluated: 1) International Society of Urological Pathology Grade Group (ISUP GG) ≥2 with >10% of pattern 4 and 2) ISUP GG ≥ 3. Estimated annual percent changes methodology was used to show the temporal trends of mpMRI progression criteria. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of mpMRI progression criteria were also analysed. Multivariable logistic regression models tested PCa upgrading rates.

RESULTS

Lower rates over time for all mpMRI progression criteria were observed. The NPV of serial mpMRI scans ranged from 90.5% to 93.5% (ISUP GG≥2 with >10% of pattern 4 PCa upgrading) and from 98% to 99% (ISUP GG≥3 PCa upgrading), depending on the criteria used for mpMRI progression. A prostate-specific antigen density (PSAD) threshold of 0.15 ng/mL/mL was used to substratify those patients who would be able to skip a prostate biopsy. In multivariable logistic regression models assessing PCa upgrading rates, all five mpMRI progression criteria achieved independent predictor status.

CONCLUSION

During AS, approximately 27% of patients experience mpMRI progression at first repeat MRI. However, the rates of mpMRI progression decrease over time at subsequent mpMRI scans. Patients with stable mpMRI findings and with PSAD < 0.15 ng/mL/mL could safely skip surveillance biopsies. Conversely, patients who experience mpMRI progression should undergo a prostate biopsy.

Emerging role of multiparametric magnetic resonance imaging in identifying clinically relevant localized prostate cancer

PURPOSE OF REVIEW

To explore the recent advances and utility of multiparametric magnetic resonance imaging (mpMRI) in the diagnosis and risk-stratification of prostate cancer.

RECENT FINDINGS

Low-risk, clinically insignificant prostate cancer has a decreased risk of morbidity or mortality. Meanwhile, patients with intermediate and high-risk prostate cancer may significantly benefit from interventions like radiation or surgery. To appropriately risk stratify these patients, MRI has emerged as the imaging modality in the last decade to assist in defining prostate cancer significance, location, and biologic aggressiveness. Traditional 12-core transrectal ultrasound-guided biopsy is associated with over-detection, and ultimately over-treatment of clinically insignificant disease, and the under-detection of clinically significant disease. Biopsy accuracy is improved with MRI-guided targeted biopsy and with the use of standardized risk stratification imaging score systems. Cancer detection accuracy is further improved with combined biopsy techniques that include both systematic and MRI-targeted biopsy that aid in detection of MRI-invisible lesions.

SUMMARY

mpMRI is an area of expanding innovation that continues to refine the diagnostic accuracy of prostate biopsies. As mpMRI-targeted biopsy in prostate cancer becomes more commonplace, advances like artificial intelligence and less invasive dynamic metabolic imaging will continue to improve the utility of MRI.

Active Surveillance Strategies for Low-Grade Prostate Cancer: Comparative Benefits and Cost-effectiveness

Background Active surveillance (AS) is the recommended treatment option for low-risk prostate cancer (PC). Surveillance varies in MRI, frequency of follow-up, and the Prostate Imaging Reporting and Data System (PI-RADS) score that would repeat biopsy. Purpose To compare the effectiveness and cost-effectiveness of AS strategies for low-risk PC with versus without MRI. Materials and Methods This study developed a mathematical model to evaluate the cost-effectiveness of surveillance strategies in a simulation of men with a diagnosis of low-risk PC. The following strategies were compared: watchful waiting, prostate-specific antigen (PSA) and annual biopsy without MRI, and PSA testing and MRI with varied PI-RADS thresholds for biopsy. MRI strategies differed regarding scheduling and use of PI-RADS score of at least 3, or a PI-RADS score of at least 4 to indicate the need for biopsy. Life-years, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios were calculated by using microsimulation. Sensitivity analysis was used to assess the impact of varying parameter values on results. Results For the base case of 60-year-old men, all strategies incorporating prostate MRI extended QALYs and life-years compared with watchful waiting and non-MRI strategies. Annual MRI strategies yielded 16.19 QALYs, annual biopsy with no MRI yielded 16.14 QALYs, and watchful waiting yielded 15.94 QALYs. Annual MRI with PI-RADS score of at least 3 or of at least 4 as the biopsy threshold and annual MRI with biopsy even after MRI with negative findings offered similar QALYs and the same unadjusted life expectancy: 23.05 life-years. However, a PI-RADS score of at least 4 yielded 42% fewer lifetime biopsies. With a cost-effectiveness threshold of $100 000 per QALY, annual MRI with biopsy for lesions with PI-RADS scores of 4 or greater was most cost-effective (incremental cost-effectiveness ratio, $67 221 per QALY). Age, treatment type, risk of initial grade misclassification, and quality-of-life impact of procedural complications affected results. Conclusion The use of active surveillance (AS) with biopsy decisions guided by findings from annual MRI reduces the number of biopsies while preserving life expectancy and quality of life. Biopsy in lesions with PI-RADS scores of 4 or greater is likely the most cost-effective AS strategy for men with low-risk prostate cancer who are younger than 70 years. © RSNA, 2021 Online supplemental material is available for this article. An earlier incorrect version appeared online. This article was corrected on July 13, 2021.

Applications of artificial intelligence in prostate cancer imaging

PURPOSE OF REVIEW

The purpose of this review was to identify the most recent lines of research focusing on the application of artificial intelligence (AI) in the diagnosis and staging of prostate cancer (PCa) with imaging.

RECENT FINDINGS

The majority of studies focused on the improvement in the interpretation of bi-parametric and multiparametric magnetic resonance imaging, and in the planning of image guided biopsy. These initial studies showed that AI methods based on convolutional neural networks could achieve a diagnostic performance close to that of radiologists. In addition, these methods could improve segmentation and reduce inter-reader variability. Methods based on both clinical and imaging findings could help in the identification of high-grade PCa and more aggressive disease, thus guiding treatment decisions. Though these initial results are promising, only few studies addressed the repeatability and reproducibility of the investigated AI tools. Further, large-scale validation studies are missing and no diagnostic phase III or higher studies proving improved outcomes regarding clinical decision making have been conducted.

SUMMARY

AI techniques have the potential to significantly improve and simplify diagnosis, risk stratification and staging of PCa. Larger studies with a focus on quality standards are needed to allow a widespread introduction of AI in clinical practice.

What is the effect of MRI with targeted biopsies on the rate of patients discontinuing active surveillance? A reflection of the use of MRI in the PRIAS study

BACKGROUND

The reduction of overtreatment by active surveillance (AS) is limited in patients with low-risk prostate cancer (PCa) due to high rates of patients switching to radical treatment. MRI improves biopsy accuracy and could therewith affect inclusion in or continuation of AS. We aim to assess the effect of MRI with target biopsies on the total rate of patients discontinuing AS, and in particular discontinuation due to Grade Group (GG) reclassification.

METHODS

Three subpopulations included in the prospective PRIAS study with GG 1 were studied. Group A consists of patients diagnosed before 2009 without MRI before or during AS. Group B consists of patients diagnosed without MRI, but all patients underwent MRI within 6 months after diagnosis. Group C consists of patients who underwent MRI before diagnosis and during follow-up. We used cumulative incidence curves to estimate the rates of discontinuation.

RESULTS

In Group A (n = 500), the cumulative probability of discontinuing AS at 2 years is 27.5%; GG reclassification solely accounted for 6.9% of the discontinuation. In Group B (n = 351) these numbers are 30.9 and 22.8%, and for Group C (n = 435) 24.2 and 13.4%. The three groups were not randomized, however, baseline characteristics are highly comparable.

CONCLUSIONS

Performing an MRI before starting AS reduces the cumulative probability of discontinuing AS at 2 years. Performing an MRI after already being on AS increases the cumulative probability of discontinuing AS in comparison to not performing an MRI, especially because of an increase in GG reclassification. These results suggest that the use of MRI could lead to more patients being considered unsuitable for AS. Considering the excellent long-term cancer-specific survival of AS before the MRI era, the increased diagnostic accuracy of MRI could potentially lead to more overtreatment if definitions and treatment options of significant PCa are not adapted.

Establishment of two new predictive models for prostate cancer to determine whether to require prostate biopsy when the PSA level is in the diagnostic gray zone (4-10 ng ml-1)

Our goal was to establish two new predictive models of prostate cancer to determine whether to require a prostate biopsy when the prostate-specific antigen level is in the diagnostic gray zone. A retrospective analysis of 197 patients undergoing prostate biopsy with prostate-specific antigens between 4 and 10 ng ml⁻¹ was conducted. Of these, 47 patients were confirmed to have cancer, while the remaining 150 patients were diagnosed with benign prostate disease after examining biopsy pathology. Two multivariate logistic regression models were established including age, prostate volumes, free/total prostate-specific antigen ratio, and prostate-specific antigen density using SPSS 19.0 to obtain the predicted probability and Logit P, and then, two receiver operating characteristic (ROC) curves were drawn to obtain the best cutoff value for prostate biopsy: one for the group of all the prostate cancers and one for the group of clinically significant prostate cancers. The best cutoff value for prostate biopsy was 0.25 from the multivariate logistic regression ROC curve model of all the prostate cancers, which gave a sensitivity of 75.4% and a specificity of 75.8%. The best cutoff value for prostate biopsy was 0.20 from the multivariate logistic regression model of clinically significant prostate cancers, which gave a sensitivity of 76.7% and a specificity of 80.1%. We identified the best cutoff values for prostate biopsy (0.25 for all prostate cancers and 0.20 for clinically significant prostate cancers) to determine whether to require prostate biopsy when the PSA level is in the diagnostic gray zone.

Diagnosis of Prostate Cancer in Patients with Prostate-Specific Antigen (PSA) in the Gray Area: Construction of 2 Predictive Models

Background

Two diagnostic models of prostate cancer (PCa) and clinically significant prostate cancer (CS-PCa) were established using clinical data of among patients whose prostate-specific antigen (PSA) levels are in the gray area (4.0–10.0 ng/ml).

Material/Methods

Data from 181 patients whose PSA levels were in the gray area were retrospectively analyzed, and the following data were collected: age, digital rectal examination, total PSA, PSA density (PSAD), free/total PSA (f/t PSA), transrectal ultrasound, multiparametric magnetic resonance imaging (mpMRI), and pathological reports. Patients were diagnosed with benign prostatic hyperplasia (BPH) and PCa by pathology reports, and PCa patients were separated into non-clinically significant PCa (NCS-PCa) and CS-PCa by Gleason score. Afterward, predictor models constructed by above parameters were researched to diagnose PCa and CS-PCa, respectively.

Results

According to the analysis of included clinical data, there were 109 patients with BPH, 44 patients with NCS-PCa, and 28 patients with CS-PCa. Regression analysis showed PCa was correlated with f/t PSA, PSAD, and mpMRI (P<0.01), and CS-PCa was correlated with PSAD and mpMRI (P<0.01). The area under the receiver operating characteristic curves of 2 models for PCa (sensitivity=73.64%, specificity=64.23%) and for CS-PCa (sensitivity=71.41%, specificity=81.82%) were 0.79 and 0.87, respectively.

Conclusions

The prediction models had satisfactory diagnostic value for PCa and CS-PCa among patients with PSA in the gray area, and use of these models may help reduce overdiagnosis.

Update on Multiparametric Prostate MRI During Active Surveillance: Current and Future Trends and Role of the PRECISE Recommendations

Active surveillance for low-to-intermediate risk prostate cancer is a conservative management approach that aims to avoid or delay active treatment until there is evidence of disease progression. In recent years, multiparametric MRI (mpMRI) has been increasingly used in active surveillance and has shown great promise in patient selection and monitoring. This has been corroborated by publication of the Prostate Cancer Radiologic Estimation of Change in Sequential Evaluation (PRECISE) recommendations, which define the ideal reporting standards for mpMRI during active surveillance. The PRECISE recommendations include a system that assigns a score from 1 to 5 (the PRECISE score) for the assessment of radiologic change on serial mpMRI scans. PRECISE scores are defined as follows: a score of 3 indicates radiologic stability, a score of 1 or 2 denotes radiologic regression, and a score of 4 or 5 indicates radiologic progression. In the present study, we discuss current and future trends in the use of mpMRI during active surveillance and illustrate the natural history of prostate cancer on serial scans according to the PRECISE recommendations. We highlight how the ability to classify radiologic change on mpMRI with use of the PRECISE recommendations helps clinical decision making.

Systematic and MRI-Cognitive Targeted Transperineal Prostate Biopsy Accuracy in Detecting Clinically Significant Prostate Cancer after Previous Negative Biopsy and Persisting Suspicion of Malignancy

Background and objectives: Overdiagnosis, overtreatment, and the need for repeated procedures caused by transrectal ultrasound guided prostate biopsies and their related complications places a heavy burden on healthcare systems. This was a prospective cohort validating study to access the clinical accuracy of systematic and MRI-cognitive targeted transperineal prostate biopsies in detecting clinically significant prostate cancer after a previous negative biopsy and persistent suspicion of malignancy. The primary goal was to assess the ability of multiparametric magnetic resonance imaging (mpMRI) to detect clinically significant prostate cancer with an additional goal to assess the diagnostic value of systematic and MRI-cognitive transperineal biopsies. Materials and Methods: In total, 200 patients were enrolled who had rising serum prostate specific antigen (PSA) levels for at least 4 months after a previous negative transrectal ultrasound (TRUS) biopsy. All eligible men underwent 1.5T prostate mpMRI, reported using the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2), followed by a 20-region transperineal prostate systematic biopsy and additional targeted biopsies. Results: Systematic 20-core transperineal prostate biopsies (TPBs) were performed for 38 (19%) patients. Systemic 20-core TPB with additional cognitive targeted biopsies were performed for 162 (81%) patients. Clinically significant prostate cancer (csPC) was detected for 31 (15.5%) patients, of which 20 (64.5%) cases of csPC were detected by systematic biopsy, eight (25.8%) cases were detected by targeted biopsy, and three (9.7%) both by systematic and targeted biopsies. Conclusions: Cognitive mpMRI guided transperineal target biopsies increase the detection rate of clinically significant prostate cancer after a previously negative biopsy. However, in a repeat prostate biopsy setting, we recommend applying a cognitive targeted biopsy with the addition of a systematic biopsy.

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.

Clinically significant prostate cancer detection and segmentation in low-risk patients using a convolutional neural network on multi-parametric MRI

OBJECTIVES

To develop an automatic method for identification and segmentation of clinically significant prostate cancer in low-risk patients and to evaluate the performance in a routine clinical setting.

METHODS

A consecutive cohort (n = 292) from a prospective database of low-risk patients eligible for the active surveillance was selected. A 3-T multi-parametric MRI at 3 months after inclusion was performed. Histopathology from biopsies was used as reference standard. MRI positivity was defined as PI-RADS score ≥ 3, histopathology positivity was defined as ISUP grade ≥ 2. The selected cohort contained four patient groups: (1) MRI-positive targeted biopsy-positive (n = 116), (2) MRI-negative systematic biopsy-negative (n = 55), (3) MRI-positive targeted biopsy-negative (n = 113), (4) MRI-negative systematic biopsy-positive (n = 8). Group 1 was further divided into three sets and a 3D convolutional neural network was trained using different combinations of these sets. Two MRI sequences (T2w, b = 800 DWI) and the ADC map were used as separate input channels for the model. After training, the model was evaluated on the remaining group 1 patients together with the patients of groups 2 and 3 to identify and segment clinically significant prostate cancer.

RESULTS

The average sensitivity achieved was 82-92% at an average specificity of 43-76% with an area under the curve (AUC) of 0.65 to 0.89 for different lesion volumes ranging from > 0.03 to > 0.5 cc.

CONCLUSIONS

The proposed deep learning computer-aided method yields promising results in identification and segmentation of clinically significant prostate cancer and in confirming low-risk cancer (ISUP grade ≤ 1) in patients on active surveillance.

KEY POINTS

• Clinically significant prostate cancer identification and segmentation on multi-parametric MRI is feasible in low-risk patients using a deep neural network. • The deep neural network for significant prostate cancer localization performs better for lesions with larger volumes sizes (> 0.5 cc) as compared to small lesions (> 0.03 cc). • For the evaluation of automatic prostate cancer segmentation methods in the active surveillance cohort, the large discordance group (MRI positive, targeted biopsy negative) should be included.

When to biopsy Prostate Imaging and Data Reporting System version 2 (PI-RADSv2) assessment category 3 lesions? Use of clinical and imaging variables to predict cancer diagnosis at targeted biopsy

INTRODUCTION

We aimed to determine if clinical and imaging features can stratify men at higher risk for clinically significant (CS, International Society of Urological Pathology [ISUP] grade group ≥2) prostate cancer (PCa) in equivocal Prostate Imaging and Data Reporting System (PI-RADS) category 3 lesions on magnetic resonance imaging (MRI).

METHODS

Approved by the institutional review board, this retrospective study involved 184 men with 198 lesions who underwent 3T-MRI and MRI-directed transrectal ultrasound biopsy for PI-RADS 3 lesions. Men were evaluated including clinical stage, prostate-specific antigen density (PSAD), indication, and MRI lesion size. Diagnoses for all men and by indication (no cancer, any PCa, CSPCa) were compared using multivariate logistic regression, including stage, PSAD, and lesion size.

RESULTS

We found an overall PCa rate of 31.8% (63/198) and 10.1% (20/198) CSPCa (13 grade group 2, five group 3, and two group 4). Higher stage (p=0.001), PSAD (p=0.007), and lesion size (p=0.015) were associated with CSPCa, with no association between CSPCa and age, PSA, or prostate volume (p>0.05). PSAD modestly predicted CSPCa area under the curve (AUC) 0.66 (95% confidence interval [CI] 0.518-0.794) in all men and 0.64 (0.487-0.799) for those on active surveillance (AS). Model combining clinical stage, PSAD, and lesion size improved accuracy for all men and AS (AUC 0.82 [0.736-0.910], p<0.001 and 0.785 [0.666-0.904], p<0.001). In men with prior negative biopsy and persistent suspicion, PSAD (0.90 [0.767-1.000]) was not different from the model (p>0.05), with optimal cutpoint of ≥0.215 ng/mL/cc achieving sensitivity/specificity of 85.7/84.4%.

CONCLUSIONS

PI-RADSv2 category 3 lesions are often not CSPCa. PSAD predicted CSPCa in men with a prior negative biopsy; however, PSAD alone had limited value, and accuracy improved when using a model incorporating PSAD with clinical stage and MRI lesion size.

The role of multiparametric magnetic resonance imaging and magnetic resonance-guided biopsy in active surveillance for low-risk prostate cancer: A systematic review

The performance of multiparametric magnetic resonance imaging (mpMRI) and subsequent biopsy in monitoring prostate cancer in men on active surveillance (AS) have not been defined clearly. In this systematic review, we aimed to review current literature about the usage of MRI examination in men with low-risk prostate cancer during active surveillance. For that, we searched seven databases to include all studies reporting magnetic resonance imaging in the AS of low-risk prostate cancer. We finally included 11 studies with 1237 patients included. Our results showed an adequate sensitivity and specificity of both modalities to detect disease progression; including disease upgrading and upstaging. However, the performance in the prediction of unfavorable disease was inferior to the detection of upgrading and upstaging. In terms of MRGB, the previous literature agreed on the superiority of using a combination of different biopsy schemes to get a better progression section. Noteworthy, mp-MRI and MRGB had a good predictive value limited to the first year, with TRUSGB showing a superior role in detecting patients with a GS ≥ 7, after that. In conclusion, both of mpMRI and MRGB have shown an adequate performance on assessing disease progression in the AS of low-risk prostate cancer patients. They can be used for disease staging and grading for successful treatment planning.

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In comparison to the literature, few papers discuss the benefit of MRI screening in low-risk prostate cancer groups.

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Biopsy is considered more invasive than MRI, thus reducing the burden of such methods on the patients.

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PSA values can be misinterpreted especially that it can rise in other diseases such as Benign Prostatic Hyperplasia.

Computer-Aided Diagnosis in Multiparametric MRI of the Prostate: An Open-Access Online Tool for Lesion Classification with High Accuracy

Computer-aided diagnosis (CADx) approaches could help to objectify reporting on prostate mpMRI, but their use in many cases is hampered due to common-built algorithms that are not publicly available. The aim of this study was to develop an open-access CADx algorithm with high accuracy for classification of suspicious lesions in mpMRI of the prostate. This retrospective study was approved by the local ethics commission, with waiver of informed consent. A total of 124 patients with 195 reported lesions were included. All patients received mpMRI of the prostate between 2014 and 2017, and transrectal ultrasound (TRUS)-guided and targeted biopsy within a time period of 30 days. Histopathology of the biopsy cores served as a standard of reference. Acquired imaging parameters included the size of the lesion, signal intensity (T2w images), diffusion restriction, prostate volume, and several dynamic parameters along with the clinical parameters patient age and serum PSA level. Inter-reader agreement of the imaging parameters was assessed by calculating intraclass correlation coefficients. The dataset was stratified into a train set and test set (156 and 39 lesions in 100 and 24 patients, respectively). Using the above parameters, a CADx based on an Extreme Gradient Boosting algorithm was developed on the train set, and tested on the test set. Performance optimization was focused on maximizing the area under the Receiver Operating Characteristic curve (ROC_AUC). The algorithm was made publicly available on the internet. The CADx reached an ROC_AUC of 0.908 during training, and 0.913 during testing (p = 0.93). Additionally, established rule-in and rule-out criteria allowed classifying 35.8% of the malignant and 49.4% of the benign lesions with error rates of <2%. All imaging parameters featured excellent inter-reader agreement. This study presents an open-access CADx for classification of suspicious lesions in mpMRI of the prostate with high accuracy. Applying the provided rule-in and rule-out criteria might facilitate to further stratify the management of patients at risk.

The value of a first MRI and targeted biopsies after several years of active surveillance for low-risk prostate cancer - results from the SAMS trial

OBJECTIVE

To assess the value of a first MRI examination and image-fusion-guided biopsies in men with low-risk prostate cancer who have been on active surveillance (AS) for several years with no signs of progression.

PATIENTS AND METHODS

All 45 participants from two centers who had not previously had an MRI were included. They had been on AS for T1c Gleason score 6 prostate cancer for 2.6 to 6.7 years and had 2 to 5 sets of systematic biopsies with a total of 1640 cores. All underwent a bi-parametric MRI, PI-RADS ≥ 3 lesions were targeted with image-fusion-guided biopsies. Primary outcome measure: detection of Gleason score ≥7 cancer.

RESULTS

Twenty-five of the 45 men (56%) had a total of 30 suspicious MRI lesions. The lesion with the highest score was a PI-RADS 3 in 18, a PI-RADS 4 in 5 and PI-RADS 5 in 3 men. Targeted biopsies from the 30 lesions detected Gleason score 7 cancer in 6 men. Of these six cancers, four were located in the apical and one in the anterior/apical part of the prostate. A Gleason score 7 cancer was detected in 3 of 5 men with PSA density >0.15 ng/ml/cm³.

CONCLUSIONS

Even after several years of AS with stable PSA values and many sets of systematic biopsies, a first MRI and targeted biopsies lead to the detection of Gleason score 7 (ISUP 2 and ISUP 3) cancer in a significant proportion of men, particularly among those with a high PSA density.

Using decision curve analysis to benchmark performance of a magnetic resonance imaging-based deep learning model for prostate cancer risk assessment

OBJECTIVES

To benchmark the performance of a calibrated 3D convolutional neural network (CNN) applied to multiparametric MRI (mpMRI) for risk assessment of clinically significant prostate cancer (csPCa) using decision curve analysis (DCA).

METHODS

We retrospectively analyzed 499 patients who had positive mpMRI (PI-RADSv2 ≥ 3) and MRI-targeted biopsy. The training cohort comprised 449 men, including a calibration set of 50 men. Biopsy decision strategies included using risk estimates from the CNN (original and calibrated), to perform biopsy in men with PI-RADSv2 ≥ 4 only, or additionally in men with PI-RADSv2 3 and PSA density (PSAd) ≥ 0.15 ng/ml/ml. Discrimination, calibration and clinical usefulness in the unseen test cohort (n = 50) were assessed using C-statistic, calibration plots and DCA, respectively.

RESULTS

The calibrated CNN achieved moderate calibration (Hosmer-Lemeshow calibration test, p = 0.41) and good discrimination (C = 0.85). DCA revealed consistently higher net benefit and net reduction in biopsies for the calibrated CNN compared with the original CNN, PI-RADSv2 ≥ 4 and the combined strategy of PI-RADSv2 and PSAd. Original CNN predictions were severely miscalibrated (p < 0.0001) resulting in net harm compared with a 'biopsy all' patients strategy. At-risk thresholds ≥ 10% using the calibrated CNN and the combined strategy reduced the number of biopsies by an estimated 201 and 55 men, respectively, per 1000 men at risk, without missing csPCa, while original CNN and PI-RADSv2 ≥ 4 could not achieve a net reduction in biopsies.

CONCLUSIONS

DCA revealed that our calibrated 3D-CNN resulted in fewer unnecessary biopsies compared with using PI-RADSv2 alone or in combination with PSAd. CNN calibration is important in achieving clinical utility.

KEY POINTS

• A 3D deep learning model applied to multiparametric MRI may help to prevent unnecessary prostate biopsies in patients eligible for MRI-targeted biopsy. • Owing to miscalibration, original risk estimates by the deep learning model require prior calibration to enable clinical utility. • Decision curve analysis confirmed a net benefit of using our calibrated deep learning model for biopsy decisions compared with alternative strategies, including PI-RADSv2 alone and in combination with prostate-specific antigen density.

Automated Classification of Significant Prostate Cancer on MRI: A Systematic Review on the Performance of Machine Learning Applications

Significant prostate carcinoma (sPCa) classification based on MRI using radiomics or deep learning approaches has gained much interest, due to the potential application in assisting in clinical decision-making.

OBJECTIVE

To systematically review the literature (i) to determine which algorithms are most frequently used for sPCa classification, (ii) to investigate whether there exists a relation between the performance and the method or the MRI sequences used, (iii) to assess what study design factors affect the performance on sPCa classification, and (iv) to research whether performance had been evaluated in a clinical setting Methods: The databases Embase and Ovid MEDLINE were searched for studies describing machine learning or deep learning classification methods discriminating between significant and nonsignificant PCa on multiparametric MRI that performed a valid validation procedure. Quality was assessed by the modified radiomics quality score. We computed the median area under the receiver operating curve (AUC) from overall methods and the interquartile range.

RESULTS

From 2846 potentially relevant publications, 27 were included. The most frequent algorithms used in the literature for PCa classification are logistic regression (22%) and convolutional neural networks (CNNs) (22%). The median AUC was 0.79 (interquartile range: 0.77-0.87). No significant effect of number of included patients, image sequences, or reference standard on the reported performance was found. Three studies described an external validation and none of the papers described a validation in a prospective clinical trial.

CONCLUSIONS

To unlock the promising potential of machine and deep learning approaches, validation studies and clinical prospective studies should be performed with an established protocol to assess the added value in decision-making.

Multiparametric magnetic resonance imaging and clinical variables: Which is the best combination to predict reclassification in active surveillance patients?

Introduction & objectives

We tested the role of multiparametric magnetic resonance imaging (mpMRI) in disease reclassification and whether the combination of mpMRI and clinicopathological variables could represent the most accurate approach to predict the risk of reclassification during active surveillance.

Materials & methods

Three-hundred eighty-nine patients (pts) underwent mpMRI and subsequent confirmatory or follow-up biopsy according to the Prostate Cancer Research International Active Surveillance (PRIAS) protocol. Pts with negative (−) mpMRI underwent systematic random biopsy. Pts with positive (+) mpMRI [Prostate Imaging Reporting and Data System, version 2 (PI-RADS-V2) score ≥3] underwent targeted + systematic random biopsies. Multivariate analyses were used to create three models predicting the probability of reclassification [International Society of Urological Pathology ≥ Grade Group 2 (GG2)]: a basic model including only clinical variables (age, prostate-specific antigen density, and number of positive cores at baseline), an Magnetic resonance imaging (MRI) model including only the PI-RADS score, and a full model including both the previous ones. The predictive accuracy (PA) of each model was quantified using the area under the curve.

Results

mpMRI negative (−) was recorded in 127 (32.6%) pts; mpMRI positive (+) was recorded in 262 pts: 72 (18.5%) had PI-RADS 3, 150 (38.6%) PI-RADS 4, and 40 (10.3%) PI-RADS 5 lesions. At a median follow-up of 12 months, 125 pts (32%) were reclassified to GG2 prostate cancer. The rate of reclassification to GG2 prostate cancer was 17%, 35%, 38%, and 52% for mpMRI (−), PI-RADS 3, 4, and 5, respectively (P < 0.001). The PA was 69% and 64% in the basic and MRI models, respectively. The full model had the best PA of 74%: older age (P = 0.023; Odds ratio (OR) = 1.040), prostate-specific antigen density (P = 0.037; OR = 1.324), number of positive cores at baseline (P = 0.001; OR = 1.441), and PI-RADS 3, 4, and 5 (overall P = 0.001; OR = 2.458, 3.007, and 3.898, respectively) were independent predictors of reclassification.

Conclusions

Disease reclassification increased according to the PI-RADS score increase, at confirmatory or follow-up biopsy. However, a no-negligible rate of reclassification was found also in cases of mpMRI (−). The combination of mpMRI and clinicopathological variables still represents the most accurate approach to pts on active surveillance.

The Use of Multiparametric Magnetic Resonance Imaging for Follow-up of Patients Included in Active Surveillance Protocol. Can PSA Density Discriminate Patients at Different Risk of Reclassification?

INTRODUCTION

The objective of this study was to test Prostate Imaging Reporting and Data System (PI-RADS) classification on multiparametric magnetic resonance imaging (mpMRI) and MRI-derived prostate-specific antigen density (PSAD) in predicting the risk of reclassification in men in active surveillance (AS), who underwent confirmatory or per-protocol follow-up biopsy.

MATERIALS AND METHODS

Three hundred eighty-nine patients in AS underwent mpMRI before confirmatory or follow-up biopsy. Patients with negative (-) mpMRI underwent systematic random biopsy. Patients with positive (+) mpMRI underwent targeted fusion prostate biopsies + systematic random biopsies. Different PSAD cutoff values were tested (< 0.10, 0.10-0.20, ≥ 0.20). Multivariable analyses assessed the risk of reclassification, defined as clinically significant prostate cancer of grade group 2 or more, during follow-up according to PSAD, after adjusting for covariates.

RESULTS

One hundred twenty-seven (32.6%) patients had mpMRI(-); 72 (18.5%) had PI-RADS 3, 150 (38.6%) PI-RADS 4, and 40 (10.3%) PI-RADS 5 lesions. The rate of reclassification to grade group 2 PCa was 16%, 22%, 31%, and 39% for mpMRI(-) and PI-RADS 3, 4, and 5, respectively, in case of PSAD < 0.10 ng/mL²; 16%, 25%, 36%, and 44%, in case of PSAD 0.10 to 0.19 ng/mL²; and 25%, 42%, 55%, and 67% in case of PSAD ≥ 0.20 ng/mL². PSAD ≥ 0.20 ng/mL² (odds ratio [OR], 2.45; P = .007), PI-RADS 3 (OR, 2.47; P = .013), PI-RADS 4 (OR, 2.94; P < .001), and PI-RADS 5 (OR, 3.41; P = .004) were associated with a higher risk of reclassification.

CONCLUSION

PSAD ≥ 0.20 ng/mL² may improve predictive accuracy of mpMRI results for reclassification of patients in AS, whereas PSAD < 0.10 ng/mL² may help selection of patients at lower risk of harboring clinically significant prostate cancer. However, the risk of reclassification is not negligible at any PSAD cutoff value, also in the case of mpMRI(-).

Prostate cancer upgrading with serial prostate magnetic resonance imaging and repeat biopsy in men on active surveillance: are confirmatory biopsies still necessary?

Objectives

To investigate whether serial prostate magnetic resonance imaging (MRI) may guide the utility of repeat targeted (TBx) and systematic biopsy (SBx) when monitoring men with low‐risk prostate cancer (PCa) at 1‐year of active surveillance (AS).

Patients and Methods

We retrospectively included 111 consecutive men with low‐risk (International Society of Urological Pathology [ISUP] Grade 1) PCa, who received protocolled repeat MRI with or without TBx and repeat SBx at 1‐year of AS. TBx was performed in Prostate Imaging‐Reporting and Data System (PI‐RADS) score ≥3 lesions (MRI‐positive men). Upgrading defined as ISUP Grade ≥2 PCa (I), Grade ≥2 with cribriform growth/intraductal carcinoma PCa (II), and Grade ≥3 PCa (III) was investigated. Upgrading detected by TBx only (not by SBx) and SBx only (not by TBx) was investigated in MRI‐positive and ‐negative men, and related to radiological progression on MRI (Prostate Cancer Radiological Estimation of Change in Sequential Evaluation [PRECISE] score).

Results

Overall upgrading (I) was 32% (35/111). Upgrading in MRI‐positive and ‐negative men was 48% (30/63) and 10% (5/48) (P < 0.001), respectively. In MRI‐positive men, there was upgrading in 23% (seven of 30) by TBx only and in 33% (10/30) by SBx only. Radiological progression (PRECISE score 4–5) in MRI‐positive men was seen in 27% (17/63). Upgrading (I) occurred in 41% (seven of 17) of these MRI‐positive men, while this was 50% (23/46) in MRI‐positive men without radiological progression (PRECISE score 1–3) (P = 0.534). Overall upgrading (II) was 15% (17/111). Upgrading in MRI‐positive and ‐negative men was 22% (14/63) and 6% (three of 48) (P = 0.021), respectively. In MRI‐positive men, there was upgrading in three of 14 by TBx only and in seven of 14 by SBx only. Overall upgrading (III) occurred in 5% (five of 111). Upgrading in MRI‐positive and ‐negative men was 6% (four of 63) and 2% (one of 48) (P = 0.283), respectively. In MRI‐positive men, there was upgrading in one of four by TBx only and in two of four by SBx only.

Conclusion

Upgrading is significantly lower in MRI‐negative compared to MRI‐positive men with low‐risk PCa at 1‐year of AS. In serial MRI‐negative men, the added value of repeat SBx at 1‐year surveillance is limited and should be balanced individually against the harms. In serial MRI‐positive men, the added value of repeat SBx is substantial. Based on this cohort, SBx is recommended to be performed in combination with TBx in all MRI‐positive men at 1‐year of AS, also when there is no radiological progression.

Review article: MRI-targeted biopsies for prostate cancer diagnosis and management

PURPOSE

Transrectal ultrasound (TRUS)-guided biopsy has been the traditional biopsy route in the detection of prostate cancer. However, due to concern regarding overdetection of low-risk cancer and missed clinically significant cancers as well as risk of sepsis, alternative approaches have been explored. Transperineal template biopsy-sampling the gland every 5 m to 10 mm-reduces error by sampling the whole prostate but increases risk of detecting clinically insignificant cancers as well as conferring risks of side effects such as urinary retention and bleeding.

METHODS

There are various targeted biopsy techniques, each with different cancer detection rates, costs and learning curves. Current research focuses on refining biopsy methodology to maximize detection of significant cancers, whilst minimising invasiveness and complications. In this article, the up-to-date research data about MRI-targeted prostate biopsy were reviewed to show its utilization in prostate cancer management and diagnosis.

RESULTS AND CONCLUSION

Prostate multiparametric MRI has become an effective tool in the detection of significant cancers and an essential component of the prostate cancer diagnostic pathway incorporating MRI-guided biopsy decisions.

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.

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

BACKGROUND

Prostate 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 METHODS

We 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.

RESULTS

Sixty-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).

CONCLUSIONS

Only 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.

The Value of an Extensive Transrectal Repeat Biopsy with Anterior Sampling in Men on Active Surveillance for Low-risk Prostate Cancer: A Comparison from the Randomised Study of Active Monitoring in Sweden (SAMS)

BACKGROUND

A systematic repeat biopsy is recommended for men starting on active surveillance for prostate cancer, but the optimal number and distribution of cores are unknown.

OBJECTIVE

To evaluate an extensive repeat transrectal biopsy with anterior sampling in men starting on active surveillance.

DESIGN, SETTING, AND PARTICIPANTS

Randomised multicentre trial. From 2012 to 2016, 340 Swedish men, aged 40-75yr, with recently diagnosed low-volume Gleason grade group 1 prostate cancer were included.

INTERVENTION

Either an extensive transrectal biopsy with anterior sampling (median 19 cores) or a standard transrectal biopsy (median 12 cores).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Primary outcome measure: Gleason grade group ≥2 cancer.

SECONDARY OUTCOMES

Cancer in anteriorly directed biopsy cores and postbiopsy infection. Nonparametric statistical tests were applied.

RESULTS AND LIMITATIONS

Gleason grade group ≥2 cancer was detected in 16% of 156 men who had an extensive biopsy and in 10% of 164 men who had a standard biopsy, a 5.7% difference (95% confidence interval [CI]-0.2% to 13%, p=0.09). There was a strong linear association between prostate-specific antigen (PSA) density and cancer in the anteriorly directed biopsy cores. The odds ratios for cancer in the anteriorly directed cores were for any cancer 2.2 (95% CI 1.3-3.9, p=0.004) and for Gleason grade group ≥2 cancer 2.3 (95% CI 1.2-4.4, p=0.015) per 0.1-ng/ml/cm³ increments. Postbiopsy infections were equally common in the two groups. A limitation is that magnetic resonance imaging was not used.

CONCLUSIONS

The trial did not support general use of the extensive transrectal repeat biopsy template, but cancer in the anteriorly directed cores was common, particularly in men with high PSA density. The higher the PSA density, the stronger the reason to include anterior sampling at a systematic repeat biopsy.

PATIENT SUMMARY

This trial compared two different templates for transrectal prostate biopsy in men starting on active surveillance for low-risk prostate cancer. Cancer was often found in the front part of the prostate, which is not sampled on a standard prostate biopsy.

Standardized Magnetic Resonance Imaging Reporting Using the Prostate Cancer Radiological Estimation of Change in Sequential Evaluation Criteria and Magnetic Resonance Imaging/Transrectal Ultrasound Fusion with Transperineal Saturation Biopsy to Select Men on Active Surveillance

BACKGROUND

Contemporary selection criteria for men with prostate cancer (PC) suitable for active surveillance (AS) are unsatisfactory, leading to high disqualification rates based on tumor misclassification. Conventional biopsy protocols are based on standard 12-core transrectal ultrasound (TRUS) biopsy.

OBJECTIVE

To assess the value of magnetic resonance imaging (MRI)/TRUS fusion biopsy over 4-yr follow-up in men on AS for low-risk PC.

DESIGN, SETTING, AND PARTICIPANTS

Between 2010 and 2018, a total of 273 men were included. Of them, 157 men with initial 12-core TRUS biopsy and 116 with initial MRI/TRUS fusion biopsy were followed by systematic and targeted transperineal MRI/TRUS fusion biopsies based on Prostate Cancer Research International Active Surveillance criteria. MRI from follow-up MRI/TRUS fusion biopsy was assessed using the Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) scoring system.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

AS-disqualification rates for patients on AS initially diagnosed by either 12-core TRUS biopsy or by MRI/TRUS fusion biopsy were compared using Kaplan-Meier estimates, log-rank tests, and regression analyses. We also analyzed the influence of negative primary MRI and PRECISE scoring to predict AS disqualification using Kaplan-Meier estimates, log-rank tests, and receiver operating characteristic (ROC) curve analysis.

RESULTS AND LIMITATIONS

Of men diagnosed by 12-core TRUS biopsy, 59% were disqualified from AS based on the results of subsequent MRI/TRUS fusion biopsy. In the initial MRI fusion biopsy cohort, upgrading occurred significantly less frequently (19%, p<0.001). ROC curve analyses demonstrated good discrimination for the PRECISE score with an area under the curve of 0.83. No men with a PRECISE score of 1 or 2 (demonstrating absence or downgrading of lesions in follow-up MRI) were disqualified from AS. In our cohort, a negative baseline MRI scan was not a predictor of nondisqualification from AS. Limitations include transperineal approach and extended systematic biopsies used with MRI/TRUS fusion biopsy, which may not be representative of other centers.

CONCLUSIONS

MRI/TRUS fusion biopsies allow a reliable risk classification for patients who are candidates for AS. The application of the PRECISE scoring system demonstrated good discrimination.

PATIENT SUMMARY

In this study, we investigated the value of multiparametric magnetic resonance imaging (MRI) and MRI/transrectal ultrasound (TRUS) fusion biopsies for the assessment of active surveillance (AS) reliability using the Prostate Cancer Radiological Estimation of Change in Sequential Evaluation criteria. Standard TRUS biopsies lead to significant underestimation of prostate cancer. In contrast, MRI/TRUS fusion biopsies allowed for a more reliable risk classification. For appropriate inclusion into AS, men should receive either an initial or a confirmatory MRI/TRUS fusion biopsy.

Four-year outcomes from a multiparametric magnetic resonance imaging (MRI)-based active surveillance programme: PSA dynamics and serial MRI scans allow omission of protocol biopsies

OBJECTIVES

To report outcomes from a multiparametric (mp) magnetic resonance imaging (MRI)-based active surveillance programme that did not include performing protocol biopsies after the first confirmatory biopsy.

PATIENTS AND METHODS

All patients diagnosed with Gleason 3 + 3 prostate cancer because of a raised PSA level who underwent mpMRI after diagnosis were included. Patients were recorded in a prospective clinical database and followed up with PSA monitoring and repeat MRI. In patients who remained on active surveillance after the first MRI (with or without confirmatory biopsy), we investigated PSA dynamics for association with subsequent progression. Comparison between first and second MRI scans was undertaken. Outcomes assessed were: progression to radical therapy at first MRI/confirmatory biopsy and progression to radical therapy in those who remained on active surveillance after first MRI.

RESULTS

A total of 211 patients were included, with a median of 4.2 years of follow-up. The rate of progression to radical therapy was significantly greater at all stages among patients with visible lesions than in those with initially negative MRI (47/125 (37.6%) vs 11/86 (12.8%); odds ratio 4.1 (95% CI 2.0-8.5), P < 0.001). Only 1/56 patients (1.8%) with negative initial MRI scans who underwent a confirmatory systematic biopsy had upgrading to Gleason 3 + 4 disease. PSA velocity was significantly associated with subsequent progression in patients with negative initial MRI (area under the curve 0.85 [95% CI 0.75-0.94]; P <0.001). Patients with high-risk visible lesions on first MRI who remained on active surveillance had a high risk of subsequent progression 19/76 (25.0%) vs 9/84 (10.7%) for patients with no visible lesions, despite reassuring targeted and systematic confirmatory biopsies and regardless of PSA dynamics.

CONCLUSION

Men with low-risk Gleason 3 + 3 prostate cancer on active surveillance can forgo protocol biopsies in favour of MRI and PSA monitoring with selective re-biopsy.

Outcomes of magnetic resonance imaging fusion-targeted biopsy of prostate imaging reporting and data system 3 lesions

PURPOSE

To evaluate the characteristics and histological outcomes in patients with Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions undergoing magnetic resonance imaging-guided fusion-targeted biopsy (MRIFTB).

METHODS

We retrospectively reviewed 138 patients with PI-RADS category 3 lesions classified using multiparametric MRI who underwent MRIFTB between May 2016 and March 2018. The study population included biopsy-naïve and patients with prior negative biopsy. Univariate and multivariate analyzes were performed to determine significant predictors of prostate cancer (PCa) and clinically significant prostate cancer (csPCa). The definition of csPCa was set at Gleason score ≥ 3 + 4.

RESULTS

Overall, 114 (82.6%) biopsied lesions were benign and 24 (17.4%) were identified as prostate cancer. Of these 24 lesions, 14 (58.3%) harbored csPCa. Peripheral zone (PZ) lesions were more likely to be associated with malignant disease than transition zone lesions (13.7 vs. 6.2%). Multivariate logistic analysis revealed that age, PZ location, and prostate-specific antigen (PSA) density (P < 0.05) were independent predictors of both PCa and csPCa.

CONCLUSIONS

A non-negligible number of PI-RADS 3 patients harbor csPCa. Moreover, age, lesion location, and PSA density could be potential clinical predictors of PCa and csPCa. Physicians should be aware of the cancer prevalence of PI-RADS 3 lesions, as the use of the aforementioned factors can help in the decision-making process for these patients.