Search Results (158)

Background/Objectives: Prostate biopsy is essential for diagnosing prostate cancer. Social determinants of health (SDOH), including socioeconomic status, race, occupation, education, and environment, affect access, outcomes, and quality of life. Recognizing disparities from technology access to complications is crucial for equitable care. A systematic review examined how SDOH impacts biopsy access, technology, and complications. Methods: A systematic search of PubMed, Web of Science, and Scopus was performed to identify eligible studies published through February 2026. We included studies that evaluated the association between one or more SDOHs and prostate biopsy. Relevant outcomes included biopsy utilization, use of specific biopsy technologies (e.g., magnetic resonance imaging (MRI)-guided, transperineal), and post-procedural complications. Results: Nine observational studies met the inclusion criteria. The findings revealed disparities across three key domains. First, access to advanced biopsy technology was uneven. Four studies showed that Black men were significantly less likely than White men to receive MRI-guided biopsies. Additionally, post-biopsy outcomes showed that Black and Hispanic men faced significantly higher rates of post-biopsy infection and hospitalization compared to White men. Lastly, patients in rural areas, those in public hospitals, and individuals with lower socioeconomic status demonstrated reduced access to modern techniques, including MRI-guided or transperineal biopsy. Conclusions: Social and economic factors influence who receives a prostate biopsy and who has access to advanced technologies. Minority and low-income patients face diagnosis barriers and higher complication rates, highlighting systemic inequities. The healthcare system often rewards access over need, and without bold policy changes, gaps in technology and resources will worsen, moving us further from truly equitable prostate cancer care. Full article

Background/Objectives: Prostate cancer (PCa) detection via a conventional systematic biopsy (SB) may miss cancer lesions, promoting the exploration of alternative methods. Multiparametric MRI demonstrates high sensitivity and specificity for the detection of clinically significant prostate cancer and an MRI-directed three-dimensional fusion biopsy (MFB) strategy may improve cancer detection rates. There are limited data available in Taiwan regarding this novel technique. This study aimed to compare the accuracy of cancer detection rates between MFB and SB. Methods: From January, 2021 through October, 2023, patients with PSA levels of 4–20 ng/mL and no palpable prostate nodules were retrospectively reviewed. They were categorized into the MFB and SB groups. Clinical parameters and PCa detection rates were compared between the two groups. Multivariable logistic regression analyses were performed to identify independent predictors of cancer detection. A separate subgroup analysis was conducted within the MFB cohort to evaluate the association between the PI-RADS category and biopsy outcomes. Results: A total of 262 patients (89 in MFB and 173 in SB) were included in the final analysis. MFB demonstrated significantly a higher detection rate in detecting PCa compared to SB (45.0% vs. 31.8%, p = 0.036). Furthermore, MFB exhibited superior rates in detecting clinically significant PCa (csPCa) and high-grade PCa compared to SB (40.4% vs. 22.5%, p = 0.002; 20.2% vs. 5.8%, p ≤ 0.001, respectively). The MRI PIRADS score exhibited a positive correlation with the detection of PCa, csPCa, and high-grade PCa (p ≤ 0.001, p ≤ 0.001, and p = 0.015, respectively). After an adjustment for age, PSA level, and PSAD, MFB remained independently associated with overall PCa detection (adjusted OR 2.01, 95% CI 1.16–3.48, p = 0.013), csPCa detection (adjusted OR 2.83, 95% CI 1.58–5.08, p < 0.001), and high-grade PCa detection (adjusted OR 6.15, 95% CI 2.49–15.19, p < 0.001). PSAD was also independently associated with all cancer outcomes. Within the MFB cohort, PI-RADS 5 lesions demonstrated significantly higher odds of overall PCa (adjusted OR 7.38, 95% CI 2.18–24.98, p = 0.001), csPCa (adjusted OR 8.42, 95% CI 2.49–28.49, p < 0.001), and high-grade PCa detection (adjusted OR 6.93, 95% CI 1.82–26.41, p = 0.005) compared with PI-RADS 3 lesions. Conclusions: In this retrospective cohort, the MFB strategy was associated with higher detection rates of PCa, csPCa, and high-grade PCa compared with conventional SB. PSAD and MRI findings independently contributed to cancer prediction, supporting the integration of clinical and imaging parameters in prostate biopsy decision-making. These findings support the clinical value of MRI-directed biopsy strategies but should be interpreted cautiously because of the non-randomized allocation and the differences in biopsy route and sampling strategy. Full article

Objectives: To externally validate the Barcelona Predictive Models (BCN-PM 1 and 2) for detecting csPCa in an Ibero-American population. BCN-PM 1 was designed to reduce magnetic resonance imaging (MRI) use, whereas BCN-PM 2 aims to decrease unnecessary prostate biopsies. Methods: This prospective, multicenter study included 661 men with suspected PCa recruited in 2025 across three Ibero-American centers. All participants underwent MRI followed by targeted biopsies of lesions with the Prostate Imaging–Reporting and Data System (PI-RADS) ≥ 3, along with systematic biopsy. When PI-RADS lesions were <3, only systematic biopsies were performed. CsPCa was defined as International Society of Urological Pathology Grade Group ≥ 2. BCN-PM 1 incorporates age (years), family history of PCa (no vs. yes), prior negative prostate biopsy (no vs. yes), digital rectal examination (DRE: normal vs. suspicious), and prostate volume-derived estimation by DRE (small, median, or large). BCN-PM 2 includes age, family history of PCa, prior negative prostate biopsy, prostate volume measured by MRI (mL), and PI-RADS score (1–5). Results: The rate of csPCa detection was 53.7%. Both models demonstrated good calibration with strong agreement between predicted probabilities and observed csPCa rates. BCN-PM 1 closely followed the reference line, with minor deviations at higher predicted probabilities, whereas BCN-PM 2 showed modest departures at the extremes of risk. The area under the curve was 0.740 (95% CI 0.702–0.777) for BCN-PM 1 and 0.803 (95% CI 0.769–0.836) for BCN-PM 2 (p < 0.001). Decision curve analysis demonstrated a net benefit for both models compared with strategies of biopsy in all or no men. BCN-PM 2 showed greater net benefit than BCN-PM 1. At 95% sensitivity, BCN-PM 1 reduced MRI requests by 10.6%, while BCN-PM 2 avoided 19.4% of unnecessary biopsies. The sequential use of BCN-PM 1 and 2 resulted in a 10.6% reduction in MRI exams and a 23.1% reduction in biopsies, at the cost of missing 8.4% of csPCa cases. The performance of the biopsy improved from 53.7% to 64.0% (p < 0.001). Conclusions: BCN-PM1 and BCN-PM 2 were successfully validated in an Ibero-American population. Full article

Accurate multi-class segmentation of the prostate in T2-weighted magnetic resonance imaging (MRI) into the peripheral zone (PZ), central gland (CG) and tumour is essential for targeted biopsy guidance and treatment planning. We present DSBANet, an encoder–decoder architecture that combines a pretrained ResNet-50 encoder, Atrous Spatial Pyramid Pooling, Multi-Scale Attention Fusion on skip connections, a Feature Fusion Module, deep supervision and boundary refinement. We evaluate eight architectures across three input dimensionalities (2D, 2.5D, 3D), yielding 24 models trained under identical conditions on the Prostate158 dataset. DSBANet achieves the best anatomy segmentation with PZ DSC of 0.8176 and CG DSC of 0.7888 among 2D models. To address the severe class imbalance of the tumour class, we further train DSBANet 2D with a class-weighted cross-entropy term and tumour-positive slice oversampling, raising per-case tumour DSC from 0.003 to 0.170 (a sixty-fold absolute improvement). A systematic eight-variant ablation study, evaluated under matched-pairs effect-size analysis, identifies the SE-Residual blocks and skip-connection attention as the largest contributors to tumour segmentation, while every architectural component contributes a directionally consistent gain. Full article

Objective: This study aims to evaluate the additional diagnostic value of systematic (SBx) and perilesional biopsies (PBx) compared with targeted biopsy (TBx) in patients with mpMRI-detected PI-RADS 3-4–5 lesions. Methods: We performed a retrospective analysis of 208 men with PI-RADS ≥ 3 lesions who underwent mpMRI–ultrasound fusion biopsy at a single institution. Clinically significant prostate cancer (csPCa; ISUP ≥ 2) was identified in 155 patients (74.5%), who constituted the study cohort. All patients underwent a standardized biopsy protocol consisting of 3–5 TBx cores, 3 PBx cores sampled within a 10 mm radius of the index lesion, and 10 SBx cores using the KOELIS Trinity^® system. Detection rates of csPCa and ISUP grade upgrading were analyzed and stratified by PI-RADS category. Results: TBx csPCa detection rates increased progressively with PI-RADS score: 39% for PI-RADS 3, 50% for PI-RADS 4, and 60% for PI-RADS 5 lesions. PBx showed a 42.5% detection rate of csPCa in PI-RADS 3 and 58% and 85.3% of csPCa in PI-RADS 4 and 5 respectively, whereas SBx detected 34.5% of csPCa in PI-RADS 3, 46% of csPCa in PI-RADS 4, and 60.5% of csPCa in PI-RADS 5. Despite these detection rates, PBx and SBx rarely provided clinically meaningful upgrading over TBx findings. ISUP grade upgrading occurred in only 7.3% of PBx cases and 1.8% of SBx cases in PI-RADS 5 lesions, with similarly low upgrading rates observed in PI-RADS 3–4 lesions. Conclusions: In patients with high-grade lesions like PI-RADS 4–5, TBx alone identifies the vast majority of csPCa, while SBx and PBx contribute minimal additional diagnostic or grading benefit. These findings support biopsy de-escalation strategies in high-risk mpMRI settings to reduce unnecessary sampling and procedure-related morbidity. On the other hand, in the PI-RADS 3 subgroup, omitting non-targeted sampling (SBx and/or PBx) may lead to underdiagnosis of higher-grade tumors not captured by TBx alone, potentially resulting in substantial changes in therapeutic strategy and, consequently, patient prognosis. Full article

Background/Objectives: Active surveillance (AS) is recommended for men with low-risk prostate cancer to minimize overtreatment while monitoring for disease progression. However, current surveillance strategies rely heavily on repeat biopsies, which are invasive and associated with morbidity. MyProstateScore 2.0—Active Surveillance (MPS2-AS) is a urine-based biomarker test developed to predict progression to Grade Group ≥ 2 (GG ≥ 2) and Grade Group ≥ 3 (GG ≥ 3) prostate cancers in men on AS. The objective of this study was to analytically validate the reproducibility and robustness of MPS2-AS analyte detection and risk score calculation across key laboratory variables. Methods: Analytical precision was evaluated using pooled urine specimens processed using the MPS2-AS laboratory workflow. Eight pooled urine samples were tested in a within-laboratory design across five days, with two runs per day, and two replicates per run. Additional reproducibility studies assessed variability across three QuantStudio™ 12K Flex Real-Time PCR Systems and three OpenArray™ chip lots. Ten RNA biomarkers were quantified by RT-PCR and used to calculate the MPS2-AS GG1-2 and GG1-3 risk scores. Variance components were estimated using hierarchical ANOVA. Results: The MPS2-AS analyte measurements demonstrated high precision across within-laboratory testing, with standard deviations ranging from 0.00 to 0.60 and coefficients of variation (%CV) from 0.00 to 4.01%. The reproducibility across qPCR instruments and OpenArray chip lots showed similar robustness, with analyte %CVs of ≤4.57% and ≤4.10%, respectively. These stable analyte measurements translated to reproducible model outputs, with %CV ≤ 10.69% for the GG1-2 risk score and ≤7.20% for the GG1-3 risk score across all tested conditions. No systematic bias was observed between runs, days, instruments, or reagent lots. Conclusions: MPS2-AS demonstrates strong analytical precision and reproducibility for quantifying urinary biomarkers and generating GG1-2 and GG1-3 risk scores. These results support the reliability of MPS2-AS for clinical laboratory implementation and its use as a non-invasive tool to inform biopsy decisions in men with Grade Group 1 prostate cancer undergoing active surveillance. Full article

Background/Objectives: Active surveillance (AS) has become the gold standard for managing men diagnosed with low-risk or favorable intermediate-risk prostate cancer. However, both patients and healthcare providers often face a lack of clear, evidence-based guidance regarding lifestyle choices during this period. This systematic review was designed to determine whether specific lifestyle modifications—including dietary changes, physical activity, weight control, and use of supplements—can tangibly impact oncologic outcomes or improve patient-reported quality of life during surveillance. Methods: The research followed PRISMA protocols, searching PubMed, Cochrane, and Scopus for studies published between 2000 and 2025. The team included diverse methodologies, from randomized controlled trials to qualitative interviews, specifically focusing on men on AS. To ensure high standards, two independent reviewers performed data extraction and quality assessments using CASP tools, and the review was formally registered with PROSPERO. Results: The review synthesized data from over 30 heterogeneous studies. The findings suggest that lifestyle interventions are safe and highly feasible. Physical exercise emerged as the most effective intervention, consistently improving cardiorespiratory fitness and reducing psychological burdens such as fatigue and “PSA anxiety.” While dietary changes and weight loss successfully improved metabolic health markers, they did not show a consistent ability to prevent biopsy upgrading or MRI progression. Similarly, supplements showed only minor, short-term effects on PSA kinetics without providing reproducible oncologic protection. Conclusions: For men undergoing active surveillance, lifestyle interventions may be considered as supportive measures, as they appear feasible and may improve physical fitness, metabolic health, and selected patient-reported outcomes. However, current evidence remains insufficient to demonstrate a consistent effect on biopsy upgrading, MRI progression, or long-term deferral of definitive treatment. Full article

Background/Objectives: Prostate cancer (PCa) incidence is rising, with radical prostatectomy (RP) as the main curative surgery for localised cases, which includes removing seminal vesicles (SV). SV invasion (SVI) predicts poor oncological outcomes, making accurate preoperative staging to identify SVI crucial for surgical planning. This ensures oncological safety by enabling wide excision when needed, while preserving tissue to maintain function. This review synthesises current evidence on pre-biopsy MRI findings and/or clinicopathological parameters to diagnose SVI in PCa. Methods: A literature search (2005–2025) using OVID for studies assessing pre-biopsy MRI findings, with a priori eligibility for clinicopathological or combined MRI–clinicopathological models (index tests), for detecting SVI (outcome) compared to RP histopathology (standard reference) in patients with primary localised PCa (patients). This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Risk of bias was evaluated with QUADAS-2, and pooled diagnostic accuracy metrics and study heterogeneity were analysed. Results: Five studies qualified, while three used binary mpMRI classification and were quantitatively analysed. No eligible studies assessed clinicopathological predictors or combined MRI–clinicopathological models; all included studies evaluated pre-biopsy MRI findings only, and none included high-dimensional radiomics. The pooled sensitivity was 0.66 (95% CI: 0.52–0.78), specificity 0.94 (0.89–0.97), positive predictive value (PPV) 0.76 (0.60–0.87), negative predictive value (NPV) 0.92 (0.85–0.94), and diagnostic odds ratio 30.13 (12.36–73.47), with moderate heterogeneity. All included studies were retrospective cohorts with considerable risk of bias. Conclusions: In the small number of heterogeneous, single-centre retrospective studies available, pre-biopsy MRI findings show high specificity and NPV for preoperative detection of SVI but only moderate sensitivity, which limits its reliability as a standalone tool. The pooled diagnostic accuracy estimates should be interpreted as exploratory. These findings should therefore be interpreted cautiously. Future studies must integrate MRI with clinicopathological data, addressing this key evidence gap before firm conclusions can be drawn or clinical practice changed. Full article

Background and Objectives: Prostate cancer is the second most common cancer in men worldwide, with 1,466,680 new cases and 396,792 deaths reported in 2022. Accurate preoperative grading is critical, as the grade assessed on biopsy cores may be underestimated compared to radical prostatectomy specimens. The aim of this study was to assess the ability of quantitative diffusion parameters derived by the standard monoexponential model (ADC—apparent diffusion coefficient) and kurtosis model (Dapp—apparent diffusion coefficient corrected for non-Gausion behavior and K-kurtosis) to predict Gleason Grade Group (GG) upgrading from transrectal ultrasound-guided (TRUS) biopsy to radical prostatectomy within each GG. Materials and Methods: This retrospective study included 128 patients with prostate cancer who underwent systematic TRUS biopsies and multiparametric magnetic resonance imaging (mpMRI) at 3T before prostatectomies between 2017 and 2021. Mean values of quantitative diffusion parameters (ADC, Dapp, K) were compared between upgraded and non-upgraded cohorts within each Grade Group obtained at biopsy. Results: Significant differences in ADC and K values were found between upgraded and non-upgraded lesions in GG1 and GG2 cohorts at biopsy, with lower ADCs and higher K values indicating a higher likelihood of upgrading. In GG1, ADC demonstrated an AUC of 0.762 (p < 0.05) and K an AUC of 0.846 (p < 0.05). In GG2, ADC showed an AUC of 0.814 (p < 0.001) and K an AUC of 0.755 (p < 0.001). No significant differences were observed in GG3 and GG4 cohorts. Conclusions: Quantitative diffusion parameters—particularly ADC and kurtosis (K)—demonstrated significant predictive value for Grade Group upgrading in patients with biopsy-proven GG1 (AUC: K = 0.846, ADC = 0.762) and GG2 (AUC: ADC = 0.814, K = 0.755, D = 0.810) prostate cancer. These findings suggest that incorporating quantitative DWI parameters into preoperative assessments may improve risk stratification and support clinical decision-making, particularly regarding the selection of patients for active surveillance. Validation in larger, multicenter cohorts is warranted. Full article

Background: Lower urinary tract symptoms (LUTSs) are among the most common urological complaints in older men, frequently arising from benign prostatic hyperplasia (BPH) or prostate cancer (PCa). While both conditions share overlapping symptomatology, the way each condition progresses and is managed differs considerably. In sub-Saharan Africa, data on the relative burden of BPH and PCa among men presenting with LUTSs are scarce. This study aimed to determine the prevalence of histologically confirmed BPH and PCa among men presenting with LUTSs at a major tertiary referral center in Tanzania and to explore the association between specific urinary symptoms and histopathological diagnoses. Methods: A retrospective cross-sectional study was conducted at Muhimbili National Hospital (MNH), Dar es Salaam, Tanzania, reviewing medical records of adult male patients aged ≥50 years who presented with LUTSs and underwent prostatic biopsy between January and December 2023. A total of 133 patients were included through simple random sampling from an eligible population of 260. Data on demographics, comorbidities, International Prostate Symptom Score (IPSS), serum prostate-specific antigen (PSA), prostate volume, and histopathological biopsy outcomes were extracted using a purpose-built digital form. This study was conducted in compliance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Results: Most patients (39.8%) were aged 70 to 79 years. Hypertension was the most frequent comorbidity among those with chronic disease (31.65%), followed by diabetes mellitus (12.03%). The mean serum PSA was 465.1 ng/mL (SD = 1610.1), and the mean prostate volume was 80.6 cm³ (SD = 75.6). Histopathologically, 57.9% of biopsies were benign and 40.6% were malignant. The most commonly reported IPSS symptoms were urinary frequency (78.2%), weak stream (78.2%), and incomplete emptying (64.7%). Most patients (59.4%) had severe IPSSs. Statistically significant associations were observed between biopsy outcomes and incomplete emptying (p = 0.011), frequency (p = 0.014), weak stream (p = 0.022), nocturia (p = 0.001), urge incontinence (p = 0.004), and post-void dribbling (p < 0.001). IPSS severity was significantly associated with biopsy diagnosis (p < 0.001), with 63% of malignant cases presenting with moderate symptom scores. Conclusions: BPH was the predominant histopathological diagnosis among men presenting with LUTSs at this tertiary center, while prostate cancer accounted for a substantial minority of cases. Certain individual LUTSs, particularly nocturia, urge incontinence, and post-void dribbling, demonstrated significant associations with malignant histopathology. These findings underscore the necessity for systematic histopathological evaluation in all men presenting with LUTSs in resource-limited settings, irrespective of symptom severity. Full article

Given ongoing uncertainty about the benefits and harms of prostate-specific antigen (PSA) screening, this systematic review updates the evidence to inform guideline recommendations for adults aged ≥ 18 years in primary care. We searched multiple bibliographic databases from inception to 30 May 2022, with an update on 24 July 2024, for randomized controlled trials (RCTs) and comparative observational studies evaluating PSA-based screening with or without adjunctive technologies such as magnetic resonance imaging (MRI). Studies were selected in duplicate, with data extraction and quality assessment verified by a second reviewer; risk of bias and evidence certainty were assessed using study design-specific tools and GRADE. Four RCTs and one cohort study (17 articles) were included: ERSPC, PLCO and CAP compared PSA screening with no screening, while STHLM3-MRI evaluated a risk-based test combined with MRI targeted biopsy. Meta-analysis showed 0.96 fewer prostate cancer deaths per 1000 individuals invited to screen, corresponding to a 12% relative reduction over 9.5–22 years (RR 0.88, 95% CI 0.81–0.95). One trial estimated 2.3% to 10.3% overdiagnosis over 10–14 years. Overall certainty of evidence was low or very low. PSA screening may offer a small mortality benefit, but uncertainty and variable harms limit confidence, underscoring the need for high-quality evidence, particularly for MRI and risk-based screening strategies. Full article

Prostate cancer (PCa) is one of the most commonly diagnosed malignancies among men worldwide. Prostate-specific antigen (PSA) testing has improved early detection; however, PSA levels within the so-called “gray zone” (4–10 ng/mL) remain a diagnostic challenge because of their limited specificity and the associated risk of unnecessary biopsies. In this clinical context, an important objective is the accurate identification of clinically significant prostate cancer (csPCa), defined as disease with a higher likelihood of progression or clinical impact. In recent years, several diagnostic approaches and risk prediction models have been proposed to improve csPCa detection in patients within the PSA gray zone. These models combine clinical parameters, PSA-derived indices, and imaging findings—particularly magnetic resonance imaging (MRI)—and, in some cases, incorporate advanced biomarkers or radiomic features. Nevertheless, considerable heterogeneity exists across studies with respect to predictor selection, model construction, and reported diagnostic performance. This systematic review aims to synthesize current evidence on the diagnostic characteristics and predictive models used to detect clinically significant prostate cancer in men with PSA levels between 4 and 10 ng/mL. For consistency, heterogeneous outcome terms used in the included studies (e.g., “probable csPCa”, “significant cancer”, “clinically important PCa”) were harmonized and analyzed under the unified term csPCa. By identifying the most consistently reported predictors and comparing univariate with multivariate approaches, this review seeks to support clinical decision-making and to highlight areas for future research in prostate cancer diagnosis within the PSA gray zone. Full article

Background: Multiparametric MRI is central to detecting clinically significant prostate cancer (csPCa), but diagnostic accuracy depends on reader experience. Artificial intelligence (AI) tools may support prostate MRI interpretation and reduce inter-reader variability. This study compared the detection rate of a trial, non-commercial version an AI-based software (PAROS) with that of an experienced radiologist. Methods: This retrospective single-center study included 150 patients who underwent prostate MRI followed by combined systematic and MRI-targeted transperineal biopsy. MRI examinations were interpreted by an experienced radiologist according to PI-RADS v2.1 and independently analyzed using a precommercial trial version of PAROS operating on biparametric MRI. Histopathology served as the reference standard. Detection rate was evaluated using sensitivity, specificity, and positive and negative likelihood ratios (PLR and NLR) at PI-RADS thresholds ≥3 and ≥4. Results: CsPCa was present in 63.3% of patients. At both PI-RADS thresholds, PAROS and the radiologist showed comparable sensitivity and specificity, wuth extremely low NLRs, indicating excellent rule-out capability. PLRs were modest and similar at PI-RADS ≥ 3 (1.26 vs. 1.42) and 1.88 for both at PI-RADS ≥ 4. PAROS detected more lesions, particularly in the transition zone. Conclusions: PAROS achieved csPCa detection comparable to an experienced radiologist, supporting its role as a decision-support tool in prostate MRI interpretation. Full article

Background/Objectives: Despite multiparametric MRI (mpMRI)-guided biopsy, clinically significant upgrading (CSU) of ISUP Grade Group (GG) at radical prostatectomy (RP) remains common in prostate cancer (PCa). We aimed to identify predictors of CSU (biopsy GG ≤ 2 to RP GG ≥ 3) using routine preoperative variables, and to benchmark a parsimonious logistic model against multiple machine learning (ML) classifiers. Methods: In this single-center exploratory analysis, 96 consecutive PCa patients underwent pre-biopsy mpMRI, systematic ± MRI-targeted biopsy, and RP. Predictive modeling was restricted to biopsy GG 1–2 patients (n = 64). LASSO-guided feature selection and Firth-penalized logistic regression were used to build a locked reference model, evaluated against ML classifiers using cross-validated discrimination, calibration, and decision curve analysis. Results: CSU occurred in 10/64 patients (15.6%). Positive core ratio was the dominant independent predictor (adjusted OR 1.54 per 10% increase, 95% CI 1.10–2.17). PSA density (PSAD) showed a consistent positive association but did not retain independent significance. The locked two-variable model (AUC ≈ 0.75–0.79) outperformed all ML classifiers in discrimination, calibration, and net clinical benefit; however, the limited event count (n = 10) constrains model stability, and these findings require external validation. Conclusions: In a PCa mpMRI-informed diagnostic pathway, CSU is primarily driven by biopsy tumor burden. A simple logistic model based on positive core ratio and PSAD outperformed more complex ML approaches in this exploratory cohort, supporting integration of biopsy tumor burden metrics into preoperative risk stratification pending external validation. Full article