Accuracy and Variability of Prostate Multiparametric Magnetic Resonance Imaging Interpretation Using the Prostate Imaging Reporting and Data System: A Blinded Comparison of Radiologists

Natural history of PIRADS-2 lesions on serial multiparametric magnetic resonance imaging: Real-life data from an Academic Center

INTRODUCTION/BACKGROUND

The natural history of prostate imaging reporting and data system (PIRADS) score 2 lesions on serial mpMRIs is largely unknown. Herein, we aimed to evaluate the patients with PIRADS-2 index lesions by using serial mpMRI scans to reveal the rates of mpMRI upgrade in PIRADS score and prostate cancer (PCa) detection.

METHODS/MATERIALS

All mpMRI scans with a PIRADS-2 index lesion from our mpMRI database were evaluated retrospectively. Data from 214 biopsy-naïve patients with a PIRADS-2 index lesion on the initial mpMRI who then underwent at least 1 follow-up mpMRI were reevaluated by an experienced uroradiologist and only those (n = 172) who had a PIRADS-2 index lesion on the initial mpMRI according to PIRADS v2.1 were included in the study. mpMRI progression was defined as the detection of any PIRADS ≥3 lesion at follow-up mpMRI. Histopathological results were evaluated in patients undergoing biopsy upon mpMRI progression.

RESULTS

A total of 172 patients with a mean age of 60.1 ± 8.6 years were evaluated. The median PSA at baseline mpMRI was 4.7 (IQR; 3.3-6.7) ng/dl. Overall mpMRI progression was detected in 54 patients (31.4%), 37 were upgraded to PIRADS-3, 16 to PIRADS-4, and one to PIRADS-5. Multivariate logistic regression analysis revealed that a PSA increase of ≥25% during follow-up was the only predictor of mpMRI upgrade (P = 0.019, OR: 2.384). 30 out of 54 patients underwent a prostate biopsy and PCa was detected in 15 patients; 5 with ISUP grade 1, 10 with ISUP grade 2.

CONCLUSIONS

Almost half of the patients with a PIRADS-2 index lesion were upgraded to PIRADS ≥3 when evaluated with serial mpMRI when a PSA increase of ≥25% was observed during follow-up. PCa was detected in half of the patients who underwent a biopsy. Serial mpMRI can be recommended when monitoring patients with elevating PSA ≥25%, a prostate biopsy can be considered upon a mpMRI progression.

Utility of quantitative measurement of T2 using restriction spectrum imaging for detection of clinically significant prostate cancer

The Restriction Spectrum Imaging restriction score (RSIrs) has been shown to improve the accuracy for diagnosis of clinically significant prostate cancer (csPCa) compared to standard DWI. Both diffusion and T2 properties of prostate tissue contribute to the signal measured in DWI, and studies have demonstrated that each may be valuable for distinguishing csPCa from benign tissue. The purpose of this retrospective study was to (1) determine whether prostate T2 varies across RSI compartments and in the presence of csPCa, and (2) evaluate whether csPCa detection with RSIrs is improved by acquiring multiple scans at different TEs to measure compartmental T2 (cT2). Data includes two cohorts scanned for csPCa with 3T multi-b-value diffusion-weighted sequences acquired at multiple TEs. cT2 values were computed from multi-TE RSI data and compared by compartment. CsPCa detection was compared between RSIrs and a logistic regression model (LRM) to predict the probability of csPCa using cT2 in combination with RSI measurements. Two-sample t-tests (α = 0.05) and the area under the receiver operating characteristic curve (AUC) were used for the statistical analyses. In both cohorts, T2 was different (p < 0.05) across the four RSI compartments (C1, C2, C3, C4). Voxel-level, cohort 1: T2 was different in csPCa for C1, C2, C3 (p < 0.001). Patient-level, cohort 1: T2 was different in csPCa patients in C3 (p = 0.02); cohort 2: T2 differed in csPCa patients in C1 (p = 0.01), C3 (p = 0.01) and C4 (p < 0.01). Voxel-level csPCa detection: cT2 did not improve discrimination over RSIrs alone (p = 0.9). Patient-level: RSIrs and the LRM performed better than diffusion alone (p < 0.001), but the difference in AUCs between RSIrs and the LRM was not significantly different (p = 0.54). In conclusion, significant differences in cT2 were observed between normal and cancerous prostatic tissue. With our data, however, consideration of cT2 in addition to diffusion did not significantly improve cancer detection performance.

PI-RADS in Predicting csPCa: A Comparison Between Academic and Nonacademic Centers

INTRODUCTION

The introduction of multiparametric prostate magnetic resonance imaging (mpMRI) has revolutionized prostate cancer (PCa) diagnosis, enhancing the localization of clinically significant prostate cancer (csPCa) and guiding targeted biopsies. However, significant disparities in the execution, interpretation, and reporting of prostate MRI examinations across centers necessitate greater standardization and accuracy. This study compares the diagnostic efficacy of mpMRI from academic and nonacademic centers in detecting csPCa and identifies factors associated with csPCa detection.

MATERIALS AND METHODS

Between July 2018 and October 2023, we prospectively followed 810 men at SS. Annunziata Hospital of Chieti who underwent MRI/US fusion biopsies due to elevated prostate-specific antigen (PSA) and/or abnormal digital rectal examination (DRE). Patients with mpMRI-documented suspicious lesions classified as PI-RADS ≥ 3 were included. Patients were divided into two groups based on the source of their mpMRI (academic or nonacademic centers). All biopsies were conducted using the MRI/US fusion technique. Clinical, mpMRI, and pathological data were collected and analyzed. Statistical analyses were performed using R software.

RESULTS

The cohort included 354 patients from academic centers and 456 from nonacademic centers. There were no significant differences in patient demographics, such as age and PSA levels, between the groups. Patients at academic centers were more likely to receive a higher number of elevated PI-RADS scores compared to those at nonacademic centers (PI-RADS > 3: 72.6% vs. 62.3%, p = 0.003). Histopathological analysis revealed no significant differences in the ISUP grade distribution between groups. Increased age, PSA levels, and positive DRE were significantly associated with higher odds of detecting csPCa. Median PSA density was significantly higher in patients with csPCa compared to those without csPCa (0.14 vs. 0.11 ng/mL/cm³, p < 0.001). Academic centers exhibited a higher odds ratio for csPCa detection in patients with PI-RADS scores > 3 compared to nonacademic centers.

CONCLUSION

Our study highlights significant variability in PI-RADS score assignments between academic and nonacademic centers, affecting csPCa detection rates. This variability underscores the need for greater standardization in PI-RADS scoring to reduce disparities and improve diagnostic uniformity across centers.

Correlation of Prostate High-Resolution Microultrasound With Multiparametric Magnetic Resonance Imaging

OBJECTIVE

To assess the correlation between high-resolution microultrasound (microUS) and multiparametric magnetic resonance imaging (MP-MRI) in clinically significant prostate cancer (csPCa) lesion identification.

METHODS

We reviewed our prospectively maintained database of 267 consecutive patients who underwent MP-MRI and transperineal microUS-guided biopsy between February 2021 and April 2023. The Prostate Risk Identification using MicroUS (PRI-MUS) protocol was utilized to risk stratify prostate lesions, with PRI-MUS 3-5 defined as positive. MRI lesions were classified according to the Prostate Imaging Reporting and Data System (PI-RADS) version 2.1. Clinicopathologic outcomes were analyzed. Spearman correlation testing was computed to assess the relationship between PRI-MUS and PI-RADS.

RESULTS

A total of 161 patients met inclusion criteria. Mean±standard deviation age was 65.6±1.5years and prostate-specific antigen was 7.6±0.6ng/mL. Ninety-two patients were found to have PIRADS 3-5 lesions. Spearman correlation analysis revealed a moderate positive correlation between PRI-MUS and PI-RADS (r=0.40, P<.001). MicroUS-targeted cores detected higher grade disease than systematic and MRI-targeted cores in 8/161 (5.0%) patients. CsPCa would have been missed in 4/161 (2.5%) patients without microUS-targeted sampling.

CONCLUSION

MicroUS/PRI-MUS demonstrates moderate positive correlation with MP-MRI/PI-RADS and offers improved csPCa detection compared to MRI-targeted biopsy alone. MicroUS may be useful in conjunction with MP-MRI or as an alternative imaging modality in MRI-ineligible patients.

Validation of a Urine-Based Proteomics Test to Predict Clinically Significant Prostate Cancer: Complementing mpMRI Pathway

INTRODUCTION

Prostate cancer (PCa) is the most frequently diagnosed cancer among men. A major clinical need is to accurately predict clinically significant PCa (csPCa). A proteomics-based 19-biomarker model (19-BM) was previously developed using capillary electrophoresis-mass spectrometry (CE-MS) and validated in close to 1,000 patients at risk for PCa. This study aimed to validate 19-BM in a multicenter prospective cohort of 101 biopsy-naive patients using current diagnostic pathways.

METHODS

Urine samples from 101 patients with suspicious of PCa were analyzed using CE-MS. All patients underwent multiparametric or magnetic resonance imaging (mpMRI) using a 3-T system. The 19-BM score was estimated using support vector machine-based software (MosaCluster v1.7.0), employing the previously published cut-off criterion of -0.07. Diagnostic nomograms were investigated along with mpMRI.

RESULTS

Independent validation of 19-BM yielded a sensitivity of 77% and a specificity of 85% (AUC:0.81). This performance surpassed those of prostate-specific antigen (PSA; AUC:0.56) and PSA density (AUC:0.69). For PI-RADS≤ 3 patients, 19-BM showed a sensitivity of 86% and a specificity of 88%. Integrating 19-BM with mpMRI resulted in significantly better accuracy (AUC:0.90) compared to individual investigations alone (AUC19BM = 0.81; p = 0.004 and AUCmpMRI: 0.79; p = 0.001). Examining the decision curve analysis, 19-BM with mpMRI surpassed other approaches for the prevailing risk interval from a 30% cut-off.

CONCLUSIONS

19-BM exhibited favorable reproducibility for the prediction of csPCa. In patients with PI-RADS ≤3, 19-BM correctly classified 88% of the patients with insignificant PCa at the cost of 1 missed csPCa patient. Utilizing the 19-BM test could prove valuable in complementing mpMRI and reducing the need for unnecessary biopsies.

Assessment of a fully-automated diagnostic AI software in prostate MRI: Clinical evaluation and histopathological correlation

OBJECTIVE

This study aims to evaluate the diagnostic performance of a commercial, fully-automated, artificial intelligence (AI) driven software tool in identifying and grading prostate lesions in prostate MRI, using histopathological findings as the reference standard, while contextualizing its performance within the framework of PI-RADS v2.1 criteria.

MATERIAL AND METHODS

This retrospective study analyzed 123 patients who underwent multiparametric prostate MRI followed by systematic and targeted biopsies. MRI protocols adhered to international guidelines and included T2-weighted, diffusion-weighted, T1-weighted, and dynamic contrast-enhanced imaging. The AI software tool mdprostate was integrated into the Picture Archiving and Communication System to automatically segment the prostate, calculate prostate volume, and classify lesions according to PI-RADS scores using biparametric T2-weighted and diffusion-weighted imaging. Histopathological analysis of biopsy cores served as the reference standard. Diagnostic performance metrics including sensitivity, specificity, positive and negative predictive value (PPV, NPV), and area under the ROC curve (AUC) were calculated.

RESULTS

mdprostate demonstrated 100 % sensitivity at a PI-RADS ≥ 2 cutoff, effectively ruling out both clinically significant and non-significant prostate cancers for lesions remaining below this threshold. For detecting clinically significant prostate cancer (csPCa) using a PI-RADS ≥ 4 cutoff, mdprostate achieved a sensitivity of 85.5 % and a specificity of 63.2 %. The AUC for detecting cancers of any grade was 0.803. The performance metrics of mdprostate were comparable to those reported in two meta-analyses of PI-RADS v2.1, with no significant differences in sensitivity and specificity (p > 0.05).

CONCLUSION

The evaluated AI tool demonstrated high diagnostic performance in identifying and grading prostate lesions, with results comparable to those reported in meta-analyses of expert readers using PI-RADS v2.1. Its ability to standardize evaluations and potentially reduce variability underscores its potential as a valuable adjunct in the prostate cancer diagnostic pathway. The high accuracy of mdprostate, particularly in ruling out prostate cancers, highlights its clinical utility by reducing workload and enhancing patient outcomes.

Perspectives on technology: Prostate Imaging-Reporting and Data System (PI-RADS) interobserver variability

OBJECTIVES

To explore the topic of Prostate Imaging-Reporting and Data System (PI-RADS) interobserver variability, including a discussion of major sources, mitigation approaches, and future directions.

METHODS

A narrative review of PI-RADS interobserver variability.

RESULTS

PI-RADS was developed in 2012 to set technical standards for prostate magnetic resonance imaging (MRI), reduce interobserver variability at interpretation, and improve diagnostic accuracy in the MRI-directed diagnostic pathway for detection of clinically significant prostate cancer. While PI-RADS has been validated in selected research cohorts with prostate cancer imaging experts, subsequent prospective studies in routine clinical practice demonstrate wide variability in diagnostic performance. Radiologist and biopsy operator experience are the most important contributing drivers of high-quality care among multiple interrelated factors including variability in MRI hardware and technique, image quality, and population and patient-specific factors such as prostate cancer disease prevalence. Iterative improvements in PI-RADS have helped flatten the curve for novice readers and reduce variability. Innovations in image quality reporting, administrative and organisational workflows, and artificial intelligence hold promise in improving variability even further.

CONCLUSION

Continued research into PI-RADS is needed to facilitate benchmark creation, reader certification, and independent accreditation, which are systems-level interventions needed to uphold and maintain high-quality prostate MRI across entire populations.

Preoperative prostate magnetic resonance imaging does not impact surgical outcomes of radical prostatectomy

Objective

We reviewed our institutional experience of radical prostatectomy with and without preoperative multiparametric magnetic resonance imaging (mpMRI) to assess the impact of preoperative prostate mpMRI on surgical outcomes of radical prostatectomy.

Methods

We identified patients at our institution who underwent radical prostatectomy for prostate cancer (PCa) between January 2012 and December 2017 (n = 1044). Using propensity scoring analysis, patients who underwent preoperative mpMRI (n = 285) were matched 1:1 to patients who did not receive preoperative mpMRI (n = 285). Multivariable regression analysis was performed to identify factors predictive of operative time, estimated blood loss (EBL), lymph node yield, rates of complications within 30 days, and positive surgical margin (PSM).

Results

There were no significant differences in operative time, EBL, PSM, lymph node yield, or complication rates between the two cohorts. Multivariable analysis demonstrated that preoperative mpMRI was not predictive of the measured perioperative outcomes. Significant comorbidity (Charlson Comorbidity Index ≥3) was the sole predictor of perioperative complications (P = 0.015). Increasing biopsy Gleason score predicted increased lymph node yield (P < 0.001). The probability of PSM was associated with increasing preoperative prostate-specific antigen (odds ratio 1.036, P = 0.009). Body mass index was a predictor of operative time (P = 0.016) and EBL (P = 0.001).

Conclusions

Although preoperative mpMRI has an important role in the diagnosis and staging of PCa, it does not impact perioperative radical prostatectomy outcomes. Our findings do not support the routine use of preoperative mpMRI for surgical planning in patients already diagnosed with clinically localized PCa.

The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy

In recent years, advancements in single-cell and spatial transcriptomics, which are highly regarded developments in the current era, particularly the emerging integration of single-cell and spatiotemporal transcriptomics, have enabled a detailed molecular comprehension of the complex regulation of cell fate. The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine. Currently, single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors. Starting from the perspective of RNA sequencing technology, this review outlined the significance of single-cell RNA sequencing (scRNA-seq) in prostate cancer research, encompassing preclinical medicine and clinical applications. We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies, as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis, treatment, and drug resistance characteristics of prostate cancer. These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer. Furthermore, we explore the potential clinical applications stemming from other single-cell technologies in this review, paving the way for future research in precision medicine.

Variability of mpMRI diagnostic performance according to the upfront individual patient risk of having clinically significant prostate cancer

BACKGROUND

To assess the variation of multiparametric magnetic resonance imaging (mpMRI) positive predictive value (PPV) according to each patient's risk of clinically significant prostate cancer (csPCa) based exclusively on clinical factors.

METHODS

We evaluated 999 patients with positive mpMRI (PI-RADS ≥ 3) receiving targeted (TBx) plus systematic prostate biopsy. We built a multivariable logistic regression analysis (MVA) using clinical risk factors to calculate the individual patients' risk of harboring csPCa at TBx. A second MVA tested the association between individual patients' clinical risk and mpMRI PPV accounting for the PI-RADS score. Finally, we plotted the PPV of each PI-RADS score by the individual patient pretest probability of csPCa using a LOWESS approach.

RESULTS

Overall, TBx found csPCa in 21%, 51%, and 80% of patients with PI-RADS 3, 4, and 5 lesions, respectively. At MVA, age, PSA, digital rectal examination (DRE), and prostate volume were significantly associated with the risk of csPCa at biopsy. DRE yielded the highest odds ratio (OR: 2.88; p < 0.001). The individual patient's clinical risk was significantly associated with mpMRI PPV (OR: 2.49; p < 0.001) using MVA. Plotting the mpMRI PPV according to the predicted clinical risks, we observed that for patients with clinical risk close to 0 versus patients with risk higher than 90%, the mpMRI PPV of PI-RADS 3, 4, and 5 ranged from 0% to 75%, from 0% to 96%, and from 45% to 100%, respectively.

CONCLUSION

mpMRI PPV varies according to the individual pretest patient's risk based on clinical factors. These findings should be considered in the decision-making process for patients with suspect MRI findings referred for a prostate biopsy. Moreover, our data support the need for further studies to create an individualized risk prediction tool.

Comparison in Detection Rate of Clinically Significant Prostate Cancer Between Microultrasound-guided Prostate Biopsy (ExactVu) and Multiparametric Resonance Imaging-guided Prostate Biopsy (Koelis System)

OBJECTIVES

To compare the detection rate of clinically significant prostate cancer (csPC) and prostate cancer (PC) and to find out the diagnostic concordance between microultrasound (mUS), a high-resolution imaging system that can identify suspicious prostate lesions and biopsy them in real time, and multiparametric magnetic resonance imaging (mpMRI)-guided prostate fusion biopsies.

METHODS

A prospective, multicenter, single-blind, single cohort study was conducted involving 80 patients with clinically suspected PC who underwent concomitant mpMRI-guided fusion prostate biopsy (Koelis System) and mUS-guided biopsy (ExactVu System) RESULTS: The detection rate of csPC was slightly higher for image-guided fusion biopsy (21.25% vs 18.75%), but this difference was not statistically significant (P = .453). There was also no significant difference in overall PC diagnosis (50% vs 51.25%, P = .897). The degree of agreement between the 2 diagnostic techniques for the detection of csPC as assessed by Cohen's Kappa concordance index was satisfactory κ ̂ = 0.676. The degree of International Society of Urological Pathology of targeted biopsies obtained from concordant lesions was also represented by satisfactory concordance with a Kappa index of κ ̂ = 0. 696.

CONCLUSION

mUS-guided biopsy is presented as an effective diagnostic method for the diagnosis of csPC compared to image-guided fusion biopsy. No differences are found in the detection rates of csPC and PC between the 2 strategies and satisfactory concordance is found in terms of histopathological findings.

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.

Re-evaluating the diagnostic efficacy of PSA as a referral test to detect clinically significant prostate cancer in contemporary MRI-based image-guided biopsy pathways

Introduction

Modern image-guided biopsy pathways at diagnostic centres have greatly refined the investigations of men referred with suspected prostate cancer. However, the referral criteria from primary care are still based on historical prostate-specific antigen (PSA) cut-offs and age-referenced thresholds. Here, we tested whether better contemporary pathways and biopsy methods had improved the predictive utility value of PSA referral thresholds.

Methods

PSA referral thresholds, age-referenced ranges and PSA density (PSAd) were assessed for positive predictive value (PPV) in detection of clinically significant prostate cancer (csPCa - histological ⩾ Grade Group 2). Data were analysed from men referred to three diagnostics centres who used multi-parametric magnetic resonance imaging (mpMRI)-guided prostate biopsies for disease characterisation. Findings were validated in a separate multicentre cohort. Results: Data from 2767 men were included in this study. The median age, PSA and PSAd were 66.4 years, 7.3 ng/mL and 0.1 ng/mL2, respectively. Biopsy detected csPCa was found in 38.7%. The overall area under the curve (AUC) for PSA was 0.68 which is similar to historical performance. A PSA threshold of ⩾ 3 ng/mL had a PPV of 40.3%, but this was age dependent (PPV: 24.8%, 32.7% and 56.8% in men 50-59 years, 60-69 years and ⩾ 70 years, respectively). Different PSA cut-offs and age-reference ranges failed to demonstrate better performance. PSAd demonstrated improved AUC (0.78 vs 0.68, p < 0.0001) and improved PPV compared to PSA. A PSAd of ⩾ 0.10 had a PPV of 48.2% and similar negative predictive value (NPV) to PSA ⩾ 3 ng/mL and out-performed PSA age-reference ranges. This improved performance was recapitulated in a separate multi-centre cohort (n = 541).

Conclusion

The introduction of MRI-based image-guided biopsy pathways does not appear to have altered PSA diagnostic test characteristics to positively detect csPCa. We find no added value to PSA age-referenced ranges, while PSAd offers better PPV and the potential for a single clinically useful threshold (⩾0.10) for all age groups.

Level of evidence

IV.

Mass Spectrometry-Based Biomarkers to Detect Prostate Cancer: A Multicentric Study Based on Non-Invasive Urine Collection without Prior Digital Rectal Examination

(1) Background: Prostate cancer (PCa) is the most frequently diagnosed cancer in men. Wide application of prostate specific antigen test has historically led to over-treatment, starting from excessive biopsies. Risk calculators based on molecular and clinical variables can be of value to determine the risk of PCa and as such, reduce unnecessary and invasive biopsies. Urinary molecular studies have been mostly focusing on sampling after initial intervention (digital rectal examination and/or prostate massage). (2) Methods: Building on previous proteomics studies, in this manuscript, we aimed at developing a biomarker model for PCa detection based on urine sampling without prior intervention. Capillary electrophoresis coupled to mass spectrometry was applied to acquire proteomics profiles from 970 patients from two different clinical centers. (3) Results: A case-control comparison was performed in a training set of 413 patients and 181 significant peptides were subsequently combined by a support vector machine algorithm. Independent validation was initially performed in 272 negative for PCa and 138 biopsy-confirmed PCa, resulting in an AUC of 0.81, outperforming current standards, while a second validation phase included 147 PCa patients. (4) Conclusions: This multi-dimensional biomarker model holds promise to improve the current diagnosis of PCa, by guiding invasive biopsies.

Should men undergo MRI before prostate biopsy - CON

Prostate magnetic resonance imaging (MRI) is increasingly used prior to biopsy in response to the overdiagnosis and overtreatment of prostate cancer (CaP) associated with prostate-specific antigen (PSA) based screening. However, technical limitations in the conventional diffusion-weighted imaging (DWI) sequences as well as the high degree of radiologist-to-radiologist variability in interpreting prostate MRI result in inadequate accuracy. Specifically, the insufficient negative predictive value (NPV) of prostate MRI (76%-87%) does not allow biopsy to be omitted in the negative MRI setting. Additionally, the variable, and relatively low positive predictive value (PPV) of MRI (27%-44%) provides only an incremental improvement in risk prediction compared to readily available clinical tools such as the Prostate Cancer Prevention Trial risk calculator. This small benefit is likely confined to the minority of patients with positive MRI findings in a typically under-sampled region of the prostate (e.g., anterior lesions), which may be obviated by newer biopsy approaches and tools such as transperineal prostate biopsy and micro-ultrasound technology. With these considerations in mind, pre-biopsy prostate MRI in its current form is unlikely to provide a clinically significant benefit, and should not be considered as routine practice until its accuracy is sufficiently improved.

Comparison of prostate cancer detection rate at targeted biopsy of hub and spoke centers mpMRI: experience matters

BACKGROUND

Latest changes in European guidelines on prostate cancer determined a widespread of multiparametric magnetic resonance imaging (mpMRI) even in less experienced centers due to an increased demand. This could decrease diagnostic accuracy of targeted biopsy (TB) since image interpretation can be challenging and requires adequate and supervised training. Therefore we aimed to evaluate the prostate cancer (PCa) detection rate on TB according to mpMRI center's volume and experience.

METHODS

We retrospectively analyzed data of 737 patients who underwent mpMRI-TB at our institution. Patients were stratified according to mpMRI center: Hub (high volume >100 exams/year with dedicated radiologists and supervised training) and Spoke center (low volume <100 exams/year without dedicated radiologists and/or supervised training). Detection rate of PCa at TB and possible predictors of clinically significant PCa (csPCa) at TB. Differences in detection rate were explored using Chi-square test. Predictors of csPCa were evaluated through uni and multivariable logistic regression. The adjustment for casemix included: age, PSA, mpMRI center, lesion's location, PSA density, PI-RADS score and index lesion's size.

RESULTS

Four hundred forty-nine (60.9%) and 288 (39.1%) patients underwent mpMRI at a Hub or Spoke center, respectively. Hub group had higher detection rate for both any (60.3% vs. 48.1%) and csPCa (46.9% vs 38.7%; all P≤0.001). After stratifying for PI-RADS score, Hub group had higher detection rate for PI-RADS score 3 (csPCA 25.2% vs. 15.7%; p 0.04) and 4 (csPCa 65.7% vs. 45.7%; P=0.001). At multivariable analyses, receiving an mpMRI scan at a Spoke center was an independent predictor for csPCa on TB (OR 0.65; P=0.04).

CONCLUSIONS

mpMRI performed in Hub centers provided a significantly higher PCa yield on TB. A dedicated team of experienced radiologist, a supervised training for mpMRI and a central revision of mpMRI performed in non-experienced centres are essential to avoid unnecessary and potentially harmful procedures.

Single-cell Spatial Proteomic Revelations on the Multiparametric MRI Heterogeneity of Clinically Significant Prostate Cancer

PURPOSE

Multiparametric MRI (mpMRI) has become an indispensable radiographic tool in diagnosing prostate cancer. However, mpMRI fails to visualize approximately 15% of clinically significant prostate cancer (csPCa). The molecular, cellular, and spatial underpinnings of such radiographic heterogeneity in csPCa are unclear.

EXPERIMENTAL DESIGN

We examined tumor tissues from clinically matched patients with mpMRI-invisible and mpMRI-visible csPCa who underwent radical prostatectomy. Multiplex immunofluorescence single-cell spatial imaging and gene expression profiling were performed. Artificial intelligence-based analytic algorithms were developed to examine the tumor ecosystem and integrate with corresponding transcriptomics.

RESULTS

More complex and compact epithelial tumor architectures were found in mpMRI-visible than in mpMRI-invisible prostate cancer tumors. In contrast, similar stromal patterns were detected between mpMRI-invisible prostate cancer and normal prostate tissues. Furthermore, quantification of immune cell composition and tumor-immune interactions demonstrated a lack of immune cell infiltration in the malignant but not in the adjacent nonmalignant tissue compartments, irrespective of mpMRI visibility. No significant difference in immune profiles was detected between mpMRI-visible and mpMRI-invisible prostate cancer within our patient cohort, whereas expression profiling identified a 24-gene stromal signature enriched in mpMRI-invisible prostate cancer. Prostate cancer with strong stromal signature exhibited a favorable survival outcome within The Cancer Genome Atlas prostate cancer cohort. Notably, five recurrences in the 8 mpMRI-visible patients with csPCa and no recurrence in the 8 clinically matched patients with mpMRI-invisible csPCa occurred during the 5-year follow-up post-prostatectomy.

CONCLUSIONS

Our study identified distinct molecular, cellular, and structural characteristics associated with mpMRI-visible csPCa, whereas mpMRI-invisible tumors were similar to normal prostate tissue, likely contributing to mpMRI invisibility.

Use of the MyProstateScore Test to Rule Out Clinically Significant Cancer: Validation of a Straightforward Clinical Testing Approach

PURPOSE

The MyProstateScore test was validated for improved detection of clinically significant (grade group ≥2) prostate cancer relative to prostate specific antigen based risk calculators. We sought to validate an optimal MyProstateScore threshold for clinical use in ruling out grade group ≥2 cancer in men referred for biopsy.

MATERIALS AND METHODS

Biopsy naïve men provided post-digital rectal examination urine prior to biopsy. MyProstateScore was calculated using the validated, locked multivariable model including only serum prostate specific antigen, urinary prostate cancer antigen 3 and urinary TMPRSS2:ERG. The MyProstateScore threshold approximating 95% sensitivity for grade group ≥2 cancer was identified in a training cohort, and performance was measured in 2 external validation cohorts. We assessed the 1) overall biopsy referral population and 2) population meeting guideline based testing criteria (ie, prostate specific antigen 3-10, or <3 with suspicious digital rectal examination).

RESULTS

Validation cohorts were prospectively enrolled from academic (977 patients, median prostate specific antigen 4.5, IQR 3.1-6.0) and community (548, median prostate specific antigen 4.9, IQR 3.7-6.8) settings. In the overall validation population (1,525 patients), 338 men (22%) had grade group ≥2 cancer on biopsy. The MyProstateScore threshold of 10 provided 97% sensitivity and 98% negative predictive value for grade group ≥2 cancer. MyProstateScore testing would have prevented 387 unnecessary biopsies (33%), while missing only 10 grade group ≥2 cancers (3.0%). In 1,242 patients meeting guideline based criteria, MyProstateScore ≤10 provided 96% sensitivity and 97% negative predictive value, and would have prevented 32% of unnecessary biopsies, missing 3.7% of grade group ≥2 cancers.

CONCLUSIONS

In a large, clinically pertinent biopsy referral population, MyProstateScore ≤10 provided exceptional sensitivity and negative predictive value for ruling out grade group ≥2 cancer. This straightforward secondary testing approach would reduce the use of more costly and invasive procedures after screening with prostate specific antigen.

3D Registration of pre-surgical prostate MRI and histopathology images via super-resolution volume reconstruction

The use of MRI for prostate cancer diagnosis and treatment is increasing rapidly. However, identifying the presence and extent of cancer on MRI remains challenging, leading to high variability in detection even among expert radiologists. Improvement in cancer detection on MRI is essential to reducing this variability and maximizing the clinical utility of MRI. To date, such improvement has been limited by the lack of accurately labeled MRI datasets. Data from patients who underwent radical prostatectomy enables the spatial alignment of digitized histopathology images of the resected prostate with corresponding pre-surgical MRI. This alignment facilitates the delineation of detailed cancer labels on MRI via the projection of cancer from histopathology images onto MRI. We introduce a framework that performs 3D registration of whole-mount histopathology images to pre-surgical MRI in three steps. First, we developed a novel multi-image super-resolution generative adversarial network (miSRGAN), which learns information useful for 3D registration by producing a reconstructed 3D MRI. Second, we trained the network to learn information between histopathology slices to facilitate the application of 3D registration methods. Third, we registered the reconstructed 3D histopathology volumes to the reconstructed 3D MRI, mapping the extent of cancer from histopathology images onto MRI without the need for slice-to-slice correspondence. When compared to interpolation methods, our super-resolution reconstruction resulted in the highest PSNR relative to clinical 3D MRI (32.15 dB vs 30.16 dB for BSpline interpolation). Moreover, the registration of 3D volumes reconstructed via super-resolution for both MRI and histopathology images showed the best alignment of cancer regions when compared to (1) the state-of-the-art RAPSODI approach, (2) volumes that were not reconstructed, or (3) volumes that were reconstructed using nearest neighbor, linear, or BSpline interpolations. The improved 3D alignment of histopathology images and MRI facilitates the projection of accurate cancer labels on MRI, allowing for the development of improved MRI interpretation schemes and machine learning models to automatically detect cancer on MRI.

Diagnostic pathway of the biopsy-naïve patient suspected for prostate cancer: Real-life scenario when multiparametric Magnetic Resonance Imaging is not centralized

INTRODUCTION

We aimed to compare the pathway including multi-parametric Magnetic Resonance Imaging (mpMRI) versus the one without mpMRI in detection of prostate cancer (PCa) when mpMRI is not centralized.

MATERIALS

January 2019-March 2020: prospective data collection of trans-perineal prostate biopsies. Group A: biopsy-naïve patients who underwent mpMRI (at any institution) versus Group B: patients who did not. Within Group A, patients were stratified into those with negative mpMRI (mpMRI-, PIRADS v2.1=1-3, with PSA density <0.15 if PIRADS 3) who underwent standard biopsy (SB), versus those with positive mpMRI (mpMRI+, when PIRADS 3-5, with PSA density>0.15 if PIRADS 3) who underwent cognitive fusion biopsy.

RESULTS

Two hundred and eighty one biopsies were analyzed. 153 patients underwent mpMRI (Group A). 98 mpMRI+ underwent fusion biopsy; 55 mpMRI- underwent SB. 128 Group B patients underwent SB. Overall PCa detection rate was 52.3% vs. 48.4% (Group A vs. B, P=0.5). Non-clinically-significant PCa was detected in 7.8 vs. 13.3% (Group A vs. B, P=0.1). Among the 98 mpMRI+ Group A patients only 2 had non clinically-significant disease. In 55 mpMRI- patients who underwent SB, 10 (18.2%) had clinically-significant PCa. Prostate volume predicted detection of PCa. In Group B, age and PSA predicted PCa. Sensitivity of mpMRI was 75.0% for all PCa, 85.3% for clinically-significant PCa.

CONCLUSION

Higher detection of PCa and lower detection of non-clinically-significant PCa favored mpMRI pathway. A consistent number of clinically-significant PCa was diagnosed after a mpMRI-. Thus, in real-life scenario, mpMRI- does not obviate indication to biopsy when mpMRI is not centralized.

LEVEL OF EVIDENCE

3.

Role of Multiparametric Magnetic Resonance Imaging in Predicting Pathologic Outcomes in Prostate Cancer

Multiparametric magnetic resonance imaging (mpMRI) and the introduction of standardized protocols for its interpretation have had a significant impact on the field of prostate cancer (PC). Multiple randomized controlled trials have shown that the sensitivity for detection of clinically significant PC is increased when mpMRI results are the basis for indication of a prostate biopsy. The added value with regards to sensitivity has been strongest for patients with persistent suspicion for PC after a prior negative biopsy. Although enhanced sensitivity of mpMRI is convincing, studies that have compared mpMRI with prostatectomy specimens prepared by whole-mount section analysis have shown a significant number of lesions that were not detected by mpMRI. In this context, the importance of an additional systematic biopsy (SB) is still being debated. While SB in combination with targeted biopsies leads to an increased detection rate, most of the tumors detected by SB only are considered clinically insignificant. Currently, multiple risk calculation tools are being developed that include not only clinical parameters but mpMRI results in addition to clinical parameters in order to improve risk stratification for PC, such as the Partin tables. In summary, mpMRI of the prostate has become a standard procedure recommended by multiple important guidelines for the diagnostic work-up of patients with suspicion of PC.

Clinical utility and cost modelling of the phi test to triage referrals into image-based diagnostic services for suspected prostate cancer: the PRIM (Phi to RefIne Mri) study

BACKGROUND

The clinical pathway to detect and diagnose prostate cancer has been revolutionised by the use of multiparametric MRI (mpMRI pre-biopsy). mpMRI however remains a resource-intensive test and is highly operator dependent with variable effectiveness with regard to its negative predictive value. Here we tested the use of the phi assay in standard clinical practice to pre-select men at the highest risk of harbouring significant cancer and hence refine the use of mpMRI and biopsies.

METHODS

A prospective five-centre study recruited men being investigated through an mpMRI-based prostate cancer diagnostic pathway. Test statistics for PSA, PSA density (PSAd) and phi were assessed for detecting significant cancers using 2 definitions: ≥ Grade Group (GG2) and ≥ Cambridge Prognostic Groups (CPG) 3. Cost modelling and decision curve analysis (DCA) was simultaneously performed.

RESULTS

A total of 545 men were recruited and studied with a median age, PSA and phi of 66 years, 8.0 ng/ml and 44 respectively. Overall, ≥ GG2 and ≥ CPG3 cancer detection rates were 64% (349/545), 47% (256/545) and 32% (174/545) respectively. There was no difference across centres for patient demographics or cancer detection rates. The overall area under the curve (AUC) for predicting ≥ GG2 cancers was 0.70 for PSA and 0.82 for phi. AUCs for ≥ CPG3 cancers were 0.81 and 0.87 for PSA and phi respectively. AUC values for phi did not differ between centres suggesting reliability of the test in different diagnostic settings. Pre-referral phi cut-offs between 20 and 30 had NPVs of 0.85-0.90 for ≥ GG2 cancers and 0.94-1.0 for ≥ CPG3 cancers. A strategy of mpMRI in all and biopsy only positive lesions reduced unnecessary biopsies by 35% but missed 9% of ≥ GG2 and 5% of ≥ CPG3 cancers. Using PH ≥ 30 to rule out referrals missed 8% and 5% of ≥ GG2 and ≥ CPG3 cancers (and reduced unnecessary biopsies by 40%). This was achieved however with 25% fewer mpMRI. Pathways incorporating PSAd missed fewer cancers but necessitated more unnecessary biopsies. The phi strategy had the lowest mean costs with DCA demonstrating net clinical benefit over a range of thresholds.

CONCLUSION

phi as a triaging test may be an effective way to reduce mpMRI and biopsies without compromising detection of significant prostate cancers.

Interreader variability in prostate MRI reporting using Prostate Imaging Reporting and Data System version 2.1

OBJECTIVES

To evaluate the agreement among readers with different expertise in detecting suspicious lesions at prostate multiparametric MRI using Prostate Imaging Reporting and Data System (PI-RADS) version 2.1.

METHODS

We evaluated 200 consecutive biopsy-naïve or previously negative biopsy men who underwent MRI for clinically suspected prostate cancer (PCa) between May and September 2017. Of them, 132 patients underwent prostate biopsy. Seven radiologists (four dedicated uro-radiologists and three non-dedicated abdominal radiologists) reviewed and scored all MRI examinations according to PI-RADS v2.1. Agreement on index lesion detection was evaluated with Conger's k coefficient, agreement coefficient 1 (AC1), percentage of agreement (PA), and indexes of specific positive and negative agreement. Clinical and radiological features that may influence variability were evaluated.

RESULTS

Agreement in index lesion detection among all readers was substantial (AC1 0.738; 95% CI 0.695-0.782); dedicated radiologists showed higher agreement compared with non-dedicated readers. Clinical and radiological parameters that positively influenced agreement were PSA density ≥ 0.15 ng/mL/cc, pre-MRI high risk for PCa, positivity threshold of PI-RADS score 4 + 5, PZ lesions, homogeneous signal intensity of the PZ, and subjectively easy interpretation of MRI. Positive specific agreement was significantly higher among dedicated readers, up to 93.4% (95% CI 90.7-95.4) in patients harboring csPCa. Agreement on absence of lesions was excellent for both dedicated and non-dedicated readers (respectively 85.1% [95% CI 78.4-92.3] and 82.0% [95% CI 77.2-90.1]).

CONCLUSIONS

Agreement on index lesion detection among radiologists of various experiences is substantial to excellent using PI-RADS v2.1. Concordance on absence of lesions is excellent across readers' experience.

KEY POINTS

• Agreement on index lesion detection among radiologists of various experiences is substantial to excellent using PI-RADS v2.1. • Concordance between experienced readers is higher than between less-experienced readers. • Concordance on absence of lesions is excellent across readers' experience.

Performance of Combined Magnetic Resonance Imaging/Ultrasound Fusion-guided and Systematic Biopsy of the Prostate in Biopsy-naïve Patients and Patients with Prior Biopsies

BACKGROUND

As recent prospective studies showed targeted biopsies (TBs) to be superior to systematic biopsies (SBs), magnetic resonance imaging (MRI) is gaining wider acceptance in the diagnostic setup of prostate cancer (PCa).

OBJECTIVE

To examine the performance of MRI/ultrasound fusion-guided TB in combination with SB in the detection of PCa in patients with and without prior biopsy.

DESIGN, SETTING, AND PARTICIPANTS

A total of 219 men undergoing combined transrectal TB and 12-core SB from February 2014 to November 2018 were analysed. For all patients showing a suspicion of PCa in multiparametric MRI, TB was performed using fusion imaging with real-time virtual sonography.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Cancer detection rates (CDRs) and significant CDRs for TB, SB, and TB+SB were analysed. Further stratification was performed for a number of previous biopsy sessions and Prostate Imaging Reporting and Data System (PI-RADS) score. Significant PCa was defined as any PCa with Gleason score ≥3+4.

RESULTS AND LIMITATIONS

Of all, 141 patients were biopsy naïve, while 78 patients had at least one prior biopsy. Median prostate-specific antigen (PSA) level prior to biopsy was 8.4ng/ml (interquartile range 5.5-11.8ng/ml). The overall CDR was 63.5% (139/219), while the PI-RADS-dependent CDRs for the combination of TB+SB were 29.1%, 67.7%, and 86.2% for patients with PI-RADS 3, 4, and 5, respectively. Looking at TB or SB alone, CDRs were 55.7% and 57.5%. The overall CDR for significant PCa was 51.6%. (18.2%, 50.5%, and 81.5% for PI-RADS 3, 4, and 5, respectively). CDRs were significantly higher for biopsy-naïve patients (65.2% vs 67.4% vs 71.6% for TB vs SB vs TB+SB) than for patients with one previous negative biopsy (38.2% vs 43.6% vs 50.9% for TB vs SB vs TB+SB; all p<0.01).

CONCLUSIONS

Multiparametric MRI can raise the CDR in patients with and without biopsies performed earlier. With higher PI-RADS lesions, the risk of harbouring PCa increases. Combining TB with SB further improved the diagnostic accuracy in biopsy-naïve patients and after one previous negative biopsy.

PATIENT SUMMARY

Multiparametric magnetic resonance imaging before prostate biopsy increases cancer detection rates in biopsy-naïve patients and patients with a previous negative biopsy. The combination of targeted biopsy with systematic biopsy improved the diagnostic accuracy in biopsy-naïve patients and after one previous negative biopsy.