Prostate-Specific Membrane Antigen Expression in Patients with Primary Prostate Cancer: Diagnostic and Prognostic Value in Positron Emission Tomography-Prostate-Specific Membrane Antigen.

Prostate cancer represents a significant public health challenge, with its management requiring precise diagnostic and prognostic tools. Prostate-specific membrane antigen (PSMA), a cell surface enzyme overexpressed in prostate cancer cells, has emerged as a pivotal biomarker. PSMA's ability to increase the sensitivity of PET imaging has revolutionized its application in the clinical management of prostate cancer. The advancements in PET-PSMA imaging technologies and methodologies, including the development of PSMA-targeted radiotracers and optimized imaging protocols, led to diagnostic accuracy and clinical utility across different stages of prostate cancer. This highlights its superiority in staging and its comparative effectiveness against conventional imaging modalities. This paper analyzes the impact of PET-PSMA on prostate cancer management, discussing the existing challenges and suggesting future research directions. The integration of recent studies and reviews underscores the evolving understanding of PET-PSMA imaging, marking its significant but still expanding role in clinical practice. This comprehensive review serves as a crucial resource for clinicians and researchers involved in the multifaceted domains of prostate cancer diagnosis, treatment, and management.

The value of synthetic magnetic resonance imaging in the diagnosis and assessment of prostate cancer aggressiveness.

Background: Synthetic magnetic resonance imaging (SyMRI) is a fast, standardized, and robust novel quantitative technique that has the potential to circumvent the subjectivity of interpretation in prostate multiparametric magnetic resonance imaging (mpMRI) and the limitations of existing MRI quantification techniques. Our study aimed to evaluate the potential utility of SyMRI in the diagnosis and aggressiveness assessment of prostate cancer (PCA). Methods: We retrospectively analyzed 309 patients with suspected PCA who had undergone mpMRI and SyMRI, and pathologic results were obtained by biopsy or PCA radical prostatectomy (RP). Pathological types were classified as PCA, benign prostatic hyperplasia (BPH), or peripheral zone (PZ) inflammation. According to the Gleason Score (GS), PCA was divided into groups of intermediate-to-high risk (GS ≥4+3) and low-risk (GS ≤3+4). Patients with biopsy-confirmed low-risk PCA were further divided into upgraded and nonupgraded groups based on the GS changes of the RP results. The values of the apparent diffusion coefficient (ADC), T1, T2 and proton density (PD) of these lesions were measured on ADC and SyMRI parameter maps by two physicians; these values were compared between PCA and BPH or inflammation, between the intermediate-to-high-risk and low-risk PCA groups, and between the upgraded and nonupgraded PCA groups. The risk factors affecting GS grades were identified via univariate analysis. The effects of confounding factors were excluded through multivariate logistic regression analysis, and independent predictive factors were calculated. Subsequently, the ADC+Sy(T2+PD) combined models for predicting PCA risk grade or GS upgrade were constructed through data processing analysis. The diagnostic performance of each parameter and the ADC+Sy(T2+PD) model was analyzed. The calibration curve was calculated by the bootstrapping internal validation method (200 bootstrap resamples). Results: The T1, T2, and PD values of PCA were significantly lower than those of BPH or inflammation (P≤0.001) in both the PZ or transitional zone. Among the 178 patients with PCA, intermediate-to-high-risk PCA group had significantly higher T1, T2, and PD values but lower ADC values compared with the low-risk group (P<0.05), and the diagnostic efficacy of each single parameter was similar (P>0.05). The ADC+Sy(T2+PD) model showed the best performance, with an area under the curve (AUC) 0.110 [AUC =0.818; 95% confidence interval (CI): 0.754-0.872] higher than that of ADC alone (AUC =0.708; 95% CI: 0.635-0.774) (P=0.003). Among the 68 patients initially classified as PCA in the low-risk group by biopsy, PCA in the postoperative upgraded GS group had significantly higher T1, T2, and PD values but lower ADC values than did those in the nonupgraded group (P<0.01). In addition, the ADC+Sy(T2+PD) model better predicted the upgrade of GS, with a significant increase in AUC of 0.204 (AUC =0.947; 95% CI: 0.864-0.987) compared with ADC alone (AUC =0.743; 95% CI: 0.622-0.841) (P<0.001). Conclusions: Quantitative parameters (T1, T2, and PD) derived from SyMRI can help differentiate PCA from non-PCA. Combining SyMRI parameters with ADC significantly improved the ability to differentiate between intermediate-to-high risk PCA from low-risk PCA and could predict the upgrade of low-risk PCA as confirmed by biopsy.

Patients ask and pathologists answer: ten questions around prostate cancer grading.

Pathologists have closely collaborated with clinicians, mainly urologists, to update the Gleason grading system to reflect the current practice and approach in prostate cancer diagnosis, prognosis, and treatment. This has led to the development of what is called patient advocacy and patient information. Ten common questions asked by patients to pathologists concerning PCa grading and the answers given by the latter are reported.

Addressing intra- and inter-institution variability of a radiomic framework based on Apparent Diffusion Coefficient in prostate cancer.

BACKGROUND: Prostate cancer (PCa) is a highly heterogeneous disease, making tailored treatment approaches challenging. Magnetic resonance imaging (MRI), notably diffusion-weighted imaging (DWI) and the derived Apparent Diffusion Coefficient (ADC) maps, plays a crucial role in PCa characterization. In this context, radiomics is a very promising approach able to disclose insights from MRI data. However, the sensitivity of radiomic features to MRI settings, encompassing DWI protocols and multicenter variations, requires the development of robust and generalizable models. PURPOSE: To develop a comprehensive radiomics framework for noninvasive PCa characterization using ADC maps, focusing on identifying reliable imaging biomarkers against intra- and inter-institution variations. MATERIALS AND METHODS: Two patient cohorts, including an internal cohort (118 PCa patients) used for both training (75%) and hold-out testing (25%), and an external cohort (50 PCa patients) for independent testing, were employed in the study. DWI images were acquired with three different DWI protocols on two different MRI scanners: two DWI protocols acquired on a 1.5-T scanner for the internal cohort, and one DWI protocol acquired on a 3-T scanner for the external cohort. One hundred and seven radiomics features (i.e., shape, first order, texture) were extracted from ADC maps of the whole prostate gland. To address variations in DWI protocols and multicenter variability, a dedicated pipeline, including two-way ANOVA, sequential-feature-selection (SFS), and ComBat features harmonization was implemented. Mann-Whitney U-tests (α = 0.05) were performed to find statistically significant features dividing patients with different tumor characteristics in terms of Gleason score (GS) and T-stage. Support-Vector-Machine models were then developed to predict GS and T-stage, and the performance was assessed through the area under the curve (AUC) of receiver-operating-characteristic curves. RESULTS: Downstream of ANOVA, two subsets of 38 and 41 features stable against DWI protocol were identified for GS and T-stage, respectively. Among these, SFS revealed the most predictive features, yielding an AUC of 0.75 (GS) and 0.70 (T-stage) in the hold-out test. Employing ComBat harmonization improved the external-test performance of the GS model, raising AUC from 0.72 to 0.78. CONCLUSION: By incorporating stable features with a harmonization procedure and validating the model on an external dataset, model robustness, and generalizability were assessed, highlighting the potential of ADC and radiomics for PCa characterization.

A comparative study of 18F-PSMA-1007 PET/CT and pelvic MRI in newly diagnosed prostate cancer.

PURPOSE: To evaluate the difference in the diagnostic efficacy of 18F-PSMA-1007 PET/CT and pelvic MRI in primary prostate cancer, as well as the correlation between the two methods and histopathological parameters and serum PSA levels. METHODS: A total of 41 patients with suspected prostate cancer who underwent 18F-PSMA-1007 PET/CT imaging in our department from 2018 to 2023 were retrospectively collected. All patients underwent 18F-PSMA-1007 PET/CT and MRI scans. The sensitivity, PPV and diagnostic accuracy of MRI and 18F-PSMA-1007 PET/CT in the diagnosis of prostate cancer were calculated after comparing the results of MRI and 18F-PSMA-1007 PET/CT with biopsy. The Spearman test was used to calculate the correlation between 18F-PSMA-1007 PET/CT, MRI parameters, histopathological indicators, and serum PSA levels. RESULTS: Compared with histopathological results, the sensitivity, PPV and diagnostic accuracy of 18F-PSMA-1007 PET/CT in the diagnosis of prostate cancer were 95.1%, 100.0% and 95.1%, respectively. The sensitivity, PPV and diagnostic accuracy of MRI in the diagnosis of prostate cancer were 82.9%, 100.0% and 82.9%, respectively. There was a mild to moderately positive correlation between Gleason (Gs) score, Ki-67 index, serum PSA level and 18F-PSMA-1007 PET/CT parameters (p < 0.05). There was a moderately negative correlation between the expression of AMACR (P504S) and 18F-PSMA-1007 PET/CT parameters (p < 0.05). The serum PSA level and the Gs score were moderately positively correlated with the MRI parameters (p < 0.05). There was no correlation between histopathological parameters and MRI parameters (p > 0.05). CONCLUSION: Compared with MRI, 18F-PSMA-1007 PET/CT has higher sensitivity and diagnostic accuracy in the detection of malignant prostate tumors. In addition, the Ki-67 index and AMACR (P504S) expression were only correlated with 18F-PSMA-1007 PET/CT parameters. Gs score and serum PSA level were correlated with 18F-PSMA-1007 PET/CT and MRI parameters. 18F-PSMA-1007 PET/CT examination can provide certain reference values for the clinical diagnosis, evaluation, and treatment of malignant prostate tumors.

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

BACKGROUND: In this work, we compare input level, feature level and decision level data fusion techniques for automatic detection of clinically significant prostate lesions (csPCa). METHODS: Multiple 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. RESULTS: The 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. CONCLUSION: The 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 REGISTRATION: The trial was registered retrospectively at the German Register for Clinical Studies (DRKS) under proposal number Nr. 476/14 & 476/19.

Impact of a pharmacist-led intervention on prostate cancer illness perception.

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: Illness perception (IP) significantly determines illness outcomes. This study determined the impact of a pharmacist educational intervention on IP in patients with prostate cancer (PCa) and predictors of IP. METHODS: Using a brief IP questionnaire, an interventional study of patients with PCa was conducted in all cancer reference hospitals in one Nigerian state. After a pre-post assessment of patients' IP, descriptive and inferential statistical analyses were performed. The impact of pharmacists' intervention on IP was determined by paired-sample statistics and correlation analysis at the 95% CI. Relationships and predictors of IP were determined using Kendall's tau-b (τb), likelihood ratio, and F tests of equality of means, respectively. P < 0.05 was considered statistically significant. RESULTS: Pharmacists' educational intervention significantly improved IP (SEM, 0.13; r = 0.875; P < 0.0001) among the 200 participants. The analyses also showed a significant paired sample difference (2.662; SEM, 0.06; 95%CI, 2.536-2.788; t = 41.69; df = 199; P < 0.0001). All subscales of patients' IP significantly improved except for illness consequences (P = 0.173) and identity (mean [SD], 4.40 [3.730] in both pre- and postintervention assessments). Pre- and postintervention assessments showed a significant negative relationship of IP with age (τb = -110 [P = 0.040] and τb = -14 [P = 0.021], respectively), Gleason score (τb = -0.125 [P = 0.021] and τb = -0.124 [P=0.012], respectively), and age at diagnosis (τb = -0.103 [P = 0.036] post intervention). IP was significantly dependent on the drug therapy (df = 8; mean square [M] = 6.292; F = 2.825; P = 0.006), alcohol intake (df = 1; M = 9.608; F = 4.082; P = 0.045) and Gleason score (df = 9; M = 6.706; F = 3.068; P = 0.002). CONCLUSION: Patients' IP significantly improved after pharmacists' educational intervention. Predictors of IP were drug therapies, alcohol use and Gleason score. Findings can be extrapolated in clinical settings to improve treatment outcomes.

Predictive Factors for Early Biochemical Recurrence Following Robot-assisted Radical Prostatectomy.

BACKGROUND/AIM: The primary objective of this study was to identify predictors for biochemical recurrence (BCR) within 2 years following robot-assisted radical prostatectomy (RARP). Identifying predictors will enable insights that enhance personalized patient management and facilitate the ongoing refinement of postoperative therapy strategies. PATIENTS AND METHODS: This retrospective study included patients undergoing RARP from September 2014 to January 2021. Exclusion criteria were preoperative endocrine therapy, BCR beyond 2 years post-surgery, and incomplete postoperative data. Multivariate analyses were conducted to evaluate predictors of BCR, focusing on preoperative prostate-specific antigen (PSA) level, pathological tumor (pT) stage, Gleason score (GS), extraprostatic extension (EPE), and surgical margin status. RESULTS: Among 374 patients, 40 experienced BCR within 2 years. Significant predictors of early BCR included initial PSA level ≥10 ng/ml, pT3 or greater, GS ≥8, EPE, and positive surgical margins (RM1). Multivariate analysis identified pT3 or higher, GS ≥8, and RM1 as independent risk factors for early BCR. CONCLUSION: Early BCR after RARP is significantly associated with advanced pathological stage, high GS, and positive surgical margins. These findings emphasize the need for tailored postoperative management strategies and highlight the importance of precision in surgical technique to improve patient outcomes.

The value of apparent diffusion coefficient values in predicting Gleason grading of low to intermediate-risk prostate cancer.

OBJECTIVES: To investigate the diagnostic performance of the apparent diffusion coefficient (ADC) for low to intermediate-risk prostate cancer (PCa), as well as its correlation with the prognostic Gleason score (GS). MATERIALS AND METHODS: Retrospective analysis of MRI images and relevant clinical data from patients with prostate disease. The differences in ADC between different GS groups were compared, and the efficacy of ADC in PCa diagnosis were analyzed. Furthermore, the diagnostic performance of the mean ADC (ADCmean) and minimum ADC (ADCmin) values was compared. RESULTS: There were 1414 patients with 1631 lesions. In terms of GS, both ADCmin and ADCmean values of the GS 4 + 3 group were significantly lower than those of the GS 3 + 4 group, GS 3 + 3 group, and the benign group, with all differences being statistically significant (p < 0.01). The AUC values for diagnosing PCa based on ADCmin and ADCmean were 0.914 and 0.944, respectively. The corresponding diagnostic thresholds were 0.703 × 10-3 mm2/s for ADCmin and 0.927 × 10-3 mm2/s for ADCmean. The magnitudes of ADCmin and ADCmean values exhibited a negative correlation with GS values (ρ = -0.750, p < 0.001; ρ = -0.752, p < 0.001). CONCLUSIONS: ADC values demonstrate an inverse relationship with the invasiveness of PCa, indicating that higher invasiveness is associated with lower ADC values. Additionally, ADC values exhibit high diagnostic potential, sensitivity, and specificity for distinguishing between GS 3 + 4 and GS 4 + 3 lesions. Moreover, the diagnostic value of ADCmean is even more significant, highlighting its crucial role in the diagnosis of low to intermediate-risk PCa. CRITICAL RELEVANCE STATEMENT: ADC values are a valuable tool for distinguishing different levels of aggressiveness in PCa. They help in the preoperative assessment of the biological characteristics of PCa, allowing clinicians to develop personalized treatment strategies, effectively mitigating the risk of unnecessary interventions. KEY POINTS: The preoperative GS is crucial for planning the clinical treatment of PCa. The invasiveness of PCa is inversely correlated with ADC values. ADC values play a crucial role in the accurate preoperative evaluation of low to intermediate-risk PCa, thus aiding clinicians in developing tailored treatment plans.

The role of PSMA PET/CT in predicting downgrading in patients with Gleason score 4+4 prostate cancer in prostate biopsy.

BACKGROUND: To investigate the predictable parameters associated with downgrading in patients with a Gleason score (GS) 8 (4+4) in prostate biopsy after radical prostatectomy. METHODS: We retrospectively analyzed 62 patients with a GS of 4+4 on prostate biopsy who underwent robotic radical prostatectomy between 2017 and 2022. RESULTS: 38 of 62 (61.2%) were downgraded. In multivariable logistic regression model, Ga-68 prostate-specific membrane antigen (PSMA) positron-emission tomography (PET)/computed tomography (CT) SUV max was independent predictor of downgrading (OR 0.904; p = 0.011) and a Logistic Regression model was constructed using the following formula: Y = 1.465-0.95 (PSMA PET/CT SUV max). The model using this variable correctly predicted the downgrading in 72.6% of patients. The AUC for PSMA PET/CT SUV max was 0.709 the cut off being 8.8. A subgroup analysis was performed in 37 patients who had no other European Association of Urology (EAU) high risk features. 25 out of 37 (67.5%) were downgraded, and 21 of these 25 had organ confined disease. Low PSMA SUV max (<8.1) and percentage of GS 4+4 biopsy cores to cancer bearing cores (45.0%) were independently associated with downgrading to GS 7. CONCLUSION: PSMA PET/CT can be used to predict downgrading in patients with GS 4+4 PCa. Patients with GS 4+4 disease, but no other EAU high risk features, low percentage of GS 4+4 biopsy cores to cancer bearing cores, and a low PSMA PET/CT SUV max are associated with a high likelihood of the cancer reclassification to intermediate risk group.

Low-Density Lipoprotein Cholesterol and Prostate Cancer: A Retrospective Study.

BACKGROUND: This work aimed to investigate the potential role of abnormal lipid metabolism in the development of prostate cancer (PCa). METHODS: A retrospective study design was used. The clinical data of 520 patients who underwent rectal prostate biopsy in our hospital from January 2020 to June 2023 were analysed. The patients were enrolled and divided into the anterior PCa group including 112 patients and benign prostatic hyperplasia (BPH) group including 408 patients. Univariate and multivariate logistic regression analyses were performed for the two patient groups, and further comparisons were made according to the Gleason score and TNM staging. RESULTS: Low-density lipoprotein cholesterol (LDL-C) level may be an independent risk factor for PCa, and it was significantly associated with the risk of PCa (odds ratio (OR) = 1.363, p = 0.030). Patients with PCa were further divided into the low risk group and the high risk group according to the Gleason score. Univariate analysis (p = 0.047) and logistic regression analysis (OR = 2.249, p = 0.036) revealed that LDL-C was a significant factor influencing the Gleason score. Patients with PCa were categorised into four groups based on TNM staging. One-way analysis of variance (ANOVA) analysis (p = 0.015) and ordinal logistic regression analysis (OR = 2.414, p = 0.007) demonstrated that LDL-C was a significant factor influencing TNM staging. CONCLUSIONS: This study revealed the important role of LDL-C in the development of PCa, highlighting its influence as an independent risk factor. Thus, LDL-C may promote the proliferation and invasion of PCa cells.

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

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

Ribosome-binding protein-1 (RRBP1) expression in prostate carcinomas and its relationship with clinicopathological prognostic factors.

INTRODUCTION: Studies in recent years have shown that ribosome-binding protein-1 (RRBP1) is expressed at high rates in many cancers and that it may be a potential prognostic biomarker. The objective of the present study is to determine the RRBP1 expression level in prostatic carcinoma and neighboring non-neoplastic prostate tissue, the relationship between its expression level with prognostic factors, and the role of RRBP1 in the development of prostate cancer. MATERIALS AND METHODS: The study included 45 patients who were diagnosed with prostatic carcinoma and underwent radical prostatectomy in our center between the years 2010 and 2021. Pathology reports were reviewed. Mann-Whitney U test was used for the comparison of RRBP1 and GADPH values of the cases (control and tumoral tissue) between the primary tumor stage (pT) and Gleason score (GS) groups. Hierarchical regression analysis was used to explain the effective variables in explaining the RRBP1 value of the research cases. RESULTS: According to the Mann-Whitney U test, mean and median RRBP1-T values of the cases with GS ≥ 8 were detected to be statistically significantly higher than the mean and median RRBP1-T values of the cases with GS < 8. CONCLUSION: We found out that RRBP1 was expressed at higher rates in patients with high GS and advanced-stage patients. This result indicated that RRBP1 expression may be important in predicting the prognosis of prostate carcinoma.

Prediction of prostate cancer aggressiveness using magnetic resonance imaging radiomics: a dual-center study.

PURPOSE: The Gleason score (GS) and positive needles are crucial aggressive indicators of prostate cancer (PCa). This study aimed to investigate the usefulness of magnetic resonance imaging (MRI) radiomics models in predicting GS and positive needles of systematic biopsy in PCa. MATERIAL AND METHODS: A total of 218 patients with pathologically proven PCa were retrospectively recruited from 2 centers. Small-field-of-view high-resolution T2-weighted imaging and post-contrast delayed sequences were selected to extract radiomics features. Then, analysis of variance and recursive feature elimination were applied to remove redundant features. Radiomics models for predicting GS and positive needles were constructed based on MRI and various classifiers, including support vector machine, linear discriminant analysis, logistic regression (LR), and LR using the least absolute shrinkage and selection operator. The models were evaluated with the area under the curve (AUC) of the receiver-operating characteristic. RESULTS: The 11 features were chosen as the primary feature subset for the GS prediction, whereas the 5 features were chosen for positive needle prediction. LR was chosen as classifier to construct the radiomics models. For GS prediction, the AUC of the radiomics models was 0.811, 0.814, and 0.717 in the training, internal validation, and external validation sets, respectively. For positive needle prediction, the AUC was 0.806, 0.811, and 0.791 in the training, internal validation, and external validation sets, respectively. CONCLUSIONS: MRI radiomics models are suitable for predicting GS and positive needles of systematic biopsy in PCa. The models can be used to identify aggressive PCa using a noninvasive, repeatable, and accurate diagnostic method.

Long term evaluation of optimized Gleason grading in a large cohort of men with prostate cancer in Canada.

OBJECTIVES: To evaluate the International Society of Urological Pathology (ISUP) 5-tier grade grouping (GG) system of prostate cancers as well as previously proposed optimizations. PATIENTS AND METHODS: The PROCURE biobank is a prospective cohort study of patients with localized prostate cancer who underwent radical prostatectomy in Quebec province between 2005 and 2013. Surgical specimens were graded by experienced genitourinary pathologists using 2019 ISUP criteria. Follow-up was conducted until November 2021. The current 5-tier and a proposed 6-tier GG system were evaluated, the latter having two changes: 1) Gleason 3 + 4 and 4 + 3 tumors with minor/tertiary Gleason 5 patterns were upgraded to GG 3 and 4, respectively; and 2) patients in GG5 were separated based on primary Gleason pattern (4 or 5). Cox proportional hazards models and Harrell's concordance (C) indices were used for statistical analyses. RESULTS: 2003 patients were included (median follow-up: 8.7 years). The current 5-tier GG system predicted time to recurrence (hazard ratio [HR] 2.12, 95% confidence interval [95%CI] 1.99-2.25, C 0.717), androgen-deprivation therapy (HR 2.58, 95%CI 2.38-2.80, C 0.790), metastasis (HR 2.48, 95%CI 2.17-2.83, C 0.806), castration-resistant prostate cancer (HR 2.67, 95%CI 2.28-3.13, C 0.829), and cancer-specific mortality (HR 2.80, 95%CI 2.27-3.44, C 0.835). Goodness-of-fit further improved with the proposed 6-tier GG system, with Harrell's C of 0.733, 0.807, 0.827, 0.853, and 0.853, respectively. CONCLUSIONS: The 5-tier GG system predicted short- and long-term outcomes for patients with localized prostate cancer, and the proposed 6-tier GG system further improved its accuracy.

Analysis of the Gene Networks and Pathways Correlated with Tissue Differentiation in Prostate Cancer.

Prostate cancer (PCa) is the most prevalent non-cutaneous cancer in men. Early PCa detection has been made possible by the adoption of screening methods based on the serum prostate-specific antigen and Gleason score (GS). The aim of this study was to correlate gene expression with the differentiation level of prostate adenocarcinomas, as indicated by GS. We used data from The Cancer Genome Atlas (TCGA) and included 497 prostate cancer patients, 52 of which also had normal tissue sample sequencing data. Gene ontology analysis revealed that higher GSs were associated with greater responses to DNA damage, telomere lengthening, and cell division. Positive correlation was found with transcription factor activator of the adenovirus gene E2 (E2F) and avian myelocytomatosis viral homolog (MYC) targets, G2M checkpoints, DNA repair, and mitotic spindles. Immune cell deconvolution revealed high M0 macrophage counts and an increase in M2 macrophages dependent on the GS. The molecular pathways most correlated with GSs were cell cycle, RNA transport, and calcium signaling (depleted). A combinatorial approach identified a set of eight genes able to differentiate by k-Nearest Neighbors (kNN) between normal tissues, low-Gleason tissues, and high-Gleason tissues with high accuracy. In conclusion, our study could be a step forward to better understanding the link between gene expression and PCa progression and aggressiveness.

The influence of Gleason score ≤ 6 histology on the outcome of high-risk localized prostate cancer after modern radiotherapy.

We aimed to retrospectively review outcomes in patients with high-risk prostate cancer and a Gleason score ≤ 6 following modern radiotherapy. We analyzed the outcomes of 1374 patients who had undergone modern radiotherapy, comprising a high-risk low grade [HRLG] group (Gleason score ≤ 6; n = 94) and a high-risk high grade [HRHG] group (Gleason score ≥ 7, n = 1125). We included 955 patients who received brachytherapy with or without external beam radio-therapy (EBRT) and 264 who received modern EBRT (intensity-modulated radiotherapy [IMRT] or stereotactic body radiotherapy [SBRT]). At a median follow-up of 60 (2-177) months, actuarial 5-year biochemical failure-free survival rates were 97.8 and 91.8% (p = 0.017), respectively. The frequency of clinical failure in the HRLG group was less than that in the HRHG group (0% vs 5.4%, p = 0.012). The HRLG group had a better 5-year distant metastasis-free survival than the HRHG group (100% vs 96.0%, p = 0.035). As the HRLG group exhibited no clinical failure and better outcomes than the HRHG group, the HRLG group might potentially be classified as a lower-risk group.

Interaction of patient age and high-grade prostate cancer on targeted biopsies of MRI suspicious lesions.

OBJECTIVES: To evaluate the interaction of patient age and Prostate Imaging-Reporting and Data System (PI-RADS) score in determining the grade of prostate cancer (PCa) identified on magnetic resonance imaging (MRI)-targeted biopsy in older men. PATIENTS AND METHODS: From a prospectively accrued Institutional Review Board-approved comparative study of MRI-targeted and systematic biopsy between June 2012 and December 2022, men with at least one PI-RADS ≥3 lesion on pre-biopsy MRI and no prior history of PCa were selected. Ordinal and binomial logistic regression analyses were performed. RESULTS: A total of 2677 men met study criteria. The highest PI-RADS score was 3 in 1220 men (46%), 4 in 950 men (36%), and 5 in 507 men (19%). The median (interquartile range [IQR]) patient age was 66.7 (60.8-71.8) years, median (IQR) prostate-specific antigen (PSA) level was 6.1 (4.6-9.0) ng/mL, median (IQR) prostate volume was 48 (34-68) mL, and median (IQR) PSA density was 0.13 (0.08-0.20) ng/mL/mL. Clinically significant (cs)PCa and high-risk PCa were identified on targeted biopsy in 1264 (47%) and 321 (12%) men, respectively. Prevalence of csPCa and high-risk PCa were significantly higher in the older age groups. On multivariable analyses, patient age was significantly associated with csPCa but not high-risk PCa; PI-RADS score and the interaction of age and PI-RADS score were significantly associated with high-risk PCa but not csPCa. CONCLUSION: In our cohort, the substantial rate of high-risk PCa on MRI-ultrasound fusion targeted biopsies in older men, and its significant association with MRI findings, supports the value of pre-biopsy MRI to localise disease that could cause cancer mortality even in older men.

Comparative Study of Eclipse and RayStation Multi-Criteria Optimization-Based Prostate Radiotherapy Treatment Planning Quality.

Multi-criteria optimization (MCO) function has been available on commercial radiotherapy (RT) treatment planning systems to improve plan quality; however, no study has compared Eclipse and RayStation MCO functions for prostate RT planning. The purpose of this study was to compare prostate RT MCO plan qualities in terms of discrepancies between Pareto optimal and final deliverable plans, and dosimetric impact of final deliverable plans. In total, 25 computed tomography datasets of prostate cancer patients were used for Eclipse (version 16.1) and RayStation (version 12A) MCO-based plannings with doses received by 98% of planning target volume having 76 Gy prescription (PTV76D98%) and 50% of rectum (rectum D50%) selected as trade-off criteria. Pareto optimal and final deliverable plan discrepancies were determined based on PTV76D98% and rectum D50% percentage differences. Their final deliverable plans were compared in terms of doses received by PTV76 and other structures including rectum, and PTV76 homogeneity index (HI) and conformity index (CI), using a t-test. Both systems showed discrepancies between Pareto optimal and final deliverable plans (Eclipse: -0.89% (PTV76D98%) and -2.49% (Rectum D50%); RayStation: 3.56% (PTV76D98%) and -1.96% (Rectum D50%)). Statistically significantly different average values of PTV76D98%,HI and CI, and mean dose received by rectum (Eclipse: 76.07 Gy, 0.06, 1.05 and 39.36 Gy; RayStation: 70.43 Gy, 0.11, 0.87 and 51.65 Gy) are noted, respectively (p < 0.001). Eclipse MCO-based prostate RT plan quality appears better than that of RayStation.

High-volume prostate biopsy core involvement is not associated with an increased risk of cancer recurrence following 5-fraction stereotactic body radiation therapy monotherapy.

PURPOSE: Percentage of positive cores involved on a systemic prostate biopsy has been established as a risk factor for adverse oncologic outcomes and is a National Comprehensive Cancer Network (NCCN) independent parameter for unfavorable intermediate-risk disease. Most data from a radiation standpoint was published in an era of conventional fractionation. We explore whether the higher biological dose delivered with SBRT can mitigate this risk factor. METHODS: A large single institutional database was interrogated to identify all patients diagnosed with localized prostate cancer (PCa) treated with 5-fraction SBRT without ADT. Pathology results were reviewed to determine detailed core involvement as well as Gleason score (GS). High-volume biopsy core involvement was defined as ≥ 50%. Weighted Gleason core involvement was reviewed, giving higher weight to higher-grade cancer. The PSA kinetics and oncologic outcomes were analyzed for association with core involvement. RESULTS: From 2009 to 2018, 1590 patients were identified who underwent SBRT for localized PCa. High-volume core involvement was a relatively rare event observed in 19% of our cohort, which was observed more in patients with small prostates (p < 0.0001) and/or intermediate-risk disease (p = 0.005). Higher PSA nadir was observed in those patients with low-volume core involvement within the intermediate-risk cohort (p = 0.004), which was confirmed when core involvement was analyzed as a continuous variable weighted by Gleason score (p = 0.049). High-volume core involvement was not associated with biochemical progression (p = 0.234). CONCLUSIONS: With a median follow-up of over 4 years, biochemical progression was not associated with pretreatment high-volume core involvement for patients treated with 5-fraction SBRT alone. In the era of prostate SBRT and MRI-directed prostate biopsies, the use of high-volume core involvement as an independent predictor of unfavorable intermediate risk disease should be revisited.