PSA Density Research Articles

Elevating precision: A thorough investigation of multiparametric prostate MRI for prolonged insights into early continence prediction after robot-assisted laparoscopic prostatectomy

BackgroundWhile radical prostatectomy stands out as one of the most effective curative treatments for prostate cancer, it does come with annoying side effects, such as urinary incontinence (UI). We aimed to investigate the predictability of UI using MRI measurements, along with clinical and disease-related variables. MethodsWe included 191 patients who underwent robot-assisted laparoscopic radical prostatectomy between July 2020 and October 2022 in the study. Preoperative MRIs of the patients are re-evaluated by an experienced uroradiologist, and membranous urethral length (MUL), urethra wall thickness, levator ani thickness, outer levator distance, Lee's apex shape, intravesical prostate protrusion length, prostate apex depth, and pubic height measurements were made. Additionally, retrospective data on patients' age, BMI, PSA, PSA density, prostate volume, IPSS, clinical stage, and nerve-sparing status were collected. Patients were categorized into two groups based on continence status in the third postoperative month: continent or incontinent. The definition of UI was accepted as the use of one or more pads per day. ResultsUI was observed in 38.21 % of the patients in the postoperative third month. Among MRI measurements, only MUL showed a significant relationship with UI (p < 0.001). IPSS (p = 0.004) and Clinical Stage (p < 0.001) were also significantly associated with continence status. Logistic regression analysis identified BMI (p = 0.023; CI 0.73–0.97), IPSS (p = 0.002; CI 1.03–1.17), MUL (p = 0.001; CI 0.66–0.90), and Clinical Stage (p < 0.001; CI 1.53–2.71) as significant predictors. In Multivariable Regression analysis, Clinical Stage emerged as the most powerful predictor of UI (p < 0.001). ConclusionsExcept for MUL, MRI measurements may not predict postoperative UI. A combination of IPSS, clinical stage, and MUL effectively informs patients about postoperative outcomes. These findings contribute to enhancing preoperative counseling for patients undergoing radical prostatectomy.

Abstract C014: Lower negative predictive value of prostate MRI in Black men

Abstract Introduction: PIRADS scoring with multiparametric-MRI (MRI) has a pooled 90% negative predictive value (NPV) allowing men to defer biopsy while enhancing Gleason Grade group 2-5 (GG2-5) prostate cancer (PCa) detection. PSA density (PSAD) ≥0.15ng/ml/cm3 has been shown to enhance NPV of the prostate MRI in non-Black men. We assessed the performance of the prostate MRI in Black vs. non-Black men by evaluating sensitivity and NPV, and identified a PSAD threshold providing ≥90% NPV in Black men. Methods: We prospectively recruited Black and non-Black men referred to outpatient urology clinics for abnormal PSA or prostate exam in three similar biomarker validation studies from 2017–23 before MRI-informed diagnostic transrectal or transperineal prostate biopsy. We combined this research cohort with a retrospective clinical cohort of clinically similar Black and non-Black men from one academic institution who also underwent prostate MRIs and MRI-informed biopsies for elevated PSA. Trained radiologists used PIRADS version 2.0 or 2.1 for scoring. Results: Following the combination of the research and clinical cohorts, 286 Black men and 965 non-Black men with PSA&amp;lt;15.0ng/ml were included in the analysis. PIRADS ≥3 had an NPV of 77.1% versus 87.6% and a sensitivity of 90.7% vs. 96.3% for GG2-5 PCa in Black versus non-Black men, respectively (both p&amp;lt;0.05). Using PSAD ≥0.09 for Black men with PIRADS 1-2 lesions increased sensitivity to 92.9%. For PIRADS 1-2, GG2-5 PCa frequency was 5.3% higher in Black versus non-Black men with PSAD&amp;lt;0.15, and 11.0% higher in Black versus non-Black men with PSAD≥0.15. For PIRADS=3, GG2-5 PCa frequency was 9.1% higher in Black men with PSAD&amp;lt;0.15 and 27.9% higher for PSAD≥0.15. For PIRADS=4, GG2-5 PCa frequency was 15.9% higher in Black men with PSAD&amp;lt;0.15, and 9.5% higher for PSAD≥0.15. Conclusion: The PIRADS ≥3 threshold has a lower NPV and sensitivity in Black men. A negative prostate MRI requires a PSAD ≥0.09 threshold for safe biopsy deferral in Black men to maintain a sensitivity ≥90%. Citation Format: Sarah Sandlow, Samuel Carbunaru MD, Zequn Sun PhD, Bernice Ofori MPH, Courtney M. P. Hollowell MD, Patricia Vidal MD, Eric Li MD, Edward M. Schaeffer MD, PhD, Peter Gann MD, ScD, Ashley Ross MD, PhD, Shilajit Kundu MD, Adam B. Murphy MD, MBA, MSCI. Lower negative predictive value of prostate MRI in Black men [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C014.

Abstract C180: Not all PIRADS 3s are equal; fusion biopsy outcomes by PIRADS score and ethnicity in a diverse population

Abstract Introduction and Objective: Magnetic resonance imaging (MRI) is increasingly utilized in the diagnosis of prostate cancer (PCa). Although PIRADS 3 lesions have been associated with a lower likelihood of detecting clinically significant prostate cancer (csPCa) at the time of targeted fusion biopsy (FB), existing data on multiethnic populations are sparse. We assessed the pathologic concordance of PIRADS 3 vs 4 or 5 lesions in detection of PCa and csPCa in comparison to PSA density in a diverse population. Methods: A retrospective study of all patients who underwent image-guided FB for PIRADS 3-5 lesions from 2016-2022 was conducted. Demographic, clinical, and pathologic data were extracted from electronic medical records. Mixed-effects logistic regression models were used to examine the association of race/ethnicity and PSA density with risks of overall PCa and csPCa. A stratified analysis by PIRADS score (3 vs 4 or 5) was also carried out to explore the associations between detection rates of PCa and race/ethnicity. Results: A total of 565 men with 997 lesions were analyzed, with average age 63.2 years (SD: 7.5) at the time of biopsy. Of the men, 279 (49.4%) were Non-Hispanic Black (NHB), 112 (19.8%) were Non-Hispanic White, and 174 (30.8%) were Hispanic. 520 (52.16%), 310 (31.09%), and 167 (16.75%) individual MRI lesions were PIRADS 3, 4, and 5, respectively with distributions of PIRADS scores being similar across all race/ethnicities. The overall rates of PCa detection were 44.8% in NHB, 37.6% in Hispanics, and 33.0% in NHW. Compared to NHW, NHB has 2.52 higher odds of detecting overall PCa (95% CI 1.10-5.78; p = 0.03), whereas Hispanic men had an OR = 1.18 (p = 0.72). Interestingly, the increase in PCa detection among NHB was only observed for PIRADs 3 lesions (OR = 4.84 95% CI 1.11-21.2, p = 0.04). NHB men also had 2.1-fold higher odds of detecting csPCa (95% CI 0.92-4.77; p = 0.08) in comparison to NHW with a similar trend mimicking association with PRIADS scores, although results were not statistically significant. Conclusions: We report that NHB men have higher odds of detection rates of overall PCa in FB in comparison to NHW and Hispanic men, albeit only at PIRADS 3 scores. These findings may serve to improve risk stratification and assist with shared decision making when discussing triggers for biopsy. Source of funding: None Citation Format: David G. Hanelin, Andrewe Baca, Priya Dave, Rutul Patel, Ilir Agalliu, Alexander Sankin, Ahmed Aboumohamed, Kara Watts. Not all PIRADS 3s are equal; fusion biopsy outcomes by PIRADS score and ethnicity in a diverse population [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C180.

Upgrading of Grade Group 1 Prostate Cancer at Prostatectomy: Germline Risk Factors in a Prospective Cohort.

Localized prostate tumors show significant spatial heterogeneity, with regions of high-grade disease adjacent to lower-grade disease. Consequently, prostate cancer biopsies are prone to sampling bias, potentially leading to underestimation of tumor grade. To study the clinical, epidemiologic and molecular hallmarks of this phenomenon, we conducted a prospective study of grade upgrading: differences in detected prostate cancer grade between biopsy and surgery. We established a prospective, multi-institutional cohort of men with Grade Group 1 (GG1) prostate cancer on biopsy who underwent radical prostatectomy. Upgrading was defined as detection of GG2+ in the resected tumor. Germline DNA from 192 subjects was subjected to whole-genome sequencing to quantify ancestry, pathogenic variants in DNA damage response genes and polygenic risk. Of 285 men, 67% upgraded at surgery. PSA density and percent of cancer in pre-prostatectomy positive biopsy cores were significantly associated with upgrading. No assessed genetic risk factor was predictive of upgrading, including polygenic risk scores for prostate cancer diagnosis. In a cohort of low-grade prostate cancer patients, a majority upgraded at radical prostatectomy. PSA density and percent of cancer in pre-prostatectomy positive biopsy cores portended the presence of higher-grade disease, while germline genetics was not informative in this setting. Patients with low-risk prostate cancer, but elevated PSA density or percent cancer in positive biopsy cores, may benefit from repeat biopsy, additional imaging or other approaches to complement active surveillance. Further risk stratification of patients with low-risk prostate cancer may provide useful context for active surveillance decision-making.

Predicting clinically significant prostate cancer in elderly patients: A nomogram approach with shear wave elastography.

This study was to construct a nomogram utilizing shear wave elastography and assess its efficacy in detecting clinically significant prostate cancer (csPCa). 290 elderly people with suspected PCa who received prostate biopsy and shear wave elastography (SWE) imaging were respectively registered from April 2022 to December 2023. The elderly participants were stratified into two groups: those with csPCa and those without csPCa, which encompassed cases of clinically insignificant prostate cancer (cisPCa) and non-prostate cancer tissue, as determined by pathology findings. The LASSO algorithm, known as the least absolute shrinkage and selection operator, was utilized to identify features. Logistic regression analysis was utilized to establish models. Receiver operating characteristic (ROC) and calibration curves were utilized to evaluate the discriminatory ability of the nomogram. Bootstrap (1000 bootstrap iterations) was employed for internal validation and comparison with two models. A decision curve and a clinical impact curve were employed to assess the clinical usefulness. Our nomogram, which contained Emean, ΔEmean, prostate volume, prostate-specific antigen density (PSAD), and transrectal ultrasound (TRUS), showed better discrimination (AUC = 0.89; 95% CI: 0.83-0.94), compared to the clinical model without SWE parameters (p = 0.0007). Its accuracy, sensitivity and specificity were 0.83, 0.89 and 0.78, respectively. Based on the analysis of decision curve, the thresholds ranged from 5% to 90%. According to our nomogram, biopsying patients at a 20% probability threshold resulted in a 25% reduction in biopsies without missing any csPCa. The clinical impact curve demonstrated that the nomogram's predicted outcome is closer to the observed outcome when the probability threshold reaches 20% or greater. Our nomogram demonstrates efficacy in identifying elderly individuals with clinically significant prostate cancer, thereby facilitating informed clinical decision-making based on diagnostic outcomes and potential clinical benefits.

Consistent predictive ability of prostate-specific antigen density prediction model for clinically significant prostate cancer across age strata.

Prebiopsy prostate-specific antigen density (PSAD) is a well-known predictor of clinically significant prostate cancer (csPCa). Since prostate-specific antigen(PSA) and prostate volume (PV) increase normally with aging, PSAD thresholds may vary. The purpose of the study was to determine if PSAD was predictive of csPCa in different age strata. We retrospectively reviewed our institutional database for patients who underwent multiparametricmagnetic resonance imaging (MRI) between January 2016 and December 2021. We included patients who had post-MRI prostate biopsies. Based on age, we divided our cohort into four subgroups (groups 1-4): <55, 55-64, 65-74, and ≥75 years old. PSAD accuracy was estimated by the area under the curve (AUC) as a predictive model for differentiating csPCa between the groups. CsPCa was defined as a Gleason Grade Group 2 or higher. Three different PSAD thresholds (0.1, 0.15, and 0.2) were tested across the groups for sensitivity, specificity, and positive predictive value (PPV) and negative predictive value(NPV). Chi-square and analysis of variance tests were used for bivariate analysis. All analyswere completed using R 4.3 (R Core Team, 2023). Among 1913 patients, 883 (46.1%) had prostate biopsies. In groups 1, 2, 3, and 4, there were 62 (7%), 321 (36.4%), 404 (45.8%), and 96 (10.9%) patients, respectively. Median PSA was 5.6 (interquartile range 3.4-8.1), 6.2 (4.8-9), 6.8 (5.1-9.7), and 9 (5.6-13), respectively (p < 0.01). Median PV was 42.3 (30-62), 51 (36-77), 55.5 (38-85.9), and 59.3 (42-110) mL, respectively (p < 0.01). No difference was observed in median PSAD between age groups 1-4 (0.1 [0.07-0.16], 0.11 [0.08-0.18], 0.1 [0.07-0.19], and 0.1 [0.07-0.2]), respectively (p = 0.393). CsPCa was diagnosed in 241 (27.3%) patients, of which 10 (16.1%), 65 (20.2%), 121 (30%), and 45 (46.7%) were in groups 1-4, respectively (p < 0.001). For groups 1-4, the PSAD AUC for predicting csPCa was 0.75, 0.68, 0.71, and 0.74. While testing PSAD threshold of 0.15 across the different age groups (1-4), the PPV vs.NPV was 39.1 vs. 93.2, 33.6 vs. 87, 50.9 vs. 80.8, and 66.1 vs. 64.7, respectively. PSAD prediction model was found to be similar among different age groups. In young patients, PSAD had a high NPV but low PPV. With increasing age, the opposite trend was observed, likely due to higher disease prevalence. While PSAD thresholds may be less useful in older patients to rule out higher-grade prostate cancer, the clinical consequences of these diagnoses require a case-by-case evaluation.

A modified sampling method for the precise detection of prostate cancer tissues using a three-dimensional stereotaxic location technique.

The rapid and accurate acquisition of prostate cancer pathological tissue is critical to prostate cancer research but has traditionally proven challenging. However, the gradual application of three-dimensional (3D) modeling in medical practice has overcome many of the related limitations. This cohort study aimed to compare the difference between a 3D stereotaxic sampling method and traditional cognitive sampling method to clarify the factors affecting sampling. An analysis of 111 men who received radical prostatectomy for prostate cancer at The First Affiliated Hospital of Soochow University between November 2020 and April 2022 was conducted. The positive rate of the cognitive sampling method and the 3D stereotaxic sampling method and their respective influencing factors, such as age, body mass index (BMI), prostate-specific antigen (PSA), PSA density (PSAD), International Society of Urological Pathology (ISUP) grade, tumor volume, number of positive needles from perineal puncture, clinical T stage, and tumor image location, were compared and analyzed, and a cohort study was conducted. Among the 111 patients, there were 57 cases of cognitive sampling and 54 cases of 3D stereotaxic sampling. In this study, the positive rate of cognitive sampling was 29.82% (17/57,), and the positive rate of 3D stereotaxic sampling was 61.11% (33/54), with the positive rate of 3D stereotaxic sampling being significantly higher than that of cognitive sampling (P=0.001). In cognitive sampling, tumor volume [odds ratio (OR) =1.10; 95% confidence interval (CI): 1.02-1.20], number of positive biopsy cores (OR =1.30; 95% CI: 1.06-1.60), Prostate Imaging Report and Data System (PI-RADS) score (OR =5.54; 95% CI: 1.60-19.12), and clinical T stage (OR =2.36; 95% CI: 1.31-4.25) were identified as influencing factors; in 3D stereotaxic sampling, these influencing factors were eliminated, with ORs of 1.22 (95% CI: 0.78-1.90), 0.88 (95% CI: 0.72-1.09), 1.09 (95% CI: 0.62-1.92), and 1.51 (95% CI: 0.86-2.65), respectively, representing a statistically significant difference (P<0.05). The 3D stereotaxic sampling method can accurately obtain the required prostate cancer tissue from the prostate in vitro within a short time, and the factors affecting the positive rate of sampling can be eliminated.

Development of prediction models based on risk scores for clinically significant prostate cancer on MRI/TRUS fusion biopsy

BackgroundThe implementation of population screening for prostate cancer has increased the number of patients with biochemical suspicion. Prediction models may reduce the number of unnecessary biopsies by identifying patients who benefit the most from them. Our aim is to develop a prediction model that is easily applicable in patients with suspicion of prostate cancer in the urology clinic setting to avoid unnecessary biopsies. MethodsWe developed prediction models based on risk scores for the detection of prostate cancer and clinically significant prostate cancer using the TRIPOD guidelines. For this, we conducted an observational and retrospective review of computerised medical records of 204 patients undergoing prostate fusion biopsy between 2018 and 2021. We also reviewed other prediction models for prostate cancer including radiological parameters and targeted sampling of suspicious lesions. ResultsA total of 204 patients underwent a biopsy, 138 were diagnosed of prostate cancer, and from them, 60 of clinically significant prostate cancer. Multivariate regression and random forest analysis were performed. Age, PSA density, diameter of the index lesions and PIRADS score on MRI were identified as predictors with an Area Under the Curve ranging between 0.71 and 0.80 and acceptable calibration results. Risk scores may avoid between 21.7% and 48.1% of biopsies. ConclusionOur prediction models are characterised by ease of use and may reduce unnecessary biopsies with satisfactory discrimination and calibration results while bringing benefits to the healthcare system and patients.

The predictive impact of hematological inflammatory markers in detecting prostate cancer in patients with PI-RADS 3 lesions on multiparametric magnetic resonance imaging.

The diagnostic accuracy of suspicious lesions that are classified as PI-RADS 3 in multiparametric prostate magnetic-resonance imaging (mpMRI) is controversial. This study aims to assess the predictive capacity of hematological inflammatory markers such as neutrophil-lymphocyte ratio (NLR), pan-immune-inflammation value (PIV), and systemic immune-response index (SIRI) in detecting prostate cancer in PI-RADS 3 lesions. 276 patients who underwent mpMRI and subsequent prostate biopsy after PI-RADS 3 lesion detection were included in the study. According to the biopsy results, the patients were distributed to two groups as prostate cancer (PCa) and no cancer (non-PCa). Data concerning age, PSA, prostate volume, PSA density, PI-RADS 3 lesion size, prostate biopsy results, monocyte counts (109/L), lymphocyte counts (109/L), platelet counts (109/L), neutrophils count (109/L) were recorded from the complete blood count. From these data; PIV value is obtained by monocyte × neutrophil × platelet/lymphocyte, NLR by neutrophil/lymphocyte, and SIRI by monocyte number × NLR. Significant variations in neutrophil, lymphocyte, and monocyte levels between PCa and non-PCa patient groups were detected (p = 0.009, p = 0.001, p = 0.005 respectively, p < 0.05). NLR, PIV, and SIRI exhibited significant differences, with higher values in PCa patients (p = 0.004, p = 0.001, p < 0.001 respectively, p < 0.05). The area under curve of SIRI was 0.729, with a cut-off value of 1.20 and with a sensitivity 57.70%, and a specificity of 68.70%. SIRI outperformed NLR and PIV in detecting PCa in PI-RADS 3 lesions, showcasing its potential as a valuable biomarker. Implementation of this parameter to possible future nomograms has the potential to individualize and risk-stratify the patients in prostate biopsy decision.

Prediction of Clinically Significant Prostate Cancer Using Multiparametric MRI, Biparametric MRI, and Clinical Parameters

Introduction: Multiparametric MRI (mpMRI) is gold standard for the primary diagnostic work-up of clinically significant prostate cancer (csPCa). The aim of this study was to assess the benefit of the perfusion sequence and the non-inferiority of an MRI without contrast administration (bpMRI) compared to mpMRI while taking clinical parameters into account. Methods: In this retrospective, non-interventional study we examined MRI data from 355 biopsy-naïve patients, performed on a 3T MRI system, evaluated by a board-certified radiologist with over 10 years of experience with subsequent mpMRI-TRUS fusion biopsy. Discussion: Only 16/355 (4.5%) patients benefited from dynamic contrast enhanced. In only 3/355 (0.8%) patients, csPCa would have been missed in bpMRI. BpMRI provided sensitivity and specificity (81.4%; 79.4%) comparable to mpMRI (75.2%; 81.8%). Additionally, bpMRI and mpMRI were independent predictors for the presence of csPCa, individually (OR: 15.36; p < 0.001 vs. 12.15; p = 0.006) and after accounting for established influencing factors (OR: 12.81; p < 0.001 vs. 6.50; p = 0.012). When clinical parameters were considered, a more balanced diagnostic performance between sensitivity and specificity was found for mpMRI and bpMRI. Overall, PSA density showed the highest diagnostic performance (area under the curve = 0.81) for the detection of csPCa. Conclusion: The premise of the study was confirmed. Therefore, bpMRI should be adopted as soon as existing limitations have been lifted by prospective multi-reader studies.

Analysis of risk factors for persistent PSA after radical prostatectomy: results from a high-volume center in Southeast China

BackgroundFor localized prostate cancer, a comprehensive treatment approach centered around radical prostatectomy (RP) is often their optimal choice. Successful RP can typically reduce prostate-specific antigen (PSA) levels to below 0.1 ng/mL within 6 to 8 weeks postoperatively. However, in clinical practice, 5 to 24% of patients may have a PSA ≥ 0.1 ng/mL at 6 to 8 weeks after surgery, a phenomenon known as PSA persistence. Many studies based on data from Europe and United States have shown an association between PSA persistence and poor postoperative outcomes, further analyzing the risk factors for PSA persistence. However, relevant research based on data from China remains scarce.MethodsRetrospective study of 1,347 prostate cancer patients who underwent RP at the First Affiliated Hospital of Zhejiang University School of Medicine from July 15, 2016, to August 31, 2022. Based on inclusion criteria, univariate and multivariate logistic regression analyses were conducted to explore the independent risk factors for persistent PSA.ResultsAmong the 826 prostate cancer patients after RP, 124 patients experienced persistent PSA. In univariate logistic regression analysis, robot-assisted laparoscopic radical prostatectomy (RARP), preoperative PSA, high-risk group, preoperative International Society of Urological Pathology (ISUP) grades 2–5, postoperative ISUP grades 3–5, percentage of positive cores, cT3, ≥pT3b, extracapsular extension (EPE), seminal vesicle invasion (SVI), positive surgical margins (PSM) and Prostate Specific Antigen Density (PSAD) were all significantly associated with PSA persistence after RP (P < 0.05). In terms of surgical approach, RARP was considered a protective factor against postoperative PSA persistence (OR:0.53, p < 0.05). In multivariate logistic regression analysis, preoperative ISUP grade 4, percentage of positive cores and PSM were independent risk factors of PSA persistence after RP (P < 0.05).ConclusionPreoperative PSA, high-risk group, preoperative ISUP grades 2–5, postoperative ISUP grades 3–5, percentage of positive cores, cT3, ≥pT3b, EPE, SVI, PSM and PSAD were independent risk factors for PSA persistence in prostate cancer patients after RP. This provides assistance for early monitoring and treatment of patients at high risk of persistent PSA in clinical practice.

Limited Utility of Dynamic Contrast Enhancement Imaging Sequences Within the PI-RADS v2.1 Classification Scheme: A Retrospective Cross-Sectional Study of MRI Reports.

Background/Objective: We sought to characterize the proportion of peripheral zone lesions "upgraded" within the PI-RADS v2.1 protocol using DCE imaging sequences in a large patient population undergoing multiparametric prostate MRI. Methods: A retrospective review of radiologist reports for 2742 prostate MRI exams at 2 large Alberta teaching hospitals between January 2017 and January 2022 was conducted. Prostate specific antigen (PSA), prostate volume, sequence specific and overall PI-RADS scores, and lesion positivity for DCE were collected if present in the accompanying radiology report. Further, pathology reports of biopsies of the upgraded lesions within upgraded patients were reviewed to see if upgraded lesions were deemed clinically significant by gleason score/grade group. Results: The median age was 63 years, with a median PSA and PSA density of 7.5 ng/mL and 0.13 ng/mL2 respectively. A total of 1809 lesions were reported, with 69.4% of all lesions being DCE positive. Of the lesions within the peripheral zone, 548 were overall PI-RADS 4. A total of 87/2742 (3.2%) of patients were upgraded to a PI-RADS 4 by DCE imaging. Within these patients, 65 had pathology reports available, of which 18 had a clinically significant lesion at the upgrade site. Conclusion: Contrast enhancement is only beneficial for a very small portion of patients undergoing prostate MRI. Given the invasive nature of contrast enhanced studies, potential contrast induced side effects, added imaging time, and the cost of contrast agent, routine use of contrast for prostate MRI is questioned. Further studies are necessary to determine if it should be part of routine prostate MRI imaging protocols.

Development and validation of a novel nomogram to avoid unnecessary biopsy in patients with PI-RADS category ≥ 4 lesions and PSA ≤ 20 ng/ml.

To develop and validate a prediction model for identifying non-prostate cancer (non-PCa) in biopsy-naive patients with PI-RADS category ≥ 4 lesions and PSA ≤ 20 ng/ml to avoid unnecessary biopsy. Eligible patients who underwent transperineal biopsies at West China Hospital between 2018 and 2022 were included. The patients were randomly divided into training cohort (70%) and validation cohort (30%). Logistic regression was used to screen for independent predictors of non-PCa, and a nomogram was constructed based on the regression coefficients. The discrimination and calibration were assessed by the C-index and calibration plots, respectively. Decision curve analysis (DCA) and clinical impact curves (CIC) were applied to measure the clinical net benefit. A total of 1580 patients were included, with 634 non-PCa. Age, prostate volume, prostate-specific antigen density (PSAD), apparent diffusion coefficient (ADC) and lesion zone were independent predictors incorporated into the optimal prediction model, and a corresponding nomogram was constructed ( https://nomogramscu.shinyapps.io/PI-RADS-4-5/ ). The model achieved a C-index of 0.931 (95% CI, 0.910-0.953) in the validation cohort. The DCA and CIC demonstrated an increased net benefit over a wide range of threshold probabilities. At biopsy-free thresholds of 60%, 70%, and 80%, the nomogram was able to avoid 74.0%, 65.8%, and 55.6% of unnecessary biopsies against 9.0%, 5.0%, and 3.6% of missed PCa (or 35.9%, 30.2% and 25.1% of foregone biopsies, respectively). The developed nomogram has favorable predictive capability and clinical utility can help identify non-PCa to support clinical decision-making and reduce unnecessary prostate biopsies.

Modern predictors and management of incidental prostate cancer at holmium enucleation of prostate.

To evaluate contemporary preoperative risk factors and subsequent postoperative management of incidental prostate cancer (iPCa) and incidental clinically significant prostate cancer (icsPCa, Grade Group [GG] ≥ 2 PCa). A retrospective cohort of 811 men undergoing Holmium enucleation of the prostate (HoLEP) (January 2021-July 2022) were identified. Advanced preoperative testing was defined as prostate health index (PHI), prostate MRI, and/or negative preoperative biopsy. Descriptive statistics (Whitney-Mann U test, Chi-squared test) and multivariable logistic regression were performed. iPCa and icsPCa detection rates were 12.8% (104/811) and 4.4% (36/811), respectively. Advanced preoperative testing (406/811, 50%) was associated with younger age and higher (prostate specific antigen) PSA, prostate volume, and PSA density. On multivariable analysis, PHI ≥ 55 was associated with iPCa (OR 6.91, 95% CI 1.85-26.3, p = 0.004), and % free PSA (%fPSA) was associated with icsPCa (OR 0.83, 95% CI 0.67, 0.94, p = 0.01). GG1 disease comprised the majority of iPCa (65%, 68/104) with median 1% involvement. iPCa patients were followed with active surveillance (median follow up 9.3 months), with higher risk patients receiving prostate MRI and confirmatory biopsy. Three patients proceeded to radical prostatectomy or radiation. In the era of MRI and advanced biomarkers, the majority of iPCa following HoLEP is low volume GG1 suitable for active surveillance. A tentative follow-up strategy is proposed. Patients with PHI ≥ 55 or low %fPSA, even with negative prostate MRI, can consider preoperative prostate biopsy before HoLEP.

Prevalence and potential predictors of incidental prostate Cancer in patients undergoing surgery for Benign Prostatic obstruction: a retrospective study in the MRI era.

Despite advancements in prostate multiparametric magnetic resonance imaging (mpMRI) and fusion biopsy (FB), the management of incidental prostate cancer (IPCa) after surgery for benign prostatic obstruction (BPO) remains unclear. The aim of this retrospective study is to determine the prevalence of IPCa in our cohort and identify potential predictors for its occurrence. We enrolled patients underwent TURP or simple prostatectomy for BPO at our high-volume center between January 2020-December 2022. Data on age, pre-operative total PSA (tPSA) and PSA density (PSAd) levels, prostate volume, previous MRI, biopsies, specimen weight, rates of positive tissue slices, ISUP score and three-month tPSA were collected. Of 454 patients with negative digital rectal examination who underwent BPO surgery, 74 patients (16.3%) were found to have IPCa. Of these, 33 patients (44.6%) had undergone previous mpMRI. Among the patients who had mpMRI, 23 had negative mpMRI results for suspected prostate cancer, while 10 had positive mpMRI findings (PIRADS ≥ 3) but no evidence of tumor upon FB. KW analysis indicates that PSAd was statistically associated with higher ISUP score, while at univariable regression analysis negative mpMRI (p = 0.03) was the only potential predictor for IPCa. Among the ISUP groups, PSAd showed a correlation with the tumor, while negative mpMRI was protective against clinically significant PCa. In the era of mpMRI and FB, the IPCa rates found at our center is higher than reported in existing literature and if it were confirmed with further studies, maybe there is a need for expansion in urology guidelines.

Tailoring biopsy strategy in the MRI-fusion prostate biopsy era: systematic, targeted or neither?

BackgroundMagnetic resonance imaging (MRI) followed by targeted biopsy (TBx) is utilized for prostate cancer (PCa) detection. However, the value of adding systematic biopsies (SBx) to targeted biopsy procedures (combined biopsy; CBx) in men with suspicious MRI findings has not been determined.MethodsWe analysed biopsy outcomes in 429 men with MRI lesions in the prospective multicenter STHLM3MRI pilot study, planned for prostate biopsy. Participants underwent 1.5T biparametric MRI without contrast enhancement, reported according to the PI-RADS v2, and with TBx plus SBx if the MRI lesion score was ≥ 3. The endpoints were clinically nonsignificant (nsPCa) and clinically significant PCa (csPCa), defined as ISUP grade groups 1 and ≥ 2, respectively.ResultsThe median age was 65 years (59–70), and the median PSA 6.0 ng/ml (4.1–9.0). The detection rates of csPCa when using TBx or SBx combined were 18%, 46%, and 85% in men with PIRADS scores of 3 (n = 195), 4 (n = 121), and 5 (n = 113), respectively. This combined strategy detected csPCa in more men than TBx alone (43.6% vs 39.2%, p < 0.02), with similar detection of nsPCa (19.3% vs 17.7%, p = 0.2).In men with equivocal lesions (PI-RADS 3), the detection rates for csPCa were similar for the combined strategy and for TBx alone (17.9% and 15.4%, p = 0.06). However, there was an increase in the detection of nsPCa when using the combined strategy (21.0% vs 15.4%, p < 0.02).Men with equivocal lesions and a PSA density < 0.1 ng/ml2 or a Stockholm 3 test < 0.11 had a low risk of harboring csPCa.ConclusionsSupplementing targeted with systematic biopsies enhances clinically significant cancer detection. However, in men with equivocal lesions, this combination has potential for detecting nonsignificant disease. A subgroup of men with equivocal MRI findings may be identified as having a low risk for significant cancer and spared unnecessary biopsies.

Precision in prostate cancer detection: integrating prostate-specific antigen density (PSAD) and the Prostate Imaging Reporting and Data System (PI-RADS) to provide additional risk stratification for a more accurate diagnostic decision.

This study focuses on integrating prostate-specific antigen density (PSAD) and Prostate Imaging Reporting and Data System (PI-RADS) for enhanced risk stratification in biopsy-naïve patients. A prospective study was conducted on 339 patients with suspected prostate cancer, utilizing PSAD and PI-RADS in combination. Logistic regression models were employed, and receiver operating characteristic (ROC) analysis performed to evaluate predictive performance. The patient cohort underwent multiparametric MRI, targeted biopsy, and systematic biopsy. When patients were stratified into four PSAD risk groups, the rate of clinically significant prostate cancer (csPCa) increased significantly with higher PSAD levels. Logistic regression confirmed the independent contribution of PI-RADS and PSAD, highlighting their role in the prediction of csPCa. Combined models showed superior performance, as evidenced by the area under the curve (AUC) for PI-RADS category and PSAD (0.756), which exceeded that of the individual predictors (PSA AUC, 0.627, PI-RADS AUC 0.689, PSAD AUC 0.708). This study concludes that combining PSAD and PI-RADS improves diagnostic accuracy and predictive value for csPCa in biopsy-naïve men, resulting in a promising strategy to provide additional risk stratification for more accurate diagnostic decision in biopsy-naïve patients, especially in the PI-RADS 3 group.

Prior Negative Biopsy, PSA Density, and Anatomic Location Impact Cancer Detection Rate of MRI-Targeted PI-RADS Index Lesions.

MRI fusion prostate biopsy has improved the detection of clinically significant prostate cancer (CSC). Continued refinements in predicting the pre-biopsy probability of CSC are essential for optimal patient counseling. We investigated potential factors related to improved cancer detection rates (CDR) of CSC in patients with PI-RADS ≥ 3 lesions. The pathology of 980 index lesions in 980 patients sampled by transrectal mpMRI-targeted prostate biopsy across four medical centers between 2017-2020 was reviewed. PI-RADS lesion distribution included 291 PI-RADS-5, 374 PI-RADS-4, and 315 PI-RADS-3. We compared CDR of index PI-RADS ≥ 3 lesions based on location (TZ) vs. (PZ), PSA density (PSAD), and history of prior negative conventional transrectal ultrasound-guided biopsy (TRUS). Mean age, PSA, prostate volume, and level of prior negative TRUS biopsy were 66 years (43-90), 7.82 ng/dL (5.6-11.2), 54 cm3 (12-173), and 456/980 (46.5%), respectively. Higher PSAD, no prior history of negative TRUS biopsy, and PZ lesions were associated with higher CDR. Stratified CDR highlighted significant variance across subgroups. CDR for a PI-RADS-5 score, PZ lesion with PSAD ≥ 0.15, and prior negative biopsy was 77%. Conversely, the CDR rate for a PI-RADS-4 score, TZ lesion with PSAD < 0.15, and prior negative biopsy was significantly lower at 14%. For index PI-RADS ≥ 3 lesions, CDR varied significantly based on location, prior history of negative TRUS biopsy, and PSAD. Such considerations are critical when counseling on the merits and potential yield of prostate needle biopsy.

Risk factors for Gleason score upgrade from prostate biopsy to radical prostatectomy.

Accurate identification of prostate cancer Gleason grade group remains an important component of the initial management of clinically localized disease. However, Gleason score upgrading (GSU) from biopsy to radical prostatectomy can occur in up to a third of patients treated with surgery. Concern for disease undergrading remains a source of diagnostic uncertainty, contributing to both over-treatment of low-risk disease as well as under-treatment of higher-risk prostate cancer. This review examines the published literature concerning risk factors for GSU from time of biopsy to prostatectomy final pathology. Risk factors identified for Gleason upgrading include patient demographic and clinical factors including age, body mass index, race, prostate volume, and biomarker based assays, including prostate-specific antigen (PSA) density, and testosterone values. In addition, prostate magnetic resonance imaging (MRI) findings have also been associated with GSU. Biopsy-specific characteristics associated with GSU include lower number of biopsy cores and lack of targeted methodology, and possibly increasing percent biopsy core positivity. Recognition of risk factors for disease undergrading may prompt confirmatory testing including repeat sampling or imaging. Continued refinements in imaging guided biopsy techniques may also reduce sampling error contributing to undergrading.

Comparison of data fusion strategies for automated prostate lesion detection using mpMRI correlated with whole mount histology

BackgroundIn this work, we compare input level, feature level and decision level data fusion techniques for automatic detection of clinically significant prostate lesions (csPCa).MethodsMultiple deep learning CNN architectures were developed using the Unet as the baseline. The CNNs use both multiparametric MRI images (T2W, ADC, and High b-value) and quantitative clinical data (prostate specific antigen (PSA), PSA density (PSAD), prostate gland volume & gross tumor volume (GTV)), and only mp-MRI images (n = 118), as input. In addition, co-registered ground truth data from whole mount histopathology images (n = 22) were used as a test set for evaluation.ResultsThe CNNs achieved for early/intermediate / late level fusion a precision of 0.41/0.51/0.61, recall value of 0.18/0.22/0.25, an average precision of 0.13 / 0.19 / 0.27, and F scores of 0.55/0.67/ 0.76. Dice Sorensen Coefficient (DSC) was used to evaluate the influence of combining mpMRI with parametric clinical data for the detection of csPCa. We compared the DSC between the predictions of CNN’s trained with mpMRI and parametric clinical and the CNN’s trained with only mpMRI images as input with the ground truth. We obtained a DSC of data 0.30/0.34/0.36 and 0.26/0.33/0.34 respectively. Additionally, we evaluated the influence of each mpMRI input channel for the task of csPCa detection and obtained a DSC of 0.14 / 0.25 / 0.28.ConclusionThe results show that the decision level fusion network performs better for the task of prostate lesion detection. Combining mpMRI data with quantitative clinical data does not show significant differences between these networks (p = 0.26/0.62/0.85). The results show that CNNs trained with all mpMRI data outperform CNNs with less input channels which is consistent with current clinical protocols where the same input is used for PI-RADS lesion scoring.Trial registrationThe trial was registered retrospectively at the German Register for Clinical Studies (DRKS) under proposal number Nr. 476/14 & 476/19.