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

Contemporary Diagnosis of Very Low-risk Prostate Cancer in a Multihospital Health Care System

The National Comprehensive Cancer Network (NCCN) very low risk (VLR) category for prostate cancer (PCa) represents clinically insignificant disease, and detection of VLR PCa contributes to overdiagnosis. Greater use of magnetic resonance imaging (MRI) and biomarkers before patient selection for prostate biopsy (PBx) reduces unnecessary biopsies and may reduce the diagnosis of clinically insignificant PCa. We tested a hypothesis that the proportion of VLR diagnoses has decreased with greater use of MRI-informed PBx using data from our 11-hospital system. From 2018 to 2023, 351/3197 (11%) men diagnosed with PCa met the NCCN VLR criteria. The proportion of VLR diagnoses did not change from 2018 to 2023 (p = 0.8) despite an increase in the use of MRI-informed PBx (from 49% to 82%; p < 0.001). Of patients who underwent combined systematic and targeted PBx and were diagnosed with VLR disease, cancer was found in systematic PBx regions in 79% of cases and in targeted PBx regions in 31% of cases. When performing both systematic and targeted PBx, prebiopsy MRI-based risk calculators could limit VLR diagnosis by 41% using a risk threshold of >5% for Gleason grade group ≥3 PCa to recommend biopsy; the reduction would be 77% if performing targeted PBx only. These findings suggest that VLR disease continues to account for a significant minority of PCa diagnoses and could be limited by targeted PBx and risk stratification calculators. PATIENT SUMMARY: We looked at recent trends for the diagnosis of very low-risk (VLR) prostate cancer. We found that VLR cancer still seems to be frequently diagnosed despite the use of MRI (magnetic resonance imaging) scans before biopsy. The use of risk calculators to identify men who could avoid biopsy and/or biopsy only for lesions that are visible on MRI could reduce the overdiagnosis of VLR prostate cancer.

Diagnostic Performance of Prostate-specific Antigen Density for Detecting Clinically Significant Prostate Cancer in the Era of Magnetic Resonance Imaging: A Systematic Review and Meta-analysis

CONTEXT

There has been a dramatic increase in the use of prostate magnetic resonance imaging (MRI) in the diagnostic workup. With prostate volume calculated from MRI, prostate-specific antigen density (PSAD) now is a ready-to-use parameter for prostate cancer (PCa) risk stratification before prostate biopsy, especially among patients with negative MRI or equivocal lesions.

OBJECTIVE

In this review, we aimed to evaluate the diagnostic performance of PSAD for clinically significant prostate cancer (CSPCa) among patients who received MRI before prostate biopsy.

EVIDENCE ACQUISITION

Two investigators performed a systematic review according of the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) criteria. Studies (published between January 1, 2012, and December 31, 2021) reporting the diagnostic performance (outcomes) of PSAD (intervention) for CSPCa among men who received prebiopsy prostate MRI and subsequent prostate biopsy (patients), using biopsy pathology as the gold standard (comparison), were eligible for inclusion.

EVIDENCE SYNTHESIS

A total of 1536 papers were identified in PubMed, Scopus, and Embase. Of these, 248 studies were reviewed in detail and 39 were qualified. The pooled sensitivity (SENS) and specificity (SPEC) for diagnosing CSPCa among patients with positive MRI were, respectively, 0.87 and 0.35 for PSAD of 0.1 ng/ml/ml, 0.74 and 0.61 for PSAD of 0.15 ng/ml/ml, and 0.51 and 0.81 for PSAD of 0.2 ng/ml/ml. The pooled SENS and SPEC for diagnosing CSPCa among patients with negative MRI were, respectively, 0.85 and 0.36 for PSAD of 0.1 ng/ml/ml, 0.60 and 0.66 for PSAD of 0.15 ng/ml/ml, and 0.33 and 0.84 for PSAD of 0.2 ng/ml/ml. The pooled SENS and SPEC among patients with Prostate Imaging Reporting and Data System (PI-RADS) 3 or Likert 3 lesions were, respectively, 0.87 and 0.39 for PSAD of 0.1 ng/ml/ml, 0.61 and 0.69 for PSAD of 0.15 ng/ml/ml, and 0.42 and 0.82 for PSAD of 0.2 ng/ml/ml. The post-test probability for CSPCa among patients with negative MRI was 6% if PSAD was <0.15 ng/ml/ml and dropped to 4% if PSAD was <0.10 ng/ml/ml.

CONCLUSIONS

In this systematic review, we quantitatively evaluated the diagnosis performance of PSAD for CSPCa in combination with prostate MRI. It demonstrated a complementary performance and predictive value, especially among patients with negative MRI and PI-RADS 3 or Likert 3 lesions. Integration of PSAD into decision-making for prostate biopsy may facilitate improved risk-adjusted care.

PATIENT SUMMARY

Prostate-specific antigen density is a ready-to-use parameter in the era of increased magnetic resonance imaging (MRI) use in clinically significant prostate cancer (CSPCa) diagnosis. Findings suggest that the chance of having CSPCa was very low (4% or 6% for those with negative prebiopsy MRI or Prostate Imaging Reporting and Data System (Likert) score 3 lesion, respectively, if the PSAD was <0.10 ng/ml/ml), which may lower the need for biopsy in these patients.

The diagnostic accuracy of micro-ultrasound for prostate cancer diagnosis: a review

PURPOSE

Micro-UltraSound (microUS) is a new imaging modality capable of identifying and targeting suspicious areas, which might further increase the diagnostic yield of prostate biopsy (PBx). Aim of this review is to provide insights into the usefulness of microUS for the sub-stratification of prostate cancer (PCa), clinically significant PCa (i.e., any Gleason score ≥ 7 PCa; csPCa) along with non-organ-confined disease in patients undergoing PBx.

METHODS

A PubMed literature search was performed using keywords: prostate cancer diagnosis, prostate cancer diagnosis surveillance, systematic biopsy, target biopsy, micro-ultrasound, and prostate risk identification using micro-ultrasound.

RESULTS

MicroUS could significantly improve multiparametric magnetic resonance imaging (mpMRI) findings by adding valuable anatomical and pathological information provided by real-time examination. Furthermore, microUS target biopsy could replace systematic biopsy in clinical practice by reducing the detection of clinically insignificant (ciPCa) and increasing that of csPCa. Finally, microUS may be useful in predicting the presence of non-organ confined PCa before radical prostatectomy and it could also be an effective add-on tool for patient monitoring within the active surveillance program.

CONCLUSION

MicroUS may represent an attractive step forward for the management of csPCa as a complementary or alternative tool to mpMRI. Nevertheless, further longitudinal studies are warranted, and the strength of the evidence is still suboptimal to provide clear recommendations for daily clinical practice.

Optimal PSA density threshold and predictive factors for the detection of clinically significant prostate cancer in patient with a PI-RADS 3 lesion on MRI

INTRODUCTION

While Prostate Imaging Reporting and Data System (PI-RADS) 4 and 5 lesions usually justify prostate biopsy (PBx), the management of a PI-RADS 3 lesion can be discussed. The aim of our study was to determine the optimal prostate-specific antigen density (PSAD) threshold and predictive factors of clinically significant prostate cancer (csPCa) in patients with a PI-RADS 3 lesion on MRI.

PATIENTS AND METHODS

Using our prospectively maintained database, we conducted a monocentric retrospective study, including all patients with a clinical suspicious of prostate cancer (PCa), all of them had a PI-RADS 3 lesion on the mpMRI prior to PBx. Patients under active surveillance or displaying suspicious digital rectal examination were excluded. Clinically significant (csPCa) was defined as PCa with any ISUP grade group ≥ 2 (Gleason ≥ 3 + 4).

RESULTS

We included 158 patients. The detection rate of csPCa was 22.2%. In case of PSAD ≤ 0.15 ng/ml/cm³, PBx would be omitted in 71.5% (113/158) of men at the cost of missing 15.0% (17/113) of csPCa. With a threshold of 0.15 ng/ml/cm³, the sensitivity and the specificity were 0.51 and 0.78 respectively. The positive predictive value was 0.40 and the negative predictive value was 0.85. According to multivariate analysis, age (OR = 1.10, CI95% 1.03-1.19, P = 0.007), and PSAD ≥ 0.15 ng/ml/cm³ (OR = 3.59, CI95% 1.41-9.47, P = 0.008) were independent predictive factors of csPCa. Previous negative PBx was negatively associated with csPCa (OR = 0.24, CI 95% 0.07-0.66, P = 0.01).

CONCLUSION

Our result suggests that the optimal PSAD threshold was 0.15 ng/ml/cm³. However, in this case omitting PBx in 71.5% of cases would be at the cost of missing 15.0% of csPCa. PSAD should not be used alone, other predictive factors as age and PBx history should also be considered in the discussion with the patient, to avoid PBx while missing few csPCa.

Clinical performance of magnetic resonance imaging and biomarkers for prostate cancer diagnosis in men at high genetic risk

OBJECTIVES

To evaluate different scenarios for the management of early diagnosis of cancer (PCa) in men at high genetic risk, using recently developed blood and urinary molecular biomarkers in combination with clinical information alongside multiparametric magnetic resonance imaging (mpMRI).

PATIENTS AND METHODS

A total of 322 patients with a high genetic risk (familial or personal history of cancers or a predisposing germline variant) were included in this study. The primary outcome was the detection rates of PCa (positive biopsy) or clinically significant PCa (biopsy with International Society of Urological Pathology [ISUP] grade >1). Clinical parameters included age, body mass index, ancestry, and germline mutational status, mpMRI, prostate-specific antigen density (PSAD), Prostate Health Index and urinary markers (Prostate Cancer Associated 3, SelectMdx™ and T2:ERG score) were assessed. Sensitivity (Se) and specificity (Sp) for each marker at their recommended cut-off for clinical practice were calculated. Comparison between diagnoses accuracy of each procedure and scenario was computed using mutual information based and direct effect contribution using a supervised Bayesian network approach.

RESULTS

A mpMRI Prostate Imaging-Reporting and Data System (PI-RADS) score ≥3 showed higher Se than mpMRI PI-RADS score ≥4 for detection of PCa (82% vs 61%) and for the detection of ISUP grade >1 lesions (96% vs 80%). mpMRI PI-RADS score ≥3 performed better than a PSA level of ≥3 ng/mL (Se 96%, Sp 53% vs Se 91%, Sp 8%) for detection of clinically significant PCa. In case of negative mpMRI results, the supervised Bayesian network approach showed that urinary markers (with the same accuracy for all) and PSAD of ≥0.10 ng/mL/mL were the most useful indicators of decision to biopsy.

CONCLUSIONS

We found that screening men at high genetic risk of PCa must be based on mpMRI without pre-screening based on a PSA level of >3 ng/mL, to avoid missing too many ISUP grade >1 tumours and to significantly reduce the number of unnecessary biopsies. However, urinary markers or a PSAD of ≥0.10 ng/mL/mL when mpMRI was negative increased the detection of ISUP grade >1 cancers. We suggest that a baseline mpMRI be discussed for men at high genetic risk from the age of 40 years.

Micro-Ultrasound in the Diagnosis and Staging of Prostate and Bladder Cancer: A Comprehensive Review

Background and Objectives: Multiparametric magnetic resonance imaging (mpMRI) of the prostate and prostate-specific membrane antigen positron emission tomography (PSMA PET) are some examples of how the advancement of imaging techniques have revolutionized the diagnosis, staging, and consequently management of patients with prostate cancer (PCa). Although with less striking results, novel radiological modalities have also been proposed for bladder cancer (BCa) in recent years. Micro-ultrasound (MUS) is an imaging examination characterized by high real-time spatial resolution, recently introduced in the urological field. This article aimed to describe the current evidence regarding the application of MUS for the diagnosis and staging of PCa and BCa. Materials and Methods: We designed a narrative review. A comprehensive search in the MEDLINE, Scopus, and Cochrane Library databases was performed. Articles in English-language and published until July 2022 were deemed eligible. Retrospective and prospective primary clinical studies, as well as meta-analyses, were included. Results: MUS-guided prostate biopsy showed high sensitivity (0.91, 95% CI, 0.79-0.97) in the diagnosis of clinically significant PCa (csPCa). It was associated with a higher detection rate of csPCa than a systematic biopsy (1.18, 95% CI 0.83-1.68). No significant difference was found between MUS and mpMRI-guided biopsy in the total detection of PCa (p = 0.89) and in the detection of Grade Groups ≥ 2 (p = 0.92). The use of MUS to distinguish between non-muscle-invasive and muscle-invasive BCa was described, highlighting an up-staging with MUS only in a minority of cases (28.6%). Conclusions: Promising findings have emerged regarding the feasibility and accuracy of MUS in the diagnosis and staging of PCa and BCa. However, the available evidence is limited and should be considered preliminary.

Alternatives for MRI in Prostate Cancer Diagnostics-Review of Current Ultrasound-Based Techniques

Simple Summary

Prostate cancer (PCa) is the most common solid malignant tumor in men worldwide with various clinical manifestations. Due to overdiagnosis and overtreatment of a clinically insignificant disease, multiparametric magnetic resonance imaging is recommended for every patient before performing prostate biopsy. However, the diagnostic pathway currently has many limitations and is still far from ideal. Therefore, further alternatives need to be investigated. As the novel ultrasound-based techniques, such as shear wave elastography, contrast-enhanced ultrasound or high frequency micro-ultrasound are able to, overcome the limitations of magnetic resonance imaging presenting good performance in recent studies, we have summarized and compared the results of each technique in the detection of PCa. Furthermore, we analyzed the future perspectives for ultrasound modalities that may soon significantly improve their diagnostic value.

Abstract

The purpose of this review is to present the current role of ultrasound-based techniques in the diagnostic pathway of prostate cancer (PCa). With overdiagnosis and overtreatment of a clinically insignificant PCa over the past years, multiparametric magnetic resonance imaging (mpMRI) started to be recommended for every patient suspected of PCa before performing a biopsy. It enabled targeted sampling of the suspicious prostate regions, improving the accuracy of the traditional systematic biopsy. However, mpMRI is associated with high costs, relatively low availability, long and separate procedure, or exposure to the contrast agent. The novel ultrasound modalities, such as shear wave elastography (SWE), contrast-enhanced ultrasound (CEUS), or high frequency micro-ultrasound (MicroUS), may be capable of maintaining the performance of mpMRI without its limitations. Moreover, the real-time lesion visualization during biopsy would significantly simplify the diagnostic process. Another value of these new techniques is the ability to enhance the performance of mpMRI by creating the image fusion of multiple modalities. Such models might be further analyzed by artificial intelligence to mark the regions of interest for investigators and help to decide about the biopsy indications. The dynamic development and promising results of new ultrasound-based techniques should encourage researchers to thoroughly study their utilization in prostate imaging.

Transrectal Ultrasound in Prostate Cancer: Current Utilization, Integration with mpMRI, HIFU and Other Emerging Applications

Transrectal ultrasound (TRUS) has been an invaluable tool in the assessment of prostate size, anatomy and aiding in prostate cancer (PCa) diagnosis for decades. Emerging techniques warrant an investigation into the efficacy of TRUS, how it compares to new techniques, and options to increase the accuracy of prostate cancer diagnosis. Currently, TRUS is used to guide both transrectal and transperineal biopsy approaches with similar cancer detection rates, but lower rates of infection have been reported with the transperineal approach, while lower rates of urinary retention are often reported with the transrectal approach. Multiparametric MRI has substantial benefits for prostate cancer diagnosis and triage such as lesion location, grading, and can be combined with TRUS to perform fusion biopsies targeting specific lesions. Micro-ultrasound generates higher resolution images that traditional ultrasound and has been shown effective at diagnosing PCa, giving it the potential to become a future standard of care. Finally, high-intensity focused ultrasound focal therapy administered via TRUS has been shown to offer safe and effective short-term oncological control for localized disease with low morbidity, and the precise nature makes it a viable option for salvage and repeat therapy.

Use of high-resolution micro-ultrasound to predict extraprostatic extension of prostate cancer prior to surgery: a prospective single-institutional study

PURPOSE

We aim to evaluate the accuracy of micro-ultrasound (microUS) in predicting extraprostatic extension (EPE) of Prostate Cancer (PCa) prior to surgery.

METHODS

Patients with biopsy-proven PCa scheduled for robot-assisted radical prostatectomy (RARP) were prospectively recruited. The following MRI-derived microUS features were evaluated: capsular bulging, visible breach of the prostate capsule (visible extracapsular extension; ECE), presence of hypoechoic halo, and obliteration of the vesicle-prostatic angle. The ability of each feature to predict EPE was determined.

RESULTS

Overall, data from 140 patients were examined. All predictors were associated with non-organ-confined disease (p < 0.001). Final pathology showed that 79 patients (56.4%) had a pT2 disease and 61 (43.3%) ≥ pT3. Rate of non-organ-confined disease increased from 44% in those individuals with only 1 predictor (OR 7.71) to 92.3% in those where 4 predictors (OR 72.00) were simultaneously observed. The multivariate logistic regression model including clinical parameters showed an area under the curve (AUC) of 82.3% as compared to an AUC of 87.6% for the model including both clinical and microUS parameters. Presence of ECE at microUS predicted EPE with a sensitivity of 72.1% and a specificity of 88%, a negative predictive value of 80.5% and positive predictive value of 83.0%, with an AUC of 80.4%.

CONCLUSIONS

MicroUS can accurately predict EPE at the final pathology report in patients scheduled for RARP.

Multiparametric ultrasound of prostate: role in prostate cancer diagnosis

Recent advances in ultrasonography (US) technology established modalities, such as Doppler-US, HistoScanning, contrast-enhanced ultrasonography (CEUS), elastography, and micro-ultrasound. The early results of these US modalities have been promising, although there are limitations including the need for specialized equipment, inconsistent results, lack of standardizations, and external validation. In this review, we identified studies evaluating multiparametric ultrasonography (mpUS), the combination of multiple US modalities, for prostate cancer (PCa) diagnosis. In the past 5 years, a growing number of studies have shown that use of mpUS resulted in high PCa and clinically significant prostate cancer (CSPCa) detection performance using radical prostatectomy histology as the reference standard. Recent studies have demonstrated the role mpUS in improving detection of CSPCa and guidance for prostate biopsy and therapy. Furthermore, some aspects including lower costs, real-time imaging, applicability for some patients who have contraindication for magnetic resonance imaging (MRI) and availability in the office setting are clear advantages of mpUS. Interobserver agreement of mpUS was overall low; however, this limitation can be improved using standardized and objective evaluation systems such as the machine learning model. Whether mpUS outperforms MRI is unclear. Multicenter randomized controlled trials directly comparing mpUS and multiparametric MRI are warranted.

Developing Strategy to Predict the Results of Prostate Multiparametric Magnetic Resonance Imaging and Reduce Unnecessary Multiparametric Magnetic Resonance Imaging Scan

Purpose

The clinical utility of multiparametric magnetic resonance imaging (mpMRI) for the detection and localization of prostate cancer (PCa) has been evaluated and validated. However, the implementation of mpMRI into the clinical practice remains some burden of cost and availability for patients and society. We aimed to predict the results of prostate mpMRI using the clinical parameters and multivariable model to reduce unnecessary mpMRI scans.

Methods

We retrospectively identified 784 men who underwent mpMRI scans and subsequent prostate biopsy between 2016 and 2020 according to the inclusion criterion. The cohort was split into a training cohort of 548 (70%) patients and a validation cohort of 236 (30%) patients. Clinical parameters including age, prostate-specific antigen (PSA) derivates, and prostate volume (PV) were assessed as the predictors of mpMRI results. The mpMRI results were divided into groups according to the reports: “negative”, “equivocal”, and “suspicious” for the presence of PCa.

Results

Univariate analysis showed that the total PSA (tPSA), free PSA (fPSA), PV, and PSA density (PSAD) were significant predictors for suspicious mpMRI (P < 0.05). The PSAD (AUC = 0.77) and tPSA (AUC = 0.74) outperformed fPSA (AUC = 0.68) and PV (AUC = 0.62) in the prediction of the mpMRI results. The multivariate model (AUC = 0.80) had a similar diagnostic accuracy with PSAD (P = 0.108), while higher than tPSA (P = 0.024) in predicting the mpMRI results. The multivariate model illustrated a better calibration and substantial improvement in the decision curve analysis (DCA) at a threshold above 20%. Using the PSAD with a 0.13 ng/ml² cut-off could spare the number of mpMRI scans by 20%, keeping a 90% sensitivity in the prediction of suspicious MRI-PCa and missing three (3/73, 4%) clinically significant PCa cases. At the same sensitivity level, the multivariate model with a 32% cut-off could spare the number of mpMRI scans by 27%, missing only one (1/73, 1%) clinically significant PCa case.

Conclusion

Our multivariate model could reduce the number of unnecessary mpMRI scans without comprising the diagnostic ability of clinically significant PCa. Further prospective validation is required.