Prostate cancer with elevated free prostate-specific antigen density: A case report.

BACKGROUND: Prostate cancer is the second most common cancer among men worldwide, and prostate-specific antigen (PSA) is often used in clinical practice to screen for prostate cancer. Normal total PSA (tPSA) level initially excludes prostate cancer. Here, we report a case of prostate cancer with elevated free PSA density (fPSAD). CASE SUMMARY: A patient diagnosed with benign prostatic hyperplasia underwent prostatectomy, and the postoperative pathological results showed acinar adenocarcinoma of the prostate. The patient is currently undergoing endocrine chemotherapy. CONCLUSION: We provide a clinical reference for diagnosis and treatment of patients with normal tPSA but elevated fPSAD.

The Impact of Prostate Volume on Prostate Cancer Detection: Comparing Magnetic Resonance Imaging with Transrectal Ultrasound in Biopsy-naïve Men.

Background and objective: This study aimed to determine the difference in prostate volume (PV) derived from transrectal ultrasound (TRUS) and multiparametric magnetic resonance imaging (mpMRI), and to further investigate the role of TRUS prostate-specific antigen density (PSAD) and mpMRI-PSAD in prostate cancer (PCa) detection in biopsy-naïve men. Methods: Patients who underwent an initial prostate biopsy within 3 mo after mpMRI between January 2016 and December 2021 were analyzed retrospectively. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of both TRUS-PSAD and mpMRI-PSAD for PCa detection were calculated and compared. The Pearson correlation coefficient, Bland-Altman plot, and receiver operating characteristic curve were also utilized to explore the interests of this study. Key findings and limitations: The median prostate-specific antigen level of 875 patients was 9.79 (interquartile range [IQR]: 7.09-13.50) ng/ml. The median mpMRI-PV and TRUS-PV were 41.92 (IQR: 29.29-60.73) and 41.04 (IQR: 29.24-57.27) ml, respectively, demonstrating a strong linear correlation (r = 0.831, 95% confidence interval: 0.809, 0.850; p < 0.01) and sufficient agreement. No significant difference was observed in terms of the sensitivity, specificity, PPV, and NPV between TRUS-PSAD and mpMRI-PSAD for any PCa and clinically significant PCa (csPCa) detection. The overall discriminative ability of TRUS-PSAD for detecting PCa or non-PCa, as well as csPCa and non-csPCa, was comparable with that of mpMRI-PSAD, and similar results were also observed in the subsequent analysis stratified by mpMRI-PV quartiles, prostate-specific antigen level, and age. The limitations include the retrospective and single-center nature and a lack of follow-up information. Conclusions and clinical implications: TRUS-PV and MRI-PV exhibited a strong linear correlation and reached sufficient agreement. The efficiency of TRUS-PSAD and mpMRI-PSAD for PCa detection was comparable. TRUS could be used for PV estimation and dynamic monitoring of PSAD, and TRUS-PSAD could effectively guide clinical decision-making and optimize diagnostic strategies. Patient summary: In this work, prostate volume (PV) derived from transrectal ultrasound (TRUS) exhibited a strong linear correlation with the PV derived from multiparametric magnetic resonance imaging (mpMRI). The efficiency of TRUS prostate-specific antigen density (PSAD) and mpMRI-PSAD for the detection of prostate cancer was comparable. TRUS could be used for PV estimation and TRUS-PSAD could help in clinical decision-making and optimizing diagnostic strategies.

Evaluación del valor predictivo negativo de la resonancia magnética multiparamétrica de próstata al combinar su puntuación con parámetros del antígeno prostático específico en pacientes con PSA en zona gris / The effect of the combination of prostate-specific antigen derivatives with multiparametric prostate magnetic resonance imaging scores on the negative predictive value of it in grey zone patients

Objetivo Calcular el valor predictivo negativo (VPN) de la resonancia magnética multiparamétrica (RMmp) de próstata negativa, definida como la ausencia de lesiones en las imágenes, cuando se combina con la densidad del PSA (DPSA) y el índice PSA libre/total (PSA l/t) en pacientes cuyo PSA se encuentra en la zona gris (4-10mg/ml). Métodos Se analizaron 191 pacientes con niveles de PSA entre 4 y 10mg/ml y RMmp negativa. El VPN de la RMmp negativa se calculó de acuerdo con un nivel de DPSA<0,15ng/ml/ml, un índice PSA l/t>0,15 y una combinación de ambos. Los pacientes se dividieron en 3 grupos de riesgo según estos dos parámetros, de la siguiente manera: • DPSA 0,01-0,07ng/ml/ml e índice PSA l/t≥25 en el grupo de bajo riesgo. • DPSA 0,08-0,15ng/ml/ml e índice PSA l/t 0,15-0,24 en el grupo de riesgo intermedio. • DPSA>0,15ng/ml/ml e índice PSA l/t<15 en el grupo de riesgo alto. Resultados El VPN de la RMmp negativa fue del 92,6% para el carcinoma de próstata clínicamente significativo (CPCS). El VPN aumentó al 97,5% en el grupo de riesgo bajo, y disminuyó al 33,3% en el de riesgo alto. El resultado al combinar la RMmp negativa con la DPSA<0,15ng/ml/ml fue muy similar al de su combinación con el PSA l/t>15. Conclusión el índice PSA l/t también podría utilizarse para aumentar el VPN de la RMmp, al igual que la DPSA. No recomendamos evitar la biopsia de próstata con una DPSA>0,15ng/ml/ml y un índice PSA l/t<0,15. Sin embargo, se requieren estudios controlados aleatorizados con más pacientes para confirmar los hallazgos de nuestro estudio. (AU)

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 One hundred ninety-one patients with PSA levels between 4-10mg/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: • 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. • PSAD>0.15 ng/ml/ml and f/t PSA ratio <15 in high-risk group, 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. (AU)

Pretreatment prostate-specific antigen density as a predictor of biochemical recurrence in patients with prostate cancer: a meta-analysis.

BACKGROUND: A consensus has not been reached on the value of prostate-specific antigen density (PSAD) as a predictor of biochemical recurrence of prostate cancer. This meta-analysis aimed to evaluate the association between PSAD and biochemical recurrence of prostate cancer after primary treatment. METHODS: Two authors systematically searched PubMed, Web of Science, and Embase databases (up to August September 10, 2023) to identify studies that assessed the value of pretreatment PSAD in predicting biochemical recurrence after primary treatment (radical prostatectomy or radiotherapy) of prostate cancer. A random effect model was used to pool adjusted hazard ratios (HR) with 95% confidence intervals (CI) for biochemical recurrence. RESULTS: Nine studies with 4963 patients were eligible for the meta-analysis. The reported prevalence of biochemical recurrence ranged from 4 to 55.1%. For patients with higher PSAD compared to those with low PSAD, the pooled HR of biochemical recurrence was 1.59 (95% CI 1.21-2.10). Subgroup analysis showed that the pooled HR of biochemical recurrence was 1.80 (95% CI 1.34-2.42) for patients who received radical prostatectomy, and 0.98 (95% CI 0.66-1.45) for patients who received radiotherapy. CONCLUSIONS: Elevated pretreatment PSAD may be an independent predictor for biochemical recurrence of prostate cancer after radical prostatectomy. Determining PSAD could potentially improve the prediction of biochemical recurrence in patients with prostate cancer.

PI-RADS v2.1 evaluation of prostate "nodule in nodule" variants: clinical, imaging, and pathological features.

OBJECTIVES: To analyze the correlation among the imaging features of prostate "nodule in nodule," clinical prostate indices, and pathology results. METHODS: We retrospectively analyzed the prostate images from 47 male patients who underwent MRI scans and pathological biopsy from January 2022 to July 2023. Two radiologists (R1/R2) evaluated the morphology and signal intensity of the "nodule in nodule" in a double-blind manner and calculated the PI-RADS v2.1 score, which was compared with clinical prostate indices and pathological results. RESULTS: 34.04% (16/47) of patients were pathologically diagnosed with clinically significant prostate cancer (csPCa). Total prostate-specific antigen (tPSA), free/t PSA, PSA density (PSAD), and prostate gland volume (PGV) were significantly different between csPCa patients and benign prostatic hyperplasia (BPH) patients with prostate "nodule in nodule". R1/R2 detected 17/17 prostate "nodule in nodule" pathologically confirmed as csPCa on MRI; 10.60% (16/151) (R1) and 11.11% (17/153) (R2) had diffusion-weighted imaging (DWI) PI-RADS v2.1 score of 4, and 0.66% (1/151) (R1) had a score of 3. The percentages of encapsulated, circumscribed, and atypical nodules and obscured margins were 0.00% (0/151), 0.00% (0/151), 5.96% (9/151), and 5.30% (8/151), respectively, for R1, and 0.00% (0/153), 0.00% (0/153), 5.88% (9/153), and 4.58% (7/153) for R2. CONCLUSION: When the inner nodules of "nodule in nodule" lesions in PI-RADS v2.1 category 1 in the TZ show incomplete capsulation or obscured margins, they are considered atypical nodules and might be upgraded to PI-RADS v2.1 category 3 if they exhibit marked diffusion restriction. However, further validation is needed. CRITICAL RELEVANCE STATEMENT: This study first analyzed the relationship between clinical and pathological findings and the size, margin, and multimodal MRI manifestations of the prostate "nodule in nodule." These findings could improve the diagnostic accuracy of PI-RADS v2.1 for prostate lesions. KEY POINTS: • The margin of the prostate inner nodules affects the PI-RADS v2.1 score. • The morphology of prostate "nodule in nodule" is related to their pathology. • The PI-RADS v2.1 principle requires consideration of prostate "nodule in nodule" variants.

Reduction of false positives using zone-specific prostate-specific antigen density for prostate MRI-based biopsy decision strategies.

OBJECTIVES: To develop and test zone-specific prostate-specific antigen density (sPSAD) combined with PI-RADS to guide prostate biopsy decision strategies (BDS). METHODS: This retrospective study included consecutive patients, who underwent prostate MRI and biopsy (01/2012-10/2018). The whole gland and transition zone (TZ) were segmented at MRI using a retrained deep learning system (DLS; nnU-Net) to calculate PSAD and sPSAD, respectively. Additionally, sPSAD and PI-RADS were combined in a BDS, and diagnostic performances to detect Grade Group ≥ 2 (GG ≥ 2) prostate cancer were compared. Patient-based cancer detection using sPSAD was assessed by bootstrapping with 1000 repetitions and reported as area under the curve (AUC). Clinical utility of the BDS was tested in the hold-out test set using decision curve analysis. Statistics included nonparametric DeLong test for AUCs and Fisher-Yates test for remaining performance metrics. RESULTS: A total of 1604 patients aged 67 (interquartile range, 61-73) with 48% GG ≥ 2 prevalence (774/1604) were evaluated. By employing DLS-based prostate and TZ volumes (DICE coefficients of 0.89 (95% confidence interval, 0.80-0.97) and 0.84 (0.70-0.99)), GG ≥ 2 detection using PSAD was inferior to sPSAD (AUC, 0.71 (0.68-0.74)/0.73 (0.70-0.76); p < 0.001). Combining PI-RADS with sPSAD, GG ≥ 2 detection specificity doubled from 18% (10-20%) to 43% (30-44%; p < 0.001) with similar sensitivity (93% (89-96%)/97% (94-99%); p = 0.052), when biopsies were taken in PI-RADS 4-5 and 3 only if sPSAD was ≥ 0.42 ng/mL/cc as compared to all PI-RADS 3-5 cases. Additionally, using the sPSAD-based BDS, false positives were reduced by 25% (123 (104-142)/165 (146-185); p < 0.001). CONCLUSION: Using sPSAD to guide biopsy decisions in PI-RADS 3 lesions can reduce false positives at MRI while maintaining high sensitivity for GG ≥ 2 cancers. CLINICAL RELEVANCE STATEMENT: Transition zone-specific prostate-specific antigen density can improve the accuracy of prostate cancer detection compared to MRI assessments alone, by lowering false-positive cases without significantly missing men with ISUP GG ≥ 2 cancers. KEY POINTS: • Prostate biopsy decision strategies using PI-RADS at MRI are limited by a substantial proportion of false positives, not yielding grade group ≥ 2 prostate cancer. • PI-RADS combined with transition zone (TZ)-specific prostate-specific antigen density (PSAD) decreased the number of unproductive biopsies by 25% compared to PI-RADS only. • TZ-specific PSAD also improved the specificity of MRI-directed biopsies by 9% compared to the whole gland PSAD, while showing identical sensitivity.

Utility of Prostate Health Index Density for Biopsy Strategy in Biopsy-Naïve Patients With PI-RADS v2.1 Category 3 Lesions.

BACKGROUND: Category 3 lesions in PI-RADSv2.1 pose diagnostic challenges, complicating biopsy decisions. Recent biomarkers like prostate health index (PHI) have shown higher specificity in detecting clinically significant prostate cancer (csPCa) than prostate-specific antigen (PSA). Yet their integration with MRI remains understudied. PURPOSE: To evaluate the utility of PSA and PHI with its derivatives for detecting csPCa in biopsy-naïve patients with category 3 lesion on initial prostate MRI scan. STUDY TYPE: Retrospective. POPULATION: One hundred ninety-three biopsy-naïve patients who underwent MRI, PSA, and PHI testing, followed by both targeted and systematic biopsies. FIELD STRENGTH/SEQUENCE: Turbo spin-echo T2-weighted imaging, diffusion-weighted single-shot echo-planar imaging, and dynamic contrast-enhanced T1-weighted fast field echo sequence imaging in 3 T. ASSESSMENT: PHI density (PHID) and PSA density (PSAD) derived by dividing serum PHI and PSA with prostate volume (MRI based methodology suggested by PI-RADSv2.1). Risk-stratified models to evaluate the utility of markers in triaging patients for biopsy, including low-, intermediate-, and high-risk groups. STATISTICAL TESTS: Independent t-test, Mann-Whitney U test, Mantel-Haenszel test, generalized estimating equation, and receiver operating characteristic (ROC) curve analysis were used. Statistical significance defined as P < 0.05. RESULTS: CsPCa was found in 16.6% (32/193) of patients. PHID had the highest area under the ROC curve (AUROC) of 0.793, followed by PHI of 0.752, PSAD of 0.750, and PSA of 0.654. PHID with two cut-off points (0.88/mL and 1.82/mL) showed the highest potential biopsy avoidance of 47.7% (92/193) with 5% missing csPCa, and the lowest intermediate-risk group (borderline decision group) at 38.9% (75/193), compared to PSA and PHI. DATA CONCLUSION: PHID demonstrated better potential in triaging patients with category 3 lesions, possibly aiding more selective and confident biopsy decisions for csPCa detection, than traditional markers. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 5.

Oncological outcomes in robot-assisted radical prostatectomy: the value of PSA density as a preoperative predictive factor.

Background: Pretreatment assessment of patients diagnosed with localized prostate cancer (PCa) is essential for therapeutic decision-making. Currently available staging systems based on prostate-specific antigen (PSA), Gleason score, and clinical stage allow for determining the prognostic characteristics of these patients. Several studies have evaluated the preoperative use of prostate-specific antigen density (PSAD) as a prognostic factor for further risk stratification. To date, the role of PSAD in this setting is still an object of debate. Objectives: The present analysis aimed to assess the predictive potential of PSAD for adverse oncological outcomes after robot-assisted radical prostatectomy (RARP) and to compare its accuracy to preoperative PSA (pPSA). Design and methods: We retrospectively reviewed 427 patients diagnosed with localized PCa who underwent RARP at a single institution between January 2015 and January 2020. Generating receiver operator characteristic (ROC) curves, calculating areas under the curves (AUCs), and using a linear regression model, we analyzed the association of PSAD and pPSA with postoperative positive surgical margins (PSM), Gleason score ⩾ 7, persistent PSA, and biochemical recurrence (BCR), with a median follow-up of 47 months. Results: PSAD showed a significant association with PSM (p < 0.0001), PSA persistence (p < 0.0001), and Gleason ⩾ 7 (p < 0.0001), without being statistically significant in predicting BCR (p = 0.098). The predictive value of PSAD was comparable to pPSA for outcomes of PSA persistence (AUC 0.727 versus 0.771) and Gleason ⩾ 7 (AUC 0.683 versus 0.649). Conclusion: PSAD is a predictive factor for postoperative oncological outcomes of PSM, Gleason score ⩾ 7, and persistence of PSA. Despite the need for further studies, PSAD could be useful as a prognostic parameter in conjunction with established staging systems.

Oncological outcomes in robot-assisted radical prostatectomy: the value of PSA density as a preoperative predictive factor Prostate-specific antigen density (PSAD) has an established role in the diagnostic process of prostate cancer (PCa). However, controversy remains on the assessment of its value as a pretreatment prognostic factor. The aim of our study was to evaluate the predictive ability of PSAD for oncological outcomes in PCa patients treated with robot-assisted radical prostatectomy (RARP) and to compare with the value of preoperative PSA (pPSA). The present analysis showed a significant association of PSAD with positive surgical margins (PSM), Gleason Score >=7 and prostate-specific antigen (PSA) persistence after RARP. Moreover, PSAD demonstrated to perform comparably to pPSA in predicting the outcomes of clinically significant PCa (csPCa) and post-RARP PSA persistence. Therefore, PSAD is considered a preoperative predictive factor potentially useful in conjunction with other previously established prognostic criteria and clinical features.

Diagnostic Performance of Prostate-specific Antigen Density for Detecting Clinically Significant Prostate Cancer in the Era of Magnetic Resonance Imaging: A Systematic Review and Meta-analysis.

CONTEXT: There has been a dramatic increase in the use of prostate magnetic resonance imaging (MRI) in the diagnostic workup. With prostate volume calculated from MRI, prostate-specific antigen density (PSAD) now is a ready-to-use parameter for prostate cancer (PCa) risk stratification before prostate biopsy, especially among patients with negative MRI or equivocal lesions. OBJECTIVE: In this review, we aimed to evaluate the diagnostic performance of PSAD for clinically significant prostate cancer (CSPCa) among patients who received MRI before prostate biopsy. EVIDENCE ACQUISITION: Two investigators performed a systematic review according of the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) criteria. Studies (published between January 1, 2012, and December 31, 2021) reporting the diagnostic performance (outcomes) of PSAD (intervention) for CSPCa among men who received prebiopsy prostate MRI and subsequent prostate biopsy (patients), using biopsy pathology as the gold standard (comparison), were eligible for inclusion. EVIDENCE SYNTHESIS: A total of 1536 papers were identified in PubMed, Scopus, and Embase. Of these, 248 studies were reviewed in detail and 39 were qualified. The pooled sensitivity (SENS) and specificity (SPEC) for diagnosing CSPCa among patients with positive MRI were, respectively, 0.87 and 0.35 for PSAD of 0.1 ng/ml/ml, 0.74 and 0.61 for PSAD of 0.15 ng/ml/ml, and 0.51 and 0.81 for PSAD of 0.2 ng/ml/ml. The pooled SENS and SPEC for diagnosing CSPCa among patients with negative MRI were, respectively, 0.85 and 0.36 for PSAD of 0.1 ng/ml/ml, 0.60 and 0.66 for PSAD of 0.15 ng/ml/ml, and 0.33 and 0.84 for PSAD of 0.2 ng/ml/ml. The pooled SENS and SPEC among patients with Prostate Imaging Reporting and Data System (PI-RADS) 3 or Likert 3 lesions were, respectively, 0.87 and 0.39 for PSAD of 0.1 ng/ml/ml, 0.61 and 0.69 for PSAD of 0.15 ng/ml/ml, and 0.42 and 0.82 for PSAD of 0.2 ng/ml/ml. The post-test probability for CSPCa among patients with negative MRI was 6% if PSAD was <0.15 ng/ml/ml and dropped to 4% if PSAD was <0.10 ng/ml/ml. CONCLUSIONS: In this systematic review, we quantitatively evaluated the diagnosis performance of PSAD for CSPCa in combination with prostate MRI. It demonstrated a complementary performance and predictive value, especially among patients with negative MRI and PI-RADS 3 or Likert 3 lesions. Integration of PSAD into decision-making for prostate biopsy may facilitate improved risk-adjusted care. PATIENT SUMMARY: Prostate-specific antigen density is a ready-to-use parameter in the era of increased magnetic resonance imaging (MRI) use in clinically significant prostate cancer (CSPCa) diagnosis. Findings suggest that the chance of having CSPCa was very low (4% or 6% for those with negative prebiopsy MRI or Prostate Imaging Reporting and Data System (Likert) score 3 lesion, respectively, if the PSAD was <0.10 ng/ml/ml), which may lower the need for biopsy in these patients.

Estimated Prostate Volume by Semiautomatic Segmentation of MRI Is More Accurately Correlated with Radical Prostatectomy Specimen Weight than the Volume Calculated by Ellipsoid Formula.

INTRODUCTION: Accurate in vivo prostate volume (PV) estimation is important for obtaining prostate-specific antigen density (PSAD) and further predicting clinically significant prostate cancer (csPCa). We aimed to evaluate the accuracy of multiparametric magnetic resonance imaging (mpMRI)-estimated PV compared to both volume and weight of radical prostatectomy (RP). METHODS: We identified 310 PCa patients who underwent RP following combined targeted and systematic biopsy in our institution from September 2019 to February 2021. The MRI PV was determined using a semiautomated segmentation algorithm. RP PV was calculated using the prolate ellipsoid formula (length × width × height × π/6). Formula (prostate weight = [actual weight-3.8 g]/1.05 g/mL) was applied, and the resulting volume was used in further analysis. RESULTS: The median PV from MRI, RP, and RP weight were 39 mL, 38 mL, and 44 mL, respectively. Spearman's rank correlation coefficients (ρ) were 0.841 (MRI PV vs. RP weight), 0.758 (RP PV vs. RP weight), and 0.707 (MRI PV vs. RP PV) (all p < 0.001). Decreased correlation between the MRI PV and RP PV was observed in the larger (more than 55 mL) prostate. The PSAD derived from MRI PV showed most efficient to detect csPCa in RP specimen (57.9% vs. 57.6% vs. 45.4%). CONCLUSION: MRI PV is correlated better with RP weight than calculated RP PV, especially in larger prostate. The high csPCa detection rate in final pathology suggested that PSAD derived from MRI PV can be confidently used in clinical practice.

The effect of the combination of prostate-specific antigen derivatives with multiparametric prostate magnetic resonance imaging scores on the negative predictive value of it in grey zone patients.

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.

INTEGRATING PROSTATE SPECIFIC ANTIGEN DENSITY BIOMARKER INTO DEEP LEARNING PROSTATE MRI LESION SEGMENTATION MODELS.

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.

Quantitative Evaluation of Apparent Diffusion Coefficient Values, ISUP Grades and Prostate-Specific Antigen Density Values of Potentially Malignant PI-RADS Lesions.

The aim of this study was to demonstrate the correlation between ADC values and the ADC/PSAD ratio for potentially malignant prostate lesions classified into ISUP grades and to determine threshold values to differentiate benign lesions (noPCa), clinically insignificant (nsPCa) and clinically significant prostate cancer (csPCa). We enrolled a total of 403 patients with 468 prostate lesions, of which 46 patients with 50 lesions were excluded for different reasons. Therefore, 357 patients with a total of 418 prostate lesions remained for the final evaluation. For all lesions, ADC values were measured; they demonstrated a negative correlation with ISUP grades (p < 0.001), with a significant difference between csPCa and a combined group of nsPCa and noPCa (ns-noPCa, p < 0.001). The same was true for the ADC/PSAD ratio, but only the ADC/PSAD ratio proved to be a significant discriminator between nsPCa and noPCa (p = 0.0051). Using the calculated threshold values, up to 31.6% of biopsies could have been avoided. Furthermore, the ADC/PSAD ratio, with the ability to distinguish between nsPCa and noPCa, offers possible active surveillance without prior biopsy.

The Value of Prostate-Specific Antigen Density in Combination with Lesion Diameter for the Accuracy of Prostate Cancer Prediction in Prostate Imaging-Reporting and Data System 3 Prostate Lesions.

INTRODUCTION: The aim of the study was to investigate the value of prostate-specific antigen density (PSAD) and lesion diameter (LD) combination in prostate cancer (PCa) detection. METHODS: 181 patients who were detected to have prostate imaging-reporting and data system (PI-RADS) 3 lesions in mpMRI and underwent prostate biopsies were included in the study. Demographic, clinical, and pathological data of all patients were evaluated. The patients were divided into four groups according to PSAD and LD status (PSAD <0.15 ng/mL/cc + LD <1 cm, PSAD <0.15 ng/mL/cc + LD ≥1 cm, PSAD ≥0.15 ng/mL/cc + LD <1 cm, and PSAD ≥0.15 ng/mL/cc + LD ≥1 cm). Diagnostic ability for PCa and clinical significant PCa (csPCa) was evaluated by PSAD and LD. RESULTS: PSAD ≥0.15 ng/mL/cc (OR = 6; 95% Cl = 2.847-12.647; p < 0.001), LD ≥1 cm (OR = 7.341; 95% confidence interval [CI] = 2.91-18.52; p < 0.001), and combination of PSAD ≥0.15 ng/mL/cc and LD ≥1 cm (OR = 10.023; 95% CI = 4.32-23.252; p < 0.001) were associated with PCa detection rates. The most sensitivity, specificity, negative, and positive predictive values were found in PSAD ≥0.15 ng/mL/cc + LD ≥1 cm group for both PCa and csPCa detection (48.8%, 92%, 85.2%, and 65.6% for any PCa detection; 66.7%, 85.2%, 97.3%, and 24.2% for csPCa detection, respectively). CONCLUSION: The presence of PSAD ≥0.15 ng/mL/cc or LD ≥1 cm in mpMRI of patients with PI-RADS 3 lesions is associated significantly with the finding of PCa and particularly with the detection of csPCa.

A novel clinically significant prostate cancer prediction system with multiparametric MRI and PSA: P.Z.A. score.

PURPOSE: This study aims to establish and validate a new diagnosis model called P.Z.A. score for clinically significant prostate cancer (csPCa). METHODS: The demographic and clinical characteristics of 956 patients were recorded. Age, prostate-specific antigen (PSA), free/total PSA (f/tPSA), PSA density (PSAD), peripheral zone volume ratio (PZ-ratio), and adjusted PSAD of PZ (aPSADPZ) were calculated and subjected to receiver operating characteristic (ROC) curve analysis. The nomogram was established, and discrimination abilities of the new nomogram were verified with a calibration curve and area under the ROC curve (AUC). The clinical benefits of P.Z.A. score were evaluated by decision curve analysis and clinical impact curves. External validation of the model using the validation set was also performed. RESULTS: The AUCs of aPSADPZ, age, PSA, f/tPSA, PSAD and PZ-ratio were 0.824, 0.672, 0.684, 0.715, 0.792 and 0.717, respectively. The optimal threshold of P.Z.A. score was 0.41. The nomogram displayed excellent net benefit and better overall calibration for predicting the occurrence of csPCa. In addition, the number of patients with csPCa predicted by P.Z.A. score was in good agreement with the actual number of patients with csPCa in the high-risk threshold. The validation set provided better validation of the model. CONCLUSION: P.Z.A. score (including PIRADS(P), aPSADPZ(Z) and age(A)) can increase the detection rate of csPCa, which may decrease the risk of misdiagnosis and reduce the number of unnecessary biopsies. P.Z.A. score contains data that is easy to obtain and is worthy of clinical replication.

Development and validation of a novel nomogram predicting clinically significant prostate cancer in biopsy-naive men based on multi-institutional analysis.

BACKGROUND: Prediction of clinically significant prostate cancer (csPCa) is essential to select biopsy-naive patients for prostate biopsy. This study was to develop and validate a nomogram based on clinicodemographic parameters and exclude csPCa using prostate-specific antigen density (PSAD) stratification. METHODS: Independent predictors were determined via univariate and multivariate logistic analysis and adopted for developing a predictive nomogram, which was assessed in terms of discrimination, calibration, and net benefit. Different PSAD thresholds were used for deciding immediate biopsies in patients with Prostate Imaging-Reporting and Data System (PI-RADS) 3 lesions. RESULTS: A total of 932 consecutive patients who underwent ultrasound-guided transperineal cognitive biopsy were enrolled in our study. In the development cohort, age (odds ratio [OR], 1.075; 95% confidence interval [CI], 1.036-1.114), PSAD (OR, 6.003; 95% CI, 2.826-12.751), and PI-RADS (OR, 3.419; 95% CI, 2.453-4.766) were significant predictors for csPCa. On internal and external validation, this nomogram showed high areas under the curve of 0.943, 0.922, and 0.897, and low Brier scores of 0.092, 0.102, and 0.133 and insignificant unreliability tests of 0.713, 0.490, and 0.859, respectively. Decision curve analysis revealed this model could markedly improve clinical net benefit. The probability of excluding csPCa was 98.51% in patients with PI-RADS 3 lesions and PSAD <0.2 ng/ml2 . CONCLUSION: This novel nomogram including age, PSAD, and PI-RADS could be applied to accurately predict csPCa, and 44.08% of patients with equivocal imaging findings plus PSAD <0.2 ng/ml2 could safely forgo biopsy.

Clinical value of prostate health index as an indicator for recommending magnetic resonance imaging in patients with gray-zone prostate-specific antigen level.

PURPOSE: To evaluate the usefulness of prostate health index (PHI) as an indicator for recommending magnetic resonance imaging (MRI) in patients with prostate-specific antigen (PSA) gray zone level < 10 ng/mL. METHODS: 443 patients who underwent prostate biopsy (PB) after serum PHI test and MRI between April 2019 and December 2022 were enrolled. For patients with visible lesion on MRI with Prostate Imaging Reporting and Data System Score (PI-RADS) ≥ 3, MRI-targeted PB was performed in addition to systematic 12-core PB. RESULTS: The optimal cutoff value of PHI for predicting PI-RADS ≥ 3 lesions was 39.6, which was significantly associated with overall prostate cancer (OR 3.07, p = 0.018) and clinically significant prostate cancer (csPCa) (OR 4.15, p = 0.006) at MRI-targeted PB cores. When MRI was restricted to patients with PHI ≥ 39.6 alone, 28.7% of unnecessary MRI could be saved at the cost of missing 13.6% of csPCa. When omitting MRI for patients with PHI < 39.6 and PSAD < 0.12 ng/mL2, unnecessary MRI could be reduced by 20.1% with the risk of missing 6.2% of csPCa. With addition of systematic PB, 21.0% of patients with negative MRI-targeted PB were diagnosed as csPCa. CONCLUSIONS: For patients in PSA gray zone, PHI of 39.6 might be an indicator for MRI and further MRI-targeted PB in additional to PSAD of 0.12 ng/mL2, reducing 20.1% of unnecessary MRI with the minimal risk of missing 6.2% of csPCa. To maximize csPCa detection, combining both MRI-targeted and systematic PB should be also considered.

Added Value of Prostate-specific Antigen Density in Selecting Prostate Biopsy Candidates Among Men with Elevated Prostate-specific Antigen and PI-RADS ≥3 Lesions on Multiparametric Magnetic Resonance Imaging of the Prostate: A Systematic Assessment by PI-RADS Score.

BACKGROUND: A significant proportion of patients with positive multiparametric magnetic resonance imaging (mpMRI; Prostate Imaging-Reporting and Data System [PI-RADS] scores of 3-5) have negative biopsy results. OBJECTIVE: To systematically assess all prostate-specific antigen density (PSAD) values and identify an appropriate cutoff for identification of patients with positive mpMRI who could potentially avoid biopsy on the basis of their PI-RADS score. DESIGN, SETTING, AND PARTICIPANTS: The study included a cohort of 1341 patients with positive mpMRI who underwent combined targeted and systematic biopsies. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Multivariable logistic regression analysis (MVA) was used to assess the association between PSAD and the risk of clinically significant prostate cancer (csPCa, grade group ≥2) after adjusting for confounders. We used locally weighted scatterplot smoothing to explore csPCa risk according to PSAD and PI-RADS scores. PSAD utility was observed only for patients with PI-RADS 3 lesions, so we plotted the effect of each PSAD value as a cutoff for this subgroup in terms of biopsies saved, csPCa cases missed, and clinically insignificant PCa (ciPCa, grade group 1) cases not detected. RESULTS AND LIMITATIONS: Overall, 667 (50%) csPCa cases were identified. On MVA, PSAD independently predicted csPCa (odds ratio 1.57; p < 0.001). For PI-RADS ≥4 lesions, the csPCa risk was ≥40% regardless of PSAD. Conversely, among patients with PI-RADS 3 lesions, csPCa risk ranged from 0% to 60% according to PSAD values, and a PSAD cutoff of 0.10 ng/ml/cm3 corresponded to a threshold probability of 10% for csPCa. Using this PSAD cutoff for patients with PI-RADS 3 lesions would have saved 32% of biopsies, missed 7% of csPCa cases, and avoided detection of 34% of ciPCa cases. Limitations include selection bias and the high experience of the radiologists and urologists involved. CONCLUSIONS: Patients with PI-RADS ≥4 lesions should undergo prostate biopsy regardless of their PSAD, while PSAD should be used to stratify patients with PI-RADS 3 lesions. Using a threshold probability of 10% for csPCa, our data suggest that the appropriate strategy is to avoid biopsy in patients with PI-RADS 3 lesions and PSAD <0.10 ng/ml/cm3. Our results also provide information to help in tailoring an appropriate strategy for every patient with positive mpMRI findings. PATIENT SUMMARY: We investigated whether a cutoff value for PSAD (prostate-specific antigen density) could identify patients with suspicious prostate lesions on MRI (magnetic resonance imaging) who could avoid biopsy according to the PI-RADS score for their scan. We found that patients with PI-RADS ≥4 should undergo prostate biopsy regardless of their PSAD. A PSAD cutoff of 0.10 should be used to stratify patients with PI-RADS 3.

Evaluating the Utility of Prostate-Specific Antigen Density in Risk Stratification of PI-RADS 3 Peripheral Zone Lesions on Non-Contrast-Enhanced Prostate MRI: An Exploratory Single-Institution Study.

Objective This study aimed to explore the potential of prostate-specific antigen density (PSAD) as a supplementary tool for defining high-risk Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions in the peripheral zone on non-contrast-enhanced MRI. This additional stratification tool could supplement the decision-making process for biopsy, potentially helping in identifying higher-risk patients more accurately, minimizing unnecessary procedures in lower-risk patients, and limiting the need for dynamic contrast-enhanced (DCE) scans. Materials and methods Between January 2019 and April 2023, 30 patients with PI-RADS 3 lesions underwent MRI-ultrasound fusion biopsies at our institution. Age and PSAD values were investigated using logistic regression and chi-square automatic interaction detection (CHAID) analysis to discern their predictive value for malignancy. Results The mean patient age was 64.7 years, and the mean PSAD was 0.13 ng/mL2. Logistic regression demonstrated PSAD to be a significant predictor of cancer (p=0.012), but not age (p=0.855). CHAID analysis further identified a PSAD cut-off value of 0.12, below which the cancer detection rate was 23.1% and above which the rate increased to 76.5%. Conclusions This exploratory study suggests that PSAD might be utilized to enhance the stratification of high-risk PI-RADS 3 lesions in the peripheral zone on non-contrast-enhanced MRI, aiding in decision-making for biopsy. While biopsy remains the gold standard for definitive diagnosis, a high PSAD value may suggest a greater need for biopsy in this specific group. Although further validation in larger cohorts is required, our findings contribute to the ongoing discourse on optimizing PI-RADS 3 lesion management. Limitations include a small sample size, the retrospective nature of the study, and the single-center setting, which may impact the generalizability of our results.

Comparison of Prostate-Specific Antigen and Its Density and Prostate Health Index and Its Density for Detection of Prostate Cancer.

As the incidence of prostate cancer (PCa) has increased, screening based on prostate-specific antigen (PSA) has become controversial due to the low specificity of PSA. Therefore, we investigated the diagnostic performance of prostate health index (PHI) density (PHID) for the detection of PCa and clinically significant PCa (csPCa) compared to PSA, PSA density (PSAD), and PHI as a triaging test. We retrospectively reviewed 306 men who underwent prostate biopsy for PSA levels of 2.5 to 10 ng/mL between January 2020 and April 2023. Of all cohorts, 86 (28.1%) and 48 (15.7%) men were diagnosed with PCa and csPCa, respectively. In ROC analysis, the highest AUC was identified for PHID (0.812), followed by PHI (0.791), PSAD (0.650), and PSA (0.571) for PCa. A similar trend was observed for csPCa: PHID (AUC 0.826), PHI (AUC 0.796), PSAD (AUC 0.671), and PSA (0.552). When the biopsy was restricted to men with a PHID ≥ 0.56, 26.5% of unnecessary biopsies could be avoided; however, 9.3% of PCa cases and one csPCa case (2.1%) remained undiagnosed. At approximately 90% sensitivity for csPCa, at the given cut-off values of PHI ≥ 36.4, and PHID ≥ 0.91, 48.7% and 49.3% of unnecessary biopsies could be avoided. In conclusion, PHID had a small advantage over PHI, about 3.6%, for the reduction in unnecessary biopsies for PCa. The PHID and PHI showed almost the same diagnostic performance for csPCa detection. PHID can be used as a triaging test in a clinical setting to pre-select the risk of PCa and csPCa.