Results of Targeted Biopsy in Men with Magnetic Resonance Imaging Lesions Classified Equivocal, Likely or Highly Likely to Be Clinically Significant Prostate Cancer

The detection rate for prostate cancer in systematic and targeted prostate biopsy in biopsy-naive patients, according to the localization of the lesion at the mpMRI: A single-center retrospective observational study

OBJECTIVE

Evaluate the detection rates of systematic, targeted and combined cores at biopsy according to tumor positions in biopsy-naïve patients.

MATERIAL AND METHODS

A retrospective analysis of a single-center patient cohort (n = 501) that underwent transrectal prostate biopsy between January 2017 and December 2019 was performed. Multi-parametric MRI was executed as a prebiopsy investigation. Biopsy protocol included, for each patient, 12 systematic cores plus 3 to 5 targeted cores per lesion identified at the mpMRI. Pearson and McNemar chi-squared tests were used for statistical analysis to compare tumor location-related detection rates of systematic, targeted and combined (systematic + targeted) cores at biopsy.

RESULTS

Median age of patients was 70 years (IQR 62-72), with a median PSA of 8.5 ng/ml (IQR 5.7-15.6). Positive biopsies were obtained in 67.7% of cases. Overall, targeted cores obtained higher detection rates compared to systematic cores (54.3% vs. 43.1%, p < 0.0001). Differences in detection rates were, however, higher for tumors located at the apex (61.1% vs. 26.3%, p < 0.05) and anteriorly (44.4% vs. 19.3%, p < 0.05). Targeted cores similarly obtained higher detection rates in the posterior zone of the prostate gland for clinically significant prostate cancer. A poor agreement was reported between targeted and systematic cores for the apex and anterior zone of the prostate with, respectively κ = 0.028 and κ = -0.018.

CONCLUSION

A combined approach of targeted and systematic biopsy delivers the highest detection rate in prostate cancer (PCa). The location of the tumor could however greatly influence overall detection rates, indicating the possibility to omit (as for the base or posterior zone of the gland) or add (as for the apex or anterior zone of the gland) further targeted cores.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The Value of 68Ga-PSMA PET/MRI for Classifying Patients with PI-RADS 3 Lesions on Multiparametric MRI: A Prospective Single-Center Study

Prostate Imaging Reporting and Data System (PI-RADS) category 3 lesions remain a diagnostic challenge for detecting clinically significant prostate cancer (csPCa). This article evaluates the added value of 68Ga-labeled prostate-specific membrane antigen-11 (68Ga-PSMA) PET/MRI in classifying PI-RADS 3 lesions to avoid unnecessary biopsies. Methods: Sixty biopsy-naïve men with PI-RADS 3 lesions on multiparametric MRI were prospectively enrolled between February 2020 and October 2022. In all, 56 participants underwent 68Ga-PSMA PET/MRI and prostate systematic biopsy. 68Ga-PSMA PET/MRI was independently evaluated and reported by the 5-level PRIMARY score developed within the PRIMARY trial. Receiver-operating-characteristic curve analysis was used to estimate the diagnostic performance. Results: csPCa was detected in 8 of 56 patients (14.3%). The proportion of patients with csPCa and a PRIMARY score of 1, 2, 3, 4, and 5 was 0% (0/12), 0% (0/13), 6.3% (1/16), 38.5% (5/13), and 100% (2/2), respectively. The estimated area under the curve of the PRIMARY score was 0.91 (95% CI, 0.817-0.999). For a PRIMARY score of 4-5 versus a PRIMARY score of 1-3, the sensitivity, specificity, positive predictive value, and negative predictive value were 87.5%, 83.3%, 46.7%, and 97.5%, respectively. With a PRIMARY score of at least 4 to make a biopsy decision in men with PI-RADS 3 lesions, 40 of 48 patients (83.3%) could avoid unnecessary biopsies, at the expense of missing 1 of 8 (12.5%) csPCa cases. Conclusion: 68Ga-PSMA PET/MRI has great potential to classify patients with PI-RADS 3 lesions and help avoid unnecessary biopsies.

Based on PI-RADS v2.1 combining PHI and ADC values to guide prostate biopsy in patients with PSA 4-20 ng/mL

PURPOSE

The study aimed to investigate the diagnostic accuracy of prostate health index (PHI) and apparent diffusion coefficient (ADC) values in predicting prostate cancer (PCa) and construct a nomogram for the prediction of PCa and clinically significant PCa (CSPCa) in Prostate Imaging-Reporting and Data System (PI-RADS) three lesions cohort.

METHODS

This study prospectively enrolled 301 patients who underwent multiparametric magnetic resonance (mpMRI) and were scheduled for prostate biopsy. The receiver operating characteristic curve (ROC) was performed to estimate the diagnostic accuracy of each predictor. Univariable and multivariable logistic regression analysis was conducted to ascertain hidden risk factors and constructed nomograms in PI-RADS three lesions cohort.

RESULTS

In the whole cohort, the area under the ROC curve (AUC) of PHI is relatively high, which is 0.779. As radiographic parameters, the AUC of PI-RADS and ADC values was 0.702 and 0.756, respectively. The utilization of PHI and ADC values either individually or in combination significantly improved the diagnostic accuracy of the basic model. In PI-RADS three lesions cohort, the AUC for PCa was 0.817 in the training cohort and 0.904 in the validation cohort. The AUC for CSPCa was 0.856 in the training cohort and 0.871 in the validation cohort. When applying the nomogram for predicting PCa, 50.0% of biopsies could be saved, supplemented by 6.9% of CSPCa being missed.

CONCLUSION

PHI and ADC values can be used as predictors of CSPCa. The nomogram included PHI, ADC values and other clinical predictors demonstrated an enhanced capability in detecting PCa and CSPCa within PI-RADS three lesions cohort.

Histomic and transcriptomic features of MRI-visible and invisible clinically significant prostate cancers are associated with prognosis

Magnetic resonance imaging (MRI) is increasingly used to triage patients for prostate biopsy. However, 9% to 24% of clinically significant (cs) prostate cancers (PCas) are not visible in MRI. We aimed to identify histomic and transcriptomic determinants of MRI visibility and their association to metastasis, and PCa-specific death (PCSD). We studied 45 radical prostatectomy-treated patients with csPCa (grade group [GG]2-3), including 30 with MRI-visible and 15 with MRI-invisible lesions, and 18 men without PCa. First, histological composition was quantified. Next, transcriptomic profiling was performed using NanoString technology. MRI visibility-associated differentially expressed genes (DEGs) and Reactome pathways were identified. MRI visibility was classified using publicly available genes in MSK-IMPACT and Decipher, Oncotype DX, and Prolaris. Finally, DEGs and clinical parameters were used to classify metastasis and PCSD in an external cohort, which included 76 patients with metastatic GG2-4 PCa, and 84 baseline-matched controls without progression. Luminal area was lower in MRI-visible than invisible lesions and low luminal area was associated with short metastasis-free and PCa-specific survival. We identified 67 DEGs, eight of which were associated with survival. Cell division, inflammation and transcriptional regulation pathways were upregulated in MRI-visible csPCas. Genes in Decipher, Oncotype DX and MSK-IMPACT performed well in classifying MRI visibility (AUC = 0.86-0.94). DEGs improved classification of metastasis (AUC = 0.69) and PCSD (AUC = 0.68) over clinical parameters. Our data reveals that MRI-visible csPCas harbor more aggressive histomic and transcriptomic features than MRI-invisible csPCas. Thus, targeted biopsy of visible lesions may be sufficient for risk stratification in patients with a positive MRI.

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

Objectives

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

Materials and Methods

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

Results

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

Conclusion

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

Prostate Cancer Local Staging with Magnetic Resonance Imaging

Accurate determination of the local stage of prostate cancer is crucial for treatment planning and prognosis. The primary objective of local staging is to distinguish between organ-confined and locally advanced disease, with the latter carrying a worse clinical prognosis. The presence of locally advanced disease features of prostate cancer, such as extra-prostatic extension, seminal vesicle invasion, and positive surgical margin, can impact the choice of treatment. Over the past decade, multiparametric MRI (mpMRI) has become the preferred imaging modality for the local staging of prostate cancer and has been shown to provide accurate information on the location and extent of disease. It has demonstrated superior performance compared to staging based on traditional clinical nomograms. Despite being a relatively new technique, mpMRI has garnered considerable attention and ongoing investigations. Therefore, in this review, we will discuss the current use of mpMRI on prostate cancer local staging.

Clinical and Radiological Factors for Predicting Clinically Significant Prostate Cancer in Biopsy-Naive Patients With PI-RADS 3 Lesions

OBJECTIVE

This study intends to examine the anticipatory power of clinical and radiological parameters in detecting clinically significant prostate cancer in patients demonstrating Prostate Imaging Reporting and Data System 3 lesions.

METHODS

This was a retrospective study. The study included participation from 453 patients at the First Affiliated Hospital of Soochow University, sampled between September 2017 through August 2022. Each patient underwent a routine 12-core prostate biopsy followed by a 2 to 5 core fusion-targeted biopsy. We utilized both univariate and multivariate logistic regression analyses to identify the parameters that have a correlation with clinically significant prostate cancer. The predictive ability of these parameters was assessed using the receiver operating characteristic curve, leading to the creation of a nomogram.

RESULTS

Clinically significant prostate cancer was detected in 68 out of 453 patients with Prostate Imaging Reporting and Data System 3 lesions (15.01%). Among Prostate Imaging Reporting and Data System 3a and 3b patients, 4.78% (3.09% of the total) and 33.75% (11.92% of the total), respectively, had clinically significant prostate cancer. Systematic biopsy improved prostate cancer and clinically significant prostate cancer detection rates by 7.72% and 3.09%, respectively, compared to targeted biopsy. Without systematic biopsy, there would be an undetected rate of 15% for prostate cancer and 8.13% for clinically significant prostate cancer in Prostate Imaging Reporting and Data System 3b patients. Several clinical parameters, including age, prostate-specific antigen density, lesion volume, apparent diffusion coefficient, and digital rectal examination, were statistically significant in the logistic regression analysis for clinically significant prostate cancer. The individual diagnostic accuracies of these parameters for clinically significant prostate cancer were 0.648, 0.645, 0.75, 0.763, and 0.7, respectively, but their combined accuracy improved to 0.866. A well-fit nomogram based on the identified risk factors was constructed (χ2 = 10.254, P = .248).

CONCLUSION

The combination of age, prostate-specific antigen density, lesion volume, apparent diffusion coefficient, and digital rectal examination presented a higher diagnostic value for clinically significant prostate cancer than any single parameter in patients with Prostate Imaging Reporting and Data System 3 lesions. Systematic biopsy proved crucial for biopsy-naive patients with Prostate Imaging Reporting and Data System 3 lesions and should not be omitted.

Predictors of prostate cancer detection in MRI PI-RADS 3 lesions - Reality of a tertiary center

INTRODUCTION AND OBJECTIVES

The Prostate Imaging Reporting and Data System (PI-RADS) score reports the likelihood of a clinically significant prostate cancer (CsPCa) based on various multiparametric prostate magnetic resonance imaging (mpMRI) characteristics. The PI-RADS category 3 is an intermediate status, with an equivocal risk of malignancy. The PSA density (PSAD) has been proposed as a tool to facilitate biopsy decisions on PI-RADS category 3 lesions. The objective of this study is to determine the frequency of CsPCa, assess the diagnostic value of targeted biopsy and identify clinical predictors to improve the CsPCa detection rate in PI-RADS category 3 lesions.

METHODS

Between 1st January 2017 and 31st December 2022, a total of 1661 men underwent a prostate biopsy at our institution. Clinical and mpMRI data of men with PI-RADS 3 lesions was reviewed. The study population was divided into two groups: target group, including those submitted to systematic plus targeted biopsy versus non-target group when only systematic or saturation biopsy were performed. Patients with PI-RADS 3 lesions were divided into three categories based on pathological biopsy results: benign, clinically insignificant disease (score Gleason = 6 or International Society of Urologic Pathologic (ISUP) 1) and clinically significant cancer (score Gleason ≥ 7 (3+4) or ISUP ≥ 2) according to target and non-target group. Univariate and multivariate analyses were performed to identify clinical predictors to improve the CsPCa detection rate in PI-RADS category 3 lesions.

RESULTS

A total of 130 men with PIRADS 3 index lesions were identified. Pathologic results were benign in 77 lesions (59.2%), 19 (14.6%) were clinically insignificant (Gleason score 6) and 34 (26.2%) were clinically significant (Gleason score 7 or higher). Eighty-seven of the patients were included in the target group (66.9%) and 43 in the non-target group (33.1%). The CsPCa detection was higher in the non-target group (32.6%, n = 14 vs 23.0%, n = 20 respectively). When systematic and target biopsies were jointly performed, if the results of systematic biopsies are not considered and only the results of target biopsies are taken into account, a CsPCa diagnosis would be missed on 9 patients. The differences of insignificant cancer and CsPCa rates among the target or non-target group were not statistically significant (p = 0.50 and p = 0.24, respectively). on multivariate analysis, the abnormal DRE and lesions localized in Peripheral zone (PZ) were significantly associated with a presence of CsPCa in PI-RADS 3 lesions (oR = 3.61, 95% CI [1.22,10.72], p = 0.02 and oR = 3.31, 95% CI [1.35, 8.11], p = 0.01, respectively). A higher median PSAD significantly predisposed for CsPCa on univariate analyses (p = 0.05), however, was not significant in the multivariate analysis (p = 0.76). In our population, using 0.10 ng/ml/ml as a cut-off to perform biopsy, 41 patients would have avoided biopsy (31.5%), but 5 cases of CsPCa would not have been detected (3.4%). We could not identify any statistical significance between other clinical and imagiological variables and CsPCa detection.

CONCLUSIONS

PI-RADS 3 lesions were associated with a low likelihood of CsPCa detection. A systematic biopsy associated or not with target biopsy is essential in PI-RADS 3 lesions, and targeted biopsy did not demonstrate to be superior in the detection of CsPCa. The presence of abnormal DRE and lesions localized in PZ potentially predict the presence of CsPCa in biopsied PI-RADS 3 lesions.

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.

The Added Value of Systematic Sampling in In-Bore Magnetic Resonance Imaging-Guided Prostate Biopsy

We sought to quantify the additive value of systematic biopsy (SB) using in-bore magnetic resonance (MR)-guided prostate biopsy (IBMRGpB) by retrospectively reviewing the records of 189 patients who underwent IBMRGpB for suspected prostate cancer or as part of the surveillance protocol for previously diagnosed prostate cancer. The endpoints included clinically significant and non-clinically significant cancer diagnosis. SB detected clinically significant disease in 67 (35.5%) patients. Five (2.65%) patients whose targeted biopsies indicated benign or non-clinically significant disease had clinically significant disease based on SB. SB from the lobe contralateral to the lesion detected clinically significant disease in 15 (12%) patients. The size of the prostate was larger and the percentage of lesions located in the peripheral zone of the prostate was higher in patients with SB-detected clinically significant disease. The location of the main lesion in the peripheral zone of the prostate was a predictor for clinically significant disease in the multivariate analysis (OR = 8.26, p = 0.04), a finding supported by a subgroup analysis of biopsy-naïve patients (OR = 10.52, p = 0.034). The addition of SB during IBMRGpB increased the diagnosis of clinically significant as well as non-clinically significant prostate cancer. The location of the main lesion in the peripheral zone emerged as a positive predictive factor for clinically significant disease based on SB. These findings may enhance patient-tailored management.

PI-RADS 3 score: A retrospective experience of clinically significant prostate cancer detection

Rationale and objectives

The study aims to propose an optimal workflow in patients with a PI-RADS 3 (PR-3) assessment category (AC) through determining the timing and type of pathology interrogation used for the detection of clinically significant prostate cancer (csPCa) in these men based upon a 5-year retrospective review in a large academic medical center.

Materials and methods

This United States Health Insurance Probability and Accountability Act (HIPAA)-compliant, institutional review board-approved retrospective study included men without prior csPCa diagnosis who received PR-3 AC on magnetic resonance (MR) imaging (MRI). Subsequent incidence and time to csPCa diagnosis and number/type of prostate interventions was recorded. Categorical data were compared using Fisher's exact test and continuous data using ANOVA omnibus F-test.

Results

Our cohort of 3238 men identified 332 who received PR-3 as their highest AC on MRI, 240 (72.3%) of whom had pathology follow-up within 5 years. csPCa was detected in 76/240 (32%) and non-csPCa in 109/240 (45%) within 9.0 ± 10.6 months. Using a non-targeted trans-rectal ultrasound biopsy as the initial approach (n = 55), another diagnostic procedure was required to diagnose csPCa in 42/55 (76.4%) of men, compared with 3/21(14.3%) men with an initial MR targeted-biopsy approach (n = 21); (p < 0.0001). Those with csPCa had higher median serum prostate-specific antigen (PSA) and PSA density, and lower median prostate volume (p < 0.003) compared with non-csPCa/no PCa.

Conclusion

Most patients with PR-3 AC underwent prostate pathology exams within 5 years, 32% of whom were found to have csPCa within 1 year of MRI, most often with a higher PSA density and a prior non-csPCa diagnosis. Addition of a targeted biopsy approach initially reduced the need for a second biopsy to reach a for csPCa diagnosis. Thus, a combination of systematic and targeted biopsy is advised in men with PR-3 and a co-existing abnormal PSA and PSA density.

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.

Automatic detection of prostate cancer grades and chronic prostatitis in biparametric MRI

BACKGROUND AND OBJECTIVE

With emerging evidence to improve prostate cancer (PCa) screening, multiparametric magnetic prostate imaging is becoming an essential noninvasive component of the diagnostic routine. Computer-aided diagnostic (CAD) tools powered by deep learning can help radiologists interpret multiple volumetric images. In this work, our objective was to examine promising methods recently proposed in the multigrade prostate cancer detection task and to suggest practical considerations regarding model training in this context.

METHODS

We collected 1647 fine-grained biopsy-confirmed findings, including Gleason scores and prostatitis, to form a training dataset. In our experimental framework for lesion detection, all models utilized 3D nnU-Net architecture that accounts for anisotropy in the MRI data. First, we explore an optimal range of b-values for diffusion-weighted imaging (DWI) modality and its effect on the detection of clinically significant prostate cancer (csPCa) and prostatitis using deep learning, as the optimal range is not yet clearly defined in this domain. Next, we propose a simulated multimodal shift as a data augmentation technique to compensate for the multimodal shift present in the data. Third, we study the effect of incorporating the prostatitis class alongside cancer-related findings at three different granularities of the prostate cancer class (coarse, medium, and fine) and its impact on the detection rate of the target csPCa. Furthermore, ordinal and one-hot encoded (OHE) output formulations were tested.

RESULTS

An optimal model configuration with fine class granularity (prostatitis included) and OHE has scored the lesion-wise partial Free-Response Receiver Operating Characteristic (FROC) area under the curve (AUC) of 1.94 (CI 95%: 1.76-2.11) and patient-wise ROC AUC of 0.874 (CI 95%: 0.793-0.938) in the detection of csPCa. Inclusion of the auxiliary prostatitis class has demonstrated a stable relative improvement in specificity at a false positive rate (FPR) of 1.0 per patient, with an increase of 3%, 7%, and 4% for coarse, medium, and fine class granularities.

CONCLUSIONS

This paper examines several configurations for model training in the biparametric MRI setup and proposes optimal value ranges. It also shows that the fine-grained class configuration, including prostatitis, is beneficial for detecting csPCa. The ability to detect prostatitis in all low-risk cancer lesions suggests the potential to improve the quality of the early diagnosis of prostate diseases. It also implies an improved interpretability of the results by the radiologist.

The use of 68 Ga-PSMA PET/CT to stratify patients with PI-RADS 3 lesions according to clinically significant prostate cancer risk

BACKGROUND

Prostate imaging reporting and data system (PI-RADS) category 3 lesions represent a "gray zone," having an equivocal risk of presenting as clinically significant prostate cancer (csPCa). ⁶⁸ Ga-labelled prostate-specific membrane antigen (⁶⁸ Ga-PSMA) positron emission tomography/computed tomography (PET/CT) has been identified as a diagnostic tool that can help to predict cases of primary PCa. We aimed to explore diagnostic value of ⁶⁸ Ga-PSMA PET/CT for csPCa in PI-RADS 3 lesions to aid in decision-making and avoid unnecessary biopsies.

METHODS

A total of 78 men with PI-RADS 3 lesions who underwent both ⁶⁸ Ga-PSMA PET/CT and transrectal ultrasound/magnetic resonance imaging (MRI) fusion-guided biopsy were enrolled. Images were analyzed by respective physicians who were blinded to the pathological results. Receiver operating characteristic (ROC) curve analysis and decision curve analysis were used to evaluate the diagnostic performance of univariate and multivariate analyses.

RESULTS

A total of 26/78 men had pathologically confirmed csPCa. A lower ADCT/ADCCLP (0.65 vs. 0.71, p = 0.018), smaller prostate volume (25.27 vs. 42.79 ml, p < 0.001), lower free prostate-specific antigen/total prostate-specific antigen (0.11 vs. 0.16, p < 0.001), higher PSA level (13.45 vs. 7.90 ng/ml, p = 0.001), higher PSA density (0.40 vs. 0.16 ng/ml² , p < 0.001), higher SUVmax (9.80 vs. 4.40, p < 0.001) and SUVT/BGp (2.41 vs. 1.00, p < 0.001) were associated with csPCa. ROC analysis illustrated the improvement in SUVmax and SUVT/BGp compared with all independent and combined clinical features as well as multiparametric magnetic resonance imaging (mpMRI) features for csPCa detection. The net benefits of SUVmax and SUVT/BGp were superior to those of other features, respectively. With cutoff values of 5.0 for SUVmax and 1.4 for SUVT/BGp, the diagnostic sensitivity and specificity for csPCa were 96.2%, 100% and 80.8%, 84.6%, respectively.

CONCLUSION

⁶⁸ Ga-PSMA PET/CT is potentially capable of stratifying men with PI-RADS 3 lesions according to the presence of csPCa and has better performance than the model established based on clinical and mpMRI features.

Prediction of Significant Prostate Cancer in Equivocal Magnetic Resonance Imaging Lesions: A High-volume International Multicenter Study

BACKGROUND

Decision of performing prostate biopsy in men with Prostate Imaging Reporting and Data System (PI-RADS) 3 findings in prostate magnetic resonance imaging (MRI) is challenging as they have a low but still relevant risk of harboring significant prostate cancer (sPC).

OBJECTIVE

To identify clinical predictors of sPC in men with PI-RADS 3 lesions in prostate MRI and to analyze the hypothetical effect of incorporating prostate-specific antigen density (PSAD) into biopsy decision.

DESIGN, SETTING, AND PARTICIPANTS

We analyzed a retrospective multinational cohort from ten academic centers comprising 1476 men who underwent a combined prostate biopsy (MRI targeted plus systematic biopsy) between February 2012 and April 2021 due to a PI-RADS 3 lesion in prostate MRI.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The primary outcome was the detection of sPC (ISUP ≥2) in a combined biopsy. Predictors were identified by a regression analysis. Descriptive statistics were applied to evaluate the hypothetical effect of involving PSAD into biopsy decision.

RESULTS AND LIMITATIONS

Of all patients, 273/1476 (18.5%) were diagnosed with sPC. MRI-targeted biopsy diagnosed fewer sPC cases than combined strategy: 183/1476 (12.4%) versus 273/1476 (18.5%), p < 0.01. Age (odds ratio [OR] 1.10 [95% confidence interval {CI}: 1.05-1.15], p < 0.001), prior negative biopsy (OR 0.46 [0.24-0.89], p = 0.022), and PSAD (p < 0.001) were found to be independent predictors of sPC. Applying a PSAD cutoff of 0.15, 817/1398 (58.4%) biopsies would have been avoided at the cost of missing sPC in 91 (6.5%) men. Limitations were the retrospective design, heterogeneity of the study cohort due to the long inclusion period, and no central revision of MRI.

CONCLUSIONS

Age, previous biopsy status, and PSAD were found to be independent predictors of sPC in men with equivocal prostate MRI. Implementation of PSAD into biopsy decision can avoid unnecessary biopsies. Clinical parameters such as PSAD need validation in a prospective setting.

PATIENT SUMMARY

In this study, we looked for clinical predictors of significant prostate cancer in men with Prostate Imaging Reporting and Data System 3 lesions in prostate magnetic resonance imaging. We identified age, previous biopsy status, and especially prostate-specific antigen density as independent predictors.

A Review of Modern Imaging Landscape for Prostate Cancer: A Comprehensive Clinical Guide

The development of prostate cancer imaging is rapidly evolving, with many changes to the way patients are diagnosed, staged, and monitored for recurrence following treatment. New developments, including the potential role of imaging in screening and the combined diagnostic and therapeutic applications in the field of theranostics, are underway. In this paper, we aim to outline the current landscape in prostate cancer imaging and look to the future at the potential modalities and applications to come.

Monoparametric high-resolution diffusion weighted MRI as a possible first step in an MRI-directed diagnostic pathway for men with suspicion of prostate cancer

Purpose

To explore if a high-resolution diffusion weighted MRI sequence (DWI-only) could be used as a first step in an MRI-directed diagnostic pathway.

Methods

Prospective single center study that between December 2017 and August 2018 included 129 consecutive patients with suspicion of prostate cancer into a PI-RADS-based MRI-directed diagnostic pathway. All patients had multiparametric MRI (mpMRI). Based on only the transversal high-resolution DWI images two consultant radiologists prospectively categorized the findings as positive, equivocal, or negative for clinically significant cancer. The radiologists then interpreted the mpMRI and assigned a PI-RADS score. A third independent reader retrospectively categorized the DWI-only exams without access to the mpMRI. The interpretations of DWI-only were compared to the PI-RADS classification from mpMRI and the histopathology from the biopsies. Non-biopsied patients were followed in a safety net monitoring for 56 months.

Results

Based on DWI-only, 29 (22.5%) of the exams were categorized as negative, 38 (29.5%) as equivocal and 62 (48.1%) as positive. Of the 56 patients with PI-RADS 4-5 at mpMRI, 55 were also categorized as positive at DWI-only. All patients diagnosed with clinically significant cancer were identified using DWI-only. 56 months of safety net monitoring did not reveal any clinically significant cancers among patients with exams categorized as negative or equivocal. There was high inter-reader agreement on positive findings, but less agreement on negative and equivocal findings.

Conclusions

In this concept study, the monoparametric DWI-only identified all patients with clinically significant cancer in a mpMRI-directed diagnostic pathway.

MRI-based analysis of different clinically significant prostate cancer detection rate of prostate imaging reporting and data system score 4 in the peripheral zone

PURPOSE

To compare the clinically significant prostate cancer (csPCa) detection rate between diffusion-weighted imaging (DWI) 4 and DWI 3 with positive dynamic contrast-enhanced (DCE) (hereinafter called 'DWI 3/DCE+') lesions in the peripheral zone (PZ) and to explore the diagnostic performance of targeted biopsy (TB) or systematic biopsy (SB) in patients with Prostate Imaging Reporting and Data System (PI-RADS) 4 lesions.

METHODS

We retrospectively enrolled 206 patients who underwent multiparametric magnetic resonance imaging and had at least one PI-RADS 4 lesion in the PZ. All patients subsequently underwent combined magnetic resonance imaging/ultrasound fusion-guided TB and ultrasound-guided 12-core SB. The chi-square test was used to compare the csPCa detection rates between DWI 4 and DWI 3/DCE+ lesions. Based on the TB + SB results as a standard reference, we analyzed the sensitivity, negative predictive value, and diagnostic accuracy of TB alone or SB alone.

RESULTS

Patients with DWI 4 lesions had higher csPCa detection rate than those with DWI 3/DCE+ lesions when using TB + SB, TB, and SB, and the differences were significant for TB + SB (72.22 vs. 54.84%, p = 0.015) or SB (65.97 vs. 46.77%, p = 0.010). For DWI 3/DCE+ patients whose prostate-specific antigen levels ranged from 4 to 10 ng/mL, TB alone showed the highest negative predictive value (95% Cl 78.12-100).

CONCLUSIONS

DWI 4 tends to have worse results than DWI 3/DCE+. TB has great diagnostic performances in DWI 3/DCE+ patients, especially for those prostate-specific antigen ranging from 4 to 10 ng/mL.

Value of machine learning-based transrectal multimodal ultrasound combined with PSA-related indicators in the diagnosis of clinically significant prostate cancer

OBJECTIVE

To investigate the effect of transrectal multimodal ultrasound combined with serum prostate-specific antigen (PSA)-related indicators and machine learning for the diagnosis of clinically significant prostate cancer.

METHODS

Based on Gleason score of postoperative pathological results, the subjects were divided into clinically significant prostate cancer groups(GS>6)and non-clinically significant prostate cancer groups(GS ≤ 6). The independent risk factors were obtained by univariate logistic analysis. Artificial neural network (ANN), logistic regression (LR), support vector machine (SVM), decision tree (DT), random forest (RF), and K-nearest neighbor (KNN) machine learning models were combined with clinically significant prostate cancer risk factors to establish the machine learning model, calculate the model evaluation indicators, construct the receiver operating characteristic curve (ROC), and calculate the area under the curve (AUC).

RESULTS

Independent risk factor items (P< 0.05) were entered into the machine learning model. A comparison of the evaluation indicators of the model and the area under the ROC curve showed the ANN model to be best at predicting clinically significant prostate cancer, with a sensitivity of 80%, specificity of 88.6%, F1 score of 0.897, and the AUC was 0.855.

CONCLUSION

Establishing a machine learning model by rectal multimodal ultrasound and combining it with PSA-related indicators has definite application value in predicting clinically significant prostate cancer.

Incorporating Prostate-specific Membrane Antigen Positron Emission Tomography in Management Decisions for Men with Newly Diagnosed or Biochemically Recurrent Prostate Cancer

CONTEXT

Prostate-specific membrane antigen (PSMA) is a promising molecular target for prostate cancer (PCa) that has allowed the development of a novel diagnostic approach to PCA in the primary and recurrent settings.

OBJECTIVE

To summarize available data and recommendations regarding the use of PSMA in newly diagnosed and recurrent PCa via a narrative review.

EVIDENCE ACQUISITION

A literature review was conducted using MEDLINE (via PubMed) and Scopus. The search strategy included meta-analyses, reviews, and original studies on staging and restaging with ⁶⁸Ga-PSMA positron emission tomography (PET)/computed tomography (CT).

EVIDENCE SYNTHESIS

Studies comparing PSMA-targeted imaging and conventional imaging suggest superior performance of PSMA-targeted imaging in primary and recurrent PCa, albeit with several clinically relevant limitations. Pretreatment ⁶⁸Ga-PSMA PET/CT allowed more accurate PCa staging in compared to routine practice for high-risk cases, and identified a number of otherwise unknown metastatic lesions. In biochemically recurrent PCa, PSMA PET can reveal sites of recurrence with greater sensitivity and specificity than conventional imaging, potentially detecting a major proportion of occult disease. This review will help providers in applying the most up-to-date and relevant literature to (1) determine which patients truly have oligometastatic disease and (2) ascertain who is most likely to experience a meaningful response to local consolidation in the biochemical recurrence setting.

CONCLUSIONS

Data on PSMA diagnostic studies in primary and recurrent PCa highlight the accuracy and clinical application of PSMA PET. While this review and the evidence to date might lead to a perception of superiority in metastasis directed therapy, fundamental lack of phase III clinical trials with clinically meaningful outcomes are yet to be determined.

PATIENT SUMMARY

PSMA (prostate-specific membrane antigen) scans have shown great promise for initial evaluation of prostate cancer (PCa) and in detection of PCa recurrence. The benefits are more apparent for initial staging of PCa. There are more limited clinical trial results for PCa recurrence on how best to use this new technique to guide cancer treatment.

Performance of multiparametric prostate magnetic resonance imaging validated by targeted and systematic transperineal biopsies

Objective

To measure the performance of multiparametric (mp) magnetic resonance imaging (MRI) to identify intraprostatic tumour deposits using a systematic and targeted MR-guided transperineal prostate biopsy technique.

Materials and Methods

Patients underwent a combined systematic and targeted MR-guided transperineal biopsy procedure in the dorsal lithotomy position under general anaesthesia. Systematic biopsies were spaced 10 mm or less apart and additional biopsies targeted any Prostate Imaging-Reporting and Data System (PI-RADS) 3, 4 or 5 lesions identified on mpMRI. Cancer detection rates were calculated on a per patient and per lesion basis.

Results

A total of 125 patients underwent the biopsy procedure. The positive predictive value (PPV) of mpMRI per patient was 59% for any cancer and 49% for Gleason score (GS) ≥ 7 cancer. The negative predictive value (NPV) of mpMRI per patient was 67% for any cancer and 88% for GS ≥ 7 cancer. On a per lesion basis, the PPV of PI-RADS 3 lesions for any and GS ≥ 7 cancer was 24% and 10%. For PI-RADS 4 lesions it was 42% and 32%. For PI-RADS 5 lesions, it was 76% and 70%. MpMRI failed to identify GS ≥ 7 cancer found on systematic biopsy in 22% of patients.

Conclusion

Based on a combination of systematic and targeted transperineal prostate biopsies, mpMRI showed a high NPV and low PPV for GS ≥ 7 cancer on a per patient basis. The PPV of mpMRI on a per lesion basis increased with increasing PI-RADS score. However, there were a significant number of both false positive as well as false negative (mpMRI invisible) areas within the prostate that contained GS ≥ 7 cancer. Therefore, pathologic confirmation using both targeted and systematic mapping biopsy is necessary to accurately identify all intraprostatic tumour deposits.

Machine Learning and Clinical-Radiological Characteristics for the Classification of Prostate Cancer in PI-RADS 3 Lesions

The Prostate Imaging Reporting and Data System (PI-RADS) classification is based on a scale of values from 1 to 5. The value is assigned according to the probability that a finding is a malignant tumor (prostate carcinoma) and is calculated by evaluating the signal behavior in morphological, diffusion, and post-contrastographic sequences. A PI-RADS score of 3 is recognized as the equivocal likelihood of clinically significant prostate cancer, making its diagnosis very challenging. While PI-RADS values of 4 and 5 make biopsy necessary, it is very hard to establish whether to perform a biopsy or not in patients with a PI-RADS score 3. In recent years, machine learning algorithms have been proposed for a wide range of applications in medical fields, thanks to their ability to extract hidden information and to learn from a set of data without previous specific programming. In this paper, we evaluate machine learning approaches in detecting prostate cancer in patients with PI-RADS score 3 lesions via considering clinical-radiological characteristics. A total of 109 patients were included in this study. We collected data on body mass index (BMI), location of suspicious PI-RADS 3 lesions, serum prostate-specific antigen (PSA) level, prostate volume, PSA density, and histopathology results. The implemented classifiers exploit a patient’s clinical and radiological information to generate a probability of malignancy that could help the physicians in diagnostic decisions, including the need for a biopsy.

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

OBJECTIVE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Paradigm Shift in Prostate Cancer Diagnosis: Pre-Biopsy Prostate Magnetic Resonance Imaging and Targeted Biopsy

With regard to the indolent clinical characteristics of prostate cancer (PCa), the more selective detection of clinically significant PCa (CSC) has been emphasized in its diagnosis and management. Magnetic resonance imaging (MRI) has advanced technically, and recent international cooperation has provided a standardized imaging and reporting system for prostate MRI. Accordingly, prostate MRI has recently been investigated and utilized as a triage tool before biopsy to guide tissue sampling to increase the detection rate of CSC beyond the staging tool for patients in whom PCa was already confirmed on conventional systematic biopsy. Radiologists must understand the current paradigm shift for better PCa diagnosis and management. This article reviewed the recent literature, demonstrating the diagnostic value of pre-biopsy prostate MRI with targeted biopsy and discussed unsolved issues regarding the paradigm shift in the diagnosis of PCa.

Single center analysis of an advisable control interval for follow-up of patients with PI-RADS category 3 in multiparametric MRI of the prostate

To evaluate if follow-up mpMRI scans of patients in PI-RADS category 3 are safe enough to omit or delay prostate biopsy in the future and to determine an optimal control interval. This retrospective single center study includes consecutive PI-RADS category 3 patients with one or more follow-up mpMRI (T2WI, DWI, DCE) and subsequent MRI-targeted and systematic TRUS-guided biopsy between 2012 and 2018. Primary study objective was the verification of a significant PI-RADS category upgrade in follow-up mpMRI in patients with subsequent PCA positive biopsy versus patients with negative biopsy. Further objectives were development of the PI-RADS category and clinical parameters between initial and follow-up mpMRI in the context of histopathologic results and time interval. Eighty-nine patients (median PSA 6.6 ng/ml; PSAD 0.13 ng/ml/ml) were finally included (follow-up period 31 ± 18 months). 19 cases had PCA (median PSA 7.8 ng/ml; PSAD 0.14 ng/ml/ml). 4 cases had csPCA (median PSA 5.4 ng/ml; PSAD 0.13 ng/ml/ml) for which there was a significant PI-RADS upgrade after 12-24 months (mean 3.75; p = 0.01) compared to patients without PCA (mean 2.74). Without PCA the mean PI-RADS category decreased after 25-36 months (mean 2.74; p = 0.02). Clinical parameters did not change significantly except a PSAD increase for PCA patients after 24 months. Patients within PI-RADS category 3 may not need prompt biopsy since those with PCA reliably demonstrate a PI-RADS category upgrade in follow-up mpMRI after 12-24 months. PI-RADS 3 patients with negative biopsy do not benefit from follow-up mpMRI earlier than 24 months.

Clinically Significant Prostate Cancer Detection After A Negative Prebiopsy MRI Examination: Comparison of Biparametric Versus Multiparametric MRI

Background: The frequency of clinically significant prostate cancer (csPCa) following negative biparametric MRI (bpMRI) and multiparametric MRI (mpMRI) has not been well investigated in direct comparative studies. Objective: To compare the frequency of csPCa after negative prebiopsy bpMRI and mpMRI, and to evaluate factors that predict csPca in the two cohorts. Methods: This retrospective study included 232 men (mean age, 64.5 years) with negative bpMRI from August 2017 to March 2020 and193 men (mean age, 69.0 years) with negative mpMRI from January 2018 to December 2018, defining PI-RADS category of 1 or 2 as negative. Our institution offers bpMRI as a low-cost self-pay option for patients without insurer coverage of prebiospy mpMRI. Patient characteristics and subsequent biopsy results were recorded. csPCa was defined as Gleason score ≥3+4. Multivariable regression analyses were performed to identify independent predictors of csPCa. AUC of prostate specific antigen density (PSAD) for csPCA was computed, and diagnostic performance of PSAD was assessed at a clinically established threshold of 0.15 ng/mL2. Results: Systematic biopsy was performed after negative bpMRI in 41.4% (96/232), versus after negative mpMRI in 30.5% (59/193) (p=.02). Among those undergoing biopsy, csPCa was present in 15.6% (15/96) in the mpMRI cohort versus 13.6% (8/59) in the bpMRI cohort (p=.69). NPV for csPCa was 84% (81/96) for bpMRI and 86% (51/59) for mpMRI. In multivariable analyses, independent predictors of csPCa included smaller prostate volume (OR=0.27, p<.001) and greater PSAD (OR=3.09, p<.001). In multivariable models, bpMRI (compared with mpMRI) did not independently predict csPCa (p>.05). PSAD had AUC for csPCa of 0.77 (95% CI: 0.64, 0.89) in the bpMRI cohort versus 0.68 (95% CI: 0.42, 0.93) in the mpMRI cohort. For detecting csPCa, PSAD threshold of 0.15 ng/mL2 had NPV of 90% and PPV of 28%, in the bpMRI cohort, versus NPV of 92% and PPV of 44%in the mpMRI cohort. Conclusion: The frequency of csPCa was not significantly different on systematic biopsy performed after negative bpMRI and mpMRI examinations. PSAD had similar diagnostic utility for csPca in both cohorts. Clinical Impact: Either bpMRI or mpMRI, in combination with PSAD, can help avoid negative prostate biopsies.

Textured-Based Deep Learning in Prostate Cancer Classification with 3T Multiparametric MRI: Comparison with PI-RADS-Based Classification

The current standardized scheme for interpreting MRI requires a high level of expertise and exhibits a significant degree of inter-reader and intra-reader variability. An automated prostate cancer (PCa) classification can improve the ability of MRI to assess the spectrum of PCa. The purpose of the study was to evaluate the performance of a texture-based deep learning model (Textured-DL) for differentiating between clinically significant PCa (csPCa) and non-csPCa and to compare the Textured-DL with Prostate Imaging Reporting and Data System (PI-RADS)-based classification (PI-RADS-CLA), where a threshold of PI-RADS ≥ 4, representing highly suspicious lesions for csPCa, was applied. The study cohort included 402 patients (60% (n = 239) of patients for training, 10% (n = 42) for validation, and 30% (n = 121) for testing) with 3T multiparametric MRI matched with whole-mount histopathology after radical prostatectomy. For a given suspicious prostate lesion, the volumetric patches of T2-Weighted MRI and apparent diffusion coefficient images were cropped and used as the input to Textured-DL, consisting of a 3D gray-level co-occurrence matrix extractor and a CNN. PI-RADS-CLA by an expert reader served as a baseline to compare classification performance with Textured-DL in differentiating csPCa from non-csPCa. Sensitivity and specificity comparisons were performed using Mcnemar's test. Bootstrapping with 1000 samples was performed to estimate the 95% confidence interval (CI) for AUC. CIs of sensitivity and specificity were calculated by the Wald method. The Textured-DL model achieved an AUC of 0.85 (CI [0.79, 0.91]), which was significantly higher than the PI-RADS-CLA (AUC of 0.73 (CI [0.65, 0.80]); p < 0.05) for PCa classification, and the specificity was significantly different between Textured-DL and PI-RADS-CLA (0.70 (CI [0.59, 0.82]) vs. 0.47 (CI [0.35, 0.59]); p < 0.05). In sub-analyses, Textured-DL demonstrated significantly higher specificities in the peripheral zone (PZ) and solitary tumor lesions compared to the PI-RADS-CLA (0.78 (CI [0.66, 0.90]) vs. 0.42 (CI [0.28, 0.57]); 0.75 (CI [0.54, 0.96]) vs. 0.38 [0.14, 0.61]; all p values < 0.05). Moreover, Textured-DL demonstrated a high negative predictive value of 92% while maintaining a high positive predictive value of 58% among the lesions with a PI-RADS score of 3. In conclusion, the Textured-DL model was superior to the PI-RADS-CLA in the classification of PCa. In addition, Textured-DL demonstrated superior performance in the specificities for the peripheral zone and solitary tumors compared with PI-RADS-based risk assessment.

Pathological features of Prostate Imaging Reporting and Data System (PI-RADS) 3 MRI lesions in biopsy and radical prostatectomy specimens

OBJECTIVE

To assess the whole pathology spectrum of Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions, identified on magnetic resonance imaging, using systematic (SB), targeted biopsy (TB) and radical prostatectomy (RP) specimen analysis.

METHODS

From a prospective database of patients undergoing RP after a combination of SB (median 12 cores) and fusion TB (median 3 cores), we included 150 PI-RADS 3 cases. Clinically significant prostate cancer (csPCa) was defined by a Grade Group 2 or more. The primary endpoints were unfavourable features in RP specimens.

RESULTS

Targeted biopsy was negative in 20.7% of patients. Final Grade Group 3 or more and a pT3 stage was reported in 36.7% and 38.7% of RP specimens. The upgrading rate was 38.2% between biopsy and RP specimens. The concordance rate between Grade Group on TB and RP was only 38.0%. The two independent predictive factors for unfavourable disease (pT3-4 and/or final Grade Group 3-5) were prostate-specific antigen density (PSAD; P = 0.001) and presence of csPCa on TB (odds ratio 3.7; P = 0.001). The risk of unfavourable disease was increased 2.3-fold and 5.8-fold, respectively, for patients with a PSAD between 0.15 and 0.20, and a PSAD >0.20 ng/mL/g. The 5-year biochemical recurrence-free survival rate was 93.2%.

CONCLUSIONS

PI-RADS 3 lesions exhibited aggressive features in almost 40% of cases. PSAD and presence of csPCa on TB are independent predictive factors for high-grade and/or extraprostatic disease. A combination of SB and TB improve grade prediction compared to use of TB alone.

Does Adding Standard Systematic Biopsy to Targeted Prostate Biopsy in PI-RADS 3 to 5 Lesions Enhance the Detection of Clinically Significant Prostate Cancer? Should All Patients with PI-RADS 3 Undergo Targeted Biopsy?

INTRODUCTION

Our aim was to assess the value of adding standard biopsy to targeted biopsy in cases of suspicious multiparametric magnetic resonance imaging (mp-MRI) and also to evaluate when a biopsy of a PI-RADS 3 lesion could be avoided.

METHODS

A retrospective study of patients who underwent targeted biopsy plus standard systematic biopsy between 2016-2019 was performed. All the 1.5 T magnetic resonance images were evaluated according to PI-RADSv.2. An analysis focusing on the clinical scenario, lesion location, and PI-RADS score was performed.

RESULTS

A total of 483 biopsies were evaluated. The mean age was 65 years, with a PSA density of 0.12 ng/mL/cc. One-hundred and two mp-MRIs were categorized as PI-RADS-3. Standard biopsy was most helpful in detecting clinically significant prostate cancer (csPCa) in patients in the active surveillance (AS) cohort (increasing the detection rate 12.2%), and in peripheral lesions (6.5%). Adding standard biopsy showed no increase in the detection rate for csPCa in patients with PI-RADS-5 lesions. Considering targeted biopsy in patients with PI-RADS 3 lesions, a higher detection rate was shown in biopsy-naïve patients versus AS and in patients with a previous negative biopsy (p = 0.002). Furthermore, in these patients, the highest rate of csPCa detection was in anterior lesions [42.9% (p = 0.067)].

CONCLUSIONS

Our results suggest that standard biopsy could be safely omitted in patients with anterior lesions and in those with PI-RADS-5 lesions. Targeted biopsy for PI-RADS-3 lesions would be less effective in peripheral lesions with a previous negative biopsy.

Avoiding Unnecessary Biopsy: MRI-based Risk Models versus a PI-RADS and PSA Density Strategy for Clinically Significant Prostate Cancer

Background In validation studies, risk models for clinically significant prostate cancer (csPCa; Gleason score ≥3+4) combining multiparametric MRI and clinical factors have demonstrated poor calibration (over- and underprediction) and limited use in avoiding unnecessary prostate biopsies. Purpose MRI-based risk models following local recalibration were compared with a strategy that combined Prostate Imaging Data and Reporting System (PI-RADS; version 2) and prostate-specific antigen density (PSAd) to assess the potential reduction of unnecessary prostate biopsies. Materials and Methods This retrospective study included 385 patients without prostate cancer diagnosis who underwent multipara-metric MRI (PI-RADS category ≥3) and MRI-targeted biopsy between 2015 and 2019. Recalibration and selection of the best-performing MRI model (MRI-European Randomized Study of Screening for Prostate Cancer [ERSPC], van Leeuwen, Radtke, and Mehralivand models) were undertaken in cohort C1 (n = 242; 2015-2017). The impact on biopsy decisions was compared with an alternative strategy (no biopsy for PI-RADS category 3 plus PSAd < 0.1 ng/mL per milliliter) in cohort C2 (n = 143; 2018-2019). Discrimination, calibration, and clinical utility were assessed by using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis, respectively. Results The prevalence of csPCa was 38% (93 of 242 patients) and 45% (64 of 143 patients) in cohorts C1 and C2, respectively. Decision curve analysis demonstrated the highest net benefit for the van Leeuwen and Mehralivand models in C1. Used for biopsy decisions in C2, van Leeuwen (AUC, 0.84; 95% CI: 0.77, 0.9) and Mehralivand (AUC, 0.79; 95% CI: 0.72, 0.86) enabled no net benefit at a risk threshold of 10%. Up to a risk threshold of 15%, net benefit remained inferior to the PI-RADS plus PSAd strategy, which avoided biopsy in 63 per 1000 men, without missing csPCa. Without prior recalibration in C1, three of four models (MRIERSPC, Radtke, Mehralivand) were poorly calibrated and not clinically useful in C2. Conclusion The number of unnecessary prostate biopsies in men with positive MRI may be safely reduced by using a prostate-specific antigen density-based strategy. In a risk-averse scenario, this strategy enabled better biopsy decisions compared with MRI-based risk models. ©RSNA, 2021 Online supplemental material is available for this article.

Serum miRNAs Support the Indication for MRI-Ultrasound Fusion-Guided Biopsy of the Prostate in Patients with Low-PI-RADS Lesions

Multiparametric MRI (mpMRI) and targeted biopsy of the prostate enhance the tumor detection rate. However, the prediction of clinically significant prostate cancer (PCa) is still limited. Our study tested the additional value of serum levels of selected miRNAs in combination with clinical and mpMRI information for PCa prediction and classification. A total of 289 patients underwent targeted mpMRI-ultrasound fusion-guided prostate biopsy complemented by systematic biopsy. Serum miRNA levels of miRNAs (miR-141, miR-375, miR-21-5p, miR-320b, miR-210-3p, let-7c, and miR-486) were determined by quantitative PCR. Detection of any PCa and of significant PCa were the outcome variables. The patient age, pre-biopsy PSA level, previous biopsy procedure, PI-RADS score, and serum miRNA levels were covariates for regularized binary logistic regression models. The addition of miRNA expression of miR-486 and let-7c to the baseline model, containing only clinical parameters, increased the predictive accuracy. Particularly in patients with PI-RADS ≤3, we determined a sensitivity for detecting significant PCa (Gleason score ≥ 7a corresponding to Grade group ≥2) of 95.2%, and an NPV for absence of significant PCa of 97.1%. This accuracy could be useful to support patient counseling in selected cases.

Cost-effectiveness of multiparametric magnetic resonance imaging and MRI-guided biopsy in a population-based prostate cancer screening setting using a micro-simulation model

BACKGROUND

The introduction of multiparametric magnetic resonance imaging (mpMRI) and MRI-guided biopsy has improved the diagnosis of prostate cancer. However, it remains uncertain whether it is cost-effective, especially in a population-based screening strategy.

METHODS

We used a micro-simulation model to assess the cost-effectiveness of an MRI-based prostate cancer screening in comparison to the classical prostate-specific antigen (PSA) screening, at a population level. The test sensitivity parameters for the mpMRI and MRI-guided biopsy, grade misclassification rates, utility estimates, and the unit costs of different interventions were obtained from literature. We assumed the same screening attendance rate and biopsy compliance rate for both strategies. A probabilistic sensitivity analysis, consisting of 1000 model runs, was performed to estimate a mean incremental cost-effectiveness ratio (ICER) and assess uncertainty. A €20,000 willingness-to-pay (WTP) threshold per quality-adjusted life year (QALY) gained, and a discounting rate of 3.5% was considered in the analysis.

RESULTS

The MRI-based screening improved the life-years (LY) and QALYs gained by 3.5 and 3, respectively, in comparison to the classical screening pathway. Based on the probabilistic sensitivity analyses, the MRI screening pathway leads to total discounted mean incremental costs of €15,413 (95% confidence interval (CI) of €14,556-€16,272) compared to the classical screening pathway. The corresponding discounted mean incremental QALYs gained was 1.36 (95% CI of 1.31-1.40), resulting in a mean ICER of €11,355 per QALY gained. At a WTP threshold of €20,000, the MRI screening pathway has about 84% chance to be more cost-effective than the classical screening pathway.

CONCLUSIONS

For triennial screening from age 55-64, incorporation of mpMRI as a reflex test after a positive PSA test result with a subsequent MRI-guided biopsy has a high probability to be more cost-effective as compared with the classical prostate cancer screening pathway.

Developing a coordinate-based strategy to support cognitive targeted prostate biopsies and correlative spatial-histopathological outcome analysis

Lack of investment for magnetic resonance (MR) fusion systems is an obstacle to deliver targeted prostate biopsies within the prostate cancer diagnostic pathway. We developed a coordinate-based method to support cognitive targeted prostate biopsies and then performed an audit on cancer detection and the location of lesions. In each patient, the prostate is considered as two separate hemiprostates, and each hemiprostate is divided into 4 × 4 × 4 units. Each unit is therefore defined by a three-dimensional coordinate. We prospectively applied our coordinates approach to target 106 prostatic lesions in 93 men. Among 45 (of 106; 42.5%) lesions positive for cancer, 27 lesions (60.0%) harbored clinically significant disease. PSA density was significantly higher in patients with proven cancer (median: 0.264 ng ml-2) when compared to the noncancer group (median: 0.145 ng ml-2; P = 0.003, Wilcoxon rank-sum test). Lesions with Prostate Imaging-Reporting and Data System (PIRADS) score of 5 were found to have a cancer incidence of 65.2%, while PIRADS 4 and 3 lesions have a lower risk of cancer detection, as expected, at 37.3% and 31.3%, respectively. The probability of a lesion being cancerous in our series significantly decreases as we go from the "apex-to-base" dimension (odds ratio [OR]: 2.62, 95% confidence interval [CI]: 1.55-4.44, P = 0.00034). Our analysis also indicates that the probability of cancer decreases as the prostate volume increases (OR: 1.03, 95% CI: 1.01-1.05, P = 0.00327). Based on this feasibility study, the use of coordinates to guide cognitive targeted prostate biopsies warrants future validation study in additional centers.

Diagnostic Accuracy of Single-plane Biparametric and Multiparametric Magnetic Resonance Imaging in Prostate Cancer: A Randomized Noninferiority Trial in Biopsy-naïve Men

BACKGROUND

Urological guidelines recommend multiparametric magnetic resonance imaging (mpMRI) in men with a suspicion of prostate cancer (PCa). The resulting increase in MRI demand might place health care systems under substantial stress.

OBJECTIVE

To determine whether single-plane biparametric MRI (fast MRI) workup could represent an alternative to mpMRI in the detection of clinically significant (cs) PCa.

DESIGN, SETTING, AND PARTICIPANTS

Between April 2018 and February 2020, 311 biopsy-naïve men aged ≤75 yr with PSA ≤15 ng/ml and negative digital rectal examination were randomly assigned to 1.5-T fast MRI (n = 213) or mpMRI (n = 98).

INTERVENTION

All MRI examinations were classified according to Prostate Imaging-Reporting and Data System (PI-RADS) version 2. Men scored PI-RADS 1-2 underwent 12-core standard biopsy (SBx) and those with PI-RADS 4-5 on fast MRI or PI-RADS 3-5 on mpMRI underwent targeted biopsy in combination with SBx. Equivocal cases on fast MRI (PI-RADS 3) underwent mpMRI and then biopsy according to the findings.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The primary outcome was to compare the detection rate of csPCa in both study arms, setting a 10% difference for noninferiority. The secondary outcome was to assess the role of prostate-specific antigen density (PSAD) in ruling out men who could avoid biopsy among those with equivocal findings on fast MRI.

RESULTS AND LIMITATIONS

The overall MRI detection rate for csPCa was 23.5% (50/213; 95% confidence interval [CI] 18.0-29.8%) with fast MRI and 32.7% (32/98; 95% CI 23.6-42.9%) with mpMRI (difference 9.2%; p = 0.09). The reproducibility of the study could have been affected by its single-center nature.

CONCLUSIONS

Fast MRI followed by mpMRI in equivocal cases is not inferior to mpMRI in the detection of csPCa among biopsy-naïve men aged ≤75 yr with PSA ≤15 ng/ml and negative digital rectal examination. These findings could pave the way to broader use of MRI for PCa diagnosis.

PATIENT SUMMARY

A faster MRI (magnetic resonance imaging) protocol with no contrast agent and fewer scan sequences for examination of the prostate is not inferior to the typical MRI approach in the detection of clinically significant prostate cancer. If our findings are confirmed in other studies, fast MRI could represent a time-saving and less invasive examination for men with suspicion of prostate cancer. This trial is registered at ClinicalTrials.gov as NCT03693703.

Prostate Imaging-Reporting and Data System: Comparison of the Diagnostic Performance between Version 2.0 and 2.1 for Prostatic Peripheral Zone

Objective

To compare the diagnostic performance between Prostate Imaging-Reporting and Data System version 2.0 (PI-RADSv2.0) and version 2.1 (PI-RADSv2.1) for clinically significant prostate cancer (csPCa) in the peripheral zone (PZ).

Materials and Methods

This retrospective study included 317 patients who underwent multiparametric magnetic resonance imaging and targeted biopsy for PZ lesions. Definition of csPCa was International Society of Urologic Pathology grade ≥ 2 cancer. Area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy for csPCa were analyzed by two readers. The cancer detection rate (CDR) for csPCa was investigated according to the PI-RADS categories.

Results

AUC of PI-RADSv2.1 (0.856 and 0.858 for reader 1 and 2 respectively) was higher than that of PI-RADSv2.0 (0.795 and 0.747 for reader 1 and 2 respectively) (both p < 0.001). Sensitivity, specificity, PPV, NPV, and accuracy for PI-RADSv2.0 vs. PI-RADSv2.1 were 93.2% vs. 88.3% (p = 0.023), 52.8% vs. 76.6% (p < 0.001), 48.7% vs. 64.5% (p < 0.001), 94.2% vs. 93.2% (p = 0.504), and 65.9% vs. 80.4% (p < 0.001) for reader 1, and 96.1% vs. 92.2% (p = 0.046), 34.1% vs. 72.4% (p < 0.001), 41.3% vs. 61.7% (p < 0.001), 94.8% vs. 95.1% (p = 0.869), and 54.3% vs. 78.9% (p < 0.001) for reader 2, respectively. CDRs of PI-RADS categories 1–2, 3, 4, and 5 for PI-RADSv2.0 vs. PI-RADSv2.1 were 5.9% vs. 5.9%, 5.8% vs. 12.5%, 39.8% vs. 56.2%, and 88.9% vs. 88.9% for reader 1; and 4.5% vs. 4.1%, 6.1% vs. 11.1%, 32.5% vs. 53.4%, and 85.0% vs. 86.8% for reader 2, respectively.

Conclusion

Our data demonstrated improved AUC, specificity, PPV, accuracy, and CDRs of category 3 or 4 of PI-RADSv2.1, but decreased sensitivity, compared with PI-RADSv2.0, for csPCa in PZ.

Correlation of Likert scores III–V with increasingly worse pathology in radical prostatectomy specimens significant only for men aged <60 or PSAD >0.15, with age <60 as good as PSAD <0.15 at discriminating lower risk in Likert III

Objectives:

This study aimed to compare Likert scores with radical prostatectomy specimens.

Methods:

This study examined 443 men with validated pre-biopsy magnetic resonance imaging results and used cross-tabulation and chi-square significance testing with National Comprehensive Cancer Network risk categories.

Results:

The mean prostate-specific antigen (PSA) was 10, and the mean age was 64 years. Comparing Likert III to Likert V and Likert IV to Likert V, both (each p=0.02) were significantly associated with higher prostate cancer risk groups, but Likert III versus Likert IV was not ( p=0.1). Within the subgroup PSA density (PSAD) <0.15 ( n=140), the correlation of Likert score and final pathological risk group was lost ( p=0.5), but it was not lost within the subgroup PSAD >0.15 ( n=281; p=0.045 III vs. IV only and p=0.055 overall). Within the subgroup age <60 ( n=104), the correlation of Likert score and final pathological risk group was significant ( p=0.006 for III vs. IV and p=0.04 overall), whereas within the subgroup age >60 ( n=339) this significant difference was lost ( p=0.34). Further subgroup analysis within Likert III ( n=86) found that men <60 ( n=22) had neither high-grade (G3 or G4 or G5) nor very high-risk disease. There were only two high-risk cases, both of which were G2T3a (2/22; 10%). In men with Likert III and PSAD <0.15 ( n=31), there were seven high-risk and two very high-risk cases (9/31; 25%). This difference was not significant ( p=0.31)

Conclusion:

With these two findings, we recommend that men <60 with Likert III can be counselled like men with Likert III and PSAD <0.15, that they are unlikely to have unfavourable or high-risk disease and that they may wish to avoid biopsy or treatment.

Level of evidence:

Level 1b.

Detection limits of significant prostate cancer using multiparametric MR and digital rectal examination in men with low serum PSA: Up-date of the Italian Society of Integrated Diagnostic in Urology

Reasons why significant prostate cancer is still missed in early stage were investigated at the 22nd National SIEUN (Italian Society of integrated diagnostic in Urology, Andrology, Nephrology) congress took place from 30th November to 1st December 2020, in virtual modality. Even if multiparametric magnetic resonance (MR) has been introduced in the clinical practice several, limitations are emerging in patient with regular digital rectal examination (DRE) and serum prostate specific antigen (PSA) levels approaching the normal limits. The present paper summarizes highlights observed in those cases where significant prostate cancer may be missed by PSA or imaging and DRE. The issue of multidisciplinary interest had been subdivided and deepened under four main topics: biochemical, clinical, pathological and radiological point of view with a focus on PI-RADS 3 lesions.

Combined Utility of 68Ga-Prostate-specific Membrane Antigen Positron Emission Tomography/Computed Tomography and Multiparametric Magnetic Resonance Imaging in Predicting Prostate Biopsy Pathology

BACKGROUND

⁶⁸Gallium-labelled prostate-specific membrane antigen positron emission tomography (⁶⁸Ga-PSMA-11 PET) is a valuable staging tool, but its utility in characterising primary prostate cancer remains unclear. The maximum standardised uptake value (SUVmax) is a quantification measure of highest radiotracer uptake within PET-avid lesions.

OBJECTIVE

To assess the utility of SUVmax in detecting clinically significant prostate cancer (csPCa) on biopsy alone and in combination with multiparametric magnetic resonance imaging (mpMRI).

DESIGN, SETTING, AND PARTICIPANTS

This was a retrospective analysis of 200 men who underwent ⁶⁸Ga-PSMA-11 PET/CT, mpMRI, and transperineal template prostate biopsy between 2016 and 2018.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The primary and secondary outcomes were detection of grade group (GG) 3-5 and GG 2-5 prostate cancer, respectively. We used the Mann-Whitney U test to compare SUVmax by GG, and calculated sensitivity and specificity for csPCa detection via ⁶⁸Ga-PSMA-11 PET/CT, mpMRI, and both. Multivariable logistic regression analyses were used to identify predictors of csPCa on biopsy.

RESULTS AND LIMITATIONS

The median SUVmax was greater for GG 3-5 tumours (6.40, interquartile range [IQR] 4.47-11.0) than for benign and GG 1-2 tumours (3.14, IQR 2.55-3.91; p <  0.001). The median SUVmax was greater for GG 3 (5.70, IQR 3.68-8.67) than for GG 2 (3.47, IQR 2.70-4.74; p <  0.001). For GG 3-5 disease, sensitivity was 86.5%, 95.9%, and 98.6%, and the negative predictive value (NPV) was 88.4%, 88.5%, and 93.3% using SUVmax ≥4, a Prostate Imaging-Reporting and Data System (PI-RADS) score of 3-5, and both, respectively. This combined model detected more GG 3-5 disease than mpMRI alone (98.6% vs 95.9%; p =  0.04). SUVmax was an independent predictor of csPCa for GG 3-5 disease only (odds ratio 1.27 per unit, 95% confidence interval 1.13-1.45). Our results are limited by the retrospective study design.

CONCLUSIONS

Greater SUVmax on ⁶⁸Ga-PSMA-11 PET/CT is associated with detection of GG 3-5 cancer on biopsy. The combination of PI-RADS score and SUVmax provides higher sensitivity and NPV than either alone. ⁶⁸Ga-PSMA-11 PET/CT may be useful alongside mpMRI in improving risk stratification for localised disease.

PATIENT SUMMARY

The amount of a radioactive tracer taken up in the prostate during a type of scan called PET (positron emission tomography) can predict whether aggressive prostate cancer is likely to be found on biopsy. This may complement the more usual type of scan, MRI (magnetic resonance imaging), used to detect prostate cancer.

The Prostate Health Index aids multi-parametric MRI in diagnosing significant prostate cancer

To evaluate the performance of the Prostate Health Index (PHI) in magnetic resonance imaging-transrectal ultrasound (MRI-TRUS) fusion prostate biopsy for the detection of clinically significant prostate cancer (csPCa). We prospectively enrolled 164 patients with at least one Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) ≥ 3 lesions who underwent MRI-TRUS fusion prostate biopsy. Of the PSA-derived biomarkers, the PHI had the best performance in predicting csPCa (AUC 0.792, CI 0.707–0.877) in patients with PI-RADS 4/5 lesions. Furthermore, the predictive power of PHI was even higher in the patients with PI-RADS 3 lesions (AUC 0.884, CI 0.792–0.976). To minimize missing csPCa, we used a PHI cutoff of 27 and 7.4% of patients with PI-RADS 4/5 lesions could have avoided a biopsy. At this level, 2.0% of cases with csPCa would have been missed, with sensitivity and NPV rates of 98.0% and 87.5%, respectively. However, the subgroup of PI-RADS 3 was too small to define the optimal PHI cutoff. PHI was the best PSA-derived biomarker to predict csPCa in MRI-TRUS fusion prostate biopsies in men with PI-RADS ≥ 3 lesions, especially for the patients with PI-RADS 3 lesions who gained the most value.

The comparative effectiveness of mpMRI and MRI-guided biopsy vs regular biopsy in a population-based PSA testing: a modeling study

The benefit of prostate cancer screening is counterbalanced by the risk of overdiagnosis and overtreatment. The use of a multi-parametric magnetic resonance imaging (mpMRI) test after a positive prostate-specific antigen (PSA) test followed by magnetic resonance imaging-guided biopsy (MRIGB) may reduce these harms. The aim of this study was to determine the effects of mpMRI and MRIGB vs the regular screening pathway in a population-based prostate cancer screening setting. A micro-simulation model was used to predict the effects of regular PSA screening (men with elevated PSA followed by TRUSGB) and MRI based screening (men with elevated PSA followed by mpMRI and MRIGB). We predicted reduction of overdiagnosis, harm-benefit ratio (overdiagnosis per cancer death averted), reduction in number of biopsies, detection of clinically significant cancer, prostate cancer death averted, life-years gained (LYG), and quality adjusted life years (QALYs) gained for both strategies. A univariate sensitivity analysis and threshold analysis were performed to assess uncertainty around the test sensitivity parameters used in the MRI strategy.In the MRI pathway, we predicted a 43% reduction in the risk of overdiagnosis, compared to the regular pathway. Similarly a lower harm-benefit ratio (overdiagnosis per cancer death averted) was predicted for this strategy compared to the regular screening pathway (1.0 vs 1.8 respectively). Prostate cancer mortality reduction, LY and QALYs gained were also slightly increased in the MRI pathway than the regular screening pathway. Furthermore, 30% of men with a positive PSA test could avoid a biopsy as compared to the regular screening pathway. Compared to regular PSA screening, the use of mpMRI as a triage test followed by MRIGB can substantially reduce the risk of overdiagnosis and improve the harm-benefit balance, while maximizing prostate cancer mortality reduction and QALYs gained.

Effect of lesion diameter and prostate volume on prostate cancer detection rate of magnetic resonance imaging: Transrectal-ultrasonography-guided fusion biopsies using cognitive targeting

OBJECTIVE

This study aimed to evaluate the effect of prostate volume and lesion size on the clinically significant prostate cancer (csPCa) detection rates of transrectal ultrasonography (TRUS)-guided prostate biopsies, performed by a cognitive targeting method for sampling peripheral zone lesions.

MATERIAL AND METHODS

We retrospectively enrolled 219 consecutive patients, who underwent multiparametric magnetic resonance imaging with a 3-T scanner and had peripheral zone lesions suspected for prostate cancer. All of these patients underwent combined cognitive targeted biopsy of suspicious lesions and TRUS-guided systematic biopsy. The detection rates of csPCa according to different lesion diameters (<5 mm, 5-9.9 mm, and ≥10 mm) and prostate volumes (<30 mL, 30-49.9 mL, 50-79.9 mL, and ≥80 mL) were calculated per lesion basis. In addition, subgroup analysis of csPCa detection rates was performed according to Prostate Imaging Reporting and Data System scores of lesions.

RESULTS

The csPCa detection rates according to lesion diameters <5 mm, 5-9.9 mm, and ≥10 mm were 4%, 9.8%, and 33.1%, respectively, and were significantly lower for lesions <10 mm (p<0.001). The csPCa detection rates were 61.5%, 24.1%, 16.2%, and 6.9%, respectively, for prostate volumes <30 mL, 30-49.9 mL, 50-79.9 mL, and ≥80 mL, and were significantly higher for prostate volumes <30 mL (p<0.001).

CONCLUSIONS

Clinicians should be very careful when they prefer cognitive targeted prostatic biopsy in patients with periferal zone lesions less than 10 mm and with prostate volumes greater than 30 mL, because of significantly low csPCa detection rates.

Histopathological Ratios to Predict Gleason Score Agreement between Biopsy and Radical Prostatectomy

Biopsy proven Gleason score is essential to decide treatment modalities for prostate cancer, either surgical (radical prostatectomy) or non-surgical (active surveillance, watchful waiting, radiation therapy and hormone therapy). Several studies indicated that biopsy proven Gleason score may underestimate Gleason score at radical prostatectomy, hence we aimed to calculate the minimum length of biopsy cores needed to have Gleason score agreement. We evaluated 115 prostate cancer patients who underwent multiparametric magnetic resonance/transperineal ultrasonography fusion biopsy and subsequently, radical prostatectomy. Biopsy proven Gleason score was consistent with Gleason score at subsequent radical prostatectomy in 82.6% of patients, while in 17.4% of patients, Gleason score was higher at radical prostatectomy. Gleason score agreement showed a strong direct association with a ratio > 0.05 between the total volume of biopsies performed in tumor area and the volume of the corresponding tumor at radical prostatectomy. A significant association was also found with a ratio ≥ 0.0034 between the tumor volume in the biopsy and the volume of the corresponding tumor at radical prostatectomy and with a ratio ≥ 0.086 between the tumor volume in the biopsy and the total volume of biopsies performed in the tumor area. These results could be exploited to calculate the minimum length of biopsy cores needed to have a correct Gleason score estimation and therefore be used in fusion targeted biopsies with volume adjustments.

The utility of in-bore multiparametric magnetic resonance-guided biopsy in men with negative multiparametric magnetic resonance-ultrasound software-based fusion targeted biopsy

OBJECTIVES

To evaluate the utility of in-bore multiparametric magnetic resonance-guided biopsy of the prostate (IB) in patients with visible lesion/s and previous negative software-based multiparametric magnetic resonance imaging/ultrasonography fusion-targeted biopsy of the prostate (FTB).

PATIENTS AND METHODS

We retrospectively analysed prospectively maintained database including consecutive men undergoing IB from March 2013 to October 2017 in 2 European centres expert in this procedure. We selected men with the following criteria: No previous treatment for prostate cancer (CaP), multiparametric magnetic resonance imaging (mpMRI) lesion(s) PIRADS score ≥ 3, FTB showing no clinically significant cancer (csCaP), and subsequent IB. Patient's characteristics, mpMRI findings, biopsy technique, and histopathological results were extracted. The primary outcome was to determine the detection rate of csCaP, defined as any Gleason pattern ≥ 4. A multivariable analysis was performed to identify predictors of positive findings at IB.

RESULTS

Fifty-three men were included. Median age was 68 years (interquartile range [IQR] 64-68), median Prostate-Specific Antigen (PSA) was 7.6 ng/ml (IQR 5.2-10.9), and median prostate volume was 59 ml (IQR 44-84). Fifty-six lesions with PIRADS score 3 in 9 cases (16%), 4 in 30 cases (54%), and 5 in 17 cases (30%) were detected. FTB was performed in all cases using a transrectal approach with 3 different platforms (Toshiba, Koelis, and Artemis). Median time between FTB and IB was 3 months (IQR 1-7). A median of 2 cores per lesion were collected with IB (IQR 2-3). No cancer, clinically insignificant and clinically significant cancer were found in 33 (59%), 9 (16%), and 14 (25%) targeted lesions, respectively. Median maximum cancer core length and maximum positive percentage were 9 mm (3-13) and 55% (21%-80%). The only predictor of csCaP on IB was prostate volume (P = 0.026) with an ideal cut-off at 70 ml.

CONCLUSION

One in 4 patients with previous negative FTB, IB was able to detect csCaP. According to this study, IB would be of particularly useful in patients with large glands.

Equivocal PI-RADS Three Lesions on Prostate Magnetic Resonance Imaging: Risk Stratification Strategies to Avoid MRI-Targeted Biopsies

We aimed to investigate the relation between largest lesion diameter, prostate-specific antigen density (PSA-D), age, and the detection of clinically significant prostate cancer (csPCa) using first-time targeted biopsy (TBx) in men with Prostate Imaging-Reporting and Data System (PI-RADS) 3 index lesions. A total of 292 men (2013-2019) from two referral centers were included. A multivariable logistic regression analysis was performed. The discrimination and clinical utility of the built model was assessed by the area under the receiver operation curve (AUC) and decision curve analysis, respectively. A higher PSA-D and higher age were significantly related to a higher risk of detecting csPCa, while the largest index lesion diameter was not. The discrimination of the model was 0.80 (95% CI 0.73-0.87). When compared to a biopsy-all strategy, decision curve analysis showed a higher net benefit at threshold probabilities of ≥2%. Accepting a missing ≤5% of csPCa diagnoses, a risk-based approach would result in 34% of TBx sessions and 23% of low-risk PCa diagnoses being avoided. In men with PI-RADS 3 index lesions scheduled for first-time TBx, the balance between the number of TBx sessions, the detection of low-risk PCa, and the detection of csPCa does not warrant a biopsy-all strategy. To minimize the risk of missing the diagnosis of csPCa but acknowledging the need of avoiding unnecessary TBx sessions and overdiagnosis, a risk-based approach is advisable.

Improving Prostate Cancer (PCa) Classification Performance by Using Three-Player Minimax Game to Reduce Data Source Heterogeneity

PCa is a disease with a wide range of tissue patterns and this adds to its classification difficulty. Moreover, the data source heterogeneity, i.e. inconsistent data collected using different machines, under different conditions, by different operators, from patients of different ethnic groups, etc., further hinders the effectiveness of training a generalized PCa classifier. In this paper, for the first time, a Generative Adversarial Network (GAN)-based three-player minimax game framework is used to tackle data source heterogeneity and to improve PCa classification performance, where a proposed modified U-Net is used as the encoder. Our dataset consists of novel high-frequency ExactVu ultrasound (US) data collected from 693 patients at five data centers. Gleason Scores (GSs) are assigned to the 12 prostatic regions of each patient. Two classification tasks: benign vs. malignant and low- vs. high-grade, are conducted and the classification results of different prostatic regions are compared. For benign vs. malignant classification, the three-player minimax game framework achieves an Area Under the Receiver Operating Characteristic (AUC) of 93.4%, a sensitivity of 95.1% and a specificity of 87.7%, respectively, representing significant improvements of 5.0%, 3.9%, and 6.0% compared to those of using heterogeneous data, which confirms its effectiveness in terms of PCa classification.

Diagnostic yields in patients with suspected prostate cancer undergoing MRI as the first-line investigation in routine practice

AIM

To document cancer yields of magnetic resonance imaging (MRI)-directed biopsies in men with suspected prostate cancer referred to secondary care.

MATERIALS AND METHODS

Men with suspected cancer undergoing multiparametric prostate MRI as the first-line investigation were included in the present study. Systematic transrectal prostate biopsies with/without cognitive targeted biopsies were performed. Diagnostic yields of International Society of Urological Pathology (ISUP) ≥2 cancers by the Prostate Imaging Reporting and Data System (PI-RADS) category were recorded. Impacts of prostate-specific antigen (PSA) density on biopsy results and yields of non-targeted biopsies in MRI non-suspicious prostate sextants assessed.

RESULTS

Of 262 men (90.5% biopsy naive), 86 (33%) MRI examinations were negative (PI-RADS 1-2) and 176 (67%) positive (PI-RADS 3: 8%; PI-RADS 4: 21%; PI-RADS 5: 38%). Two hundred and thirteen of 262 patients underwent a biopsy. ISUP ≥2 cancer detection rates were 8% (5/61) for PI-RADS 1-2, 18% (3/17) for PI-RADS 3, 49% (22/45) for PI-RADS 4, and 80% (72/90) for PI-RADS 5. Proportions of ISUP ≥2 increased with higher PSA densities in positive patients (%ISUP ≥2 for PSA density groups <0.12, 0.12 to <0.15 and ≥ 0.15 was 0%, 0%, 25% for PI-RADS 3, 21%, 33%, 68% for PI-RADS 4 and 40%, 83%, 89% for PI-RADS 5 respectively). ISUP ≥2 cancers were twice as likely in tumour adjacent sextants (52% versus 24%), without upgrading of gland level histology from insignificant to clinically significant prostate cancer by the sampling of normal-appearing tumour non-adjacent sextants.

CONCLUSIONS

One third of men can avoid biopsy after negative MRI. Cancer detection rates increase with PSA density values within positive MRI suspicion categories. Sampling normal-appearing tumour non-adjacent sextants may be unnecessary for whole-gland therapy.

Negative Predictive Value of Multiparametric Magnetic Resonance Imaging in the Detection of Clinically Significant Prostate Cancer in the Prostate Imaging Reporting and Data System Era: A Systematic Review and Meta-analysis

CONTEXT

Prebiopsy multiparametric magnetic resonance imaging (mpMRI) is increasingly used in prostate cancer diagnosis. The reported negative predictive value (NPV) of mpMRI is used by some clinicians to aid in decision making about whether or not to proceed to biopsy.

OBJECTIVE

We aim to perform a contemporary systematic review that reflects the latest literature on optimal mpMRI techniques and scoring systems to update the NPV of mpMRI for clinically significant prostate cancer (csPCa).

EVIDENCE ACQUISITION

We conducted a systematic literature search and included studies from 2016 to September 4, 2019, which assessed the NPV of mpMRI for csPCa, using biopsy or clinical follow-up as the reference standard. To ensure that studies included in this analysis reflect contemporary practice, we only included studies in which mpMRI findings were interpreted according to the Prostate Imaging Reporting and Data System (PIRADS) or similar Likert grading system. We define negative mpMRI as either (1) PIRADS/Likert 1-2 or (2) PIRADS/Likert 1-3; csPCa was defined as either (1) Gleason grade group ≥2 or (2) Gleason grade group ≥3. We calculated NPV separately for each combination of negative mpMRI and csPCa.

EVIDENCE SYNTHESIS

A total of 42 studies with 7321 patients met our inclusion criteria and were included for analysis. Using definition (1) for negative mpMRI and csPCa, the pooled NPV for biopsy-naïve men was 90.8% (95% confidence interval [CI] 88.1-93.1%). When defining csPCa using definition (2), the NPV for csPCa was 97.1% (95% CI 94.9-98.7%). Calculation of the pooled NPV using definition (2) for negative mpMRI and definition (1) for csPCa yielded the following: 86.8% (95% CI 80.1-92.4%). Using definition (2) for both negative mpMRI and csPCa, the pooled NPV from two studies was 96.1% (95% CI 93.4-98.2%).

CONCLUSIONS

Multiparametric MRI of the prostate is generally an accurate test for ruling out csPCa. However, we observed heterogeneity in the NPV estimates, and local institutional data should form the basis of decision making if available.

PATIENT SUMMARY

The negative predictive values should assist in decision making for clinicians considering not proceeding to biopsy in men with elevated age-specific prostate-specific antigen and multiparametric magnetic resonance imaging reported as negative (or equivocal) on Prostate Imaging Reporting and Data System/Likert scoring. Some 7-10% of men, depending on the setting, will miss a diagnosis of clinically significant cancer if they do not proceed to biopsy. Given the institutional variation in results, it is of upmost importance to base decision making on local data if available.