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OBJECTIVE: To determine cut-off values for prostate specific antigen density (PSAD) in diagnosing prostate carcinoma in symptomatic patients. METHODS: This cross sectional, observational study conducted at Department of Chemical Pathology and Endocrinology, Armed Forces Institute of Pathology, Rawalpindi, Pakistan from June 2020 to May 2021. Symptomatic patients (309) having prostatic enlargement on ultrasound were selected through consecutive sampling. All the patients underwent prostate biopsy for histopathological diagnosis. Prostate specific antigen density was calculated and compared between different age groups and different diseases. ROC curve was constructed and area under the curve was calculated to find out cut-off values value for PSAD. Sensitivity, specificity and accuracy were calculated at the cut-off values. RESULTS: Among 309 patients of median age was 68 years (IQR 43 – 75). There was a significant difference of PSAD in different age groups (p

Objective: The objective of the study is to identify the rate of significant prostate cancer (PCa) detection in PI-RADS3 lesions in AA patients stratified by PSAD threshold of < 0.15 vs. ≥ 0.15 ng/ml2 and lesion diameter of < 1 cm vs ≥ 1 cm. Methods: We analyzed our institutional database of MRI-TB to identify the rate of significant prostate cancer (PCa) detection in PI-RADS3 lesions in AA patients stratified by PSAD threshold of < 0.15 vs. ≥ 0.15 ng/ml2 and lesion diameter of < 1 cm vs ≥ 1 cm. Significant prostate cancer was defined as Gleason grade group 2 or higher on MRI-TB of the PI-RADS 3 lesion. Results: Of 768 patients included in the database, 211 (27.5%) patients identified themselves as AAs. Mean age of AA patients was 63 years and mean PSAD was 0.21. Sixty nine (32.7%) AA patients were found to have PI-RADS 3 lesions. Mean PSAD of AA patients with PI-RADS 3 lesions was 0.21 ng/ml2 as well. Fifty percent of AA patients with PI-RADS 3 lesions had PSAD ≥ 0.15 ng/ml2. Significant PCa detection rate for AA patients with PI-RADS 3 lesions was 9% for PSAD of ≥ 0.15 vs. 0.03% percent for AA patients with PSAD < 0.15 ng/ml2 (OR 7.056, CI 1.017–167.9, P = 0.04). Stratification by lesion diameter (< 1 cm vs. > 1 cm) resulted in missing 0% of significant PCa when only AA patients with PSAD ≥ 0.15 ng/ml2 and lesion diameter ≥ 1 cm received MRI-TB. Conclusions: We report on the performance of a reported PSAD density threshold in detecting significant PCa in one of the largest series of AA patients receiving MRI-TB of the prostate. Our results have direct clinical implications when counseling AA patients with PI-RADS 3 lesion on whether they should undergo MRI-TB of such lesions. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the influence of endogenous testosterone density (ETD) on pelvic lymph node invasion (PLNI) in high risk (HR) prostate cancer (PCa) treated with radical prostatectomy (RP) and staged with extended pelvic lymph node dissection (ePLND). Materials and methods: ETD was evaluated as the ratio of endogenous testosterone (ET) on prostate volume (PV). HR-PCa was assessed according to the European Association of Urology (EAU) system. The association of ETD and other routinely clinical factors (BPC: percentage of biopsy positive cores; PSA: prostate specific antigen; ISUP: tumor grade system according to the International Society of Urologic Pathology; cT: tumor clinical stage) with the risk of PLNI was assessed by the logistic regression model. Results: Overall, 201 out of 805 patients (24.9%) were classified HR and PLNI occurred in 42 subjects (20.9%). On multivariate analysis, PLNI was independently predicted by BPC (OR 1.020; 95% CI 1.006–1.035; p = 0.019), ISUP > 3 (OR 2.621; 95% CI 1.170–5.869; p = 0.019) and ETD (OR 0.932; 95% CI 0.870–0.999; p = 0.045). After categorizing continuous clinical predictors, the risk of PLNI was independently increased by ETD up to the median (OR 2.379; 95% CI 1.134–4.991; p = 0.022), BPC > 50% (OR 3.125; 95% CI 1.520–6.425; p = 0.002) as well as by ISUP > 3 (OR 2.219; 95% CI 1.031–4.776; p = 0.042). Conclusions: As ETD measurements decreased, patients were more likely to have PLNI. In HR disease with PLNI, the influence of PCa on ETD should be addressed by higher level studies. [ABSTRACT FROM AUTHOR]

Objective: To calculate the negative predictive value (NPV) of negative multiparametric prostate magnetic resonance imaging (mpMRI), accepted as no lesions on images, when combined with prostate-specific antigen density (PSAD) and free/total prostate-specific antigen ratio (f/t PSA) in grey zone patients., Methods: 191 patients with PSA levels between 4-10 mg/mL and negative mpMRI were analyzed. The NPV of negative mpMRI was calculated according to a PSAD level of <0.15 ng/mL/mL, f/t PSA ratio of >0.15, and a combination of both. Patients were divided into three risk groups according to these two parameters, which were PSAD 0.01-0.07 ng/mL/mL and f/t PSA ratio ≥25 in a low-risk group, PSAD 0.08-0.15 ng/mL/mL, and f/t PSA ratio 0.15-0.24 in an intermediate-risk group and high-risk group, in which PSAD > 0.15 ng/mL/mL and f/t PSA ratio <15., Results: NPV of negative mpMRI was 92.6% for clinically significant prostate carcinoma (CSPCa). It increased to 97.5% in a low-risk group and decreased to 33.3% for CSPCa in a high-risk group. NPV of negative mpMRI results were so close when combined with PSAD < 0.15 ng/mL/mL and f/t PSA > 15., Conclusion: f/t PSA ratio might also be used to increase the NPV of mpMRI, like PSAD. We advise not to avoid prostate biopsy when PSAD is >0.15 ng/mL/mL and the f/t PSA ratio is <0.15. However, we need randomized controlled studies with more patients to confirm our study., (Copyright © 2023 AEU. Published by Elsevier España, S.L.U. All rights reserved.)

Objectives: The incidence of prostate cancer is increasing every year, and precision diagnosis and treatment can help reduce unnecessary prostate punctures for prostate cancer patients in the gray area. This study aims to investigate the diagnostic value of 18 F-prostate specific membrane antigen (PSMA) imaging combined with prostate specific antigen (PSA)-derived indicators for gray zone prostate cancer., Methods: A total of 107 patients who underwent 18 F-PSMA PET/CT imaging for suspicious prostate cancer with tPSA of 4 to 10 μg/L (PSA gray zone) in a hospital were retrospectively included, and were divided into a prostate cancer group and a non-prostate cancer group based on pathological findings. Patients underwent PSA testing, 18 F-PSMA, and abdominal ultrasound, and age, tPSA, fPSA, f/tPSA, prostate volume, PSA density (PSAD), maximum standardized uptake value (SUVmax), and molecular imaging prostate specific membrane antigen (miPSMA) score were compared between the 2 groups. Multivariate logistic regression was used to analyze the influencing factors the diagnosis of gray zone prostate cancer. Receiver operating characteristic (ROC) curves were constructed to evaluate the efficacy of PSAD and SUVmax alone and in combination in diagnosing gray zone prostate cancer., Results: The volume of the prostate cancer group [42.00(34.00, 58.00) cm 3 vs 49.00(41.27, 60.41) cm 3 ] was smaller than that of the non-prostate cancer group ( Z =-2.376, P =0.017), and the PSAD [(0.18±0.06) μg/(L·cm 3 ) vs 0.15±0.05 μg/(L·cm 3 )] and SUVmax [18.63(8.03, 28.57) vs 9.33(5.90, 13.52)] were higher than those in the non-prostate cancer group (both P <0.05). The percentage of miPSMA score ≥2 in the prostate cancer group was higher than that in the non-prostate cancer group ( χ 2 =40.987, P< 0.001). PSAD ( OR =22.154, 95% CI 1.430 to 873.751, P =0.042) and SUVmax ( OR =1.301, 95% CI 1.034 to 1.678, P =0.009) were independent influential factors for the diagnosis of prostate cancer in the gray zone. The optimal cut-off values of PSAD and SUVmax were 0.22 μg/(L·cm 3 ) and 8.02, respectively, and the AUCs for the diagnosis of prostate cancer in the gray zone alone and in combination were 0.628 (95% CI 0.530 to 0.720, P <0.05) and 0.806 (95% CI 0.718 to 0.876, P <0.05), 0.847 (95% CI 0.765 to 0.910, P <0.05), with sensitivities of 41.03%, 76.92%, and 74.36% and specificities of 79.41%, 89.71%, and 92.65%, respectively., Conclusions: PSAD and SUVmax are increased in patients with gray zone prostate cancer, and the combination of PSAD and SUVmax is of high value in diagnosing gray zone prostate cancer.

Introduction: The University of California, San Francisco Cancer of the Prostate Risk Assessment (CAPRA) score is a validated tool using factors at diagnosis to predict prostate cancer outcomes after radical prostatectomy (RP). This study evaluates whether substitution of prostate-specific antigen (PSA) density for serum PSA improves predictive performance of the clinical CAPRA model., Methods: Participants were diagnosed in 2000-2019 with stage T1/T2 cancer, underwent RP, with at least a 6-month follow-up. We computed standard CAPRA score using diagnostic age, Gleason grade, percent positive cores, clinical T stage, and serum PSA, and an alternate score using similar variables but substituting PSA density for PSA. We reported CAPRA categories as low (0-2), intermediate (3-5), and high (6-10) risk. Recurrence was defined as two consecutive PSA ≥ 0.2 ng/mL or receipt of salvage treatment. Life table and Kaplan-Meier analysis evaluated recurrence-free survival after prostatectomy. Cox proportional hazards regression models tested associations of standard or alternate CAPRA variables with recurrence risk. Additional models tested associations between standard or alternate CAPRA score with recurrence risk. Cox log-likelihood ratio test (-2 LOG L) assessed model accuracy., Results: A total of 2880 patients had median age 62 years, GG1 30% and GG2 31%, median PSA 6.5, and median PSA density 0.19. Median postoperative follow-up was 45 months. Alternate CAPRA model was associated with shifts in risk scores, with 16% of patients increasing and 7% decreasing (p < 0.01). Recurrence-free survival after RP was 75% at 5 years and 62% at 10 years. Both CAPRA component models were associated with recurrence risk after RP on Cox regression. Covariate fit statistics showed better fit for standard CAPRA model versus alternate (p < 0.01). Standard (hazard ratio [HR]: 1.55; 95% confidence interval [CI]: 1.50-1.61) and alternate (HR: 1.50; 95% CI: 1.44-1.55) CAPRA scores were associated with recurrence risk, with better fit for standard model (p < 0.01)., Conclusions: In a 2880 patient cohort followed for median 45 months after RP, alternate CAPRA model using PSA density was associated with higher biochemical recurrence (BCR) risk, but performed inferior to standard CAPRA at predicting BCR. While PSA density is an established prognostic variable in prediagnostic settings and sub-stratifying low-risk disease, it does not improve BCR model predictive accuracy when applied across a range of cancer risk., (© 2023 Wiley Periodicals LLC.)

Prostate cancer lesion segmentation in multi-parametric magnetic resonance imaging (mpMRI) is crucial for pre-biopsy diagnosis and targeted biopsy guidance. Deep convolution neural networks have been widely utilized for lesion segmentation. However, these methods fail to achieve a high Dice coefficient because of the large variations in lesion size and location within the gland. To address this problem, we integrate the clinically-meaningful prostate specific antigen density (PSAD) biomarker into the deep learning model using feature-wise transformations to condition the features in latent space, and thus control the size of lesion prediction. We tested our models on a public dataset with 214 annotated mpMRI scans and compared the segmentation performance to a baseline 3D U-Net model. Results demonstrate that integrating the PSAD biomarker significantly improves segmentation performance in both Dice coefficient and centroid distance metric.