Prostate Imaging Reporting And Data System Research Articles

Multiparameter magnetic resonance imaging features of prostatic malakoplakia.

To summarize the multiparameter magnetic resonance imaging (mpMRI) features of prostatic malakoplakia. Eleven patients (median age 62 years; IQR 59-71 years) with pathologically confirmed prostatic malakoplakia were included in this study. MpMRI features of the lesions were retrospectively reviewed and summarized. The Prostate Imaging-Reporting and Data System (PI-RADS) scores of the patients were 4 or 5, with a medium diameter of 3.7 cm (IQR 2.0-5.2 cm). All the lesions involved the peripheral zone, of which 3 cases (3/11, 27.3%) involved the transition zone simultaneously. A diffuse symmetrical distribution was found in 5 cases, a focal distribution in 5 cases, and a focal symmetrical distribution in 1 case. Both the surgical capsule and prostatic margin were bulged and compressed, but no signs of infiltration were found. Nearly all the lesions had moderate hypointensity on T2-weighted images and slightly higher signal intensity on T1-weighted images. Among the lesions, early enhancement occurred in all cases, prolonged enhancement occurred in 8 cases, and ring enhancement persisted in 1 case. All lesions displayed periprostatic enhancement in the delayed phase. Lesions distributed diffusely and symmetrically in the peripheral zone with preserved surgical capsule and margin are characteristic features of malakoplakia as opposed to cancer, especially in those with slightly high T1 signal intensity and delayed periprostatic enhancement. Those locally distributed lesions with the above signs should also be suspected. Prostatic malakoplakia are more likely to distribute diffusely and symmetrically, with slightly high T1 signal intensity and delayed periprostatic enhancement.

Evaluating Biparametric Versus Multiparametric Magnetic Resonance Imaging for Diagnosing Clinically Significant Prostate Cancer: An International, Paired, Noninferiority, Confirmatory Observer Study

Background and objectiveBiparametric magnetic resonance imaging (bpMRI), excluding dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), is a potential replacement for multiparametric MRI (mpMRI) in diagnosing clinically significant prostate cancer (csPCa). An extensive international multireader multicase observer study was conducted to assess the noninferiority of bpMRI to mpMRI in csPCa diagnosis. MethodsAn observer study was conducted with 400 mpMRI examinations from four European centers, excluding examinations with prior prostate treatment or csPCa (Gleason grade [GG] ≥2) findings. Readers assessed bpMRI and mpMRI sequentially, assigning lesion-specific Prostate Imaging Reporting and Data System (PI-RADS) scores (3–5) and a patient-level suspicion score (0–100). The noninferiority of patient-level bpMRI versus mpMRI csPCa diagnosis was evaluated using the area under the receiver operating curve (AUROC) alongside the sensitivity and specificity at PI-RADS ≥3 with a 5% margin. The secondary outcomes included insignificant prostate cancer (GG1) diagnosis, diagnostic evaluations at alternative risk thresholds, decision curve analyses (DCAs), and subgroup analyses considering reader expertise. Histopathology and ≥3 yr of follow-up were used for the reference standard. Key findings and limitationsSixty-two readers (45 centers and 20 countries) participated. The prevalence of csPCa was 33% (133/400); bpMRI and mpMRI showed similar AUROC values of 0.853 (95% confidence interval [CI], 0.819–0.887) and 0.859 (95% CI, 0.826–0.893), respectively, with a noninferior difference of –0.6% (95% CI, –1.2% to 0.1%, p < 0.001). At PI-RADS ≥3, bpMRI and mpMRI had sensitivities of 88.6% (95% CI, 84.8–92.3%) and 89.4% (95% CI, 85.8–93.1%), respectively, with a noninferior difference of –0.9% (95% CI, –1.7% to 0.0%, p < 0.001), and specificities of 58.6% (95% CI, 52.3–63.1%) and 57.7% (95% CI, 52.3–63.1%), respectively, with a noninferior difference of 0.9% (95% CI, 0.0–1.8%, p < 0.001). At alternative risk thresholds, mpMRI increased sensitivity at the expense of reduced specificity. DCA demonstrated the highest net benefit for an mpMRI pathway in cancer-averse scenarios, whereas a bpMRI pathway showed greater benefit for biopsy-averse scenarios. A subgroup analysis indicated limited additional benefit of DCE MRI for nonexperts. Limitations included that biopsies were conducted based on mpMRI imaging, and reading was performed in a sequential order. Conclusions and clinical implicationsIt has been found that bpMRI is noninferior to mpMRI in csPCa diagnosis at AUROC, along with the sensitivity and specificity at PI-RADS ≥3, showing its value in individuals without prior csPCa findings and prostate treatment. Additional randomized prospective studies are required to investigate the generalizability of outcomes.

Unlocking Precision Enhancing Prostate Cancer Detection and Reducing Unnecessary Biopsies with Combined Prostate-Specific Antigen Density and PI-RADS Score.

To determine clinically significant prostate cancer (csPCa) detection rate by combining the prostate-specific antigen density (PSAD) and prostate imaging-reporting and data system (PI-RADS) scores. Descriptive study. Place and Duration of the Study: Department of Urology, University of Health Sciences, Ankara Oncology Training and Research Hospital, from January 2018 to April 2023. Patients who underwent prostate biopsies after multiparametric magnetic resonance imaging (mpMRI) were included in the study. PI-RADS 4 and 5 lesions were considered as MR positive. The cut-off values for PSAD were also determined to evaluate csPCa. csPCa detection rates were evaluated by grouping the patients based on the PSAD and mpMRI findings. PSAD cut-off value of 0.165 ng/mL/mL (sensitivity 80%, specificity 72%) was detected to predict csPCa (AUC = 0.81, 95% CI:0.756-0.866, p<0.001). csPCa detection rate was low (3%) in patients who have low PI-RADS scores (1-3) and a PSAD <0.165 ng/mL/mL. On the other hand, csPCa detection rate was high (50.5%) in patients who have a high PI-RADS score (4-5 lesions) and with a PSAD ≥0.165 ng/mL/mL. csPCa detection rates are low in patients with PI-RADS 1-3 lesions and low PSAD values. Unnecessary biopsy may be avoided in these patients. Gleason score, PI-RADS, Prostate cancer, Prostate-specific antigen, Prostate-specific antigen density.

Predictive ability of MRI for detecting prostate cancer and its clinical significance in MRI-targeted biopsy for PI-RADS ≥3 lesions

BackgroundIdentifying the index lesion in prostate cancer (PCa) is vital for its treatment. Therefore, various coefficients and parameters are employed to improve the diagnostic accuracy of magnetic resonance imaging (MRI). PurposeThis study aimed to analyze MRI data, utilized as a triage test before prostate biopsy, to identify independent risk factors affecting negative biopsy results in PCa and investigate the ability of these factors to predict clinically significant and insignificant PCa (csPCa and ciPCa, respectively). MethodsA retrospective analysis was conducted on data from 364 patients with a prostate imaging reporting and data system (PI-RADS) v2.1 score of 3 or higher, who underwent cognitive MRI-targeted biopsy (MRI-TB). Of the patients, 226 (62.1%) had benign lesions, 75 (20.6%) were diagnosed with ciPCa, and 63 (17.3%) with csPCa. The study assessed patients’ demographic, biochemical, and radiologic characteristics, including apparent diffusion coefficient (ADC) and ADC coefficient of variation (ADCCoV) values. ResultsThe multivariate analysis performed to differentiate PCa from benign pathologies revealed that only MRI parameters, specifically the presence of PI-RADS 4 and 5 lesions (odds ratio [OR]: 12, p<0.001 and OR: 73, p=0.008, respectively), a lower ADC value (OR: 0.996, p=0.041) and a higher ADCCoV value (OR: 1.07, p=0.003), were independent risk factors. No MRI findings had significant predictive power for csPCa, with total PSA (OR: 1.17, p=0.019) found to be the only independent risk factor. ConclusionThe results of this study suggest that data obtained from MRI can predict PCa but not csPCa.

The “Hungry Judge” effect on prostate MRI reporting: Chronobiological trends from 35’004 radiologist interpretations

AimTo investigate the associations between the hour of the day and Prostate Imaging–Reporting and Data System (PI-RADS) scores assigned by radiologists in prostate MRI reports. Materials and methodsRetrospective single-center collection of prostate MRI reports over an 8-year period. Mean PI-RADS scores assigned between 0800 and 1800 h were examined with a regression model. ResultsA total of 35′004 prostate MRI interpretations by 26 radiologists were included. A significant association between the hour of day and mean PI-RADS score was identified (β2 = 0.005, p < 0.001), with malignant scores more frequently assigned later in the day. ConclusionThese findings suggest chronobiological factors may contribute to variability in radiological assessments. Though the magnitude of the effect is small, this may potentially add variability and impact diagnostic accuracy.

AI-derived Tumor Volume from Multiparametric MRI and Outcomes in Localized Prostate Cancer.

Background An artificial intelligence (AI)-based method for measuring intraprostatic tumor volume based on data from MRI may provide prognostic information. Purpose To evaluate whether the total volume of intraprostatic tumor from AI-generated segmentations (VAI) provides independent prognostic information in patients with localized prostate cancer treated with radiation therapy (RT) or radical prostatectomy (RP). Materials and Methods For this retrospective, single-center study (January 2021 to August 2023), patients with cT1-3N0M0 prostate cancer who underwent MRI and were treated with RT or RP were identified. Patients who underwent RT were randomly divided into cross-validation and test RT groups. An AI segmentation algorithm was trained to delineate Prostate Imaging Reporting and Data System (PI-RADS) 3-5 lesions in the cross-validation RT group before providing segmentations for the test RT and RP groups. Cox regression models were used to evaluate the association between VAI and time to metastasis and adjusted for clinical and radiologic factors for combined RT (ie, cross-validation RT and test RT) and RP groups. Areas under the receiver operating characteristic curve (AUCs) were calculated for VAI and National Comprehensive Cancer Network (NCCN) risk categorization for prediction of 5-year metastasis (RP group) and 7-year metastasis (combined RT group). Results Overall, 732 patients were included (combined RT group, 438 patients; RP group, 294 patients). Median ages were 68 years (IQR, 62-73 years) and 61 years (IQR, 56-66 years) for the combined RT group and the RP group, respectively. VAI was associated with metastasis in the combined RT group (median follow-up, 6.9 years; adjusted hazard ratio [AHR], 1.09 per milliliter increase; 95% CI: 1.04, 1.15; P = .001) and the RP group (median follow-up, 5.5 years; AHR, 1.22; 95% CI: 1.08, 1.39; P = .001). AUCs for 7-year metastasis for the combined RT group for VAI and NCCN risk category were 0.84 (95% CI: 0.74, 0.94) and 0.74 (95% CI: 0.80, 0.98), respectively (P = .02). Five-year AUCs for the RP group for VAI and NCCN risk category were 0.89 (95% CI: 0.80, 0.98) and 0.79 (95% CI: 0.64, 0.94), respectively (P = .25). Conclusion The volume of AI-segmented lesions was an independent, prognostic factor for localized prostate cancer. © RSNA, 2024 Supplemental material is available for this article.

Determinants of decision-making in biopsy of PI-RADS 3 transition zone lesions.

Cancer rates for Prostate Imaging-Reporting and Data System (PI-RADS) 3 lesions are low. We aimed to determine the clinical and magnetic resonance imaging (MRI) parameters that can provide risk stratification for PI-RADS 3 transition zone (TZ) lesions to guide decision for biopsy, which can improve the cost-effectiveness of resource utilisation. The MRI scans of all patients who underwent MRI-ultrasound fusion targeted biopsy from 1 May 2016 to 31 December 2022 were retrospectively assessed by two board-certified abdominal radiologists. The following data were collected and analysed serum prostate-specific antigen, Prostatic Health Index (PHI), prostate volume, histological results, lesion size, location, diffusion-weighted imaging (DWI) parameter scores and overall PI-RADS score. Two hundred and fourteen TZ lesions were included. Among 131 PI-RADS 3 lesions, those with marked restricted diffusion (DWI score ≥4), diameter ≥1 cm, prostrate-specific antigen density (PSAD) ≥0.11 and PHI ≥34 were more likely to contain clinically significant prostate cancer (csPCa; P = 0.04, 0.02, 0.049 and 0.05, respectively), with areas under the receiver operating characteristics curve of 0.9, 0.76, 0.84 and 0.80, respectively. Apical lesions were more likely to contain csPCa compared to midgland or basal lesions (P = 0.01). Clinical parameters (PSAD and PHI) and MRI features (lesion size, DWI score, lesion location) can be used to risk stratify PI-RADS 3 TZ lesions and guide decision for targeted biopsy.

Diagnostic utility of prostate health index density prior to MRI-ultrasound fusion targeted biopsy.

Prostate biopsy can be prone to complications and thus should be avoided when unnecessary. Although the combination of magnetic resonance imaging (MRI), the prostate health index (PHI), and PHI density (PHID) has been shown to improve detection of clinically significant prostate cancer (csPCa), there is limited information available assessing its clinical utility. We sought to determine whether using PHID could enhance the detection of PCa on MRI ultrasound fusion-targeted biopsy (MRF-TB) compared to other biomarker cutoffs. Between June 2015 and December 2020, 302 men obtained PHI testing before MRF-TB at a single institution. We used descriptive statistics, multivariable logistic regression, and receiver operating characteristic curves to determine the predictive accuracy of PHID and PHI to detect ≥ Gleason grade group (GGG) 2 PCa and identify cutoff values. Any cancer grade was identified in 75.5% of patients and ≥ GGG2 PCa was identified in 45% of patients. The median PHID was 1.05 [interquartile range (IQR) 0.59-1.64]. A PHID cutoff of 0.91 had a higher discriminatory ability to predict ≥ GGG2 PCa compared to PHI > 27, PHI > 36, and prostate specific-antigen (PSA) density > 0.15 (AUC: 0.707 vs. 0.549 vs. 0.620 vs. 0.601), particularly in men with Prostate Imaging Reporting and Data System (PI-RADS) 1-2 lesions on MRI (AUC: 0.817 vs. 0.563 vs. 0.621 vs. 0.678). At this cutoff, 35.0% of all the original biopsies could be safely avoided (PHID < 0.91 and no ≥ GGG2 PCa) and csPCa would be missed in 9.67% of patients who would have been biopsied. In patients with PI-RADS 1-2 lesions using a PHID cutoff of 0.91, 56.8% of biopsies could be safely avoided while missing 0 csPCa. These findings suggest that a PHID cutoff of 0.91 improves the selection of patients with elevated prostate-specific antigen who are referred for prostate biopsy, and potentially in patients with PI-RADS 1-2 lesions.

Evaluating Prostate Cancer: The Diagnostic Impact of MRI and Its Relationship With Transrectal Ultrasound (TRUS)-Guided Biopsy.

Background Prostate disorders, including benign enlargement and malignancy, are commonly evaluated through imaging techniques. Historically, transrectal ultrasound (TRUS) has been used for prostate imaging and biopsy. However, multiparametric MRI (mpMRI), which integrates structural and functional imaging methods, offers enhanced diagnostic capabilities. This study evaluates the effectiveness of mpMRI, including its grading via Prostate Imaging - Reporting and Data System (PI-RADS) or Likert scoring, in distinguishing between benign and malignant prostatic conditionsand compares these findings with TRUS outcomes. Methodology This prospective study enrolled 30 male patients aged 45 to 75 years (mean age 60 years), selected based on prostatic abnormalities, elevated prostate-specific antigen (PSA) levels (>4 ng/dL), or palpable nodules detected via digital rectal examination. MRI, including PI-RADS or Likert scoring, was utilized to assess prostatic lesions, and results were compared with histopathological data obtained from TRUS-guided biopsies. Results Among the 30 patients, common symptoms included urinary retention (60%) and painful urination (53.3%). Malignant tumors were diagnosed in 12 patients (40%). MRI identified eight cases with enlarged transitional zones and irregular signals in peripheral zones (benign prostatic hyperplasia with tumor)and four cases with irregular signals in both zones (sarcoma). Concordance between MRI T2-weighted (T2W) observations and biopsy results showed 60% malignancy detection. Sensitivity assessments revealed MRI detected 15 true-positives (50%), TRUS detected six true positives (20%), and multivoxel spectroscopic analysis (MVS) identified 14 true-positives (46.7%). PI-RADS or Likert scoring of mpMRI was correlated with TRUS outcomes, highlighting its enhanced diagnostic accuracy compared to TRUS alone. Conclusion While TRUS remains a standard diagnostic tool, it is limited by significant sampling errors and complications. The integration of mpMRI, with its grading system, significantly improves diagnostic accuracy and treatment planning. Although mpMRI alone has limitations, its combination with contrast-enhanced MRI, diffusion-weighted imaging, and MR spectroscopy offers a comprehensive approach to enhanced prostate cancer detection.

Explainable artificial intelligence-driven prostate cancer screening using exosomal multi-marker based dual-gate FET biosensor

Prostate Imaging Reporting and Data System (PI-RADS) score, a reporting system of prostate MRI cases, has become a standard prostate cancer (PCa) screening method due to exceptional diagnosis performance. However, PI-RADS 3 lesions are an unmet medical need because PI-RADS provides diagnosis accuracy of only 30–40% at most, accompanied by a high false-positive rate. Here, we propose an explainable artificial intelligence (XAI) based PCa screening system integrating a highly sensitive dual-gate field-effect transistor (DGFET) based multi-marker biosensor for ambiguous lesions identification. This system produces interpretable results by analyzing sensing patterns of three urinary exosomal biomarkers, providing a possibility of an evidence-based prediction from clinicians. In our results, XAI-based PCa screening system showed a high accuracy with an AUC of 0.93 using 102 blinded samples with the non-invasive method. Remarkably, the PCa diagnosis accuracy of patients with PI-RADS 3 was more than twice that of conventional PI-RADS scoring. Our system also provided a reasonable explanation of its decision that TMEM256 biomarker is the leading factor for screening those with PI-RADS 3. Our study implies that XAI can facilitate informed decisions, guided by insights into the significance of visualized multi-biomarkers and clinical factors. The XAI-based sensor system can assist healthcare professionals in providing practical and evidence-based PCa diagnoses.

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

Introduction/BackgroundThe natural history of prostate imaging reporting and data system (PIRADS) score 2 lesions on serial mpMRIs is largely unknown. Herein, we aimed to evaluate the patients with PIRADS-2 index lesions by using serial mpMRI scans to reveal the rates of mpMRI upgrade in PIRADS score and prostate cancer (PCa) detection. Methods/MaterialsAll mpMRI scans with a PIRADS-2 index lesion from our mpMRI database were evaluated retrospectively. Data from 214 biopsy-naïve patients with a PIRADS-2 index lesion on the initial mpMRI who then underwent at least 1 follow-up mpMRI were reevaluated by an experienced uroradiologist and only those (n = 172) who had a PIRADS-2 index lesion on the initial mpMRI according to PIRADS v2.1 were included in the study. mpMRI progression was defined as the detection of any PIRADS ≥3 lesion at follow-up mpMRI. Histopathological results were evaluated in patients undergoing biopsy upon mpMRI progression. ResultsA total of 172 patients with a mean age of 60.1 ± 8.6 years were evaluated. The median PSA at baseline mpMRI was 4.7 (IQR; 3.3–6.7) ng/dl. Overall mpMRI progression was detected in 54 patients (31.4%), 37 were upgraded to PIRADS-3, 16 to PIRADS-4, and one to PIRADS-5. Multivariate logistic regression analysis revealed that a PSA increase of ≥25% during follow-up was the only predictor of mpMRI upgrade (P = 0.019, OR: 2.384). 30 out of 54 patients underwent a prostate biopsy and PCa was detected in 15 patients; 5 with ISUP grade 1, 10 with ISUP grade 2. ConclusionsAlmost half of the patients with a PIRADS-2 index lesion were upgraded to PIRADS ≥3 when evaluated with serial mpMRI when a PSA increase of ≥25% was observed during follow-up. PCa was detected in half of the patients who underwent a biopsy. Serial mpMRI can be recommended when monitoring patients with elevating PSA ≥25%, a prostate biopsy can be considered upon a mpMRI progression.

Optimizing prostate cancer detection in transition zone: an analysis of apparent diffusion coefficient values in prostate magnetic resonance imaging evaluation with Prostate Imaging Reporting and Data System (PI-RADS) assessment.

Multiparametric magnetic resonance imaging (mpMRI) is increasingly used for the early detection of clinically significant prostate cancer (csPCa). However, the achievement of accurate detection rates, particularly for transition zone (TZ) lesions, remains challenging. We investigated the relationship between apparent diffusion coefficient (ADC) values in Prostate Imaging Reporting and Data System (PI-RADS) 3-5 lesions and csPCa within the TZ. We retrospectively evaluated TZ lesions in patients who underwent 3.0 Tesla MRI followed by MRI-targeted/transrectal ultrasound fusion biopsies (MRI-FBx). Fusion biopsies were performed for potentially cancerous lesions, defined as lesions with PI-RADS scores 3-5. We analyzed 196 lesions for which fusion biopsies were performed. The overall prostate cancer (PCa) detection rate was 53.6% (105/196); csPCa constituted 33.7% (66/196) of cases. The minimum ADC value was significantly lower for patients with csPCa (484.9±112.3 µm2/s) than for patients with benign histology or non-csPCa (P<0.001). Older age, higher initial prostate-specific antigen level, larger region of interest, and minimum and mean ADC values were associated with the presence of csPCa. Multivariate analysis indicated that only the minimum ADC value was an independent predictor of csPCa. Using a cutoff minimum ADC value <561 µm2/s to detect csPCa in TZ lesions increased the detection rate to 57.4% (54/94). The minimum ADC value provides substantial additional information regarding the presence of csPCa in the TZ, potentially improving the detection rates for lesions rated as PI-RADS 3-5 and informing the need for follow-up biopsies in areas that are initially cancer-free.

Deep Learning-based Unsupervised Domain Adaptation via a Unified Model for Prostate Lesion Detection Using Multisite Biparametric MRI Datasets.

Purpose To determine whether the unsupervised domain adaptation (UDA) method with generated images improves the performance of a supervised learning (SL) model for prostate cancer (PCa) detection using multisite biparametric (bp) MRI datasets. Materials and Methods This retrospective study included data from 5150 patients (14 191 samples) collected across nine different imaging centers. A novel UDA method using a unified generative model was developed for PCa detection using multisite bpMRI datasets. This method translates diffusion-weighted imaging (DWI) acquisitions, including apparent diffusion coefficient (ADC) and individual diffusion-weighted (DW) images acquired using various b values, to align with the style of images acquired using b values recommended by Prostate Imaging Reporting and Data System (PI-RADS) guidelines. The generated ADC and DW images replace the original images for PCa detection. An independent set of 1692 test cases (2393 samples) was used for evaluation. The area under the receiver operating characteristic curve (AUC) was used as the primary metric, and statistical analysis was performed via bootstrapping. Results For all test cases, the AUC values for baseline SL and UDA methods were 0.73 and 0.79 (P < .001), respectively, for PCa lesions with PI-RADS score of 3 or greater and 0.77 and 0.80 (P < .001) for lesions with PI-RADS scores of 4 or greater. In the 361 test cases under the most unfavorable image acquisition setting, the AUC values for baseline SL and UDA were 0.49 and 0.76 (P < .001) for lesions with PI-RADS scores of 3 or greater and 0.50 and 0.77 (P < .001) for lesions with PI-RADS scores of 4 or greater. Conclusion UDA with generated images improved the performance of SL methods in PCa lesion detection across multisite datasets with various b values, especially for images acquired with significant deviations from the PI-RADS-recommended DWI protocol (eg, with an extremely high b value). Keywords: Prostate Cancer Detection, Multisite, Unsupervised Domain Adaptation, Diffusion-weighted Imaging, b Value Supplemental material is available for this article. © RSNA, 2024.

Oncological outcomes after radical prostatectomy of localized prostate cancer: stratified by magnetic resonance imaging and risk classification

BackgroundWe investigated whether combining T2-weighted magnetic resonance imaging (MRI) findings and clinical risk categories improves upon established prognostic indicators of oncological outcomes in prostate cancer. MethodsPatients who underwent radical prostatectomy, but not preoperative hormone therapy, radiotherapy, or chemotherapy, for localized prostate cancer at Seoul National University Bundang Hospital from October 2007 to April 2016 were included. MRIs were classified according to the Prostate Imaging-Reporting and Data System (PI-RADS). Patients were divided into the following five groups: 1, no focal suspicious lesion; 2, organ-confined suspicious lesion PI-RADS ≤3; 3, organ-confined suspicious lesion PI-RADS 4 or 5; 4, suspicious lesion with extraprostatic extension (EPE), no seminal vesicle invasion (SVI); 5, suspicious lesion with EPE and SVI. Risk classified according to the National Comprehensive Cancer Network (NCCN) and MRI findings were combined to analyze survival curves for biochemical recurrence (BCR)-free and metastasis-free survival. The area under a time-dependent receiver operating characteristic was analyzed for event prediction after 5 years. ResultsWe analyzed 1,290 patients. In multivariate Cox regression models, PI-RADS ≥4 (hazard ratio [HR] 2.33, P < 0.001), EPE (HR 1.46, P = 0.027), SVI (HR 5.03, P < 0.001) and NCCN high-risk (HR 2.33, 95% CI 1.66-3.26, P < 0.001) were associated with BCR. For metastasis, EPE (HR 2.33, P = 0.047), SVI (HR 13.08, P < 0.001) and NCCN high-risk (HR 2.78, P = 0.026) were independent risk factors. Depending on MRI group, BCR-free survival significantly decreased in NCCN intermediate-risk (P = 0.001) and high-risk (P < 0.001) groups, and metastasis-free survival decreased in the intermediate-risk group (P = 0.39) and significantly decreased in the high-risk (P < 0.001) group. Adding MRI group to NCCN risk classification significantly improved the predictive accuracy for BCR in comparison with NCCN risk classification alone (P = 0.042), but not for metastasis (P = 0.012). ConclusionCombining prostate MRI with NCCN risk classification improves the prediction value of BCR following radical prostatectomy for localized prostate cancer.

Organized prostate cancer screening program: a proposal from the Italian Society of Urology (SIU).

To contrast opportunistic PCa screening, the European Union Council suggested extending screening programs to PCa by recommending the implementation of a stepwise approach in the EU Countries to evaluate the feasibility and effectiveness of an organized program based on PSA testing in combination with additional MRI as a follow-up test. The objective of this expert-based document is to propose an organized PCa screening program according to the EU Council recommendations. The Italian Society of Urology (SIU) developed a team of experts with the aim to report 1) the most recent epidemiologic data about incidence, prevalence, and mortality of PCa; 2) the most important risk factors to identify categories of men with an increased risk to eventually develop the disease; 3) the most relevant studies presenting data on population-based screening; and 4) the current recommendations of the leading International Guidelines. According to previous evidence, the Panel proposed some indications to develop a new organized PCa screening program for asymptomatic men with a life-expectancy of at least fifteen years. The SIU Panel strongly supports the implementation of a pilot, organized PCa screening program inviting asymptomatic men in the age range of 50-55 years. Invited men who are already performing opportunistic screening will be randomized to continue opportunistic screening or to cross into the organized protocol. Men with PSA level ≤3 ng/mL and familiarity for PCa received a DRE as well as all those with PSA levels >3 ng/mL. All other men with PSA levels greater than 3 ng/mL proceed to secondary testing represented by mpMRI. Men with Prostate Imaging-Reporting and Data System (PI-RADS) lesions 3 and PSAD 0.15 ng/mL/cc or higher as well as those with PI-RADS 4-5 lesions proceed to targeted plus systematic prostate biopsy. The primary outcome of the proposed pilot PCa screening program will be the detection rate of clinically significant PCa defined as a tumor with a ISUP Grade Group ≥2. Main secondary outcomes will be the detection rate of aggressive PCa (ISUP Grade Group ≥4); the detection rate of insignificant PCa (ISUP Grade Group 1); the number of unnecessary prostate biopsy avoided, the metastasis-free survival, and the overall survival. Men will be invited over a one-year period. Preliminary analyses will be planned 2 and 5 years after the baseline enrollment. According to the recent EU Council recommendations on cancer screening, pilot studies evaluating the feasibility and effectiveness of PCa screening programs using PSA as the primary and mpMRI as the secondary screening test in selected cohorts of patients must be strongly promoted by scientific societies and supported by national governments.

Rationale for adopting a combination of monoparametric MRI with the prostate-specific antigen in detecting clinically significant prostate cancer: comparison with standard biparametric and multiparametric MRI.

To compare prostate monoparametric MRI (monoMRI), which uses only diffusion-weighted imaging (DWI), with biparametric (bpMRI) and multiparametric MRI (mpMRI) in detecting clinically significant cancer (CSC) and to evaluate the effect of the combination of monoMRI results and prostate-specific antigen (PSA) level. In this study, 193 patients (average age 70.5 years; average PSA 7.9 ng/mL) underwent prebiopsy MRI and subsequent prostate biopsy from January 2020 to February 2022. Two radiologists independently reviewed the 3 MRI protocols using the Prostate Imaging Reporting and Data System (PI-RADS). Interreader agreement was assessed using the intraclass correlation coefficient (ICC), and diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis. The Youden index was used to determine the new cutoff value of PSA for detecting CSCs in patients with negative monoMRI results. CSC was confirmed in 109 patients (56.5%). The interreader agreement on monoMRI (ICC = 0.798) was comparable to that on bpMRI and mpMRI (ICC = 0.751 and 0.714, respectively). ROC curve analysis of the 3 protocols revealed no difference in detecting CSCs (P > 0.05). Applying a new PSA cutoff value (9.5 and 7.4 ng/mL, respectively) in monoMRI-negative patients improved the sensitivity of monoMRI from 89.9% to 96.3% for Reader 1, and from 95.4% to 99.1% for Reader 2. MonoMRI based solely on DWI demonstrated similar diagnostic performance to bpMRI and mpMRI in detecting CSCs, and the combination of PSA level with monoMRI has the potential to effectively triage patients with a high likelihood of CSCs. Monoparametric MRI conducted only with diffusion-weighted imaging (DWI), may show comparable performance to biparametric and multiparametric MRI in detecting clinically significant prostate cancer. In patients with negative monoparametric MRI results, implementing a new PSA cutoff value to determine the need for a biopsy could decrease the number of missed prostate cancer.

Preliminary clinical practice of radical prostatectomy without preoperative biopsy.

At present, biopsy is essential for the diagnosis of prostate cancer (PCa) before radical prostatectomy (RP). However, with the development of prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT) and multiparametric magnetic resonance imaging (mpMRI), it might be feasible to avoid biopsy before RP. Herein, we aimed to explore the feasibility of avoiding biopsy before RP in patients highly suspected of having PCa after assessment of PSMA PET/CT and mpMRI. Between December 2017 and April 2022, 56 patients with maximum standardized uptake value (SUVmax) of ≥4 and Prostate Imaging Reporting and Data System (PI-RADS) ≥4 lesions who received RP without preoperative biopsy were enrolled from two tertiary hospitals. The consistency between clinical and pathological diagnoses was evaluated. Preoperative characteristics were compared among patients with different pathological types, T stages, International Society of Urological Pathology (ISUP) grades, and European Association of Urology (EAU) risk groups. Fifty-five (98%) patients were confirmed with PCa by pathology, including 49 (89%) with clinically significant prostate cancer (csPCa, defined as ISUP grade ≥2 malignancy). One patient was diagnosed with high-grade prostatic intraepithelial neoplasia (HGPIN). CsPCa patients, compared with clinically insignificant prostate cancer (cisPCa)andHGPIN patients, were associated with a higher level of prostate-specific antigen (22.9ng/mL vs. 10.0ng/mL, P=0.032), a lower median prostate volume (32.2mL vs. 65.0mL, P=0.001), and a higher median SUVmax (13.3 vs. 5.6, P<0.001). It might be feasible to avoid biopsy before RP for patients with a high probability of PCa based on PSMA PET/CT and mpMRI. However, the diagnostic efficacy of csPCa with PI-RADS ≥4 and SUVmax of ≥4 is inadequate for performing a procedure such as RP. Further prospective multicenter studies with larger sample sizes are necessary to confirm our perspectives and establish predictive models with PSMA PET/CT and mpMRI.

Pathological Assessment of Men with Grade Group 2 Prostate Cancer.

A variety of treatment options are now available for men with localized prostate cancer (PC); however, there is still debate in determining how and when to intervene for Grade Group (GG) 2 disease. Our study aims to formulate strategies to identify men at risk of upgrading and having adverse pathological outcomes. This retrospective study includes 243 patients with GG2 PC that were treated with radical prostatectomy between 2015 and 2021. Patients on active surveillance, previous history of prostate biopsy, hormonal and/or radiation therapy prior to surgery were excluded from this study. A retrospective analysis was conducted using clinicopathological data obtained from medical records. Prostate-specific antigen (PSA) and Prostate Imaging Reporting and Data System (PI-RADS) score were statistically significant variables for risk of upgrading. In men who had presence of composite poor outcomes, PSA, PI-RADS score, presence of extraprostatic extension and seminal vesical invasion on MRI, number of positive cores, percentage of high grade (pattern 4/5) on prostate biopsy and Gleason pattern 4 volume on biopsy were all statistically significant variables. Strategy 8 (PI-RADS 5 lesion or percentage high grade [Gleason pattern 4] on prostate biopsy grade >10% or >3 cores positive on prostate biopsy) had significant association to identifying the highest number of men with upgrading and composite poor outcomes. Our study supports the use of strategy 8 in treatment decision making of men with GG2 PC. Further validation of the use of this strategy is warranted.

Urine biomarkers can predict prostate cancer and PI-RADS score prior to biopsy

Prostate-Specific Antigen (PSA) based screening of prostate cancer (PCa) needs refinement. The aim of this study was the identification of urinary biomarkers to predict the Prostate Imaging—Reporting and Data System (PI-RADS) score and the presence of PCa prior to prostate biopsy. Urine samples from patients with elevated PSA were collected prior to prostate biopsy (cohort = 99). The re-analysis of mass spectrometry data from 45 samples was performed to identify urinary biomarkers to predict the PI-RADS score and the presence of PCa. The most promising candidates, i.e. SPARC-like protein 1 (SPARCL1), Lymphatic vessel endothelial hyaluronan receptor 1 (LYVE1), Alpha-1-microglobulin/bikunin precursor (AMBP), keratin 13 (KRT13), cluster of differentiation 99 (CD99) and hornerin (HRNR), were quantified by ELISA and validated in an independent cohort of 54 samples. Various biomarker combinations showed the ability to predict the PI-RADS score (AUC = 0.79). In combination with the PI-RADS score, the biomarkers improve the detection of prostate carcinoma-free men (AUC = 0.89) and of those with clinically significant PCa (AUC = 0.93). We have uncovered the potential of urinary biomarkers for a test that allows a more stringent prioritization of mpMRI use and improves the decision criteria for prostate biopsy, minimizing patient burden by decreasing the number of unnecessary prostate biopsies.

Utility of dynamic contrast enhancement for clinically significant prostate cancer detection.

This study aimed to evaluate the association of dynamic contrast enhancement (DCE) with clinically significant prostate cancer (csPCa, Gleason Grade Group ≥2) and compare biparametric magnetic resonance imaging (bpMRI) and multiparametric MRI (mpMRI) nomograms. We identified a retrospective cohort of biopsy naïve patients who underwent pre-biopsy MRI separated by individual MRI series from 2018 to 2022. csPCa detection rates were calculated for patients with peripheral zone (PZ) lesions scored 3-5 on diffusion weighted imaging (DWI) with available DCE (annotated as - or +). bpMRI Prostate Imaging Reporting and Data System (PIRADS) (3 = 3-, 3+; 4 = 4-, 4+; 5 = 5-, 5+) and mpMRI PIRADS (3 = 3-; 4 = 3+, 4-, 4+; 5 = 5-, 5+) approaches were compared in multivariable logistic regression models. Nomograms for detection of csPCa and ≥GG3 PCa incorporating all biopsy naïve patients who underwent prostate MRI were generated based on available serum biomarkers [PHI, % free prostate-specific antigen (PSA), or total PSA] and validated with an independent cohort. Patients (n = 1010) with highest PIRADS lesion in PZ were included in initial analysis with 127 (12.6%) classified as PIRADS 3+ (PIRADS 3 on bpMRI but PIRADS 4 on mpMRI). On multivariable analysis, PIRADS 3+ lesions were associated with higher csPCa rates compared to PIRADS 3- (3+ vs. 3-: OR 1.86, p= 0.024), but lower csPCa rates compared to PIRADS DWI 4 lesions (4 vs. 3+: OR 2.39, p< 0.001). csPCa rates were 19% (3-), 31% (3+), 41.5% (4-), 65.9% (4+), 62.5% (5-), and 92.3% (5+). bpMRI nomograms were non-inferior to mpMRI nomograms in the development (n= 1410) and independent validation (n= 353) cohorts. Risk calculators available at: https://rossnm1.shinyapps.io/MynMRIskCalculator/. While DCE positivity by itself was associated with csPCa among patients with highest PIRADS lesions in the PZ, nomogram comparisons suggest that there is no significant difference in performance of bpMRI and mpMRI. bpMRI may be considered as an alternative to mpMRI for prostate cancer evaluation in many situations.