The Role of Radiomics in the Prediction of Clinically Significant Prostate Cancer in the PI-RADS v2 and v2.1 Era: A Systematic Review.

Early detection of clinically significant prostate cancer (csPCa) has substantially improved with the latest PI-RADS versions. However, there is still an overdiagnosis of indolent lesions (iPCa), and radiomics has emerged as a potential solution. The aim of this systematic review is to evaluate the role of handcrafted and deep radiomics in differentiating lesions with csPCa from those with iPCa and benign lesions on prostate MRI assessed with PI-RADS v2 and/or 2.1. The literature search was conducted in PubMed, Cochrane, and Web of Science databases to select relevant studies. Quality assessment was carried out with Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2), Radiomic Quality Score (RQS), and Checklist for Artificial Intelligence in Medical Imaging (CLAIM) tools. A total of 14 studies were deemed as relevant from 411 publications. The results highlighted a good performance of handcrafted and deep radiomics methods for csPCa detection, but without significant differences compared to radiologists (PI-RADS) in the few studies in which it was assessed. Moreover, heterogeneity and restrictions were found in the studies and quality analysis, which might induce bias. Future studies should tackle these problems to encourage clinical applicability. Prospective studies and comparison with radiologists (PI-RADS) are needed to better understand its potential.

Diagnostic Performance of Multiparametric MRI for the Detection of suspected Prostate Cancer in Biopsy-Naive Patients: A Systematic Review and Meta-analysis.

RATIONALE AND OBJECTIVES: This meta-analysis aimed to assess the diagnostic accuracy of multiparametric MRI (mpMRI) in detecting suspected prostate cancer (PCa) in biopsy-naive men. MATERIALS AND METHODS: PubMed, Scopus, and the Cochrane Library databases were systematically searched for studies published from January 2013 to April 2024. Sixteen studies comprising 4973 patients met the inclusion criteria. Data were extracted to construct 2×2 contingency tables for sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). A random-effects model was used for pooled estimation, and subgroup analyses were conducted. Summary receiver operating characteristic (SROC) curves were generated to summarize overall diagnostic performance. RESULTS: The overall detection rate of PCa across studies was 57.3%. For detecting any PCa, mpMRI showed pooled sensitivity of 82% (95% CI, 80-83%) and specificity of 62% (95% CI, 60-64%), with positive likelihood ratio (LR) of 1.97 (95% CI, 1.71-2.26), negative LR of 0.28 (95% CI, 0.24-0.34), and diagnostic odds ratio (DOR) of 7.34 (95% CI, 5.60-9.63), and an area under the SROC curve of 0.81. For clinically significant PCa (csPCa), mpMRI had pooled sensitivity of 88% (95% CI, 87-90%) and specificity of 64% (95% CI, 63-66%), with positive LR of 2.49 (95% CI, 2.03-3.05), negative LR of 0.20 (95% CI, 0.16-0.25), DOR of 13.83 (95% CI, 9.14-20.9), and area under the curve of 0.90. CONCLUSION: This meta-analysis suggests that mpMRI is effective in detecting PCa in biopsy-naive patients, particularly for csPCa. It can help reduce unnecessary biopsies and lower the risk of missing clinically significant cases, thereby guiding informed biopsy decisions.

Cognitive Targeted Prostate Biopsy Alone for Diagnosing Clinically Significant Prostate Cancer in Selected Biopsy-Naïve Patients: Results from a Retrospective Pilot Study.

(1) Background: To identify a particular setting of biopsy-naïve patients in which it would be reasonable to offer only cognitive targeted prostate biopsy (PBx) with a transrectal approach. (2) Methods: We designed an observational retrospective pilot study. Patients with a prostatic specific antigen (PSA) level > 10 ng/mL, either a normal or suspicious digital rectal examination (DRE), and a lesion with a PI-RADS score ≥ 4 in the postero-medial or postero-lateral peripheral zone were included. All patients underwent a transrectal PBx, including both systematic and targeted samples. The detection rate of clinically significant prostate cancer (csPCa) (Gleason Score ≥ 7) was chosen as the primary outcome. We described the detection rate of csPCa in systematic PBx, targeted PBx, and overall PBx. (3) A total of 92 patients were included. Prostate cancer was detected in 84 patients (91.30%) with combined biopsies. A csPCa was diagnosed in all positive cases (100%) with combined biopsies. Systematic PBxs were positive in 80 patients (86.96%), while targeted PBxs were positive in 84 men (91.30%). Targeted PBx alone would have allowed the diagnosis of csPCa in all positive cases; systematic PBx alone would have missed the diagnosis of 8/84 (9.52%) csPCa cases (4 negative patients and 4 not csPCa) (p = 0.011). (4) Conclusions: Cognitive targeted PBx with a transrectal approach could be offered alone to diagnose csPCa in biopsy-naïve patients with PSA ≥ 10 ng/mL, either normal or suspicious DRE, and a lesion with PI-RADS score ≥ 4 in the postero-medial or postero-lateral peripheral zone.

[Transrectal ultrasonography of intravesical prostatic protrusion and the detection rate of clinically significant prostate cancer].

OBJECTIVE: To investigate the value of transrectal ultrasonography (TRUS) in the detection of clinically significant prostate cancer (CsPCa) in patients with intravesical prostatic protrusion (IPP). METHODS: We retrospectively analyzed the data on 128 patients undergoing TRUS-guided prostate biopsy in the General Hospital of Eastern Theater Command and Jiangsu Province Hospital from January 2019 to December 2022. We measured the size of and graded IPP, compared the clinicopathological and ultrasonographic features of the patients in the CsPCa group (Gleason score ≥7) and those in the control group (Gleason score <7), and analyzed the correlation of the IPP grades with the detection rate of CsPCa by multivariate logistic regression analysis. RESULTS: The prostate volume was significantly higher in the CsPCa group than in the control (ï¼»51.3±12.1ï¼½ vs ï¼»43.5±11.3ï¼½ ml, P< 0.05), while the PSA density (PSAD) remarkably lower in the former than in the latter (ï¼»0.45±1.92ï¼½ vs ï¼»0.59±2.14ï¼½ ng/ml, P< 0.05) and so was the detection rate of CsPCa in the patients with IPP grade 3 than in those with IPP grades 0, 1 and 2 (56.0% vs 85.4%, 87.1% and 80.6%, P< 0.05). Spearman correlation analysis showed that the Gleason score was correlated positively with the prostate volume (r = 0.612) but negatively with PSAD (r = －0.735) and the IPP grade (r = －0.619) (P< 0.05). Logistic regression analysis indicated that IPP grade 3 (OR: 0.690, 95% CI: 0.380－0.995, P = 0.032) was an independent protective factor for CsPCa. CONCLUSION: CsPCa is significantly correlated with the IPP grade, and the detection rate of CsPCa by TRUS-guided biopsy is lower in patients with IPP grade 3 than in those with IPP grades 0－2. Therefore, special attention should be paid to false negative probability in case of high-grade IPP.

[Causes of missed diagnosis of clinically significant prostate cancer by targeted biopsy].

OBJECTIVE: To retrospectively analyze the causes of missed diagnosis of clinically significant PCa (csPCa) by targeted biopsy (TB). METHODS: This retrospective study included 652 males aged (71.32 ± 16.53) years with elevated PSA and abnormal MRI signals detected in our hospital from June 2018 to December 2020. We further examined the patients by transperineal prostatic TB and systematic biopsy (SB), analyzed the detection rates of PCa and csPCa by TB and SB, and investigated the causes of missed diagnosis of csPCa in TB using the fishbone diagram. RESULTS: The total detection rate of PCa and csPCa by TB combined with SB was 45.7% (298/652), and that of csPCa was 37.4% (244/652), with 38 cases of csPCa missed in TB, including 23 cases of negative TB and 15 cases of low ISUP grade. The causes of missed diagnosis of csPCa by TB included low MRI image quality, PSA density ≤0.15 ng/ml/cm3, target area <10 mm, and PI-RADS 2 score ≤3. The detection rate of csPCa by TB alone was 31.6%, which was increased by 5.8% (P = 0.027) when TB combined with SB. CONCLUSION: TB combined with SB yields a higher detection rate of csPCa than either used alone. Missed diagnosis of csPCa by TB is closely related to the characteristics of tumor and MR image of the target area.

Evaluating the Quality of Local Programs for Early Detection of Significant Prostate Cancer.

Quality control of programs for detection of significant prostate cancer (sPCa) could be defined by the correlation between observed and reference 95% confidence intervals (CIs) for Prostate Imaging-Reporting and Data System (PI-RADS) categories. We used the area under the receiver operating characteristic curve (AUC) for the Barcelona magnetic resonance imaging (MRI) predictive model to screen the quality of ten participant centers in the sPCa opportunistic early detection program in Catalonia. We set an AUC of <0.8 as the criterion for suboptimal quality. Quality was confirmed in terms of the correlation between actual sPCa detection rates and reference 95% CIs. For a cohort of 2624 men with prostate-specific antigen >3.0 ng/ml and/or a suspicious digital rectal examination who underwent multiparametric MRI and two- to four-core targeted biopsies of PI-RADS ≥3 lesions and/or 12-core systematic biopsy, AUC values ranged from 0.527 to 0.914 and were <0.8 in four centers (40%). There was concordance between actual sPCa detection rates and reference 95% CIs for one or two PI-RADS categories when the AUC was <0.8, and for three or four PI-RADS categories when the AUC was ≥0.8. A review of procedures used for sPCa detection should be recommended in centers with suboptimal quality. Patient summary: We tested a method for assessing quality control for centers carrying out screening for early detection of prostate cancer. We found that the method can identify centers that may need to review their procedures for detection of significant prostate cancer.

Prostate MRI for the detection of clinically significant prostate cancer: Update and future directions.

PURPOSE OF REVIEW: In recent decades, there has been an increasing role for magnetic resonance imaging (MRI) in the detection of clinically significant prostate cancer (csPC). The purpose of this review is to provide an update and outline future directions for the role of MRI in the detection of csPC. RECENT FINDINGS: In diagnosing clinically significant prostate cancer pre-biopsy, advances include our understanding of MRI-targeted biopsy, the role of biparametric MRI (non-contrast) and changing indications, for example the role of MRI in screening for prostate cancer. Furthermore, the role of MRI in identifying csPC is maturing, with emphasis on standardization of MRI reporting in active surveillance (PRECISE), clinical staging (EPE grading, MET-RADS-P) and recurrent disease (PI-RR, PI-FAB). Future directions of prostate MRI in detecting csPC include quality improvement, artificial intelligence and radiomics, positron emission tomography (PET)/MRI and MRI-directed therapy. SUMMARY: The utility of MRI in detecting csPC has been demonstrated in many clinical scenarios, initially from simply diagnosing csPC pre-biopsy, now to screening, active surveillance, clinical staging, and detection of recurrent disease. Continued efforts should be undertaken not only to emphasize the reporting of prostate MRI quality, but to standardize reporting according to the appropriate clinical setting.

Clinical-imaging metrics for the diagnosis of prostate cancer in PI-RADS 3 lesions.

OBJECTIVE: To explore the feasibility and efficacy of clinical-imaging metrics in the diagnosis of prostate cancer (PCa) and clinically significant prostate cancer (csPCa) in prostate imaging-reporting and data system (PI-RADS) category 3 lesions. METHODS: A retrospective analysis was conducted on lesions diagnosed as PI-RADS 3. They were categorized into benign, non-csPCa and csPCa groups. Apparent diffusion coefficient (ADC), T2-weighted imaging signal intensity (T2WISI), coefficient of variation of ADC and T2WISI, prostate-specific antigen density (PSAD), ADC density (ADCD), prostate-specific antigen lesion volume density (PSAVD) and ADC lesion volume density (ADCVD) were measured and calculated. Univariate and multivariate analyses were used to identify risk factors associated with PCa and csPCa. Receiver operating characteristic curve (ROC) and decision curves were utilized to assess the efficacy and net benefit of independent risk factors. RESULTS: Among 202 patients, 133 had benign prostate disease, 25 non-csPCa and 44 csPCa. Age, PSA and lesion location showed no significant differences (P > 0.05) among the groups. T2WISI and coefficient of variation of ADC (ADCcv) were independent risk factors for PCa in PI-RADS 3 lesions, yielding an area under the curve (AUC) of 0.68. ADC was an independent risk factor for csPCa in PI-RADS 3 lesions, yielding an AUC of 0.65. Decision curve analysis showed net benefit for patients at certain probability thresholds. CONCLUSIONS: T2WISI and ADCcv, along with ADC, respectively showed considerable promise in enhancing the diagnosis of PCa and csPCa in PI-RADS 3 lesions.

Clinically significant prostate cancer detection rate in biopsy-naïve patients with mpMRI and microultrasound topographically discordant lesions: A single-center retrospective analysis.

INTRODUCTION AND OBJECTIVES: Multiparametric magnetic resonance imaging (mpMRI) has improved the detection of clinically significant prostate cancer (csPCa), and microultrasound (micro-US) shows promise in enhancing detection rates. We compared mpMRI-guided targeted biopsy (MTBx) and micro-US-guided targeted biopsy (micro-US-TBx) in biopsy-naïve patients with discordant lesions at micro-US and mpMRI to detect csPCa (grade group ≥2) and clinically insignificant PCa (ciPCa; grade group 1) and assessed the role of nontargeted systematic biopsy (SBx). MATERIAL AND METHODS: We analyzed 178 biopsy-naive men with suspected PCa and discordant lesions at mpMRI and micro-US. All patients underwent mpMRI followed by micro-US, the latter being performed immediately before the biopsy. Imaging findings were interpreted blindly, followed by targeted and SBx. Median age was 63 years (IQR, 57-70), median prostate-specific antigen level was 7 ng/mL (IQR, 5-9 ng/mL), and median prostate volume was 49 cm^3 (IQR, 35-64 cm^3). Overall, 86/178 (48%) patients were diagnosed with PCa, 51/178 (29%) with csPCa. RESULTS: Micro-USTBx detected csPCa in 36/178 men (20%; 95% CI: 26-46), and MTBx detected csPCa in 28/178 men (16%; 95% CI: 36-50), resulting in a -8% difference (95% CI: -10, 4; P = 0.022) and a relative detection rate of 0.043. Micro-USTBx detected ciPCa in 9/178 men (5%; 95% CI: 3, 15), while MTBx detected ciPCa in 12/178 men (7%; 95% CI: 5, 20), resulting in a -3% difference (95% CI: -2 to 4; P = 0.2) and a relative detection rate of 0.1. SBx detected ciPCa in 29 (16%) men. mpMRI plus micro-US detected csPCa in 51/178 men, with no additional cases with the addition of SBx. Similarly, MTBx plus micro-USTBx plus SBx detected ciPCa in 35/178 men (20%; 95% CI: 18, 37) compared to 9 (5%) in the micro-US pathway (P = 0.002) and 14/178 (8%; 95% CI: 6, 26) in the mpMRI plus micro-US pathway (P = 0.004). CONCLUSIONS: In conclusion, a combined micro-US/mpMRI approach could characterize primary disease in biopsy-naïve patients with discordant lesions, potentially avoiding SBx. Further studies are needed to validate our findings and assess micro-US's role in reducing unnecessary biopsies.

[Transperineal versus transrectal ultrasound-guided prostate biopsy in detection of clinically significant and insignificant prostate cancer: A prospective randomized controlled trial].

OBJECTIVE: To compare transperineal prostate biopsy (TPB) with transrectal ultrasound-guided prostate biopsy (TRUSB) in detection of clinically significant prostate cancer (csPCa) and insignificant PCa (insPCa). METHODS: We conducted a prospective randomized clinical study on 279 patients receiving TPB (n = 144) or TRUSB (n = 135) from January 2022 to January 2023, and compared the detection rates of csPCa and insPCa between the two groups. RESULTS: The detection rate of PCa was significantly higher in the TPB than in the TRUSB group (37.50% vs 28.15%, P = 0.026). There were no statistically significant differences between the TPB and TRUSB groups in the detection rates of insPCa (6.94% ï¼»n = 10ï¼½ vs 4.45% ï¼»n = 6ï¼½, P > 0.05) and csPCa (30.56% ï¼»n = 44ï¼½ vs 23.70% ï¼»n = 32ï¼½, P > 0.05), nor in the detection rate of csPCa between different groups of age, PSA concentration and prostate volume (P > 0.05). No statistically significant differences were observed between the TPB and TRUSB groups either in the positive rate of biopsy punctures (ï¼»16.44 ± 2.86ï¼½% vs ï¼»12.48 ± 2.39ï¼½%, P > 0.05) or in the biopsy-related complications of urinary retention, urinary tract infection, hematuria and rectal bleeding (P > 0.05). CONCLUSION: TPB is more effective than TRUSB in detection of PCa, but there is no statistically significant difference between the two approaches in the detection rates of csPCa and insPCa.

Value of perilesional biopsies in multiparametric magnetic resonance imaging-targeted biopsy and systematic biopsy in detection of prostate cancer: results of a prospective, non-randomized, surgeon-blinded study.

PURPOSE: The goal of this study is to address if detection rates of clinically significant prostate cancer (csPCa) can be increased by additional perilesional biopsies (PB) in magnetic resonance (MR)/ultrasound fusion prostate biopsy in biopsy-naïve men. METHODS: This prospective, non-randomized, surgeon-blinded study was conducted between February 2020 and July 2022. Patients were included with PSA levels < 20 ng/ml and ≥ one PI-RADS lesion (grades 3-5) per prostate lobe. Prostate biopsy was performed by two urologists. The first performed the MR-fusion biopsy with 3-5 targeted biopsies (TB) and 6 PB in a standardized pattern. The second performed the systematic (12-fold) biopsy (SB) without knowledge of the MR images. Primary outcome of this study is absence or presence of csPCa (≥ ISUP grade 2) comparing TB, PB and SB, using McNemar test. RESULTS: Analyses were performed for each PI-RADS lesion (n = 218). There was a statistically significant difference in csPC detection rate of TB + SB between PI-RADS 3, 4 and 5 lesions (18.0% vs. 42.5% vs. 82.6%, p < 0.001) and TB + PB (19.7% vs. 29.1% vs. 78.3%). Comparing only maximum ISUP grade per lesion, even SB plus TB plus PB did not detect more csPCa compared to SB plus TB (41.3% vs. 39.9%, p > 0.05). CONCLUSION: We present prospective study data investigating the role of perilesional biopsy in detection of prostate cancer. We detected no statistically significant difference in the detection of csPCa by the addition of PB. Therefore, we recommend continuing 12-fold bilateral SB in addition to TB.

Autonomous Tumor Signature Extraction Applied to Spatially Registered Bi-Parametric MRI to Predict Prostate Tumor Aggressiveness: A Pilot Study.

BACKGROUND: Accurate, reliable, non-invasive assessment of patients diagnosed with prostate cancer is essential for proper disease management. Quantitative assessment of multi-parametric MRI, such as through artificial intelligence or spectral/statistical approaches, can provide a non-invasive objective determination of the prostate tumor aggressiveness without side effects or potential poor sampling from needle biopsy or overdiagnosis from prostate serum antigen measurements. To simplify and expedite prostate tumor evaluation, this study examined the efficacy of autonomously extracting tumor spectral signatures for spectral/statistical algorithms for spatially registered bi-parametric MRI. METHODS: Spatially registered hypercubes were digitally constructed by resizing, translating, and cropping from the image sequences (Apparent Diffusion Coefficient (ADC), High B-value, T2) from 42 consecutive patients in the bi-parametric MRI PI-CAI dataset. Prostate cancer blobs exceeded a threshold applied to the registered set from normalizing the registered set into an image that maximizes High B-value, but minimizes the ADC and T2 images, appearing "green" in the color composite. Clinically significant blobs were selected based on size, average normalized green value, sliding window statistics within a blob, and position within the hypercube. The center of mass and maximized sliding window statistics within the blobs identified voxels associated with tumor signatures. We used correlation coefficients (R) and p-values, to evaluate the linear regression fits of the z-score and SCR (with processed covariance matrix) to tumor aggressiveness, as well as Area Under the Curves (AUC) for Receiver Operator Curves (ROC) from logistic probability fits to clinically significant prostate cancer. RESULTS: The highest R (R > 0.45), AUC (>0.90), and lowest p-values (<0.01) were achieved using z-score and modified registration applied to the covariance matrix and tumor signatures selected from the "greenest" parts from the selected blob. CONCLUSIONS: The first autonomous tumor signature applied to spatially registered bi-parametric MRI shows promise for determining prostate tumor aggressiveness.

A novel nomogram to predict clinically significant prostate cancer in MR assisted lesion biopsies: Turkish urooncology association nomogram.

OBJECTIVE: This study aimed to develop a novel nomogram to predict clinically significant prostate cancer in patients undergoing multi-parametric prostate MRI-assisted lesion biopsies, addressing the challenges in deciding on biopsy for patients with PI-RADS 3 lesions and follow-up strategies for patients with negative PI-RADS 4 or 5 lesions. MATERIALS AND METHODS: A retrospective case-control study was conducted using the Turkish Urooncology Association Databases (UROCaD). The final dataset included 2428 lesion biopsy data. Univariate analysis, logistic regression, and validation were performed, with 1942 and 486 lesion biopsy data in the training and validation datasets, respectively. RESULTS: Age, initial total PSA value, PSA density, prostate volume, lesion length, DRE findings, and PI-RADS score were significantly different between benign or non-significant cancer and clinically significant prostate cancer groups. The developed nomogram incorporated PSA density, age, PI-RADS score, lesion length, and DRE findings. The mean area under the curve for the 6-fold cross-validation was 0.836, while the area under the curve values for the training and validation datasets were 0.827 and 0.861, respectively. The nomogram demonstrated a sensitivity of 75.6% and a specificity of 74.8% at a cut-off score of 24.9, with positive and negative predictive values of 42.2% and 92.6%, respectively. CONCLUSION: The TUA nomogram, based on PSA density, age, PI-RADS score, lesion length, and DRE findings, provides a reliable and accurate prediction tool for detecting clinically significant prostate cancer in patients undergoing multi-parametric prostate MRI-assisted lesion (fusion) biopsies, potentially improving patient management and reducing unnecessary biopsies.

A novel model incorporating quantitative contrast-enhanced ultrasound into PI-RADSv2-based nomogram detecting clinically significant prostate cancer.

The diagnostic accuracy of clinically significant prostate cancer (csPCa) of Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) is limited by subjectivity in result interpretation and the false positive results from certain similar anatomic structures. We aimed to establish a new model combining quantitative contrast-enhanced ultrasound, PI-RADSv2, clinical parameters to optimize the PI-RADSv2-based model. The analysis was conducted based on a data set of 151 patients from 2019 to 2022, multiple regression analysis showed that prostate specific antigen density, age, PI-RADSv2, quantitative parameters (rush time, wash-out area under the curve) were independent predictors. Based on these predictors, we established a new predictive model, the AUCs of the model were 0.910 and 0.879 in training and validation cohort, which were higher than those of PI-RADSv2-based model (0.865 and 0.821 in training and validation cohort). Net Reclassification Index analysis indicated that the new predictive model improved the classification of patients. Decision curve analysis showed that in most risk probabilities, the new predictive model improved the clinical utility of PI-RADSv2-based model. Generally, this new predictive model showed that quantitative parameters from contrast enhanced ultrasound could help to improve the diagnostic performance of PI-RADSv2 based model in detecting csPCa.

Robot-Assisted Radical Prostatectomy in PIRADS 5 Lesions Without Prior Biopsy: Is Biopsy Really Necessary in This Cohort?

Introduction: Conventionally, confirmation of clinically significant prostate cancer (csPCa) (Gleason grade group ≥ 2) involves an initial multiparametric magnetic resonance imaging (mpMRI) followed by biopsy. Prostate biopsy incurs inherent risks of infection, bleeding, patient discomfort, and a 6-week delay before robot-assisted laparoscopic radical prostatectomy (RALP). We explored the feasibility of immediate RALP in men with PIRADS 5 lesions without preceding biopsy. Methodology: After obtaining institutional review board approval, a prospective analysis was conducted on 235 patients with PIRADS 5 lesions on mpMRI from December 2018 to February 2023. Patients were divided into 2 groups as follows: Group NoBiopsy (biopsy not done before RALP, cases, n = 118) and Group YesBiopsy (biopsy done before RALP, controls, n = 117). Baseline preoperative, intraoperative, and postoperative parameters were analyzed. Functional outcomes were monitored at 1, 3-, 6-, 9-, and 12-months follow-up post-RALP. Statistical analysis was performed using SPSS and STATA. Results: Ninety-five percent of cases and 87.17% controls had csPCa on final pathology post-RALP. Multivariable analysis did not find significant association between biopsy status and csPCa. Abnormal digital rectal examination (DRE), family history, preoperative PSA, and MRI lesion volume predicted csPCa. Significant differences were observed in console time (NoBiopsy vs. YesBiopsy, 60 ± 10 vs. 70 ± 9 minutes, p < 0.001) and estimated blood loss (80 ± 20 vs. 100 ± 30 mL, p < 0.01) between groups. At 6 months post-RALP, 96% of men in Group NoBiopsy were continent, compared with 88% of men in Group YesBiopsy (p < 0.04). All men in the study cohort were continent (0 pads) at 12 months post-RALP. Ninety-eight percent of cases and 92% of controls at 9 months and 12 months, respectively, were able to have penetrative sex with or without PDE-5 inhibitors post-RALP. Conclusion: RALP without antecedent prostate biopsy in men with PIRADS 5 lesions demonstrated substantial csPCa detection rates and superior functional outcomes, warranting further validation.

Combination of prostate volume and apparent diffusion coefficient can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies.

BACKGROUND: Nowadays, there are many patients who undergo unnecessary prostate biopsies after receiving a prostate imaging reporting and data system (PI-RADS) score of 3. Our purpose is to identify cutoff values of the prostate volume (PV) and minimum apparent diffusion coefficient (ADCmin) to stratify those patients to reduce unnecessary prostate biopsies. METHODS: Data from 224 qualified patients who received prostate biopsies from January 2019 to June 2023 were collected. The Mann-Whitney U test was used to compare non-normal distributed continuous variables, which were recorded as median (interquartile ranges). The correlation coefficients were calculated using Spearman's rank correlation analysis. Categorical variables are recorded by numbers (percentages) and compared by χ2 test. Both univariate and multivariate logistic regression analysis were used to determine the independent predictors. The receiver-operating characteristic curve and the area under the curve (AUC) were used to evaluate the diagnostic performance of clinical variables. RESULTS: Out of a total of 224 patients, 36 patients (16.07%) were diagnosed with clinically significant prostate cancer (csPCa), whereas 72 patients (32.14%) were diagnosed with any grade prostate cancer. The result of multivariate analysis demonstrated that the PV (p < 0.001, odds ratio [OR]: 0.952, 95% confidence interval [95% CI]: 0.927-0.978) and ADCmin (p < 0.01, OR: 0.993, 95% CI: 0.989-0.998) were the independent factors for predicting csPCa. The AUC values of the PV and ADCmin were 0.779 (95% CI: 0.718-0.831) and 0.799 (95% CI: 0.740-0.849), respectively, for diagnosing csPCa. After stratifying patients by PV and ADCmin, 24 patients (47.06%) with "PV < 55 mL and ADCmin < 685 µm2/s" were diagnosed with csPCa. However, only one patient (1.25%) with PV ≥ 55 mL and ADCmin ≥ 685 µm2/s were diagnosed with csPCa. CONCLUSIONS: In this study, we found the combination of PV and ADCmin can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies. These patients with "PV ≥ 55 mL and ADCmin ≥ 685 µm2/s" may safely avoid prostate biopsies.

Lectin-nanoparticle concept for free PSA glycovariant providing superior cancer specificity.

BACKGROUND: Using lectins to target cancer-associated modifications of PSA glycostructure for identification of clinically significant prostate cancers, e.g., Gleason score (GS) ≥ 7, from benign and indolent cancers (GS 6), is highly promising yet technically challenging. From previous findings to quantify increased PSA fucosylation in urine, we set out to construct a robust, specific test concept suitable for plasma samples. METHODS: Macrophage galactose-binding lectin (MGL) coupled to 100 nm Eu3 + -nanoparticles was used to probe PSA captured from cancer cell lines, seminal plasma, and plasma samples from 249 patients with a clinical suspicion of prostate cancer onto 3 mm dense spots of free PSA antibody fab fragments. Results were compared to four kallikrein tests: tPSA, fPSA, iPSA and hK2. RESULTS: The fPSAMGLglycovariant provided superior discrimination of the GS ≥ 7 and benign + GS 6 groups (p 0.0003) compared to fPSA (NS). The corresponding AUC in ROC analysis was 0.70 compared to 0.66 for tPSA. In contrast to all four kallikrein tests, the fPSAMGLGV was independent of prostate gland volume. Using a logistic regression analysis the fPSAMGLGV significantly improved on the four-kallikrein model. CONCLUSIONS: Due to Eu-nanoparticles and a dense fPSA capture spot, the fPSAMGL glycovariant identifies an fPSA subform with the highest cancer specificity compared to the four conventional kallikreins.

Elucidating the need for prostate cancer risk calculators in conjunction with mpMRI in initial risk assessment before prostate biopsy at a tertiary prostate cancer center.

OBJECTIVE: Utilizing personalized risk assessment for clinically significant prostate cancer (csPCa) incorporating multiparametric magnetic resonance imaging (mpMRI) reduces biopsies and overdiagnosis. We validated both multi- and univariate risk models in biopsy-naïve men, with and without the inclusion of mpMRI data for csPCa detection. METHODS: N = 565 men underwent mpMRI-targeted prostate biopsy, and the diagnostic performance of risk calculators (RCs), mpMRI alone, and clinical measures were compared using receiver operating characteristic curve (ROC) analysis and decision curve analysis (DCA). Subgroups were stratified based on mpMRI findings and quality. RESULTS: csPCa was detected in 56.3%. PI-RADS score achieved the highest area under the curve (AUC) when comparing univariate risk models (AUC 0.82, p < 0.001). Multivariate RCs showed only marginal improvement in csPCa detection compared to PI-RADS score alone, with just one of four RCs showing significant superiority. In mpMRI-negative cases, the non-MRI-based RC performed best (AUC 0.80, p = 0.016), with the potential to spare biopsies for 23%. PSA-density and multivariate RCs demonstrated comparable performance for PI-RADS 3 constellation (AUC 0.65 vs. 0.60-0.65, p > 0.5; saved biopsies 16%). In men with suspicious mpMRI, both mpMRI-based RCs and the PI-RADS score predicted csPCa excellently (AUC 0.82-0.79 vs. 0.80, p > 0.05), highlighting superior performance compared to non-MRI-based models (all p < 0.002). Quality-assured imaging consistently improved csPCa risk stratification across all subgroups. CONCLUSION: In tertiary centers serving a high-risk population, high-quality mpMRI provides a simple yet effective way to assess the risk of csPCa. Using multivariate RCs reduces multiple biopsies, especially in mpMRI-negative and PI-RADS 3 constellation.

A noninvasive method for predicting clinically significant prostate cancer using magnetic resonance imaging combined with PRKY promoter methylation level: a machine learning study.

BACKGROUND: Traditional process for clinically significant prostate cancer (csPCA) diagnosis relies on invasive biopsy and may bring pain and complications. Radiomic features of magnetic resonance imaging MRI and methylation of the PRKY promoter were found to be associated with prostate cancer. METHODS: Fifty-four Patients who underwent prostate biopsy or photoselective vaporization of the prostate (PVP) from 2022 to 2023 were selected for this study, and their clinical data, blood samples and MRI images were obtained before the operation. Methylation level of two PRKY promoter sites, cg05618150 and cg05163709, were tested through bisulfite sequencing PCR (BSP). The PI-RADS score of each patient was estimated and the region of interest (ROI) was delineated by 2 experienced radiologists. After being extracted by a plug-in of 3D-slicer, radiomic features were selected through LASSCO regression and t-test. Selected radiomic features, methylation levels and clinical data were used for model construction through the random forest (RF) algorithm, and the predictive efficiency was analyzed by the area under the receiver operation characteristic (ROC) curve (AUC). RESULTS: Methylation level of the site, cg05618150, was observed to be associated with prostate cancer, for which the AUC was 0.74. The AUC of T2WI in csPCA prediction was 0.84, which was higher than that of the apparent diffusion coefficient ADC (AUC = 0.81). The model combined with T2WI and clinical data reached an AUC of 0.94. The AUC of the T2WI-clinic-methylation-combined model was 0.97, which was greater than that of the model combined with the PI-RADS score, clinical data and PRKY promoter methylation levels (AUC = 0.86). CONCLUSIONS: The model combining with radiomic features, clinical data and PRKY promoter methylation levels based on machine learning had high predictive efficiency in csPCA diagnosis.

The impact of the relationship between lesion diameter and total core length on the detection rate of clinically significant prostate cancer for PI-RADS 3 lesions.

BACKGROUND: The aim of our study was to determine the effect of total core length (TCL) for prostate imaging reporting and data system (PI-RADS) 3 lesions to facilitate clinically significant prostate cancer (csPCa) detection based on the lesion diameter. MATERIALS AND METHODS: A total of 149 patients with at least 1 lesion with a PI-RADS 3 were evaluated retrospectively. The lesions with diameters of < 1 cm were categorized as small lesions and lesions of ≥ 1 cm were categorized as large lesions. The lengths of biopsy cores from PI-RADS 3 lesions were summed for each lesion separately, and TCL was calculated. The relationship between TCL and csPCa was analyzed separately for the small and large groups with multiple logistic regression analyses. RESULTS: A total of 208 lesions were detected by multiparametric magnetic resonance imaging (MpMRI) in 149 males included in the study. The mean TCL was 44.68 mm (26-92) and the mean lesion diameter was 10.73 mm (4-27) in PIRADS 3 lesions. For small diameter lesions (< 1 cm), the odds of finding clinically insignificant prostate cancer (ciPCa) increase by 1.67 times if TCL increases by one unit. Hence, increasing TCL for small lesions only increases the odds of ciPCa detection. For large diameter lesions (≥ 1 cm), if TCL increases by one unit, the odds of finding ciPCa increase 1.13 times and the odds of finding csPCa increases1.16 times. Accordingly, large lesions are more likely to have both csPCa and ciPCa as TCL increases. CONCLUSIONS: Our study showed that for PI-RADS 3 lesions, both more csPCa and more ciPCa were detected as TCL increased. However, in lesions with a size of < 1 cm, only ciPCa was detected more frequently as TCL increased. In conclusion, taking more and longer biopsy cores in PI-RADS 3 lesions below 1 cm does not contribute to the detection of csPCa.