The Use of Multiparametric Magnetic Resonance Imaging for Follow-up of Patients Included in Active Surveillance Protocol. Can PSA Density Discriminate Patients at Different Risk of Reclassification?

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Medium-term follow up of active surveillance for early prostate cancer at a non-academic institution

OBJECTIVES

To report oncological outcomes of active surveillance (AS) at a single non-academic institution adopting the standardised Prostate Cancer Research International Active Surveillance (PRIAS) protocol.

PATIENTS AND METHODS

Competing risk analyses estimated the incidence of overall mortality, metastases, conversion to treatment, and grade reclassification. The incidence of reclassification and adverse pathological findings at radical prostatectomy were compared between patients fulfilling all PRIAS inclusion criteria vs those not fulfilling at least one.

RESULTS

We analysed 341 men with Grade Group 1 prostate cancer (PCa) followed on AS between 2010 and 2022. There were no PCa deaths, two patients developed distant metastases and were alive at the end of the study period. The 10-year cumulative incidence of metastases was 1.9% (95% confidence interval [CI] 0.33-6.4%). A total of 111 men were reclassified, and 127 underwent definitive treatment. Men not fulfilling at least one PRIAS inclusion criteria (n = 43) had a higher incidence of reclassification (subdistribution hazards ratio 1.73, 95% CI 1.07-2.81; P = 0.03), but similar rates of adverse pathological findings at radical prostatectomy.

CONCLUSION

Metastases in men on AS at a non-academic institution are as rare as those reported in established international cohorts. Men followed without stringent inclusion criteria should be counselled about the higher incidence of reclassification and reassured they can expect rates of adverse pathological findings comparable to those fulfilling all criteria. Therefore, AS should be proposed to all men with low-grade PCa regardless of whether they are followed at academic institutions or smaller community hospitals.

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.

mpMRI Interpretation in Active Surveillance for Prostate Cancer-An overview of the PRECISE score

Active surveillance (AS) is now included in all major guidelines for patients with low-risk PCa and selected patients with intermediate-risk PCa. Several studies have highlighted the potential benefit of multiparametric magnetic resonance imaging (mpMRI) in AS and it has been adopted in some guidelines. However, uncertainty remains about whether serial mpMRI can help to safely reduce the number of required repeat biopsies under AS. In 2017, the European School of Oncology initiated the Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) panel which proposed the PRECISE scoring system to assess the likelihood of radiological tumor progression on serial mpMRI. The PRECISE scoring system remains the only major system evaluated in multiple publications. In this review article, we discuss the current body of literature investigating the application of PRECISE as it is not as yet an established standard in mpMRI reporting. We delineate the strengths of PRECISE and its potential added value. Also, we underline potential weaknesses of the PRECISE scoring system, which might be tackled in future versions to further increase its value in AS.

Radiomics in PI-RADS 3 Multiparametric MRI for Prostate Cancer Identification: Literature Models Re-Implementation and Proposal of a Clinical-Radiological Model

PI-RADS 3 prostate lesions clinical management is still debated, with high variability among different centers. Identifying clinically significant tumors among PI-RADS 3 is crucial. Radiomics applied to multiparametric MR (mpMR) seems promising. Nevertheless, reproducibility assessment by external validation is required. We retrospectively included all patients with at least one PI-RADS 3 lesion (PI-RADS v2.1) detected on a 3T prostate MRI scan at our Institution (June 2016-March 2021). An MRI-targeted biopsy was used as ground truth. We assessed reproducible mpMRI radiomic features found in the literature. Then, we proposed a new model combining PSA density and two radiomic features (texture regularity (T2) and size zone heterogeneity (ADC)). All models were trained/assessed through 100-repetitions 5-fold cross-validation. Eighty patients were included (26 with GS ≥ 7). In total, 9/20 T2 features (Hector's model) and 1 T2 feature (Jin's model) significantly correlated to biopsy on our dataset. PSA density alone predicted clinically significant tumors (sensitivity: 66%; specificity: 71%). Our model obtained a sensitivity of 80% and a specificity of 76%. Standard-compliant works with detailed methodologies achieve comparable radiomic feature sets. Therefore, efforts to facilitate reproducibility are needed, while complex models and imaging protocols seem not, since our model combining PSA density and two radiomic features from routinely performed sequences appeared to differentiate clinically significant cancers.

Confirmatory transperineal saturation prostate biopsy combined with mpMRI decrease the reclassification rate in men enrolled in Active Surveillance: Our experience in 100 men submitted to eight-years scheduled biopsy

Introduction: The reclassification rate for clinically significant prostate cancer (csPCa) in men enrolled in Active Surveillance (AS) as been prospective-ly evaluated. Patients and methods: One hundred patients with very low risk PCa underwent after 8 years a scheduled transperineal prostate biopsy (SPBx = 20 cores) combined with additionalmpMRI/TRUS fusion biopsies (4 cores) of lesions PI-RADS scores ≥ 3. All the patients, after initial diagnosis, previously had mpMRI evaluation combined with transperineal saturation prostate biopsy (confirmatory and 3-year scheduled biopsy). Risk reclassification at repeat biopsy triggering the recommen-dation for active treatment was defined as over 3 or more than 10% of positive cores, Gleason score > 6/ISUP Grade Group ≥ 2, greatest percentage of cancer (GPC) > 50%.Results: Multiparametric MRI was suspicious (PI-RADS ≥ 3) in 30 of 100 cases (30.0%); 70 (70.0%) vs. 20 (20.0%) vs. 10(10.0%) patients had a PI-RADS score ≤ 2 vs. 3 vs. 4, respec-tively. Two (2.0%) patients with PI-RADS score 3 and 4 were upgraded (ISUP Grade Group 2); SPBx and MRI/TRUS fusion biopsy diagnosed 100% and 0% of csPCa, respectively. Conclusions: Transperineal SPBx combined with mpMRI at ini-tial confirmatory biopsy allow to select an high number of men at very low risk of reclassification during the AS follow up (2.0%of the cases at 8 years from diagnosis); these data could be use-ful to reduce the number of scheduled repeated prostate biopsy during the AS follow up.

Targeted prostate biopsy: 68Ga-PSMA PET/CT vs. mpMRI in the diagnosis of prostate cancer

Introduction: To evaluate the diagnostic accuracy of 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomog-raphy (PET/CT) vs. multiparametric magnetic resonance imag-ing (mpMRI) targeted biopsy (TPBx) in the diagnosis of clinical-ly significant prostate cancer (csPCa: Grade Group ≥ 2). Materials and methods: From January 2021 to June 2022, 100 patients (median age: 66 years) with negative digital rectal examination underwent transperineal prostate biopsy for abnor-mal PSA values (median 7.5 ng/ml). Before prostate biopsy, all patients underwent mpMRI and 68Ga-PET/CT examinations and mpMRI (PI-RADS version 2 ≥ 3) or 68Ga-PET/CT index lesions suspicious for cancer (SUVmax > 5 g/ml) underwent cognitive targeted cores (mpMRI-TPBx and PSMA-TPBx: four cores) com-bined with extended systematic prostate biopsy (eSPBx: median 18 cores). The procedure was performed transperineally using a tru-cut 18-gauge needle under sedation and antibiotic prophy-laxis. Results: PCa was found in 58/100 (58.0%) men; in detail, 44/58 (75.9%) were csPCa; mpMRI and 68Ga-PSMA showed 66/100 (66%) and 62/100 (60%) lesions suspicious for PCa, respective-ly. 68Ga-PSMA-TPBx vs. mpMRI-TPBx vs. eSPBx diagnosed 42 (95.4%) vs. 36 (81.8%) vs. 30 (68.2%) csPCa, respectively; mpMRI-TPBx vs. 68Ga-PSMA-TPBx showed a diagnostic accuracy of 76.9% vs. 84.9% in diagnosing csPCa. Conclusions: 68GaPSMA PET/CT TPBx demonstrated good accuracy in the diagnosis of csPCa, which was not inferior to mpMRI TPBx (84.9% vs. 76.9%) improving the detection rate for cancer of systematic biopsy.

Could 68Ga-PSMA PET/CT Evaluation Reduce the Number of Scheduled Prostate Biopsies in Men Enrolled in Active Surveillance Protocols?

Background: To evaluate the accuracy of 68Ga-prostate specific membrane antigen (PSMA) PET/CT in the diagnosis of clinically significant prostate cancer (csPCa) (Grade Group > 2) in men enrolled in Active Surveillance (AS) protocol. Methods: From May 2013 to May 2021, 173 men with very low-risk PCa were enrolled in an AS protocol study. During the follow-up, 38/173 (22%) men were upgraded and 8/173 (4.6%) decided to leave the AS protocol. After four years from confirmatory biopsy (range: 48−52 months), 30/127 (23.6%) consecutive patients were submitted to mpMRI and 68Ga-PSMA PET/CT scan before scheduled repeated biopsy. All the mpMRI (PI-RADS > 3) and 68Ga-PET/TC standardised uptake value (SUVmax) > 5 g/mL index lesions underwent targeted cores (mpMRI-TPBx and PSMA-TPBx) combined with transperineal saturation prostate biopsy (SPBx: median 20 cores). Results: mpMRI and 68Ga-PSMA PET/CT showed 14/30 (46.6%) and 6/30 (20%) lesions suspicious for PCa. In 2/30 (6.6%) men, a csPCa was found; 68Ga-PSMA-TPBx vs. mpMRI-TPBx vs. SPBx diagnosed 1/2 (50%) vs. 1/2 (50%) vs. 2/2 (100%) csPCa, respectively. In detail, mpMRI and 68Ga-PSMA PET/TC demonstrated 13/30 (43.3%) vs. 5/30 (16.7%) false positive and 1 (50%) vs. 1 (50%) false negative results. Conclusion: 68Ga-PSMA PET/CT did not improve the detection for csPCa of SPBx but would have spared 24/30 (80%) scheduled biopsies showing a lower false positive rate in comparison with mpMRI (20% vs. 43.3%) and a negative predictive value of 85.7% vs. 57.1%, respectively.

PI-RADS v2.1 Combined With Prostate-Specific Antigen Density for Detection of Prostate Cancer in Peripheral Zone

Purpose

To evaluate the diagnostic performance of combining the Prostate Imaging Reporting and Data System (PI-RADS) scoring system v2.1 with prostate-specific antigen density (PSAD) to detect prostate cancer (PCa).

Methods

A total of 266 participants with suspicion of PCa underwent multiparametric magnetic resonance imaging (mpMRI) in our hospital, after at least 4 weeks all patients underwent subsequent systematic transrectal ultrasound (TRUS)-guided biopsy or MRI-TRUS fusion targeted biopsy. All mpMRI images were scored in accordance with the PI-RADS v2.1, and univariate and multivariate logistic regression analyses were performed to determine significant predictors of PCa.

Results

A total of 119 patients were diagnosed with PCa in the biopsy, of them 101 patients were diagnosed with clinically significant PCa. The multivariate analysis revealed that PI-RADS v2.1 and PSAD were independent predictors for PCa. For peripheral zone (PZ), the area under the ROC curve (AUC) for the combination of PI-RADS score and PSAD was 0.90 (95% CI 0.83-0.96), which is significantly superior to using PI-RADS score (0.85, 95% CI 0.78-0.93, P=0.031) and PSAD alone (0.83, 95% CI 0.75-0.90, P=0.037). For transition zone (TZ), however, the combination model was not significantly superior to PI-RADS alone, with AUC of 0.94 (95% CI 0.89-0.99) vs. 0.93 (95% CI 0.88-0.97, P=0.186).

Conclusion

The combination of PI-RADS v2.1 with PSAD could significantly improve the diagnostic performance of PCa in PZ. Nevertheless, no significant improvement was observed regarding PCa in TZ.

Utility of Clinical-Radiomic Model to Identify Clinically Significant Prostate Cancer in Biparametric MRI PI-RADS V2.1 Category 3 Lesions

Purpose

To determine the predictive performance of the integrated model based on clinical factors and radiomic features for the accurate identification of clinically significant prostate cancer (csPCa) among Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions.

Materials and Methods

A retrospective study of 103 patients with PI-RADS 3 lesions who underwent pre-operative 3.0-T MRI was performed. Patients were randomly divided into the training set and the testing set at a ratio of 7:3. Radiomic features were extracted from axial T2WI, diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) images of each patient. The minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) feature selection methods were used to identify the radiomic features and construct a radiomic model for csPCa identification. Moreover, multivariable logistic regression analysis was used to integrate the clinical factors with radiomic feature model to further improve the accuracy of csPCa identification, and the two are presented in the form of normogram. The performance of the integrated model was compared with radiomic model and clinical model on testing set.

Results

A total of four radiomic features were selected and used for radiomic model construction producing a radiomic score (Radscore). Radscore was significantly different between the csPCa and the non-csPCa patients (training set: p < 0.001; testing set: p = 0.035). Multivariable logistic regression analysis showed that age and PSA could be used as independent predictors for csPCa identification. The clinical–radiomic model produced the receiver operating characteristic (ROC) curve (AUC) in the testing set was 0.88 (95%CI, 0.75–1.00), which was similar to clinical model (AUC = 0.85; 95%CI, 0.52–0.90) (p = 0.048) and higher than the radiomic model (AUC = 0.71; 95%CI, 0.68–1.00) (p < 0.001). The decision curve analysis implies that the clinical–radiomic model could be beneficial in identifying csPCa among PI-RADS 3 lesions.

Conclusion

The clinical–radiomic model could effectively identify csPCa among biparametric PI-RADS 3 lesions and thus could help avoid unnecessary biopsy and improve the life quality of patients.

Role of multi-parametric magnetic resonance imaging fusion biopsy in active surveillance of prostate cancer: a systematic review

Background:

Our goal is to review current literature regarding the role of multi-parametric magnetic resonance imaging (mpMRI) in the active surveillance (AS) of prostate cancer (PCa) and identify trends in rate of reclassification of risk category, performance of fusion biopsy (FB) versus systematic biopsy (SB), and progression-free survival.

Methods:

We performed a comprehensive literature search in PubMed and identified 121 articles. A narrative summary was performed.

Results:

Thirty-two articles were chosen to be featured in this review. SB and FB are complementary in detecting higher-grade disease in follow-up. While FB was more likely than SB to detect clinically significant disease, FB missed 6.4–11% of clinically significant disease. Imaging factors that predicted upgrading include number of lesions on magnetic resonance imaging (MRI), lesion density, and MRI suspicion level.

Conclusion:

Incorporating mpMRI FB in conjunction with SB should be part of contemporary AS protocols. mpMRI should additionally be used routinely for follow-up; however, mpMRI is not currently sensitive enough in detecting disease progression to replace biopsy in the surveillance protocol.

Identifying Risk Factors for MRI-Invisible Prostate Cancer in Patients Undergoing Transperineal Saturation Biopsy

Purpose

Prostatic multi-parametric magnetic resonance imaging (mpMRI) has markedly improved the assessment of men with suspected prostate cancer (PCa). Nevertheless, as mpMRI exhibits a high negative predictive value, a negative MRI may represent a diagnostic dilemma. The aim of this study was to evaluate the incidence of positive transperineal saturation biopsy in men who have negative mpMRI and to analyse the factors associated with positive biopsy in this scenario.

Patients and Methods

A retrospective study of men with normal mpMRI and suspicion of PCa who underwent saturation biopsy (≥20 cores) was carried out. A total of 580 patients underwent transperineal MRI/transrectal ultrasound fusion targeted biopsies or saturation prostate biopsies from January 2017 to September 2020. Of them, 73 had a pre-biopsy negative mpMRI (with Prostate Imaging – Reporting and Data System, PI-RADS, ≤2) and were included in this study. Demographics, clinical characteristics, data regarding biopsy results and potential predictive factors of positive saturation biopsy were collected. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for MRI-invisible PCa.

Results

The detection rate of PCa with saturation biopsy in patients with negative MRI was 34/73 (46.58%). Out of 34 MRI-invisible prostate cancers detected, 12 (35.29%) were clinically significant PCa (csPCa) forms. Regarding factors of positive biopsy, in univariate analysis, the use of 5-alpha reductase inhibitors and free:total prostate-specific antigen (PSA) ratio were associated with the result of the saturation biopsy. In multivariate analysis, only an unfavourable free:total PSA ratio remained a risk factor (OR 11.03, CI95% 1.93–63.15, p=0.01). Furthermore, multivariate logistic analysis demonstrated that prostate volume >50mL significantly predicts the absence of csPCa on saturation biopsy (OR 0.11, 95% CI 0.01–0.94, p=0.04).

Conclusion

A free:total PSA ratio <20% is a risk factor for MRI-invisible PCa. Saturation biopsy could be considered in patients with suspected PCa, despite having a negative MRI.

[PI-RADS 2.1 and structured reporting of magnetic resonance imaging of the prostate]

Klinisches/methodisches Problem

Die Identifikation klinisch signifikanter Prostatakarzinome bei gleichzeitigem Vermeiden einer Überdiagnostik niedrigmaligner Tumoren stellt eine Herausforderung in der klinischen Routine dar.

Radiologische Standardverfahren

Die gemäß PI-RADS-Richtlinien (Prostate Imaging Reporting and Data System Guidelines) akquirierte und interpretierte multiparametrische Magnetresonanztomographie (MRT) der Prostata ist als klinischer Standard bei Urologen und Radiologen akzeptiert.

Methodische Innovationen

Die PI-RADS-Richtlinien sind neu auf Version 2.1 aktualisiert worden und beinhalten neben präzisierten technischen Anforderungen einzelne Änderungen in der Läsionsbewertung.

Leistungsfähigkeit

Die PI-RADS-Richtlinien haben entscheidende Bedeutung in der Standardisierung der multiparametrischen MRT der Prostata erlangt und bieten Vorlagen zur strukturierten Befundung, was die Kommunikation mit dem Zuweiser erleichtert.

Bewertung

Die nun auf Version 2.1 aktualisierten Richtlinien stellen eine Verfeinerung der verbreiteten Version 2.0 dar. Dabei wurden viele Aspekte der Befundung präzisiert, einige vorbekannte Limitationen bleiben jedoch bestehen und erfordern die weitere Verbesserung der Richtlinien in kommenden Versionen.

mpMRI PI-RADS score 3 lesions diagnosed by reference vs affiliated radiological centers: Our experience in 950 cases

INTRODUCTION

The detection rate for clinically significant prostate cancer (csPCa) in men with mpMRI PI-RADS score 3 diagnosed by affiliated radiology centers vs radiological reference center was evaluated.

MATERIALS AND METHODS

From January 2017 to December 2020, 950 men (median age 64 years) underwent mpMRI for abnormal PSA values (median 6.3 ng/ml). Among the 950 patients who underwent mpMRI 500 were evaluated by a reference center and 450 by outpatient radiological affiliated centers. All the mpMRI index lesions characterized by a PI-RADS 3 underwent targeted cores combined with extended prostate biopsy. Two radiologists of the radiological reference center revised all the mpMRI lesions 3.

RESULTS

Overall, 361/950 (38%) patients had a mpMRI lesion PI-RADS score 3: 120/500 cases (24%) vs 241/450 cases (53.5%) were diagnosed by reference vs affiliated radiological centers. The detection rate for cT1c csPCa was equal to 26.7% (35/120 cases) vs 16.6% (40/241 cases) in men with PI-RADS 3 lesions diagnosed in the reference vs the affiliated radiological centers (p < 0.05). Among the 241 PI-RADS score 3 lesions diagnosed by affiliated radiological centers 86/241 (35.7%) and 36/241 (15%) were downgraded (PI-RADS scores < 3) and upgraded (PI-RADS score 4) by the dedicated radiologists of the reference center.

CONCLUSIONS

In our series, about 35% and 15% of PI-RADS score 3 lesions diagnosed by affiliated radiological centers were downgraded and upgraded when revised by experencied radiologists, therefore a second opinion is mandatory especially in men enrolled in active surveillance protocols in whom mpMRI is recommended to reduce the number of scheduled repeated prostate biopsies.

Improvement of PI-RADS-dependent prostate cancer classification by quantitative image assessment using radiomics or mean ADC

Background Currently, interpretation of prostate MRI is performed qualitatively. Quantitative assessment of the mean apparent diffusion coefficient (mADC) is promising to improve diagnostic accuracy while radiomic machine learning (RML) allows to probe complex parameter spaces to identify the most promising multi-parametric models. We have previously developed quantitative RML and ADC classifiers for prediction of clinically significant prostate cancer (sPC) from prostate MRI, however these have not been combined with radiologist PI-RADS assessment. Purpose To propose and evaluate diagnostic algorithms combining quantitative ADC or RML and qualitative PI-RADS assessment for prediction of sPC. Methods and population The previously published quantitative models (RML and mADC) were utilized to construct four algorithms: 1) Down(ADC) and 2) Down(RML): clinically detected PI-RADS positive prostate lesions (defined as either PI-RADS≥3 or ≥4) were downgraded to MRI negative upon negative quantitative assessment; and 3) Up(ADC) and 4) Up(RML): MRI-negative lesions were upgraded to MRI-positive upon positive assessment of quantitative parameters. Analyses were performed at the individual lesion level and the patient level in 133 consecutive patients with suspicion for clinically significant prostate cancer (sPC, International Society of Urological Pathology (ISUP) grade group≥2), the test set subcohort of a previously published patient population. McNemar test was used to compare differences in sensitivity, specificity and accuracy. Differences between lesions of different prostate zones were assessed using ANOVA. Reduction in false positive assessments was assessed as ratios. Results Compared to clinical assessment at the PI-RADS≥4 cut-off alone, algorithms Down(ADC/RML) improved specificity from 43% to 65% (p = 0.001)/62% (p = 0.003), while sensitivity did not change significantly at 89% compared to 87% (p = 1.0)/89% (unchanged) on the patient level. Reduction of false positive lesions was 50% [26/52] in the PZ and 53% [15/28] in the TZ. Algorithms Up(ADC/RML) led, on a patient basis, to an unfavorable loss of specificity from 43% to 30% (p = 0.039)/32% (p = 0.106), with insignificant increase of sensitivity from 89% to 96%/96% (both p = 1.0). Compared to clinical assessment at the PI-RADS≥3 cut-off alone, similar results were observed for Down(ADC) with significantly increased specificity from 2% to 23% (p < 0.001) and unchanged sensitivity on the lesion level; patient level specificity increased only non-significantly. Conclusion Downgrading PI-RADS≥3 and ≥ 4 lesions based on quantitative mADC measurements or RML classifiers can increase diagnostic accuracy by enhancing specificity and preserving sensitivity for detection of sPC and reduce false positives.

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.

MRI/US fusion prostate biopsy in men on active surveillance: Our experience

AIM

The upgrading or staging in men with prostate cancer (PCA) undergoing active surveillance (AS), defined as Gleason score (GS) ≥ 3+4 or more than 2 area with cancer, was investigated in our experience using the software-based fusion biopsy (FB).

METHODS

We selected from our database, composed of 620 biopsies, only men on AS according to criteria of John Hopkins Protocol (T1c, < 3 positive cores, GS = 3+3 = 6). Monitoring consisted of PSA measurement every 3 months, a clinical examination every 6 months, confirmatory FB within 6 months and then annual FB in all men. The suspicious MRI lesions were scored according to the Prostate Imaging Reporting and Data System (PI-RADS) classification version 2. FB were performed with a transrectal elastic free-hand fusion platform. The overall and clinically significant cancer detection rate was reported. Secondary, the diagnostic role of systematic biopsies was evaluated.

RESULTS

We selected 56 patients on AS with mean age 67.4 years, mean PSA 6.7 ng/ml and at least one follow-up MRI-US fusion biopsy (10 had 2 or 3 follow-up biopsies). Lesions detected by MRI were: PIRADS-2 in 5, PIRADS-3 in 28, PIRADS-4 in 18 pts and PIRADS-5 in 5 patients. In each MRI lesion, FB with 2.1 ± 1.1 cores were taken with a mean total cores of 13 ± 2.4 including the systematic cores. The overall cancer detection rate was 71% (40/56): 62% (25/40) in target core and 28% (15/40) in systematic core. The overall significant cancer detection rate was 46% (26/56): 69% (18/26) in target vs 31% (8/26) in random cores.

CONCLUSIONS

The incidence of clinical significant cancer was 46% in men starting active surveillance, but it was more than doubled using MRI/US Target Biopsy 69% (18/26) rather than random cores (31%, 8/26). However, 1/3 of disease upgrades would have been missed if only the targeted biopsies were performed. Based on our experience, MRI/US fusion target biopsy must be associated to systematic biopsies to improve detection of significant cancer, reducing the risks of misclassification.

Which Prostate Biopsy in Men Enrolled in Active Surveillance? Experience in 110 Men Submitted to Scheduled Three-Years Transperineal Saturation Biopsy Combined With Fusion Targeted Cores

INTRODUCTION

The reclassification rate for clinically significant prostate cancer (csPCa) has been evaluated in men enrolled in active surveillance (AS) protocol who previously underwent confirmatory biopsy.

MATERIALS AND METHODS

From May 2013 to September 2017, 110 patients (median age 63 years) with very low risk PCa underwent 3-years scheduled prostate biopsy performing repeated transperineal saturation biopsy (SPBx); in addition, the mpMRI lesions characterized by Prostate Imaging Reporting and Data System (PI-RADS) version 2 scores ≥ 3 were submitted to additional mpMRI/TRUS fusion biopsies (4 cores). The reclassification rate for csPCa (over 3 or more than 10% of positive cores, ISUP Grade Group/GG ≥ 2, greatest percentage of cancer > 50%) has been evaluated.

RESULTS

Six (5.4%) patients with PI-RADS score 3 (4 men) vs. 4 (2 men) were reclassified based on upgraded (GG2); SPBx and MRI/TRUS fusion biopsy diagnosed 100% and 0% of csPCa, respectively. Of the remaining 104 (94.5%) patients, 75 (72.2%) were found to have very low-risk PCa and in 29 (27.8%) cancer was absent (normal parenchyma).

CONCLUSION

SPBx combined with mpMRI at confirmatory and repeated evaluation allow to reduce the reclassification rate during AS follow up (5.4% of the cases at 3 years from diagnosis).

Post Prostatectomy Pathologic Findings of Patients With Clinically Significant Prostate Cancer and no Significant PI-RADS Lesions on Preoperative Magnetic Resonance Imaging

OBJECTIVES

We present postprostatectomy pathology results from a series of prostate cancer (Pca) Gleason grade group ≥2 patients who did not have findings suggestive of cancer on preoperative pelvic magnetic resonance imaging (MRI).

METHODS

We performed an institutional retrospective study of prostate magnetic resonance imaging (MRI) examinations done from October 2015 to February 2018. We identified patients who underwent prostatectomy for Pca Gleason ≥3 + 4 diagnosed on prostate biopsy with no associated MRI findings suggestive of malignancy and analyzed their postprostatectomy pathologic findings and MRI imaging results.

RESULTS

At our institution, 850 men with Pca received MRI between 2015 and 2018, and 156/850 patients received robotic-assisted radical prostatectomy. Thirty-three patients (33/156 = 21%) had negative MRI for PIRAD 3 or greater but had a biopsy showing significant Pca. Their mean (range) age was 62.7 (50-86) years. Their median (interquartile range) PSA, and PSA density were, 4.6 (3.7) ng/mL and 0.12 (0.05) ng/mL/cm², respectively; all not significantly different from patients with visible lesions on MRI who underwent surgery. On post prostatectomy pathology, 27/33 (82%) men had Pca Gleason score 7 or greater. The most common pattern was infiltrative growth with cancer glands intermingling between benign glands.

CONCLUSION

We describe the pathologic and imaging findings in an extensive series of men with clinically significant Pca with no significant lesions on preoperative MRI. Our results support the importance of patient counseling on the risk of missing significant Pca on MRI in isolation from other clinical variables.