Defining a Cohort that May Not Require Repeat Prostate Biopsy Based on PCA3 Score and Magnetic Resonance Imaging: The Dual Negative Effect

Transcript Markers from Urinary Extracellular Vesicles for Predicting Risk Reclassification of Prostate Cancer Patients on Active Surveillance

Serum prostate-specific antigen (PSA), its derivatives, and magnetic resonance tomography (MRI) lack sufficient specificity and sensitivity for the prediction of risk reclassification of prostate cancer (PCa) patients on active surveillance (AS). We investigated selected transcripts in urinary extracellular vesicles (uEV) from PCa patients on AS to predict PCa risk reclassification (defined by ISUP 1 with PSA > 10 ng/mL or ISUP 2-5 with any PSA level) in control biopsy. Before the control biopsy, urine samples were prospectively collected from 72 patients, of whom 43% were reclassified during AS. Following RNA isolation from uEV, multiplexed reverse transcription, and pre-amplification, 29 PCa-associated transcripts were quantified by quantitative PCR. The predictive ability of the transcripts to indicate PCa risk reclassification was assessed by receiver operating characteristic (ROC) curve analyses via calculation of the area under the curve (AUC) and was then compared to clinical parameters followed by multivariate regression analysis. ROC curve analyses revealed a predictive potential for AMACR, HPN, MALAT1, PCA3, and PCAT29 (AUC = 0.614-0.655, p < 0.1). PSA, PSA density, PSA velocity, and MRI maxPI-RADS showed AUC values of 0.681-0.747 (p < 0.05), with accuracies for indicating a PCa risk reclassification of 64-68%. A model including AMACR, MALAT1, PCAT29, PSA density, and MRI maxPI-RADS resulted in an AUC of 0.867 (p < 0.001) with a sensitivity, specificity, and accuracy of 87%, 83%, and 85%, respectively, thus surpassing the predictive power of the individual markers. These findings highlight the potential of uEV transcripts in combination with clinical parameters as monitoring markers during the AS of PCa.

Radiogenomics Analysis Linking Multiparametric MRI and Transcriptomics in Prostate Cancer

Prostate cancer (PCa) is a highly prevalent cancer type with a heterogeneous prognosis. An accurate assessment of tumor aggressiveness can pave the way for tailored treatment strategies, potentially leading to better outcomes. While tumor aggressiveness is typically assessed based on invasive methods (e.g., biopsy), radiogenomics, combining diagnostic imaging with genomic information can help uncover aggressive (imaging) phenotypes, which in turn can provide non-invasive advice on individualized treatment regimens. In this study, we carried out a parallel analysis on both imaging and transcriptomics data in order to identify features associated with clinically significant PCa (defined as an ISUP grade ≥ 3), subsequently evaluating the correlation between them. Textural imaging features were extracted from multi-parametric MRI sequences (T2W, DWI, and DCE) and combined with DCE-derived parametric pharmacokinetic maps obtained using magnetic resonance dispersion imaging (MRDI). A transcriptomic analysis was performed to derive functional features on transcription factors (TFs), and pathway activity from RNA sequencing data, here referred to as transcriptomic features. For both the imaging and transcriptomic features, different machine learning models were separately trained and optimized to classify tumors in either clinically insignificant or significant PCa. These models were validated in an independent cohort and model performance was used to isolate a subset of relevant imaging and transcriptomic features to be further investigated. A final set of 31 imaging features was correlated to 33 transcriptomic features obtained on the same tumors. Five significant correlations (p < 0.05) were found, of which, three had moderate strength (|r| ≥ 0.5). The strongest significant correlations were seen between a perfusion-based imaging feature-MRDI A median-and the activities of the TFs STAT6 (-0.64) and TFAP2A (-0.50). A higher-order T2W textural feature was also significantly correlated to the activity of the TF STAT6 (-0.58). STAT6 plays an important role in controlling cell proliferation and migration. Loss of the AP2alpha protein expression, quantified by TFAP2A, has been strongly associated with aggressiveness and progression in PCa. According to our findings, a combination of texture features extracted from T2W and DCE, as well as perfusion-based pharmacokinetic features, can be considered for the prediction of clinically significant PCa, with the pharmacokinetic MRDI A feature being the most correlated with the underlying transcriptomic information. These results highlight a link between quantitative imaging features and the underlying transcriptomic landscape of prostate tumors.

Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization

Radiomics and genomics represent two of the most promising fields of cancer research, designed to improve the risk stratification and disease management of patients with prostate cancer (PCa). Radiomics involves a conversion of imaging derivate quantitative features using manual or automated algorithms, enhancing existing data through mathematical analysis. This could increase the clinical value in PCa management. To extract features from imaging methods such as magnetic resonance imaging (MRI), the empiric nature of the analysis using machine learning and artificial intelligence could help make the best clinical decisions. Genomics information can be explained or decoded by radiomics. The development of methodologies can create more-efficient predictive models and can better characterize the molecular features of PCa. Additionally, the identification of new imaging biomarkers can overcome the known heterogeneity of PCa, by non-invasive radiological assessment of the whole specific organ. In the future, the validation of recent findings, in large, randomized cohorts of PCa patients, can establish the role of radiogenomics. Briefly, we aimed to review the current literature of highly quantitative and qualitative results from well-designed studies for the diagnoses, treatment, and follow-up of prostate cancer, based on radiomics, genomics and radiogenomics research.

Disparities in magnetic resonance imaging of the prostate for traditionally underserved patients with prostate cancer

BACKGROUND

Prebiopsy magnetic resonance imaging (MRI) of the prostate improves detection of significant tumors, while decreasing detection of less-aggressive tumors. Therefore, its use has been increasing over time. In this study, the use of prebiopsy MRI among Medicare beneficiaries with prostate cancer was examined. It was hypothesized that patients of color and those in isolated areas would be less likely to undergo this approach for cancer detection.

METHODS

Using cancer registry data from the Surveillance, Epidemiology, and End Results (SEER) program linked to billing claims for fee-for-service Medicare beneficiaries, men with nonmetastatic prostate cancer were identified from 2010 through 2015 with prostate-specific antigen (PSA) <30 ng/mL. Outcome was prebiopsy MRI of the prostate performed within 6 months before diagnosis (ie, Current Procedural Terminology 72197). Exposures were patient race/ethnicity and rural/urban status. Multivariable regression estimated the odds of prebiopsy prostate MRI. Post hoc analyses examined associations with the registry-level proportion of non-Hispanic Black patients and MRI use, as well as disparities in MRI use in registries with data on more frequent use of prostate MRI.

RESULTS

There were 50,719 men identified with prostate cancer (mean age, 72.1 years). Overall, 964 men (1.9% of cohort) had a prebiopsy MRI. Eighty percent of patients with prebiopsy MRI lived in California, New Jersey, or Connecticut. Non-Hispanic Black men (0.6% vs 2.1% non-Hispanic White; odds ratio [OR], 0.28; 95% CI, 0.19-0.40) and men in less urban areas (1.1% vs 2.2% large metro; OR, 0.65; 95% CI, 0.44-0.97) were less likely to have prebiopsy MRI of the prostate.

CONCLUSIONS

Non-Hispanic Black patients with prostate cancer and those in less urban areas were less likely to have prebiopsy MRI of the prostate during its initial adoption as a tool for improving prostate cancer detection.

Can Prostate-Specific Antigen Density Be an Index to Distinguish Patients Who Can Omit Repeat Prostate Biopsy in Patients with Negative Magnetic Resonance Imaging?

Purpose

We evaluated the negative predictive value (NPV) of multiparametric magnetic resonance imaging (mpMRI) in detecting clinically significant prostate cancer (csPCa) according to biopsy setting and prostate-specific antigen density (PSAD) using transperineal template-guided saturation prostate biopsy (TPB) as the reference standard.

Methods

A total of 161 patients with biopsy histories and negative pre-biopsy mpMRI (Prostate Imaging Reporting and Data System version 2 scores of less than 3) participated in the study. TPB was performed on the following indications: “prior negative biopsy” in patients with persistent suspicion of prostate cancer (n = 91) or “confirmatory biopsy” in patients who were candidates for active surveillance (n = 70). The csPCa was defined as a Gleason score of 3 + 4 or greater. We calculated the NPV of mpMRI in detecting csPCa according to biopsy history and prostate-specific antigen density (PSAD) and conducted a logistic regression analysis to determine the clinical predicator for the absence of csPCa.

Results

The detection rate of csPCa was 5.5% in the prior negative biopsy group and 14.3% in the confirmatory biopsy group (P = 0.057). None of the variables in the logistic regression models including PSAD <0.15 ng/mL/cc and prior negative biopsy could predict the absence of csPCa. The NPV of mpMRI in detecting csPCa in patients with a prior negative biopsy worsen from 94.5% to 93.3% when combined with PSAD <0.15 ng/mL/cc.

Conclusion

Patients with negative mpMRI findings may not omit repeat biopsy even if their prior biopsy histories are negative and PSADs are <0.15 ng/mL/cc.

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.

Role of pre-biopsy multiparametric MRI in prostate cancer diagnosis: Evidence from the literature

As the conventional workup for diagnosing prostate cancer, transrectal systematic biopsy carries the risk of sepsis and overdiagnosis of insignificant prostate cancer. In recent years, multiparametric MRI (mpMRI) has revolutionized the diagnostic approach to prostate cancer. With widespread use of the prostate imaging and data system (PIRADS), MRI reporting has been more standardized. Several landmark papers have indicated that mpMRI in combination with targeted or combined biopsy can confidently diagnose more clinically significant prostate cancer while reducing diagnoses of insignificant disease. In this review, we aim to discuss the advantages of pre-biopsy MRI based on the current literature and to address its reliability in ruling out prostate cancer, reproducibility, and cost-effectiveness.

What to expect from a non-suspicious prostate MRI? A review

BACKGROUND

Many guidelines now recommend multiparametric MRI (mpMRI) prior to an initial or repeat prostate biopsy. However, clinical decision making for men with a non-suspicious mpMRI (Likert or PIRADS score 1-2) varies.

OBJECTIVES

To review the most recent literature to answer three questions. (1) Should we consider systematic biopsy if mpMRI is not suspicious? (2) Are there additional predictive factors that can help decide which patient should have a biopsy? (3) Can the low visibility of some cancers be explained and what are the implications?

SOURCES

A narrative review was performed in Medline databases using two searches with the terms "MRI" and "prostate cancer" and ("diagnosis" or "biopsy") and ("non-suspicious" or "negative" or "invisible"); "prostate cancer MRI visible". References of the selected articles were screened for additional articles.

STUDY SELECTION

Studies published in the last 5 years in English language were assessed for eligibility and selected if data was available to answer one of the three study questions.

RESULTS

Considering clinically significant cancer as ISUP grade≥2, the negative predictive value (NPV) of mpMRI in various settings and populations ranges from 76% to 99%, depending on cancer prevalence and the type of confirmatory reference test used. NPV is higher among patients with prior negative biopsy (88-96%), and lower for active surveillance patients (85-90%). The PSA density (PSAd) with a threshold of PSAd<0.15ng/ml/ml was the most studied and relevant predictive factor used in combination with mpMRI to rule out clinically significant cancer. Finally, mpMRI-invisible tumours appear to differ from a histopathological and genetic point of view, conferring clinical advantage to invisibility.

LIMITATIONS

Most published data come from expert centres and results may not be reproducible in all settings.

CONCLUSION

mpMRI has high diagnostic accuracy and in cases of negative mpMRI, PSA density can be used to determine which patient should have a biopsy. Growing knowledge of the mechanisms and genetics underlying MRI visibility will help develop more accurate risk calculators and biomarkers.

Who can safely evade a magnetic resonance imaging fusion-targeted biopsy (MRIFTB) for prostate imaging reporting and data system (PI-RADS) 3 lesion?

OBJECTIVE

To identify patients who can safely evade the magnetic resonance imaging fusion-targeted biopsy (MRIFTB) for prostate imaging reporting and data system (PI-RADS) 3 lesion.

MATERIALS AND METHODS

Overall, 755 men with PI-RADS 3-5 lesions who underwent MRIFTB were retrospectively analyzed. Univariate and multivariate analyses were performed to determine significant predictors for clinically significant prostate cancer (CSPCa), defined as Gleason grade group ≥ II. Detection rates and negative predictive values of CSPCa were estimated according to various clinical settings.

RESULTS

Median age, prostate-specific antigen (PSA), and PSA density of patients were 66.0 years, 7.39 ng/mL, and 0.19 ng/mL, respectively. Overall detection rates of CSPCa according to PI-RADS 3 (n = 347), 4 (n = 260), and 5 (n = 148) lesions were 15.0%, 30.4%, and 80.4%, respectively. The negative predictive value (NPV) of PI-RADS 3 lesion on MRI was 15.0%. On multivariate analysis, age [≥ 65 years, odds ratio (OR) = 0.427], PSA density (≥ 0.20 ng/mL², OR = 0.234), prior negative biopsy history (OR = 2.231), and PI-RADS score (4, OR = 0.427; 5, OR = 0.071) were independent predictors for the absence of CSPCa by MRIFTB. When assessed according to various conditions, NPVs of PI-RADS 3 lesions were relatively high in subgroups with low PSA density (< 0.20 ng/mL²) regardless of age or prior biopsy history (NPV range 91.1-91.9%). Contrarily, NPVs in subgroups with high PSA density were relatively low and varied according to age or prior biopsy history groups (NPV range 50.0-86.8%).

CONCLUSIONS

Men with the PI-RADS 3 lesion and low PSA density might safely evade the MRIFTB, regardless of age or prior biopsy history.

The Percentage of Free PSA and Urinary Markers Distinguish Prostate Cancer from Benign Hyperplasia and Contribute to a More Accurate Indication for Prostate Biopsy

The main advantage of urinary biomarkers is their noninvasive character and the ability to detect multifocal prostate cancer (CaP). We have previously implemented a quadruplex assay of urinary markers into clinical practice (PCA3, AMACR, TRPM8 and MSMB with KLK3 normalization). In this study, we aimed to validate it in a larger cohort with serum PSA 2.5-10 ng/mL and test other selected transcripts and clinical parameters, including the percentage of free prostate-specific antigen (PSA) (% free PSA) and inflammation. In the main cohort of 299 men, we tested the quadruplex transcripts. In a subset of 146 men, we analyzed additional transcripts (CD45, EPCAM, EZH2, Ki67, PA2G4, PSGR, RHOA and TBP). After a prostate massage, the urine was collected, RNA isolated from a cell sediment and qRT-PCR performed. Ct values of KLK3 (i.e., PSA) were strongly correlated with Ct values of other genes which play a role in CaP (i.e., PCA3, AMACR, TRPM8, MSMB and PSGR). AMACR, PCA3, TRPM8 and EZH2 mRNA expression, as well as % free PSA, were significantly different for BPH and CaP. The best combined model (% free PSA plus PCA3 and AMACR) achieved an AUC of 0.728 in the main cohort. In the subset of patients, the best AUC 0.753 was achieved for the combination of PCA3, % free PSA, EPCAM and PSGR. PCA3 mRNA was increased in patients with inflammation, however, this did not affect the stratification of patients indicated for prostate biopsy. In conclusion, the percentage of free PSA and urinary markers contribute to a more accurate indication for prostate biopsy.

Prostate Health Index and multiparametric magnetic resonance imaging to predict prostate cancer grade reclassification in active surveillance

OBJECTIVE

To identify the value of combining the Prostate Health Index (PHI) and multiparametric magnetic resonance imaging (mpMRI), tools which have previously been shown to be independently predictive of prostate cancer (PCa) grade reclassification (GR; Gleason score >6), for the purpose of predicting GR at the next surveillance biopsy to reduce unnecessary prostate biopsies for men in PCa active surveillance (AS).

PATIENTS AND METHODS

Between 2014 and 2019, we retrospectively identified 253 consecutive men in the Johns Hopkins AS programme who had mpMRI and PHI followed by a systematic ± targeted biopsy. PHI and PHI density (PHID) were evaluated across Prostate Imaging-Reporting and Data System version 2.0 (PI-RADSv2) scores and compared to those with and without GR. Next, the negative predictive value (NPV) and area under the receiver operating curve (AUC) were calculated to compare the diagnostic value of PI-RADSv2 score combined with PHI, PHID, or prostate-specific antigen density (PSAD) for GR using their respective first quartile as a cut-off.

RESULTS

Of the 253 men, 38 men (15%) had GR. Men with GR had higher PHI values (40.7 vs 32.0, P = 0.001), PHID (0.83 vs 0.57, P = 0.007), and PSAD (0.12 vs 0.10, P = 0.037). A PI-RADSv2 ≤3 alone had a NPV of 91.6% for GR (AUC 0.67). Using a PHI cut-off of 25.6 in addition to PI-RADSv2 ≤3, the NPV and AUC were both increased to 98% and 0.70, respectively. Using a PSAD cut-off of 0.07 ng/mL/mL with PI-RADSv2 had an AUC of 0.69 and NPV of 95.4%. PHI and PI-RADSv2 together could have avoided 20% of biopsies at the cost of missing 2.6% of GRs.

CONCLUSIONS

The combination of PHI and mpMRI can aid in the prediction of GR in men on AS and may be useful for decreasing the burden of surveillance prostate biopsies.

Genome-wide analysis of differentially expressed lncRNA in sporadic parathyroid tumors

Diagnosis of parathyroid carcinoma on histological examination is challenging. Thousands of differentially expressed lncRNAs were identified on the microarray data between parathyroid cancer and adenoma samples. Four lncRNAs were significantly dysregulated in further validation. The "lncRNA score" calculated from these lncRNAs differentiated parathyroid carcinomas from adenomas. LncRNAs serve as biomarkers for parathyroid cancer diagnosis.

INTRODUCTION

Diagnosis of parathyroid carcinoma (PC) on histological examination is challenging. LncRNA profile study was conducted to find diagnostic biomarkers for PC.

METHODS

LncRNA arrays containing 91,007 lncRNAs as well as 29,857 mRNAs were used to assess parathyroid specimen (5 carcinomas and 6 adenomas). Bioinformatics analyses were also conducted to compare the microarray results between parathyroid carcinomas and adenomas (PAs). Differentially expressed lncRNAs of 11 PCs and 31 PAs were validated by real-time quantitative PCR.

RESULTS

On the microarray data between PC and PA samples (fold change ≥ 2, P < 0.05), 1809 differentially expressed lncRNAs and 1349 mRNAs also were identified. All carcinomas were clustered in the same group by clustering analysis using dysregulated lncRNAs or mRNAs. Four lncRNAs (LINC00959, lnc-FLT3-2:2, lnc-FEZF2-9:2, and lnc-RP11-1035H13.3.1-2:1) identified were significantly dysregulated in further RT-PCR validation. The global "lncRNA score" calculated from the lncRNAs above also differentiated parathyroid carcinomas from adenomas.

CONCLUSIONS

LncRNA profiling shows distinct differentially expressed lncRNAs in parathyroid neoplasm. They may play a key role in parathyroid cancer and serve as potential biomarkers to distinguish parathyroid cancers from parathyroid adenomas.

PI-RADS Steering Committee: The PI-RADS Multiparametric MRI and MRI-directed Biopsy Pathway

High-quality evidence shows that MRI in biopsy-naive men can reduce the number of men who need prostate biopsy and can reduce the number of diagnoses of clinically insignificant cancers that are unlikely to cause harm. In men with prior negative biopsy results who remain under persistent suspicion, MRI improves the detection and localization of life-threatening prostate cancer with greater clinical utility than the current standard of care, systematic transrectal US-guided biopsy. Systematic analyses show that MRI-directed biopsy increases the effectiveness of the prostate cancer diagnosis pathway. The incorporation of MRI-directed pathways into clinical care guidelines in prostate cancer detection has begun. The widespread adoption of the Prostate Imaging Reporting and Data System (PI-RADS) for multiparametric MRI data acquisition, interpretation, and reporting has promoted these changes in practice. The PI-RADS MRI-directed biopsy pathway enables the delivery of key diagnostic benefits to men suspected of having cancer based on clinical suspicion. Herein, the PI-RADS Steering Committee discusses how the MRI pathway should be incorporated into routine clinical practice and the challenges in delivering the positive health impacts needed by men suspected of having clinically significant prostate cancer.

Increasing Utilization of Multiparametric Magnetic Resonance Imaging in Prostate Cancer Active Surveillance

OBJECTIVE

To characterize the use of multiparametric magnetic resonance imaging (mpMRI) in male Medicare beneficiaries electing active surveillance for prostate cancer. mpMRI has emerged as a tool that may improve risk-stratification and decrease repeated biopsies in men electing active surveillance. However, the extent to which mpMRI has been implemented in active surveillance has not been established.

METHODS

Using Surveillance, Epidemiology, and End Results registry data linked to Medicare claims data, we identified men with localized prostate cancer diagnosed between 2008 and 2013 and managed with active surveillance. We classified men into 2 treatment groups: active surveillance without mpMRI and active surveillance with mpMRI. We then fit a multivariable logistic regression models to examine changing mpMRI utilization over time, and factors associated with the receipt of mpMRI.

RESULTS

We identified 9467 men on active surveillance. Of these, 8178 (86%) did not receive mpMRI and 1289 (14%) received mpMRI. The likelihood of receiving mpMRI over the entire study period increased by 3.7% (P = .004). On multivariable logistic regression, patients who were younger, white, had lower comorbidity burden, lived in the northeast and west, had higher incomes and lived in more urban areas had greater odds of receiving mpMRI (all P < .05).

CONCLUSION

From 2008 to 2013, use of mpMRI in active surveillance increased gradually but significantly. Receipt of mpMRI among men on surveillance for prostate cancer varied significantly across demographic, geographic, and socioeconomic strata. Going forward, studies should investigate causes for this variation and define ideal strategies for equitable, cost-effective dissemination of mpMRI technology.

Use of multiparametric magnetic resonance imaging in prostate cancer active surveillance

OBJECTIVES

To review the role of multiparametric magnetic resonance imaging (mpMRI) for active surveillance (AS) of prostate cancer.

MATERIALS AND METHODS

We performed a comprehensive search of Medline and Embase databases for relevant articles in the English language. Search terms included 'prostate cancer', 'active surveillance' or 'monitoring', 'expectant management', and 'MRI'. We also reviewed practice guidelines from recognized international associations or societies involved in prostate cancer care. Articles were selected by both authors for relevance to the subject matter.

RESULTS

The ability of mpMRI to visualize primarily high-grade tumours within the prostate may improve risk stratification for men considering AS for prostate cancer. Multiple mostly single-institution studies have found that the addition of mpMRI and a targeted biopsy strategy can improve AS patient selection over standard TRUS biopsy alone. The high negative predictive value of mpMRI may allow men to avoid early repeat biopsy and may offer the possibility to tailor biopsy strategies. The presence of a radiographically positive lesion on mpMRI at baseline is predictive of higher likelihood of radiographic progression over time while on AS.

CONCLUSIONS

MRI has shown promise in both patient selection and monitoring for men who undergo AS for prostate cancer. There are multiple barriers to the widespread use of mpMRI for AS including quality, cost and access to care.

Prostate Imaging-Reporting and Data System Steering Committee: PI-RADS v2 Status Update and Future Directions

CONTEXT

The Prostate Imaging-Reporting and Data System (PI-RADS) v2 analysis system for multiparametric magnetic resonance imaging (mpMRI) detection of prostate cancer (PCa) is based on PI-RADS v1, accumulated scientific evidence, and expert consensus opinion.

OBJECTIVE

To summarize the accuracy, strengths and weaknesses of PI-RADS v2, discuss pathway implications of its use and outline opportunities for improvements and future developments.

EVIDENCE ACQUISITION

For this consensus expert opinion from the PI-RADS steering committee, clinical studies, systematic reviews, and professional guidelines for mpMRI PCa detection were evaluated. We focused on the performance characteristics of PI-RADS v2, comparing data to systems based on clinicoradiologic Likert scales and non-PI-RADS v2 imaging only. Evidence selections were based on high-quality, prospective, histologically verified data, with minimal patient selection and verifications biases.

EVIDENCE SYNTHESIS

It has been shown that the test performance of PI-RADS v2 in research and clinical practice retains higher accuracy over systematic transrectal ultrasound (TRUS) biopsies for PCa diagnosis. PI-RADS v2 fails to detect all cancers but does detect the majority of tumors capable of causing patient harm, which should not be missed. Test performance depends on the definition and prevalence of clinically significant disease. Good performance can be attained in practice when the quality of the diagnostic process can be assured, together with joint working of robustly trained radiologists and urologists, conducting biopsy procedures within multidisciplinary teams.

CONCLUSIONS

It has been shown that the test performance of PI-RADS v2 in research and clinical practice is improved, retaining higher accuracy over systematic TRUS biopsies for PCa diagnosis.

PATIENT SUMMARY

Multiparametric magnetic resonance imaging (MRI) and MRI-directed biopsies using the Prostate Imaging-Reporting and Data System improves the detection of prostate cancers likely to cause harm, and at the same time decreases the detection of disease that does not lead to harms if left untreated. The keys to success are high-quality imaging, reporting, and biopsies by radiologists and urologists working together in multidisciplinary teams.

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.

Which Patients with Negative Magnetic Resonance Imaging Can Safely Avoid Biopsy for Prostate Cancer?

PURPOSE

We sought to determine whether there is a subset of men who can avoid prostate biopsy based on multiparametric magnetic resonance imaging and clinical characteristics.

MATERIALS AND METHODS

Of 1,149 consecutive men who underwent prostate biopsy from October 2011 to March 2017, 135 had prebiopsy negative multiparametric magnetic resonance imaging with PI-RADS™ (Prostate Imaging Reporting and Data System) score less than 3. The detection rate of clinically significant prostate cancer was evaluated according to prostate specific antigen density and prior biopsy history. Clinically significant prostate cancer was defined as Grade Group 2 or greater. Multivariable logistic regression analysis was performed to identify predictors of nonclinically significant prostate cancer on biopsy.

RESULTS

The prostate cancer and clinically significant prostate cancer detection rates were 38% and 18%, respectively. Men with biopsy detected, clinically significant prostate cancer had a smaller prostate (p = 0.004), higher prostate specific antigen density (p = 0.02) and no history of prior negative biopsy (p = 0.01) compared to the nonclinically significant prostate cancer cohort. Prostate specific antigen density less than 0.15 ng/ml/cc (p <0.001) and prior negative biopsy (p = 0.005) were independent predictors of absent clinically significant prostate cancer on biopsy. The negative predictive value of multiparametric magnetic resonance imaging for biopsy detection of clinically significant prostate cancer improved with decreasing prostate specific antigen density, primarily in men with prior negative biopsy (p = 0.001) but not in biopsy naïve men. Of the men 32% had the combination of negative multiparametric magnetic resonance imaging, prostate specific antigen density less than 0.15 ng/ml/cc and negative prior biopsy, and none had clinically significant prostate cancer on repeat biopsy. The incidence of biopsy identified, clinically significant prostate cancer was 18%, 10% and 0% in men with negative multiparametric magnetic resonance imaging only, men with negative multiparametric magnetic resonance imaging and prostate specific antigen density less than 0.15 ng/ml/cc, and men with negative multiparametric magnetic resonance imaging, prostate specific antigen density less than 0.15 ng/ml/cc and negative prior biopsy, respectively.

CONCLUSIONS

We propose that a subset of men with negative multiparametric magnetic resonance imaging, prostate specific antigen density less than 0.15 ng/ml/cc and prior negative biopsy may safely avoid rebiopsy. Conversely prostate biopsy should be considered in biopsy naïve men regardless of negative multiparametric magnetic resonance imaging, particularly those with prostate specific antigen density greater than 0.15 ng/ml/cc.

The role of prostate cancer antigen 3 (PCA3) in prostate cancer detection

INTRODUCTION

The prostate cancer antigen 3 (PCA3) score has been the first urine assay to obtain the Food and Drug Administration approval for guiding decisions regarding additional biopsies. Different aspects of this urinary assay (diagnostic performance, prognostic value, cost/benefit balance, integration with other molecular and imaging modalities) have now been well evaluated. Areas covered: This expert review will summarize current achievements and future perspectives provided by this urine biomarker. Expert commentary: The clinical benefit of the PCA3 score, in addition to the other established factors has been demonstrated before regarding biopsy decision making in men with persistent risk of prostate cancer. Its potential prognostic value also suggests its usefulness in selecting low risk patients for active surveillance protocols, however future daily-practice changing studies are needed. Economics assessment and additional value compared with other biomolecular and imaging modalities are still under investigation.