Search Results (58)

Objective: Quantib^® Prostate is a commercially available machine learning software (MLS) used for prostate magnetic resonance imaging (MRI), approved by the Food and Drug Administration (FDA) and Conformité Européenne (CE). We aimed to assess the agreement between biparametric MRI (bpMRI) interpretations produced by radiologists and by Quantib^® alone. Material and Methods: This single-centre, retrospective, and observational study included 188 bpMRI scans from the Innlandet Hospital Trust, Norway. Radiologists’ Prostate Imaging Reporting and Data System (PI-RADS) scores were compared with scores produced by the Quantib^® Prostate PI-RADS, which was used as an autonomous software. Additionally, for exploratory purposes, the PI-RADS scores were compared with biopsy findings, using the radiologist’s scorings to determine biopsy indications. Results: For PI-RADS scores generated by radiologists vs. those produced by Quantib^® Prostate, the weighted kappa was 0.49 (95% CI: 0.37–0.59), and 46% of the PI-RADS scores differed by at least one unit. In the sample, 125 men (66%) had a prostate biopsy, and for male patients with PI-RADS scores of 4–5, the probability of detecting cancer grades 2–5 via biopsies was 64% (95% CI: 56–71) for radiologists and 58% (95% CI: 54–62) for Quantib^® Prostate. The main limitations of this study are the retrospective, single-centre design, the small sample size, the use of Quantib^® Prostate in an autonomous manner, and verification bias, as the biopsy decisions were based solely on PI-RADS scoring by radiologists. Conclusions: We identified inter-rater variability between PI-RADS scores generated by Quantib^® Prostate and radiologists’ assessments, and the agreement between the two scoring groups is moderate. Our results suggest that Quantib^® Prostate requires further clinical comparative studies before it is used in clinical routines. Full article

Background: Active surveillance (AS) criteria in prostate cancer (PCa) are expanding to include selected patients with intermediate-risk features. This multicenter retrospective study aimed to validate a proposed risk group (RG) classification for predicting unfavorable pathology (UP) in radical prostatectomy specimens among patients eligible for AS under expanded criteria. Methods: Patients from three Andalusian university hospitals who met the AS criteria, defined as prostate-specific antigen (PSA) ≤ 20 ng/mL, International Society of Urological Pathology (ISUP) ≤ 2, and clinical stage ≤ cT2, were included. The patients were stratified into five RGs according to PSA density, Prostate Imaging Reporting and Data System score (PI-RADS), and clinical stage. UP was defined as ≥pT3a and/or pN+ and/or ISUP grade ≥ 3. Results: A total of 244 patients were analyzed. The median age was 63 years, the median PSA 5.98 ng/mL, and the median PSA density was 0.14 ng/cc. UP was identified in 47.1% of radical prostatectomy specimens, increasing progressively across RGs from 20.8% to 93.3%. Each incremental RG was associated with a higher risk of UP, with an odds ratio of 2.14 and moderate predictive accuracy, as reflected by an area under the curve of 0.70. Conclusions: The proposed RG classification showed moderate predictive capacity for UP and may improve risk stratification in intermediate-risk patients considered for AS. 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

Background: Minimum apparent diffusion coefficient (ADC) values are independent predictors of clinically significant prostate cancer (csPC). We developed a novel ADC-based bi-color map and evaluated its utility for identifying lesions suspicious for csPC. Methods: We retrospectively analyzed 108 targeted prostate biopsy cases and 93 radical prostatectomy cases. In the biopsy cohort, we assessed the association between ADC-based bi-color map positivity and csPC in lesions with a Prostate Imaging–Reporting and Data System (PI-RADS) score ≥ 3. In the prostatectomy cohort, we evaluated additional color map-positive lesions not categorized as PI-RADS ≥ 3 on preoperative MRI. Results: In the biopsy cohort, 118 lesions were positive on the ADC-based bi-color map, including lesions outside PI-RADS ≥ 3 categories. Among 157 lesions with a PI-RADS score ≥ 3, csPC was detected in 65 lesions (41.4%). Of these lesions, 70 (44.6%) were positive on the bi-color map, and csPC was identified in 49 (70.0%). The added value of the bi-color map was most evident in PI-RADS 4 lesions, where csPC detection rates were significantly higher in color map-positive than in color map-negative lesions (74.4% vs. 23.3%). In the prostatectomy cohort, 215 lesions were positive on the bi-color map, and csPC was confirmed pathologically in 126 lesions (58.6%). Among 82 color map-positive lesions not classified as PI-RADS ≥3, 55 (67.1%) corresponded to csPC. Conclusions: The ADC-based bi-color map may improve lesion highlighting and risk stratification for csPC and help identify suspicious lesions overlooked on conventional MRI assessment. Full article

Background/Objectives: Early detection of prostate cancer (PCa) enables timely therapeutic intervention and improved clinical outcomes. Screening strategies are increasingly individualized and now incorporate multiparametric MRI findings, reported using the Prostate Imaging Reporting and Data System (PI-RADS), to refine biopsy decision-making. PROSTest is a novel machine learning (ML)-enhanced, 30-gene mRNA liquid biopsy assay developed to detect PCa from whole blood. In this prospective study (NCT06872619), we evaluated whether PROSTest could function as a pre-biopsy triage tool to inform biopsy decisions while preserving sensitivity for clinically significant prostate cancer (csPCa). Methods: Of 121 men evaluated, 111 (91.7%) completed the full diagnostic work-up—including PSA testing, PROSTest analysis, and PI-RADS assessment—and subsequently underwent image-guided biopsy. Peripheral blood samples for PROSTest were collected prior to biopsy. RNA-stabilized samples underwent RNA isolation followed by reverse transcription and quantitative PCR. Gene expression data were processed using a proprietary machine learning algorithm to generate a continuous range from 0 to 100. A clinically validated cut-off ≥ 50 was applied to produce a binary (positive/negative) result. The diagnostic accuracy of PROSTest was assessed against histology-confirmed prostate cancer. Results: The median age of participants was 69 years (47–83 years) and the median PSA was 7.5 ng/mL (IQR: 5.8–11.4 ng/mL); most patients (104 of 111; 93.7%) had a PI-RADS score of three to five. PCa was diagnosed in 97 men (87.4%) including eight in ISUP Grade Group (GG) 1, 46 in GG2, 33 in GG3, three in GG4 and seven in GG5. PROSTest was positive in 102/111 (91.9%). Among men with biopsy-confirmed PCa, diagnostic accuracy was 99% (93/94). Of the 17 men without histologic evidence of disease, eight (47%) were PROSTest-negative. The overall accuracy was 91% (84.1–95.6%) with an NPV of 89% (51.6–98.4%). Among the nine patients with positive PROSTest but negative biopsy, PI-RADS scores were 4 (n = 6), 3 (n = 1), and 2 (n = 2). Conclusions: PROSTest demonstrated an overall accuracy of 91% (95% CI: 84.1–95.6%) with an NPV of 89%. Among men without a detectable prostate cancer on biopsy, 47% (8/17) were PROSTest-negative. These results suggest that PROSTest may serve as a useful pre-biopsy triage assay. Full article

Objective: We evaluate the performance and relevance of MRI to detect csPC in men with normal PSA. Methods: Out of our database of patients referred for prostate MRI, we selected men with PSA < 4 ng/mL for whom histopathology or at least 2 years of clinical follow-up data were available as standard of reference. Subgroup analyses were performed for the patients with PSA < 3 ng/mL, <2 ng/mL, and 2–3.9 ng/mL. The reasons for prostate MRI referral despite their normal PSA level were retrieved by exploring the patients’ files. The prostate MRIs were reported according to the Prostate Imaging and Reporting Data System (PI-RADS), and the overall assessment score was registered. For evaluation of the performance, PI-RADS ≥ 3 was set as a threshold for a positive exam. The patients without PC or only International Society of Urological Pathology (ISUP) grade group 1 PC (Gleason 3+3) were considered as one category having no csPC. The performance of prostate MRI was separately evaluated for detection of ISUP ≥ 2 and for ISUP ≥ 3 csPC. Results: A total of 148 men were included, with PSA ranging from 0.42 to 3.99 ng/mL (median 2.95, IQR 1.68–3.50) and age ranging from 36 to 84 years (median 58, IQR 52–66). A total of 74 men (50.0%) had a PSA level < 3 ng/mL, 42 (28.4%) had a PSA level < 2 ng/mL, and 106 (71.6%) had a PSA level of 2–3.9 ng/mL. They were referred for prostate MRI for a wide variety, and usually a combination of, reasons, such as younger age (<60 years in 55.4%, N = 82; <50 years in 17.6%, N = 26), abnormal digital rectal examination in 31.8% of cases (N = 47), suspicious PSA dynamics in 29.7% (N = 44), positive familial history in 27.0% (N = 40), clinical signs of prostatitis in 18.2% (N = 27), suspicious findings on Transrectal Ultrasound (TRUS) in 16.9% (N = 25), hematospermia in 7.4% (N = 11), hematuria in 4.1% (N = 6), incidental hot spot in the prostate on Fluoro-Deoxy-Glucose (FDG) Positron Emission Tomography (PET)–Computed Tomography (CT) in 4.1% (N = 6), lymphadenopathies on CT in 2.7% (N = 4), or severe patient anxiety in 3.4% (N = 5). Overall, ISUP ≥ 2 PC was present in 18.9% (N = 28) of cases, and MRI detected this with a sensitivity of 92.9%, a specificity of 66.7%, and a positive predictive value of 39.4%. ISUP ≥ 3 PC was present in 9.5% (N = 14) of cases, and prostate MRI detected this with a sensitivity of 100%, a specificity of 61.2%, and a positive predictive value of 21.2%. In patients with PSA < 2 ng/mL (N = 42), no csPC was found, but MRI generated false positives in 33.3%. Conclusions: Performing prostate MRI in men with normal PSA (<4 ng/mL) seems useful if there are other reasons that increase the clinical suspicion of csPC. In about one-fifth of these patients, csPC is present and MRI has high sensitivity for its detection. Prostate MRI has, however, low positive predictive value in this patient group, and clinicians should be aware of the risk of false-positive MRI. Below a PSA level of 2 ng/mL, no csPC was found and prostate MRI generated only false positives, suggesting limited value in this subgroup. Full article

Background/Objectives: Multiparametric MRI (mpMRI) and targeted biopsies have revolutionized prostate cancer (PC) detection through the Prostate Imaging Reporting and Data System (PIRADS). However, the effect of prostate volume on cancer detection and the predictive accuracy of PIRADS in the mpMRI-guided biopsy era remains unclear. The aim was to assess whether prostate volume affects detection rates of clinically significant prostate cancer (CSPC) and high-risk prostate cancer (HRPC) and modifies the predictive performance of the PIRADS score. Methods: We retrospectively analyzed 361 biopsy-naïve men who underwent mpMRI-fusion transperineal biopsies between 2016 and 2023. Lesions graded PIRADS ≥ 3 were targeted alongside systematic sampling. A receiver-operating characteristic (ROC) curve (AUC = 0.74) defined a 44 mL cutoff separating small (<44 mL; n = 160) and large (≥44 mL; n = 193) prostates. Logistic regression and cubic-spline analyses evaluated associations between prostate volume, PIRADS, and cancer outcomes. Results: Any cancer was detected in 74.3% of small versus 35.5% of large prostates (p < 0.001); CSPC in 42.5% vs. 19.6% (p < 0.001); HRPC in 14.3% vs. 5.5% (p < 0.001). Small prostate volume independently predicted any cancer (OR 7.31; 95% CI 4.22–12.7), CSPC (OR 5.08; 95% CI 2.87–8.99), and HRPC (OR 4.50; 95% CI 1.80–11.3). Between 40 and 70 mL, each 10 mL increase in volume reduced CSPC risk by 61% (p = 0.008). Prostate volume significantly modified PIRADS accuracy: in large glands, PIRADS 3 lesions carried only 2% risk for CSPC and 0% for HRPC, while in small prostates, PIRADS 3 conferred a 16.9-fold increased CSPC risk. Conclusions: Prostate volume inversely correlates with cancer detection and aggressiveness. PIRADS performance is volume-dependent; PIRADS 3 lesions in large prostates rarely represent significant cancer and may not warrant biopsy. Full article

Background/Objectives: Whole-gland surgery or radiotherapy for localized prostate cancer (PCa) can cure the disease but often impair urinary and sexual function. Focal therapy with high-intensity focused ultrasound (HIFU) seeks to eradicate the tumor while sparing uninvolved tissue. We prospectively evaluated oncological control, functional outcomes and safety of MRI-guided focal HIFU in patients with low- or intermediate-risk PCa. Methods: In this prospective, single-arm, phase II feasibility trial (three Austrian centres, 2021–2024), treatment-naive patients with D’Amico low/intermediate-risk, PSA ≤ 15 ng/mL, clinical stage ≤ T2 and MRI-targeted, biopsy-confirmed index lesions underwent lesion-targeted HIFU (Focal One™). The primary endpoint was failure-free survival (FFS: absence of salvage whole-gland or systemic therapy, metastasis or PCa-specific death). Secondary endpoints included biopsy-proven cancer, prostate-specific antigen (PSA), patient-reported symptoms as International Prostate Symptom Score (IPSS), 5-item International Index of Erectile Function (IIEF), Gaudenz Incontinence Questionnaire and adverse events. Planned follow-up was 24 months with PSA every 3 months, mpMRI and biopsies at 12 months, and imaging- or PSA-triggered biopsies thereafter. Results: Fifty-one men were analysed in the per-protocol cohort (median age 67 years, median PSA 7.55 ng/mL). Median treated volume was 12 mL; median procedure time 85 min. At 24 months, FFS was 94.1%: 3/51 patients (5.9%) required salvage radiotherapy. Among 31 patients who underwent follow-up biopsy, 26 (83.9%) had no cancer; the five positives included three ISUP 1, one ISUP2 and one ISUP 4 lesion. Mean PSA fell by 69% at 3 months (to 2.3 ng/mL) and then stabilized under 3 ng/mL, with a mean of 2.7 ± 1.5 ng/mL at 24 months. Transient acute urinary retention occurred in 11/51 (21.6%); no Clavien–Dindo grade ≥ 4 events were reported. IPSS returned to or improved beyond baseline, erectile function largely recovered by 6–12 months, and only one new case of grade 2 incontinence was observed. Conclusions: MRI-guided focal HIFU achieved high two-year failure-free survival with low morbidity and preserved quality of life in carefully selected patients with low- or intermediate-risk PCa. These data support further randomized and longer-term investigations of focal HIFU as an organ-sparing alternative to whole-gland treatment. Full article

Background/Objectives: This study aimed to assess whether magnetic resonance elastography (MRE)-derived stiffness measurements of the central gland, entire gland, and lesions of the prostate differ among benign, premalignant, and malignant lesions and to evaluate their diagnostic performance in distinguishing these groups. Methods: This prospective study enrolled 113 men (mean age, 62.7 ± 7.2 years). Patients were categorized into benign (n = 75), premalignant (n = 15; atypical small acinar proliferation and high-grade prostatic intraepithelial neoplasia), and malignant (n = 23; adenocarcinoma) lesion groups based on histopathological findings. MRE-derived stiffness was measured at the lesion, central gland, and entire gland levels. Other evaluated parameters included diffusion restriction, contrast retention, prostate-specific antigen (PSA) levels, prostate volume, and Prostate Imaging Reporting and Data System (PI-RADS) score. Results: Mean central gland stiffness did not differ between benign and premalignant lesions, but was markedly higher in the malignant group (Benign: 3.3 ± 0.2 vs. Premalignant: 3.4 ± 0.2 vs. Malignant: 3.6 ± 0.3 kPa; p < 0.001). A similar pattern was observed for entire gland stiffness (Benign: 3.3 ± 0.4 vs. Premalignant: 3.3 ± 0.4 vs. Malignant: 4.1 ± 0.6 kPa; p < 0.001). Median lesion stiffness increased stepwise from benign to premalignant to malignant lesions (Benign: 3.6 vs. Premalignant: 5.8 vs. Malignant: 7.7 kPa; p < 0.001). Central and entire gland stiffness distinguished malignant lesions but failed to differentiate premalignant lesions from benign lesions. Lesion stiffness demonstrated superior diagnostic accuracy in distinguishing premalignant from benign (AUC 0.82; accuracy 83.3%) and malignant lesions from premalignant lesions (AUC 0.86; accuracy 82.5%) compared to central and entire gland stiffness. Conclusions: MRE-derived lesion stiffness is a promising diagnostic biomarker, effectively distinguishing benign, premalignant, and malignant prostate lesions. Prostate gland stiffness measured by MRE, especially lesion-specific measurements, may be considered as an additional candidate procedure that can be accommodated in multiparametric magnetic resonance imaging. Full article

Background/Objectives: It remains unclear whether certain areas of the prostate are more difficult to accurately sample using MRI/US-fusion-guided freehand single-access transperineal prostate biopsy (FSA-TP). The aim of this study was to evaluate the detection rates of clinically significant (cs) and clinically insignificant (ci) prostate cancer (PCa) in each prostate zone during FSA-TP MRI-target biopsies (MRI-TBs) and systematic biopsies (SB). Methods: This monocentric observational study included a cohort of 277 patients with no prior history of PCa who underwent 3 MRI-TB cores and 14 SB cores with an FSA-TP from January to December 2023. The intraclass correlation coefficient (ICC) was assessed to evaluate the correlation between the Prostate Imaging–Reporting and Data System (PI-RADS) of the index lesion and the International Society of Urological Pathology (ISUP) grade stratified according to prostate zone and region of index lesion at MRI. Multivariate logistic regression analysis was conducted to identify factors associated with PCa and csPCa in patients with discordant results between MRI-TB and SB. Results: FSA-TP-MRI-TB demonstrated higher detection rates of both ciPCa and csPCa in the anterior, apical, and intermediate zones when each of the three MRI-TB cores was analysed separately (p < 0.01). However, when all MRI-TB cores were combined, no significant differences were observed in detection rates across prostate zones (apex, mid, base; p = 0.57) or regions (anterior vs. posterior; p = 0.34). Concordance between radiologic and histopathologic findings, as measured by the intraclass correlation coefficient (ICC), was similar across all zones (apex ICC: 0.33; mid ICC: 0.34; base ICC: 0.38) and regions (anterior ICC: 0.42; posterior ICC: 0.26). Univariate analysis showed that in patients with PCa detected on SB but with negative MRI-TB, older age was the only significant predictor (p = 0.04). Multivariate analysis revealed that patients with PCa detected on MRI-TB but with negative SB, only PSA remained a significant predictor (OR 1.2, 95% CI 1.1–1.4; p = 0.01). In cases with csPCa detected on MRI-TB but with negative SB, age (OR: 1.0, 95% CI 1.0–1.1; p = 0.02), positive digital rectal examination (OR: 2.0, 95% CI 1.1–3.8; p = 0.03), PI-RADS score >3 (OR: 4.5, 95% CI 1.7–12.1; p < 0.01), and larger lesion size (OR: 1.1, 95% CI 1.1–1.2; p < 0.01) were significant predictors. Conclusions: FSA-TP using 14 SB cores and 3 MRI-TB cores ensures comprehensive sampling of all prostate regions, including anterior and apical zones, without significant differences in detection rates between nodules across different zones. Only in a small percentage of patients was csPCa detected exclusively by SB, highlighting the small but important complementary value of combining SB and MRI-TB. Full article

As the adoption of focal therapy (FT) for prostate cancer (PCa) grows, the demand for accurate post-treatment imaging to monitor outcomes and detect residual or recurrent cancer increases. Traditional diagnostic systems like the Prostate Imaging Reporting and Data System (PI-RADS) are ill-suited for post-FT evaluations due to treatment-induced tissue changes. MRI-based scoring systems specific for evaluation after FT have been developed to address these challenges and improve post-FT imaging accuracy by distinguishing benign alterations from recurrence. The currently developed scoring systems are Transatlantic Recommendations for Prostate Gland Evaluation with MRI after Focal Therapy (TARGET) and Prostate Imaging after Focal Ablation (PI-FAB). In this review, we describe and compare these two systems. These scoring systems standardize imaging assessments, enhance follow-up care, and support clinical decision-making. While promising, TARGET and PI-FAB require further large-scale validation to confirm their utility. Nevertheless, they represent critical advances in optimizing PCa management, particularly for patients undergoing FT, by improving diagnostic accuracy and guiding treatment decisions. Full article

Background/Objectives: The objective of this study was to evaluate the oncological outcomes and safety of nerve-sparing (NS) robot-assisted radical prostatectomy (RARP) when applied without Prostate Imaging-Reporting and Data System (PI-RADS) ≥3 lesions or Gleason pattern ≥4 on biopsy in the peripheral zone (PZ). Methods: We retrospectively analyzed 208 patients who underwent RARP between August 2017 and December 2022, excluding those who had received preoperative hormonal therapy. After NS status stratification and patient characteristic adjustment using propensity score matching (PSM), positive resection margin (RM) rates and prostate-specific antigen (PSA) recurrence-free survival were compared. Urinary and sexual quality of life (QOL) were assessed using the Expanded Prostate Cancer Index Composite, along with predictive factors associated with positive RM and RM locations in the NS group. Results: NS was performed in 68.6% (n = 129) patients. After PSM, there were no significant differences in RM positivity (p = 0.811) or PSA recurrence-free survival (Log-rank p = 0.79), regardless of NS status. There was no difference in sexual function between groups, but urinary QOL was significantly better in the NS group from the third month onward. In the NS group, RM positivity was 27.9% (n = 36), and diagnostic PSA (odds ratio [OR], 1.110, p = 0.038) and clinical T stage (OR, 1.400, p = 0.038) were predictive factors. The RM positivity rate on the NS side was 10.8%. Conclusions: NS, based on the absence of PI-RADS ≥3 lesions or Gleason pattern ≥4 in PZ, did not increase RM positivity rate and increased early urinary QOL. Full article

Background: The increase in multiparametric magnetic resonance imaging (mpMRI) examinations as a fundamental tool in prostate cancer (PCa) diagnostics raises the need for supportive computer-aided imaging analysis. Therefore, we evaluated the performance of a commercially available AI-based algorithm for prostate cancer detection and classification in a multi-center setting. Methods: Representative patients with 3T mpMRI between 2017 and 2022 at three different university hospitals were selected. Exams were read according to the PI-RADSv2.1 protocol and then assessed by an AI algorithm. Diagnostic accuracy for PCa of both human and AI readings were calculated using MR-guided ultrasound fusion biopsy as the gold standard. Results: Analysis of 91 patients resulted in 138 target lesions. Median patient age was 67 years (range: 49–82), median PSA at the time of the MRI exam was 8.4 ng/mL (range: 1.47–73.7). Sensitivity and specificity for clinically significant prostate cancer (csPCa, defined as ISUP ≥ 2) were 92%/64% for radiologists vs. 91%/57% for AI detection on patient level and 90%/70% vs. 81%/78% on lesion level, respectively (cut-off PI-RADS ≥ 4). Two cases of csPCa were missed by the AI on patient-level, resulting in a negative predictive value (NPV) of 0.88 at a cut-off of PI-RADS ≥ 3. Conclusions: AI-augmented lesion detection and scoring proved to be a robust tool in a multi-center setting with sensitivity comparable to the radiologists, even outperforming human reader specificity on both patient and lesion levels at a threshold of PI-RADS ≥3 and a threshold of PI-RADS ≥ 4 on lesion level. In anticipation of refinements of the algorithm and upon further validation, AI-detection could be implemented in the clinical workflow prior to human reading to exclude PCa, thereby drastically improving reading efficiency. Full article

Background. Inflammatory features can mimic PCa in suspicious MRI-lesions. Objectives: To assess the incidence of inflammatory features in targeted biopsies to suspicious lesions. Methods. A prospective analysis was conducted of 531 MRI-suspicious lesions with Prostate Imaging-Reporting and Data System (PI-RADS) scores of 3 to 5 in 364 men suspected of having PCa. Results. The incidence of inflammatory features in the MRI-suspicious lesions without PCa was 69.6%, compared to 48.1% in those with PCa (p < 0.001). Among the suspicious lesions without PCa, the incidence of inflammatory features ranged from 68.6% to 71.2% across the PI-RADS categories (p = 0.870). Mild chronic prostatitis increased with higher PI-RADS scores, while acute prostatitis decreased, and granulomatous prostatitis was exclusively observed in patients with PI-RADS scores of 4 and 5. The incidence of inflammatory features in the lesions with insignificant PCa (grade group 1) was 66.7%, compared to 42.7% in those with significant PCa (grade group 2 to 5; p = 0.027). The detection of inflammatory features in MRI-suspicious lesions was identified as an independent predictor of a lower likelihood of significant PCa detection, with an odds ratio (OR) of 0.326 (95% CI 0.196–0.541). Mild chronic prostatitis was the only type of prostatitis which was an independent predictor of a lower likelihood of significant PCa, with an OR of 0.398 (95% CI 0.268–0.590). Conclusions. These data suggest that inflammatory features may be considered mimickers of significant PCa on MRI. Full article

Background: Prostate cancer is a leading cause of cancer-related deaths in men worldwide, making accurate diagnosis critical for effective treatment. Recent advancements in artificial intelligence (AI) and machine learning (ML) have shown promise in improving the diagnostic accuracy of prostate cancer. Objectives: This systematic review aims to evaluate the effectiveness of AI-based tools in diagnosing prostate cancer using MRI, with a focus on accuracy, specificity, sensitivity, and clinical utility compared to conventional diagnostic methods. Methods: A comprehensive search was conducted across PubMed, Embase, Ovid MEDLINE, Web of Science, Cochrane Library, and Institute of Electrical and Electronics Engineers (IEEE) Xplore for studies published between 2019 and 2024. Inclusion criteria focused on full-text, English-language studies involving AI for Magnetic Resonance Imaging (MRI) -based prostate cancer diagnosis. Diagnostic performance metrics such as area under curve (AUC), sensitivity, and specificity were analyzed, with risk of bias assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Results: Seven studies met the inclusion criteria, employing various AI techniques, including deep learning and machine learning. These studies reported improved diagnostic accuracy (with AUC scores of up to 97%) and moderate sensitivity, with performance varying based on training data quality and lesion characteristics like Prostate Imaging Reporting and Data System (PI-RADS) scores. Conclusions: AI has significant potential to enhance prostate cancer diagnosis, particularly when used for second opinions in MRI interpretations. While these results are promising, further validation in diverse populations and clinical settings is necessary to fully integrate AI into standard practice. Full article