Prostate-specific Antigen Density Cutoff of 0.15 ng/ml/cc to Propose Prostate Biopsies to Patients with Negative Magnetic Resonance Imaging: Efficient Threshold or Legacy of the Past?

Development and validation of risk-stratified biopsy decision pathways incorporating MRI and PSA-derived indicators

OBJECTIVES

Develop risk-adapted conditional biopsy pathways utilizing MRI in combination with prostate-specific antigen (PSA) density (PSAD) and the ratio of free to total PSA (f/tPSA), respectively, to enhance the detection of clinically significant prostate cancer (csPCa) while minimizing 'negative' biopsies in low-risk patients.

METHODS

The Prostate Imaging Reporting and Data System (PI-RADS) category, PSAD, f/tPSA and biopsy-pathology of 1018 patients were collected retrospectively. Subsequently, PSAD and f/tPSA were divided into four intervals, which were then combined with the MRI findings to construct two risk stratification matrix tables. Six biopsy decision pathways were established: three clinical pathways based solely on PSAD and f/tPSA, and three MRI-combined pathways incorporating both PI-RADS and PSA-derived indicators. The biopsy and clinically insignificant PCa (ciPCa) avoidance, csPCa detection rate, and 'negative' biopsies proportion were assessed. Decision curve analysis (DCA) was employed to evaluate the net benefit associated with each pathway.

RESULTS

When reporting PI-RADS 1 - 2, PSAD ≥ 0.20 ng/ml/cm3 or f/tPSA ≤ 0.10 were found to be useful for patient stratification. When reporting PI-RADS 3, PSAD ≥ 0.10 - 0.15 ng/ml/cm3 and f/tPSA ≤ 0.16 - 0.25 were helpful in distinguishing the risk of csPCa. The three MRI-combined pathways showed higher csPCa detection rates (94% to 96%) than the three clinical pathways (85% to 91%); 'MRI + PSAD + f/tPSA' demonstrated a high csPCa detection rate of 94% while maintaining the maximum biopsy avoidance and lowest 'negative' biopsy proportion of 40% and 25%, respectively. The DCA showed significantly higher net benefits for three MRI-combined pathways compared to all clinical pathways.

CONCLUSIONS

The integration of MRI and PSA-derived indicators enables effective patient risk stratification, thereby providing valuable decision-making pathways to enhance the management of csPCa while minimizing 'negative' biopsies.

PSMA-Targeted Biopsy With Fusion Guidance for Detecting Clinically Significant Prostate Cancer in Men With Negative MRI-Feasibility and Diagnostic Performance of a Pilot Single-Center Prospective Study

INTRODUCTION

Contemporary prostate biopsy utilizes multiparametric magnetic resonance (MRI) guidance; however, it may fail to identify a non-negligible proportion of men with clinically significant (csPCa). The main objective of this study was to assess the feasibility and diagnostic performance of Prostate Specific Membrane Antigen-Target biopsy (PSMA-TB) to diagnose csPCa in men with negative MRI and high clinical risk of PCa.

PATIENTS AND METHODS

Open-label, single-center, nonrandomized, prospective study.

INCLUSION CRITERIA

PSA density (PSAd) ≥0.2 ng/ml2 in men with PIRADS 1-2; PSA >10 ng/ml or abnormal digital rectal examination or strong familiar history for PCa or known genetic mutation. Each patients underwent PSMA-PET and transperineal fusion PSMA-TB ± systematic biopsy (SB).

RESULTS

Overall, 35 patients were enrolled; 23 (65.7%) men had positive PSMA-PET (PRIMARY score ≥3). Overall, 14 (40%) men had csPCA and 21 (60%) patients had any PCa at PSMA-TB+SB. Only 1 patient (8.3%) with negative PSMA-PET had csPCa (ISUP 3) at SB (92% Negative Predictive Value [NPV]). Fusion PSMA-TB alone detected csPCa in 12 out of 23 (52.2%) patients with positive PSMA-PET; fusion PSMA-TB with concomitant SB increased the detection of csPCa to 56.5% (added value of 4.3%). The sensitivity, specificity, Positive Predictive Value (PPV), NPV and AUC of PSMA-TB+SB were 93%, 57%, 59%, 92% and 0.75 for detection of csPCa and 91%, 79%, 86%, 95% and 0.84 for detection of any PCa, respectively. The main limitation of this study is its small sample size.

CONCLUSIONS

Fusion PSMA-TB is technically feasible and may improve the detection of csPCa in patients with negative MRI.

The added value of artificial intelligence using Quantib Prostate for the detection of prostate cancer at multiparametric magnetic resonance imaging

PURPOSE

Artificial intelligence (AI) has been proposed to assist radiologists in reporting multiparametric magnetic resonance imaging (mpMRI) of the prostate. We evaluate the diagnostic performance of radiologists with different levels of experience when reporting mpMRI with the support of available AI-based software (Quantib Prostate).

MATERIAL AND METHODS

This is a single-center study (NCT06298305) involving 110 patients. Those with a positive mpMRI (PI-RADS ≥ 3) underwent targeted plus systematic biopsy (TBx plus SBx), while those with a negative mpMRI but a high clinical suspicion of prostate cancer (PCa) underwent SBx. Three readers with different levels of experience, identified as R1, R2, and R3 reviewed all mpMRI. Inter-reader agreement among the three readers with or without the assistance of Quantib Prostate as well as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for the detection of clinically significant PCa (csPCa) were assessed.

RESULTS

102 patients underwent prostate biopsy and the csPCa detection rate was 47%. Using Quantib Prostate resulted in an increased number of lesions identified for R3 (101 vs. 127). Inter-reader agreement slightly increased when using Quantib Prostate from 0.37 to 0.41 without vs. with Quantib Prostate, respectively. PPV, NPV and diagnostic accuracy (measured by the area under the curve [AUC]) of R3 improved (0.51 vs. 0.55, 0.65 vs.0.82 and 0.56 vs. 0.62, respectively). Conversely, no changes were observed for R1 and R2.

CONCLUSIONS

Using Quantib Prostate did not enhance the detection rate of csPCa for readers with some experience in prostate imaging. However, for an inexperienced reader, this AI-based software is demonstrated to improve the performance.

TRIAL REGISTRATION

Name of registry: clinicaltrials.gov.

TRIAL REGISTRATION NUMBER

NCT06298305. Date of registration: 2022-09.

Association of prostate-specific antigen density with prostate cancer mortality after a benign systematic prostate biopsy result

OBJECTIVE

To assess the association between prostate-specific antigen (PSA) density (PSAD) and prostate cancer mortality after a benign result on systematic transrectal ultrasonography (TRUS)-guided prostate biopsy.

PATIENTS AND METHODS

This retrospective study used data from the Finnish Randomised Study of Screening for Prostate Cancer (FinRSPC) collected between 1996 and 2020. We identified men aged 55-71 years randomised to the screening arm with PSA ≥4.0 ng/mL and a benign systematic TRUS-guided biopsy result. The cumulative prostate cancer mortality of men stratified by a PSAD cutoff of 0.15 ng/mL/cm3 was modelled with competing risk functions. The ability of PSAD, PSA, and base variables (age at biopsy, DRE result, socioeconomic status, 5α-reductase inhibitor usage, family history, and Charlson Comorbidity Index (CCI)) to predict prostate cancer death was compared using c-statistics and a likelihood ratio test.

RESULTS

After excluding 10 men without PSA data within 2 years of the biopsy and 65 without prostate volume data, 2276 men were eligible for inclusion in the study. A total of 50 men died from prostate cancer and 1028 from other causes during a median (interquartile range) follow-up of 17.4 (13.2-20.9) years. The cumulative prostate cancer mortality of men with PSAD <0.15 ng/mL/cm3 was significantly lower than that of men with PSAD ≥0.15 ng/mL/cm3: 0.5% (95% confidence interval [CI] 0.2%-1.1%) vs 2.0% (95% CI 1.2%-3.1%) at 15 years (Grey's test, P = 0.001). The model consisting of PSAD, PSA and the base variables predicted prostate cancer mortality (c-statistic 0.781) significantly better than either the base variables alone (c-statistic 0.737; likelihood-ratio test, P = 0.003) or the base variables and PSA (c-statistic 0.765; likelihood-ratio test, P = 0.039).

CONCLUSION

Prostate cancer mortality after a benign systematic TRUS-guided biopsy is low. In these patients, PSAD predicts prostate cancer mortality and provides additional value to other clinical variables. PSAD-based stratification can be used to guide follow-up strategy.

Discrepancies in volume: impact of Artemis segmented magnetic resonance imaging, ultrasound, and ExactVu measurements on prostate specific antigen density and National Comprehensive Cancer Network risk stratification

Introduction

The combination of magnetic resonance imaging (MRI) and ultrasound (US) allows for better lesion targeting and diagnostic probability compared to random prostate biopsies. The Artemis Fusion Biopsy system and ExactVu micro-US technology capitalize on this advantage and provide higher-resolution imaging of the prostate during biopsy. Their accuracy in measuring prostate volume and resulting implications on prostate specific antigen (PSA) density and risk stratification, however, has not been evaluated. We hypothesized that PSA densities as measured by these modalities will demonstrate clinically insignificant differences compared to standard measurement.

Material and methods

We retrospectively reviewed all prostate fusion biopsy cases performed at our health system with Artemis or ExactVu systems from April 2021 to July 2023 and compared the PSA density calculated from the volume obtained with these systems to standard measurement with ellipsoid calculation from MRI. Change in National Comprehensive Cancer Network (NCCN) prostate cancer risk stratification was analyzed for each system.

Results

Artemis MRI segmentation (0.179 ng/ml, p = 0.04) and US (0.181 ng/ml, p = 0.067) underestimated and ExactVu micro-US (0.247 ng/ml, p <0.001) overestimated PSA density. Risk stratification changed in 1.2% of Artemis MRI segmentation cases, 1.6% of Artemis US cases, and 1.2% of ExactVu micro-US cases.

Conclusions

Despite differences in PSA density, choice of fusion biopsy system has minimal clinical impact on risk stratification and any of these studied systems may be used without fear of misrepresenting a patient's disease state.

Optimal PSA density threshold for prostate biopsy in benign prostatic obstruction patients with elevated PSA levels but negative MRI findings

PURPOSE

This study was designed to identify a useful clinical parameter or model for prostate biopsy in surgery-indicated benign prostate hyperplasia (BPH) patients with elevated PSA levels and negative multiparametric prostate magnetic resonance imaging (MRI) results.

PATIENTS AND METHODS

We retrospectively analyzed clinical and pathological data from patients who were diagnosed with BPH and admitted to the inpatient department for surgery between January 2010 and September 2020. Clinical data, including age, prostate specific antigen (PSA) level, F/T PSA ratio, prostate volume, and PSA density (PSAD), were used for comprehensive analysis. Univariate and multivariate logistic regression analyses were performed to develop a predictive model. Receiver operating characteristic (ROC) analysis and decision curve analysis (DCA) were performed to assess the diagnostic value of the predictive model, PSA concentration, F/T PSA ratio and PSAD.

RESULTS

A total of 318 patients were included in the study, 8.2% (26/318) of whom were histologically diagnosed with prostate cancer (PCa). Univariate and multivariate logistic regression analyses revealed that PSAD was the only independent predictor of PCa biopsy. ROC curve analysis of PCa detection revealed a larger area under the curve (AUC) for the predictive model (AUC 0.855) and for PSAD (AUC 0.848) than for PSA (AUC 0.722) or the F/T PSA ratio (AUC 0.635). DCA demonstrated that the optimal strategy would be to restrict biopsies to men with a PSAD of 0.30 ng/ml/cm3.

CONCLUSIONS

Our study suggested that for BPH patients with surgical indications who present with PSA abnormalities and negative imaging findings, the use of a new PSAD threshold of 0.30 ng/ml/cm3 could facilitate convenient and sound biopsy decisions. This approach could reduce the complications and length of hospital stay associated with biopsies and reduce hospital costs.

Fluorescence confocal microscopy for margin assessment in prostatectomy: IP8-FLUORESCE study protocol

BACKGROUND

Radical prostatectomy (RP) represents the cornerstone of surgical treatment for prostate cancer. Assessing surgical margin status intraoperatively with current techniques remains challenging due to high costs in the context of an already stretched pathology workforce. Fluorescence confocal microscopy (FCM) is a promising technique to detect margins in prostate cancer surgery not bound by such limitations.

STUDY DESIGN

The Imperial Prostate 8 - Fluorescence Confocal Microscopy for Rapid Evaluation of Surgical Cancer Excision (IP8-FLUORESCE) study is a multicentre, prospective, ex vivo, 'blinded', comparative cohort study. It aims to assess the accuracy of digital FCM for detection of prostate cancer at surgical margins compared to traditional histopathology.

ENDPOINTS

The primary endpoint is the accuracy of digital FCM for detection of prostate cancer at surgical margins on a per-patient level, reported with sensitivity, specificity, positive and negative predictive values.

PATIENTS AND METHODS

A total of 153 patients with localised prostate cancer undergoing robot-assisted RP across three UK National Health Service tertiary referral centres will be recruited. Following RP, prostate specimens will undergo immediate immersion in Acridine Orange solution, scanning 'en face' with FCM using the Histolog® Scanner, and subsequent formalin fixation and paraffin embedding. Two independent, 'blinded' uro-pathologists will report both the FCM images and the histopathology slides. Recruitment commenced on 17 August 2023.

Diagnostic Accuracy of Combination of Multiparametric MRI PI-RADS Score v2.1 and Prostate-Specific Antigen Density for Prostate Cancer Detection

Introduction Prostate cancer (PCa) is the second most commonly diagnosed cancer in men worldwide. The Prostate Imaging-Reporting and Data System version 2.1 (PI-RADS v2.1) scoring system using multiparametric magnetic resonance imaging (mp-MRI) increases the accuracy for the assessment of clinically significant PCa. This study evaluates the diagnostic accuracy of a combination of PI-RADS v2.1 scores with prostate-specific antigen density (PSAD) for the detection of PCa, using biopsy outcomes as the gold standard, as well as the diagnostic accuracy of the combination of PI-RADS 3 lesion volume and PSAD. Methods This is single-center cross-sectional retrospective study including 54 subjects with serum PSA values > 4 ng/mL, who were referred for prostate mp-MRI. All patients underwent subsequent transrectal ultrasound (TRUS)-guided biopsy. Data collected includes PSA value, mp-MRI characteristics of the lesion, and histopathological findings. PI-RADS v2.1 score and PSAD were used to evaluate the diagnostic accuracy of this combination. Results In our study, the optimal PSAD cutoff was >0.18 with an area under the curve (AUC) of 0.897, indicating good diagnostic performance. The combination of PI-RADS v2.1 score ≥ 3 and PSAD ≥0.18 increased diagnostic accuracy, with a sensitivity of 96.97% and specificity of 71.43%. However, lesion volume was not a significant predictor of PCa. Conclusion In summary, our study demonstrates that the combination of PI-RADS score and PSAD yields higher diagnostic accuracy for the detection of PCa (p < 0.001) than using the PI-RADS score alone. We found an optimal PSAD cutoff of 0.18, which differs from the international consensus of 0.15. However, it cannot be used as a substitute for definitive pathological diagnosis but can be used in combination for better risk stratification, counselling, and management of patients with elevated PSA levels. Combining PI-RADS 3 lesion volume and PSAD did not have statistically significant results in our study.

MRI-based risk stratification for clinically significant prostate cancer detection at biopsy: The value of zonal-specific PSA density and PSHS

PURPOSE

To explore the use of different, zonal-specific PSA density (PSAD) variants in combination with the Prostate Signal Intensity Homogeneity Score (PSHS) to improve the detection of clinically significant prostate cancer (csPCa) and thus potentially help in risk stratification and adequate patient selection for prostate biopsy.

METHODS

This retrospective, single-center study included patients with available PSA values who were suspected of having prostate cancer and underwent multiparametric MRI (mpMRI) in combination with a subsequent prostate biopsy. Histopathologic biopsy results served as reference standard. Whole-gland (PSAD-T), peripheral zone (PSAD-PZ), and transition zone (PSAD-TZ) PSA densities were computed based on MRI-derived volume assessment. The diagnostic performance of these PSAD variants in predicting csPCa was assessed using ROC analysis. Conditional inference trees were used to examine the value of combining PI-RADS, PSAD-TZ and PSHS.

RESULTS

Among the 297 patients included, 126 (42.4 %) were diagnosed with csPCa based on histopathologic biopsy results. PSAD-TZ demonstrated superior diagnostic performance (AUC 0.78) for csPCa prediction compared to PSAD-T (AUC 0.75) and PSAD-PZ (AUC 0.63). Conditional inference tree analysis revealed that patients with negative or indeterminate mpMRI (PI-RADS ≤ 3) and an elevated PSAD-TZ in combination with low PSHS scores (≤3), which indicate increased background signal intensity changes of the peripheral zone, were at an elevated risk for a missed csPCa.

CONCLUSIONS

Integrating PI-RADS, PSAD-TZ, and PSHS may enhance risk stratification for csPCa at biopsy, enabling more precise identification of patients at an elevated risk who may require further evaluation. This approach may consequently reduce false-negative MRI results and facilitate more precise decision-making regarding biopsy indications.

A machine learning model incorporating 18F-prostate-specific membrane antigen-1007 positron emission tomography/computed tomography and multiparametric magnetic resonance imaging for predicting prostate-specific antigen persistence in patients with prostate cancer after radical prostatectomy

Background

Although 18F-prostate-specific membrane antigen-1007 (18F-PSMA-1007) positron emission tomography/computed tomography (PET/CT) and multiparametric magnetic resonance imaging (mpMRI) are good predictors of prostate cancer (PCa) prognosis, their combined ability to predict prostate-specific antigen (PSA) persistence has not been thoroughly evaluated. In this study, we assessed whether clinical, mpMRI, and 18F-PSMA-1007 PET/CT characteristics could predict PSA persistence in patients with PCa treated with radical prostatectomy (RP).

Methods

This retrospective study involved consecutive patients diagnosed with PCa who underwent both preoperative mpMRI and PSMA PET/CT scans between April 2019 and June 2022. Scatter plots and heat maps were employed to determine the correlation of mpMRI and PSMA PET/CT features with preoperative PSA. Univariate logistic regression analyses were used assess the correlation between age, maximum Prostate Imaging-Reporting and Data System (PI-RADS) score, prostate-specific antigen density (PSAD), extracapsular extension (EPE), seminal vesicle invasion (SVI), total lesion PSMA (PSMA-TL), and PSA persistence. Multivariate logistic regression analyses were used to develop a predictive model for PSA persistence, while decision tree analysis was used to classify patients into different risk groups for easy interpretation and visualization. We divided the patient cohort into training and validation sets in an 8:2 ratio. To ensure the reliability of the model, we performed five-fold cross-validation of the validation results.

Results

Ultimately, this study included 190 patients with PCa. The median age of the patients was 69 years [interquartile range (IQR) 64-73 years]. Among the patients, 35 (18%) experienced PSA persistence following RP. Additionally, SVI was identified in 31 (16%) patients. The median values for SUVmax and PSMA-TL were 11.83 (IQR 7.44-20.89) and 41.92 (IQR 21.25-113.83), respectively. Spearman correlation analysis indicated that the preoperative PSA levels in patients with PCa were slightly correlated with the maximum standardized uptake value (SUVmax) (r=0.41; P<0.001), significantly correlated with PSMA-TL (r=0.58, P<0.001), and strongly correlated with PSAD (r=0.865, P<0.001). Multivariate logistic regression analysis showed that the independent predictors of PSA persistence were SVI on mpMRI [area under the curve (AUC)=0.63; 95% confidence interval (CI): 0.516-0.739] and PSMA-TL (AUC =0.80; 95% CI: 0.723-0.877) on PSMA PET/CT (all P values <0.05). Patients with SVI and PSMA-TL >63.38 cm3 were more likely to have PSA persistence. Decision tree analysis stratified patients into low-risk (5%), intermediate-risk (36%), and high-risk (48%) categories for PSA persistence. The model exhibited good discriminatory capability in internal validation (AUC 0.93, 95% CI: 0.850-0.930).

Conclusions

18F-PSMA-1007 PET/CT and mpMRI parameters were proved effective in predicting PSA persistence in postoperative patients with PCa. The decision tree classification model could help clinicians to assess patients with individualized risk stratification. Patients with PSMA-TL levels below the threshold are highly likely not to have PSA persistence.

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

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

Added Value of Prostate-specific Antigen Density in Selecting Prostate Biopsy Candidates Among Men with Elevated Prostate-specific Antigen and PI-RADS ≥3 Lesions on Multiparametric Magnetic Resonance Imaging of the Prostate: A Systematic Assessment by PI-RADS Score

BACKGROUND

A significant proportion of patients with positive multiparametric magnetic resonance imaging (mpMRI; Prostate Imaging-Reporting and Data System [PI-RADS] scores of 3-5) have negative biopsy results.

OBJECTIVE

To systematically assess all prostate-specific antigen density (PSAD) values and identify an appropriate cutoff for identification of patients with positive mpMRI who could potentially avoid biopsy on the basis of their PI-RADS score.

DESIGN, SETTING, AND PARTICIPANTS

The study included a cohort of 1341 patients with positive mpMRI who underwent combined targeted and systematic biopsies.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Multivariable logistic regression analysis (MVA) was used to assess the association between PSAD and the risk of clinically significant prostate cancer (csPCa, grade group ≥2) after adjusting for confounders. We used locally weighted scatterplot smoothing to explore csPCa risk according to PSAD and PI-RADS scores. PSAD utility was observed only for patients with PI-RADS 3 lesions, so we plotted the effect of each PSAD value as a cutoff for this subgroup in terms of biopsies saved, csPCa cases missed, and clinically insignificant PCa (ciPCa, grade group 1) cases not detected.

RESULTS AND LIMITATIONS

Overall, 667 (50%) csPCa cases were identified. On MVA, PSAD independently predicted csPCa (odds ratio 1.57; p < 0.001). For PI-RADS ≥4 lesions, the csPCa risk was ≥40% regardless of PSAD. Conversely, among patients with PI-RADS 3 lesions, csPCa risk ranged from 0% to 60% according to PSAD values, and a PSAD cutoff of 0.10 ng/ml/cm3 corresponded to a threshold probability of 10% for csPCa. Using this PSAD cutoff for patients with PI-RADS 3 lesions would have saved 32% of biopsies, missed 7% of csPCa cases, and avoided detection of 34% of ciPCa cases. Limitations include selection bias and the high experience of the radiologists and urologists involved.

CONCLUSIONS

Patients with PI-RADS ≥4 lesions should undergo prostate biopsy regardless of their PSAD, while PSAD should be used to stratify patients with PI-RADS 3 lesions. Using a threshold probability of 10% for csPCa, our data suggest that the appropriate strategy is to avoid biopsy in patients with PI-RADS 3 lesions and PSAD <0.10 ng/ml/cm3. Our results also provide information to help in tailoring an appropriate strategy for every patient with positive mpMRI findings.

PATIENT SUMMARY

We investigated whether a cutoff value for PSAD (prostate-specific antigen density) could identify patients with suspicious prostate lesions on MRI (magnetic resonance imaging) who could avoid biopsy according to the PI-RADS score for their scan. We found that patients with PI-RADS ≥4 should undergo prostate biopsy regardless of their PSAD. A PSAD cutoff of 0.10 should be used to stratify patients with PI-RADS 3.

Clinical Trial Protocol for PRIMARY2: A Multicentre, Phase 3, Randomised Controlled Trial Investigating the Additive Diagnostic Value of [68Ga]Ga-PSMA-11 Positron Emission Tomography/Computed Tomography in Men with Negative or Equivocal Multiparametric Magnetic Resonance Imaging for the Diagnosis of Clinically Significant Prostate Cancer

BACKGROUND

Multiparametric magnetic resonance imaging (mpMRI) has an established role for the diagnosis of clinically significant prostate cancer (sPCa). The PRIMARY trial demonstrated that [68Ga]Ga-PSMA-11 positron emission tomography/computed tomography (PET/CT) was associated with a significant improvement in sensitivity and negative predictive value for sPCa detection.

OBJECTIVE

To demonstrate that addition of prostate-specific membrane antigen (PSMA) radioligand PET/CT will enable some men to avoid transperineal prostate biopsy without missing sPCa, and will facilitate biopsy targeting of PSMA-avid sites.

DESIGN, SETTING, AND PARTICIPANTS

This multicentre, two-arm, phase 3, randomised controlled trial will recruit 660 participants scheduled to undergo biopsy. Eligible participants will have clinical suspicion of sPCa with a Prostate Imaging-Reporting and Data System (PI-RADS) score of 2 and red flags, or a PI-RADS score of 3 on mpMRI (PI-RADS v2). Participants will be randomised at a 1:1 ratio in permuted blocks stratified by centre. The trial is registered on ClinicalTrials.gov as NCT05154162.

INTERVENTION

In the experimental arm, participants will undergo pelvic PSMA PET/CT. Local and central reviewers will interpret scans independently using the PRIMARY score. Participants with a positive result will undergo targeted transperineal prostate biopsies, whereas those with a negative result will undergo prostate-specific antigen monitoring alone. In the control arm, all participants undergo template transperineal prostate biopsies. Participants will be followed for subsequent clinical care for up to 2 yr after randomisation.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

sPCa is defined as Gleason score 3 + 4 (≥10%) = 7 disease (grade group 2) or higher on transperineal prostate biopsy. Avoidance of transperineal prostate biopsy will be measured at 6 mo from randomisation. The primary endpoints will be analysed on an intention-to-treat basis.

CONCLUSIONS

Patient enrolment began in March 2022, with recruitment expected to take 36 mo.

PATIENT SUMMARY

For patients with suspected prostate cancer who have nonsuspicious or unclear MRI (magnetic resonance imaging) scan findings, a different type of scan (called PSMA PET/CT; prostate-specific membrane antigen positron emission tomography/computed tomography) may identify men who could avoid an invasive prostate biopsy. This type of scan could also help urologists in better targeting of samples from suspicious lesions during prostate biopsies.

Risk factor analysis and optimal cutoff value selection of PSAD for diagnosing clinically significant prostate cancer in patients with negative mpMRI: results from a high-volume center in Southeast China

BACKGROUND

Multi-parametric magnetic resonance imaging (mpMRI) is a diagnostic tool used for screening, localizing, and staging prostate cancer. Patients with Prostate Imaging Reporting and Data System (PI-RADS) score of 1 and 2 are considered negative mpMRI, with a lower likelihood of detecting clinically significant prostate cancer (csPCa). However, relying solely on mpMRI is insufficient to completely exclude csPCa, necessitating further stratification of csPCa patients using biomarkers.

METHODS

A retrospective study was conducted on mpMRI-negative patients who underwent prostate biopsy at the First Affiliated Hospital of Zhejiang University from January 2022 to June 2023. A total of 607 patients were included based on inclusion and exclusion criteria. Univariate and multivariate logistic regression analysis were performed to identify risk factors for diagnosing csPCa in patients with negative mpMRI. Receiver Operating Characteristic (ROC) curves were plotted to compare the discriminatory ability of different Prostate-Specific Antigen Density (PSAD) cutoff values for csPCa.

RESULTS

Among the 607 patients with negative mpMRI, 73 patients were diagnosed with csPCa. In univariate logistic regression analysis, age, PSA, f/tPSA, prostate volume, and PSAD were all associated with diagnosing csPCa in patients with negative mpMRI (P < 0.05), with PSAD being the most accurate predictor. In multivariate logistic regression analysis, f/tPSA, age, and PSAD were independent predictors of csPCa (P < 0.05). PSAD cutoff value of 0.20 ng/ml/ml has better discriminatory ability for predicting csPCa and is a significant risk factor for csPCa in multivariate analysis.

CONCLUSION

Age, f/tPSA, and PSAD are independent predictors of diagnosing csPCa in patients with negative mpMRI. It is suggested that patients with negative mpMRI and PSAD less than 0.20 ng/ml/ml could avoid prostate biopsy, as a PSAD cutoff value of 0.20 ng/ml/ml has better diagnostic performance than the traditional cutoff value of 0.15 ng/ml/ml.

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.

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.

The Added Value of MRI-Based Targeted Biopsy in Biopsy-Naïve Patients: A Propensity-Score Matched Comparison

BACKGROUND

Multiparametric Magnetic Resonance Imaging (mpMRI)-based targeted biopsy has shown to be beneficial in detecting Clinically Significant Prostate Cancer (csPCa) and avoiding diagnosis of Non-csPCa (ncsPCa); however, its role in the treatment of biopsy-naïve patients is still under discussion.

METHODS

After identifying predictors for the diagnosis of csPCa via Multivariate Logistic Regression Analysis (MLRA), a propensity-score (1:1 nearest neighbor) matched comparison was performed between a Systematic-Only Biopsy (SOB) cohort and a mpMRI-based Combined (systematic + targeted) Biopsy (CB) cohort from two tertiary urologic centers (SOB: Department of Urology, University General Hospital of Heraklion, University of Crete, School of Medicine, Heraklion, Crete, Greece; CB: LKH Hall in Tirol, Austria). Only biopsy-naïve patients were included in the study. The study period for the included patients was from February 2018 to July 2023 for the SOB group and from July 2017 to June 2023 for the CB group. The primary outcome was the diagnosis of csPCa (≥ISUP 2); secondary outcomes were overall cancer detection, the added value of targeted biopsy in csPCa detection, and the reduction in ncsPCa diagnosis with CB compared to SOB. To estimate the Average Treatment effect of the Treated groups (ATT), cluster-robust standard errors were used to perform g-computation in the matched sample. p-values < 0.05 with a two-sided 95% confidence interval were considered statistically significant.

RESULTS

Matching achieved well-balanced groups (each n = 140 for CB and SOB). In the CB group, 65/140 (46.4%) patients were diagnosed with csPCa compared to 44/140 (31.4%) in the SOB group (RR 1.48, 95%-CI: 1.09-2.0, p = 0.01). In the CB group, 4.3% (6/140) and 1.4% (2/140) of csPCa cases were detected with targeted-only and systematic-only biopsy cores, respectively. In the CB group, 22/140 (15.7%) patients were diagnosed with ncsPCa compared to 33/140 (23.6%) in the SOB group (RR = 0.67, 95% CI: 0.41-1.08, p = 0.1). When comparing SOB to CB (ATT), the marginal OR was 0.56 (95% CI: 0.38-0.82, p = 0.003) for the diagnosis of csPCa and 0.75 (95% CI: 0.47-1.05, p = 0.085) for the diagnosis of overall cancer (≥ISUP 1).

CONCLUSION

The CB approach was superior to the SOB approach in detecting csPCa, while no additional detection of ncsPCa was seen. Our results support the application of mpMRI for biopsy-naïve patients with suspicions of prostate cancer.

Risk stratification of prostate cancer with MRI and prostate-specific antigen density-based tool for personalized decision making

OBJECTIVES

MRI is now established for initial prostate cancer diagnosis; however, there is no standardized pathway to avoid unnecessary biopsy in low-risk patients. Our study aimed to test previously proposed MRI-focussed and risk-adapted biopsy decision models on a real-world dataset.

METHODS

Single-centre retrospective study performed on 2055 biopsy naïve patients undergoing MRI. Diagnostic pathways included "biopsy all", "MRI-focussed" and two risk-based MRI-directed pathways. Risk thresholds were based on prostate-specific antigen (PSA) density as low (<0.10 ng mL-2), intermediate (0.10-0.15 ng mL-2), high (0.15-0.20 ng mL-2), or very high-risk (>0.20 ng mL-2). The outcome measures included rates of biopsy avoidance, detection of clinically significant prostate cancer (csPCa), missed csPCa, and overdiagnosis of insignificant prostate cancer (iPCa).

RESULTS

Overall cancer rate was 39.9% (819/2055), with csPCa (Grade-Group ≥2) detection of 30.3% (623/2055). In men with a negative MRI (Prostate Imaging-Reporting and Data System, PI-RADS 1-2), the risk of cancer was 1.2%, 2.6%, 9.0%, and 12.9% in the low, intermediate, high, and very high groups, respectively; for PI-RADS score 3 lesions, the rates were 10.5%, 14.3%, 25.0%, and 33.3%, respectively. MRI-guided pathway and risk-based pathway with a low threshold missed only 1.6% csPCa with a biopsy-avoidance rate of 54.4%, and the risk-based pathway with a higher threshold avoided 62.9% (1292/2055) of biopsies with 2.9% (61/2055) missed csPCa detection. Decision curve analysis found that the "risk-based low threshold" pathway has the highest net benefit for probability thresholds between 3.6% and 13.9%.

CONCLUSION

Combined MRI and PSA-density risk-based pathways can be a helpful decision-making tool enabling high csPCa detection rates with the benefit of biopsy avoidance and reduced iPCa detection.

ADVANCES IN KNOWLEDGE

This real-world dataset from a large UK-based cohort confirms that combining MRI scoring with PSA density for risk stratification enables safe biopsy avoidance and limits the over-diagnosis of insignificant cancers.

Developing a predictive model for clinically significant prostate cancer by combining age, PSA density, and mpMRI

PURPOSE

The study aimed to construct a predictive model for clinically significant prostate cancer (csPCa) and investigate its clinical efficacy to reduce unnecessary prostate biopsies.

METHODS

A total of 847 patients from institute 1 were included in cohort 1 for model development. Cohort 2 included a total of 208 patients from institute 2 for external validation of the model. The data obtained were used for retrospective analysis. The results of magnetic resonance imaging were obtained using Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1). Univariate and multivariate analyses were performed to determine significant predictors of csPCa. The diagnostic performances were compared using the receiver operating characteristic (ROC) curve and decision curve analyses.

RESULTS

Age, prostate-specific antigen density (PSAD), and PI-RADS v2.1 scores were used as predictors of the model. In the development cohort, the areas under the ROC curve (AUC) for csPCa about age, PSAD, PI-RADS v2.1 scores, and the model were 0.675, 0.823, 0.875, and 0.938, respectively. In the external validation cohort, the AUC values predicted by the four were 0.619, 0.811, 0.863, and 0.914, respectively. Decision curve analysis revealed that the clear net benefit of the model was higher than PI-RADS v2.1 scores and PSAD. The model significantly reduced unnecessary prostate biopsies within the risk threshold of > 10%.

CONCLUSIONS

In both internal and external validation, the model constructed by combining age, PSAD, and PI-RADS v2.1 scores exhibited excellent clinical efficacy and can be utilized to reduce unnecessary prostate biopsies.