International Society Of Urological Pathology Research Articles

The additional value of 68Ga-PSMA PET/CT SUVmax in predicting ISUP GG ≥ 2 and ISUP GG ≥ 3 prostate cancer in biopsy.

Prebiopsy magnetic resonance imaging (MRI) increases the detection rate of clinically significant prostate cancer (csPCa). Prostate-specific membrane antigen-positron emission tomography/computed tomography (PSMA PET/CT) maximum standardized uptake value(SUVmax) of the prostate may offer additional value in predicting the likelihood of csPCa in biopsy. A single-center cohort study involving patients with biopsy-proven PCa who underwent both MRI and PSMA PET/CT between 2020 and 2021. Logistic regression models were developed for International Society of Urological Pathology (ISUP) Grade Group (GG) ≥ 2 and GG ≥ 3 using noninvasive prebiopsy parameters: age, (log-)prostate-specific antigen (PSA) density, PI-RADS 5 lesion presence, extraprostatic extension (EPE) on MRI, and SUVmax of the prostate. Models with and without SUVmax were compared using Likelihood ratio tests and area under the curve (AUC). DeLong's test was used to compare the AUCs. The study included 386 patients, with 262 (68%) having ISUP GG ≥ 2 and 180 (47%) having ISUP GG ≥ 3. Including SUVmax significantly improved both models' goodness of fit (p < 0.001). The GG ≥ 2 model had a higher AUC with SUVmax 89.16% (95% confidence interval [CI]: 86.06%-92.26%) than without 87.34% (95% CI: 83.93%-90.76%) (p = 0.026). Similarly, the GG ≥ 3 model had a higher AUC with SUVmax 82.51% (95% CI: 78.41%-86.6%) than without 79.33% (95% CI: 74.84%-83.83%) (p = 0.003). The SUVmax inclusion improved the GG ≥ 3 model's calibration at higher probabilities. SUVmax of the prostate on PSMA PET/CT potentially improves diagnostic accuracy in predicting the likelihood of csPCa in prostate biopsy.

Multiparametric MRI and 18F-PSMA-1007 PET/CT for the Detection of Clinically Significant Prostate Cancer.

Background Multiparametric MRI (mpMRI) is effective for detecting prostate cancer (PCa); however, there is a high rate of equivocal Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions and false-positive findings. Purpose To investigate whether fluorine 18 (18F) prostate-specific membrane antigen (PSMA) 1007 PET/CT after mpMRI can help detect localized clinically significant PCa (csPCa), particularly for equivocal PI-RADS 3 lesions. Materials and Methods This prospective study included participants with elevated prostate-specific antigen (PSA) levels referred for prostate mpMRI between September 2020 and February 2022. 18F-PSMA-1007 PET/CT was performed within 30 days of mpMRI and before biopsy. PI-RADS category and level of suspicion (LOS) were assessed. PI-RADS 3 or higher lesions at mpMRI and/or LOS 3 or higher lesions at 18F-PSMA-1007 PET/CT underwent targeted biopsies. PI-RADS 2 or lower and LOS 2 or lower lesions were considered nonsuspicious and were monitored during a 1-year follow-up by means of PSA testing. Diagnostic accuracy was assessed, with histologic examination serving as the reference standard. International Society of Urological Pathology (ISUP) grade 2 or higher was considered csPCa. Results Seventy-five participants (median age, 67 years [range, 52-77 years]) were assessed, with PI-RADS 1 or 2, PI-RADS 3, and PI-RADS 4 or 5 groups each including 25 participants. A total of 102 lesions were identified, of which 80 were PI-RADS 3 or higher and/or LOS 3 or higher and therefore underwent targeted biopsy. The per-participant sensitivity for the detection of csPCa was 95% and 91% for mpMRI and 18F-PSMA-1007 PET/CT, respectively, with respective specificities of 45% and 62%. 18F-PSMA-1007 PET/CT was used to correctly differentiate 17 of 26 PI-RADS 3 lesions (65%), with a negative and positive predictive value of 93% and 27%, respectively, for ruling out or detecting csPCa. One additional significant and one insignificant PCa lesion (PI-RADS 1 or 2) were found at 18F-PSMA-1007 PET/CT that otherwise would have remained undetected. Two participants had ISUP 2 tumors without PSMA uptake that were missed at PET/CT. Conclusion 18F-PSMA-1007 PET/CT showed good sensitivity and moderate specificity for the detection of csPCa and ruled this out in 93% of participants with PI-RADS 3 lesions. Clinical trial registration no. NCT04487847 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Turkbey in this issue.

Evaluation of a Cascaded Deep Learning-based Algorithm for Prostate Lesion Detection at Biparametric MRI.

Background Multiparametric MRI (mpMRI) improves prostate cancer (PCa) detection compared with systematic biopsy, but its interpretation is prone to interreader variation, which results in performance inconsistency. Artificial intelligence (AI) models can assist in mpMRI interpretation, but large training data sets and extensive model testing are required. Purpose To evaluate a biparametric MRI AI algorithm for intraprostatic lesion detection and segmentation and to compare its performance with radiologist readings and biopsy results. Materials and Methods This secondary analysis of a prospective registry included consecutive patients with suspected or known PCa who underwent mpMRI, US-guided systematic biopsy, or combined systematic and MRI/US fusion-guided biopsy between April 2019 and September 2022. All lesions were prospectively evaluated using Prostate Imaging Reporting and Data System version 2.1. The lesion- and participant-level performance of a previously developed cascaded deep learning algorithm was compared with histopathologic outcomes and radiologist readings using sensitivity, positive predictive value (PPV), and Dice similarity coefficient (DSC). Results A total of 658 male participants (median age, 67 years [IQR, 61-71 years]) with 1029 MRI-visible lesions were included. At histopathologic analysis, 45% (294 of 658) of participants had lesions of International Society of Urological Pathology (ISUP) grade group (GG) 2 or higher. The algorithm identified 96% (282 of 294; 95% CI: 94%, 98%) of all participants with clinically significant PCa, whereas the radiologist identified 98% (287 of 294; 95% CI: 96%, 99%; P = .23). The algorithm identified 84% (103 of 122), 96% (152 of 159), 96% (47 of 49), 95% (38 of 40), and 98% (45 of 46) of participants with ISUP GG 1, 2, 3, 4, and 5 lesions, respectively. In the lesion-level analysis using radiologist ground truth, the detection sensitivity was 55% (569 of 1029; 95% CI: 52%, 58%), and the PPV was 57% (535 of 934; 95% CI: 54%, 61%). The mean number of false-positive lesions per participant was 0.61 (range, 0-3). The lesion segmentation DSC was 0.29. Conclusion The AI algorithm detected cancer-suspicious lesions on biparametric MRI scans with a performance comparable to that of an experienced radiologist. Moreover, the algorithm reliably predicted clinically significant lesions at histopathologic examination. ClinicalTrials.gov Identifier: NCT03354416 © RSNA, 2024 Supplemental material is available for this article.

Long-term follow-up results of multiparametric prostate MRI and the prognostic value of PI-RADS: a single-center retrospective cohort study

We aim to examine the long-term outcomes of patients who underwent multiparametric prostate magnetic resonance imaging (mp-MRI) for suspected prostate cancer (PCa), specifically based on their initial Prostate Imaging Reporting and Data System (PI-RADS) categories and various clinical factors. Our secondary aim is to evaluate the prognostic value of the PI-RADS through the National Comprehensive Cancer Network (NCCN) risk group distribution. This research was conducted as a single-center retrospective cohort study in a tertiary care hospital. A total of 1,359 cases having at least one histopathological examination after the initial mp-MRI and/or adequate clinical/radiological follow-up data were included in the clinically significant PCa (cs-PCa) diagnosis-free survival analysis. Initial mp-MRI dates were accepted as the start of follow-up for the time-to-event analysis. The event was defined as cs-PCa diagnosis (International Society of Urological Pathology ≥2). Patients who were not diagnosed with cs-PCa during follow-up were censored according to predefined literature-based criteria at the end of the maximum follow-up duration with no reasonable suspicion of PCa and no biopsy indication. The impact of various factors on survival was assessed using a log-rank test and multivariable Cox regression. Subsequently, 394 cases diagnosed with PCa during follow-up were evaluated, based on initial PI-RADS categories and NCCN risk groups. Three main risk factors for cs-PCa diagnosis during follow-up were an initial PI-RADS 5 category, initial PI-RADS 4 category, and high MRI-defined PSA density (mPSAD), with average hazard ratios of 29.52, 14.46, and 3.12, respectively. The PI-RADS 3 category, advanced age group, and biopsy-naïve status were identified as additional risk factors (hazard ratios: 2.03, 1.54-1.98, and 1.79, respectively). In the PI-RADS 1-2 cohort, 1, 3, and 5-year cs-PCa diagnosis-free survival rates were 99.1%, 96.5%, and 93.8%, respectively. For the PI-RADS 3 cohort, 1, 3, and 5-year cs-PCa diagnosis-free survival rates were 94.9%, 90.9%, and 89.1%, respectively. For the PI-RADS 4 cohort, 1, 3, and 5-year cs-PCa diagnosis-free survival rates were 56.6%, 55.1%, and 55.1%, respectively. These rates were found to all be 24.2% in the PI-RADS 5 cohort. Considering the 394 cases diagnosed with PCa during follow-up, PI-RADS ≥4 cases were more likely to harbor unfavorable PCa compared to PI-RADS ≤3 cases (P < 0.001). In the PI-RADS 3 subgroup analysis, a low mPSAD (<0.15 ng/mL2) was found to be a protective prognostic factor against unfavorable PCa (P = 0.005). The PI-RADS category has a significant impact on patient management and provides important diagnostic and prognostic information. Higher initial PI-RADS categories are associated with decreased follow-up losses, a shorter time to PCa diagnosis, increased biopsy rates, a higher likelihood of developing cs-PCa during follow-up, and a worse PCa prognosis. Combining mPSAD with PI-RADS categories could enhance diagnostic stratification in the identification of cs-PCa.

Overall survival benefit of androgen suppression in addition to dose-escalated external beam radiotherapy for high-risk prostate cancer: Nationwide real-world data indicates a shift in men that benefit

ObjectiveTo evaluate the real-world added value of androgen deprivation therapy (ADT) in addition to external beam radiotherapy (EBRT) in men with high-risk non-metastatic prostate cancer, in view of advances in radiotherapy and diagnostics. MethodsAll Dutch men diagnosed with high-risk non-metastatic prostate cancer (defined as: ≥cT2c-T3b N0M0, PSA ≥20–50 ng/ml, and/or Gleason score ≥8 (International Society of Urological Pathology [ISUP] grade ≥4)) from 2009 through 2019 and treated with EBRT with or without ADT were identified in the population-based Netherlands Cancer Registry.Propensity scores were used to match (1:1) men that received ADT to men that did not receive ADT. Subsequently, OS was compared. Analyses were also stratified by number of high-risk features, 1 (either ≥cT2c, PSA >20 ng/ml or Gleason score ≥8) versus ≥2 (out of ≥cT2c, PSA >20 ng/ml and Gleason score ≥8). ResultsA total of 14,773 men with high-risk non-metastatic prostate cancer were identified, 3,958 (27%) of which received EBRT alone. After matching, 3,427 men remained in both groups and baseline characteristics were well-balanced. After a median follow-up of 92 months, OS was better in men treated with EBRT and ADT compared to men treated with EBRT alone (10-year OS: 66.4% versus 61.8%; HR 0.88 [95%CI: 0.80–0.96]). There was no statistically significant difference in OS in the subgroup of men with only 1 high-risk feature (10-year OS 67.7% versus 64.9%; HR 0.95 [95%CI: 0.85–1.07]). ConclusionsIn a contemporary cohort of men treated for high-risk non-metastatic prostate cancer with EBRT, an OS benefit of adding ADT was only observed in men with at least 2 high-risk features. These results suggest that improvements in diagnostics and treatment in recent decades have resulted in a stage shift of men benefiting from the addition of ADT to EBRT.

Clinical features of prostate cancer by polygenic risk score.

Genome-wide association studies have identified more than 290 single nucleotide variants (SNVs) associated with prostate cancer. These SNVs can be combined to generate a Polygenic Risk Score (PRS), which estimates an individual's risk to develop prostate cancer. Identifying individuals at higher risk for prostate cancer using PRS could allow for personalized screening recommendations, improve current screening tools, and potentially result in improved survival rates, but more research is needed before incorporating them into clinical use. Our study aimed to investigate associations between PRS and clinical factors in affected individuals, including age of diagnosis, metastases, histology, International Society of Urological Pathology (ISUP) Grade Group (GG) and family history of prostate cancer, while taking into account germline genetic testing in known prostate cancer related genes. To evaluate the relationship between these clinical factors and PRS, a quantitative retrospective chart review of 250 individuals of European ancestry diagnosed with prostate cancer who received genetic counseling services at The Ohio State University's Genitourinary Cancer Genetics Clinic and a 72-SNV PRS through Ambry Genetics, was performed. We found significant associations between higher PRS and younger age of diagnosis (p = 0.002), lower frequency of metastases (p = 0.006), and having a first-degree relative diagnosed with prostate cancer (p = 0.024). We did not observe significant associations between PRS and ISUP GG, histology or a having a second-degree relative with prostate cancer. These findings provide insights into features associated with higher PRS, but larger multi-ancestral studies using PRS that are informative across populations are needed to understand its clinical utility.

Expected impact of MRI-targeted biopsy interreader variability among uropathologists on ProScreen prostate cancer screening trial: a pre-trial validation study

PurposeProstate cancer (PCa) histology, particularly the Gleason score, is an independent prognostic predictor in PCa. Little is known about the inter-reader variability in grading of targeted prostate biopsy based on magnetic resonance imaging (MRI). The aim of this study was to assess inter-reader variability in Gleason grading of MRI-targeted biopsy among uropathologists and its potential impact on a population-based randomized PCa screening trial (ProScreen).MethodsFrom June 2014 to May 2018, 100 men with clinically suspected PCa were retrospectively selected. All men underwent prostate MRI and 86 underwent targeted prostate of the prostate. Six pathologists individually reviewed the pathology slides of the prostate biopsies. The five-tier ISUP (The International Society of Urological Pathology) grade grouping (GG) system was used. Fleiss’ weighted kappa (κ) and Model-based kappa for associations were computed to estimate the combined agreement between individual pathologists.ResultsGG reporting of targeted prostate was highly consistent among the trial pathologists. Inter-reader agreement for cancer (GG1–5) vs. benign was excellent (Model-based kappa 0.90, Fleiss’ kappa κ = 0.90) and for clinically significant prostate cancer (csPCa) (GG2–5 vs. GG0 vs. GG1), it was good (Model-based kappa 0.70, Fleiss’ kappa κ 0.67).ConclusionsInter-reader agreement in grading of MRI-targeted biopsy was good to excellent, while it was fair to moderate for MRI in the same cohort, as previously shown. Importantly, there was wide consensus by pathologists in assigning the contemporary GG on MRI-targeted biopsy suggesting high reproducibility of pathology reporting in the ProScreen trial.

Can We Predict the Grade of Clear Cell Renal Cell Carcinoma from Houns-Field Unit of Renal Lesion on Computerized Tomography Scan, a Retrospective Cross-Sectional Study.

Renal cell carcinoma (RCC) is a type of urological malignancy that affects approximately 2% of the global population. Imaging modalities, especially computed tomography (CT) scanning, play a critical role in diagnosing RCC. In this study, we investigated whether there is a relationship between tumour grade of clear cell RCC and HU values of renal lesions on CT scan performed before operation. We conducted a retrospective analysis of 123 patients who underwent radical or partial (open or laparoscopic) nephrectomy for clear cell RCC between January 2017 and January 2021. Post-operation histopathological grades were recorded according to World Health Organization (WHO)/International Society of Urological Pathology (ISUP) 2016 grading system and divided into low grade (includes grade 1 and 2) and high grade (grade 3 and 4), and their links to age, sex, smoking habits, tumour size, and HUs of renal lesions were evaluated. The mean age of the patients studied was 63.02 years old. About 56.9% of the patients were low grade (grade 1 or grade 2), while 43.1% were high grade (grade 3 or 4). The mean tumour size was 6.31 cm. There were no significant differences in tumour grade according to age, sex, or smoking habits. We found a significant relation between tumour grade and HU in the pre-contrast and nephrogenic phases, with p values of 0.001 and 0.037, respectively. On the other hand, there was no significant relation linking the tumour grade to the difference in HU between these phases, where there was a p value of 0.641. HU in the pre-contrast and nephrogenic phases in addition to tumour size on CT scan have a significant relation to clear cell RCC grade.

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

ObjectivesTo 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 methodsThe 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. Results2003 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. ConclusionsThe 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.

Tumor upgrading among very favorable intermediate-risk prostate cancer patients treated with robot-assisted radical prostatectomy: how can it impact the clinical course?

We sought to investigate predictors of unfavorable tumor upgrading in very favorable intermediate-risk (IR) prostate cancer (PCa) patients treated with robot-assisted radical prostatectomy, in addition to evaluate how it may affect the risk of disease progression. A very favorable subset of IR PCa patients presenting with prostate-specific antigen (PSA) < 10ng/mL, percentage of biopsy positive cores (BPC) < 50%, and either International Society of Urological Pathology (ISUP) grade group 1 and clinical stage T2b or ISUP grade group 2 and clinical stage T1c-2b was identified. Unfavorable pathology at radical prostatectomy was defined as the presence of ISUP grade group > 2 (unfavorable tumor upgrading), extracapsular extension (ECE), and seminal vesicle invasion (SVI). Disease progression was defined as the event of biochemical recurrence and/or local recurrence and/or distant metastases. Associations were evaluated by Cox regression and logistic regression analyses. Overall, 210 patients were identified between January 2013 and October 2020. Unfavorable tumor upgrading was detected in 71 (33.8%) cases, and adverse tumor stage, including ECE or SVI in 18 (8.6%) and 11 (5.2%) patients, respectively. Median (interquartile range) follow-up was 38.5 (16-61) months. PCa progression occurred in 24 (11.4%) patients. Very favorable IR PCa patients with unfavorable tumor upgrading at final pathology showed a persistent risk of disease progression, which hold significance after adjustment for all factors (Hazard Ratio [HR]: 5.95, 95% Confidence Interval [CI]: 1.97-17.92, p = 0.002) of which PSA was an independent predictor (HR: 1.52, 95% CI 1.12-2.08, p = 0.008). Moreover, these subjects were more likely to belong to the biopsy ISUP grade group 2. Very favorable IR PCa patients hiding unfavorable tumor upgrading were more likely to experience disease progression. Unfavorable tumor upgrading involved about one-third of cases and was less likely to occur in patients presenting with biopsy ISUP grade group 1. Tumor misclassification is an issue to discuss, when counseling this subset of patients for active surveillance because of the risk of delayed active treatment.

Histogram analysis of MR quantitative parameters: are they correlated with prognostic factors in prostate cancer?

To investigate the correlation between quantitative MR parameters and prognostic factors in prostate cancer (PCa). A total of 186 patients with pathologically confirmed PCa who underwent preoperative multiparametric MRI (mpMRI), including synthetic MRI (SyMRI), were enrolled from two medical centers. The histogram metrics of SyMRI [T1, T2, proton density (PD)] and apparent diffusion coefficient (ADC) values were extracted. The Mann‒Whitney U test or Student's t test was employed to determine the association between these histogram features and the prognostically relevant factors. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the differentiation performance. Spearman's rank correlation coefficients were calculated to determine the correlations between histogram parameters and the International Society of Urological Pathology (ISUP) grade group as well as pathological T stage. Significant correlations were found between the histogram parameters and the ISUP grade as well as pathological T stage of PCa. Among these histogram parameters, ADC_minimum had the strongest correlation with the ISUP grade (r = -0.481, p<0.001), and ADC_Median showed the strongest association with pathological T stage (r = -0.285, p=0.008). The ADC_10th percentile exhibited the highest performance in identifying clinically significant prostate cancer (csPCa) (AUC 0.833; 95% CI 0.771-0.883). When discriminating between the status of different prognostically relevant factors, a significant difference was observed between extraprostatic extension-positive and -negative cancers with regard to histogram parameters of the ADC map (10th percentile, 90th percentile, mean, median, minimum) and T1 map (minimum) (p=0.002-0.032). Moreover, histogram parameters of the ADC map (90th percentile, maximum, mean, median), T2 map (10th percentile, median), and PD map (10th percentile, median) were significantly lower in PCa with perineural invasion (p=0.009-0.049). The T2 values were significantly lower in patients with seminal vesicle invasion (minimum, p=0.036) and positive surgical margin (10th percentile, 90th percentile, mean, median, and minimum, p=0.015-0.025). Quantitative histogram parameters derived from synthetic MRI and ADC maps may have great potential for predicting the prognostic features of PCa.

The Role of Adipocytokines and their Receptors in Prostate Cancer: Adiponectin May Protect Against Progression.

Obesity is correlated with an increased risk of developing malignancies, including prostate cancer. Adipocytokines, such as leptin and adiponectin, are a family of hormones derived from adipose tissue that are involved not only in metabolism, but also in the development and progression of various malignancies. However, little is known about their role in prostate cancer. This study aimed to determine how leptin, adiponectin, and their receptors impact the spread of prostate cancer. We first performed immunohistochemical analysis of prostate cancer tissue microarrays to detect leptin, leptin receptor (Ob-R), adiponectin, and adiponectin receptors 1 and 2 (AdipoR1 and AdipoR2). Wound healing assays and western blot analysis were then performed in human prostate cancer cell lines. Immunohistochemistry showed that prostate tissue was not significantly positive for adiponectin. However, its expression tended to decrease according to the International Society of Urological Pathology (ISUP) grade of prostate cancer (p=0.056). In prostate cancer cell lines, administration of the synthetic adiponectin AdipoRon suppressed cell migration as well as the expression of phospho-NF-[Formula: see text]B and cyclooxygenase-2, whereas leptin stimulated these effects. Adiponectin expression tended to be suppressed according to ISUP grade in prostate cancer tissues. In vitro, tumor cell migration was induced by leptin but suppressed by adiponectin. Targeting adipocytokines could be a novel treatment strategy for prostate cancer.

Identifying pathological groups from MRI in prostate cancer using graph representation learning

Multiparametric magnetic resonance imaging (mpMRI) plays a critical role in prostate cancer (PCa) diagnosis, aiding in clinical trial evaluation and personalized treatment planning. We propose a novel prediction approach based on graph representation learning (GRL) integrating mpMRI images for classifying International Society of Urological Pathology (ISUP) grade groups. We initially constructed a mpMRI image graph representation learning (MMIGRL) model using a graph-based representation fusion approach. After constructing a heterogeneous graph integrating T2-weighted and apparent diffusion coefficient (ADC) images, we applied an adaptive method that dynamically adjusted the edges within the graph to reveal relationships within the mpMRI images. Subsequently, we developed a residual graph convolution network (Res-GCN) model to establish the mapping relationship between the mpMRI fusion graph and ISUP grade groups. The results of 5-fold cross-validation demonstrated excellent overall performance, and the prediction results using independent testing datasets confirmed the model's generalizability. The results of ablation studies highlighted the positive impact of integrating T2-weighted and ADC images and the effectiveness of residual connections in learning hierarchical features within the graph structure. The results of comparative experiments validated the superiority of the proposed MMIGRL model compared with convolutional neural network (CNN) and vision transformer (ViT) models. This approach holds promise for accurate ISUP grade group classification in PCa diagnosis, contributing to improved patient care and clinical decision making.

Clinical risk prediction model and external validation of positive surgical margin in laparoscopic radical prostatectomy based on MRI lesion location.

To clarify the composition of lesions in different magnetic resonance imaging (MRI) partitions of positive surgical margins (PSM) after laparoscopic radical prostatectomy, explore the influence of lesion location on PSM, and construct a clinical prediction model to predict the risk of PSM. This retrospective cohort study included 309 patients who underwent laparoscopic radical prostatectomy from 2018 to 2021 in our center was performed. 129 patients who met the same criteria from January to September 2022 were external validation cohorts. The incidence of PSM in transition zone (TZ) lesions was higher than that in peripheral zone (PZ) lesions. The incidence of PSM in the middle PZ was lower than that in other regions. Prostate specific antigen (PSA), clinical T-stage, the number of positive cores, international society of urological pathology (ISUP) grade (biopsy), MRI lesion location, extracapsular extension, seminal vesicle invasion (SVI), pseudo-capsule invasion (PCI), long diameter of lesions, lesion volume, lesion volume ratio, PSA density were related to PSM. MRI lesion location and PCI were independent risk factors for PSM. Least absolute shrinkage and selection operator (LASSO) regression was used to construct a clinical prediction model for PSM, including five variables: the number of positive cores, SVI, MRI lesion location, long diameter of lesions, and PSA. The positive rate of surgical margin in middle PZ was significantly lower than that in other regions, and MRI lesion location was an independent risk factor for PSM.

The correlation between interleukin-4 (IL-4) and programmed cell death-ligand 2 (PD-L2) expression with clinicopathological characteristics on prostate cancer

Prostate cancer (PCa) is the most frequent cancer diagnosed worldwide and the second most common malignancy in men. IL-4 is one of cytokines related to the inflammation process. An increase level of IL-4 in patients with PCa might be related to progression to castrate-resistance prostate cancer. Programmedcell death-ligand 2 (PD-L2) plays an important role in the anti-tumor immune system, however the exact mechanism is not fully understood. This study aimed to investigate the correlation between IL-4 and PD-L2 expression with the clinicopathological characteristic of PCa. The IL-4 and PD-L2 examinations wereperformed using quantitative real-time polymerase chain reaction (qRT-PCR) while clinicopathological characteristics were described by the Gleason score and International Society of Urological Pathology (ISUP) grade. Data collected were then analyzed using Pearson and Spearman test. In total, 20 patients withPCa tissue were collected between 2015 and 2020. The mean level of IL-4 and PDL2 were higher in metastatic PCa/M-PCa (105.64 and 665.42 ng/mL) compared to non-metastatic PCa/NM-PCa (41.62 and 215.06 ng/mL). A significant difference with medium correlation between IL-4 and PD-L2 with Gleason score and ISUPgrade was observed on all samples (p = 0.035 and 0.045; r = 0.454 and 0.473). However, no significant difference with weak correlation was observed on each group (p = 0.136 and 0.858; r = 0.065 and 0.506). Interestingly, there was a significant difference with very strong correlation observed between IL-4 andPD-L2, both on all samples (p = 0.001; r = 0.955) and on each group (p = 0.001 and 0.001; r = 0.917 and 0.955). In conclusion, there is a correlation between IL-4 and PD-L2 with the clinicopathological characteristics of PCa.

Prediction of clinically significant prostate cancer using radiomics models in real-world clinical practice: a retrospective multicenter study

PurposeTo develop and evaluate machine learning models based on MRI to predict clinically significant prostate cancer (csPCa) and International Society of Urological Pathology (ISUP) grade group as well as explore the potential value of radiomics models for improving the performance of radiologists for Prostate Imaging Reporting and Data System (PI-RADS) assessment.Material and methodsA total of 1616 patients from 4 tertiary care medical centers were retrospectively enrolled. PI-RADS assessments were performed by junior, senior, and expert-level radiologists. The radiomics models for predicting csPCa were built using 4 machine-learning algorithms. The PI-RADS were adjusted by the radiomics model. The relationship between the Rad-score and ISUP was evaluated by Spearman analysis.ResultsThe radiomics models made using the random forest algorithm yielded areas under the receiver operating characteristic curves (AUCs) of 0.874, 0.876, and 0.893 in an internal testing cohort and external testing cohorts, respectively. The AUC of the adjusted_PI-RADS was improved, and the specificity was improved at a slight sacrifice of sensitivity. The participant-level correlation showed that the Rad-score was positively correlated with ISUP in all testing cohorts (r > 0.600 and p < 0.0001).ConclusionsThis radiomics model resulted as a powerful, non-invasive auxiliary tool for accurately predicting prostate cancer aggressiveness. The radiomics model could reduce unnecessary biopsies and help improve the diagnostic performance of radiologists’ PI-RADS. Yet, prospective studies are still needed to validate the radiomics models further.Critical relevance statementThe radiomics model with MRI may help to accurately screen out clinically significant prostate cancer, thereby assisting physicians in making individualized treatment plans.Key points• The diagnostic performance of the radiomics model using the Random Forest algorithm is comparable to the Prostate Imaging Reporting and Data System (PI-RADS) obtained by radiologists.• The performance of the adjusted Prostate Imaging Reporting and Data System (PI-RADS) was improved, which implied that the radiomics model could be a potential radiological assessment tool.• The radiomics model lowered the percentage of equivocal cases. Moreover, the Rad-scores can be used to characterize prostate cancer aggressiveness.Graphical

99mTc]Tc-HYNIC-ALUG SPECT/CT in the initial staging of 227 consecutive patients with newly diagnosed prostate cancer: a 5-year monocentric retrospective study.

The purpose of this study was to assess the effectiveness of [99mTc]Tc-HYNIC-ALUG SPECT/CT in the initial staging of patients with newly diagnosed PCa. A retrospective analysis was conducted on 227 consecutive patients who underwent [99mTc]Tc-HYNIC-ALUG SPECT/CT imaging for the primary staging of newly diagnosed PCa. The presence and location of PSMA-positive lesions were determined, and the maximum standardized uptake values (SUVmax) of the primary prostate tumor were also measured. The metastatic findings and SUVmax were stratified according to International Society of Urological Pathology (ISUP) grade, prostate-specific antigen (PSA) levels, and D'Amico classification. Furthermore, the [99mTc]Tc-HYNIC-ALUG SPECT/CT findings were compared to the histopathological findings in patients who had undergone radical prostatectomy with pelvic lymph node dissection (PLND). Of the 227 patients, 92.1% (209/227) had positive [99mTc]Tc-HYNIC-ALUG SPECT/CT findings. Advanced disease was detected in 38.8% (88/227) of the patients and was positively correlated with increasing ISUP grade and PSA levels. Lymph node metastases (both pelvic and extrapelvic), bone metastases, and visceral metastases were detected in 30.0% (68/227), 25.6% (58/227), and 3.1% (7/227) of the patients, respectively. For the 129 patients who underwent radical prostatectomy with PLND, the sensitivity of [99mTc]Tc-HYNIC-ALUG SPECT/CT in the evaluation of PCa was 90.7% (117/129). The sensitivity, specificity, accuracy, and positive and negative predictive values for detecting pelvic lymph node metastases on [99mTc]Tc-HYNIC-ALUG SPECT/CT were 23.5% (12/51), 93.6% (73/78), 65.9% (85/129), 70.6% (12/17), and 65.2% (73/112), respectively. Among the 209 patients with PSMA-avid primary prostate disease, the SUVmax of the primary prostate tumor was significantly associated with ISUP grade (p<0.0001), PSA levels (p<0.0001), D'Amico classification (p<0.0001), and advanced disease (p<0.0001). Receiver operating characteristic (ROC) analysis revealed that a PSA level >19.8 ng/ml and SUVmax of the primary prostate tumor >7.4 had a sensitivity of 71.6% and 71.6% and specificity of 76.9% and 82.6%, respectively, for detecting metastatic disease. [99mTc]Tc-HYNIC-ALUG SPECT/CT emerges as a valuable imaging tool for the initial staging of newly diagnosed PCa. The presence of advanced disease and the SUVmax of the primary prostate tumor were positively correlated with ISUP grade and PSA levels.

Quantification of eosinophilic area and its potential molecular feature in clear cell renal cell carcinoma.

Previous studies have acknowledged the presence of eosinophilic cytoplasm in clear cell renal cell carcinoma, yet the precise quantification method and potential molecular attributes in clear cell renal cell carcinoma remain elusive. This study endeavours to precisely quantify the eosinophilic attribute and probe into the molecular mechanisms governing its presence in clear cell renal cell carcinoma. Data from cohorts of clear cell renal cell carcinoma patients who underwent nephrectomy, comprising The Cancer Genome Atlas cohort (n=475) and Sun Yat-sen University Cancer Center cohort (n=480), were aggregated to assess the eosinophilic attribute. Additionally, Omics data from Clinical Proteomic Tumor Analysis Consortium (CPTAC) (n=58) were leveraged to explore the potential molecular features associated with eosinophilic clear cell renal cell carcinoma. Employing receiver operating characteristic curve analysis, the proportion of tumour cells with eosinophilic cytoplasm was determined, leading to the classification of each cohort into distinct groups: a clear group (<5%) and an eosinophilic group (≥5%). In both cohorts, the eosinophilic feature consistently correlated with higher International Society of Urological Pathology (ISUP) grade, elevated tumor stage, and the presence of necrosis. Furthermore, the Kaplan-Meier method demonstrated that patients in the eosinophilic group exhibited shorter overall survival or disease-free survival compared with those in the clear group, a pattern reaffirmed in various stratified survival analyses. Intriguingly, within The Cancer Genome Atlas cohort, the pathological characterization of cell cytoplasm (eosinophilic vs. clear) emerged as an independent risk factor for overall survival (hazard ratio = 2.507 [95% confidence interval: 1.328-4.733], P = 0.005) or disease-free survival (hazard ratio = 1.730 [95% confidence interval: 1.062-2.818], P = 0.028) via Cox regression analysis. Moreover, multi-Omics data unveiled frequent BAP1 mutations and down-regulation of Erythroblast Transformation-Specific-Related Gene associated with the eosinophilic feature in clear cell renal cell carcinoma. Additionally, patients with low expression of Erythroblast Transformation-Specific-Related Gene showed worse overall survival (P < 0.001). The quantification of the eosinophilic feature serves as a robust predictor of clinical prognosis in clear cell renal cell carcinoma. Furthermore, the manifestation of this feature may be linked to BAP1 mutations and the down-regulation of Erythroblast Transformation-Specific-Related Gene in clear cell renal cell carcinoma. Significantly, the expression levels of Erythroblast Transformation-Specific-Related Gene manifest as an exemplary prognostic marker, providing exceptional predictive accuracy for the clinical prognosis in clear cell renal cell carcinoma.

PI-RADS Upgrading Rules: Impact on Prostate Cancer Detection and Biopsy Avoidance of MRI-Directed Diagnostic Pathways.

Background: PI-RADS incorporate rules by which ancillary sequence findings upgrade a dominant score to a higher final category. Evidence on the upgrading rules' impact on diagnostic pathways remains scarce. Objective: To evaluate the clinical net benefit of the PI-RADS upgrading rules in MRI-directed diagnostic pathways. Methods: This study was a retrospective analysis of a prospectively maintained clinical registry. The study included patients without known prostate cancer who underwent prostate MRI followed by prostate biopsy from January 2016 to May 2020. Clinically significant prostate cancer (csPCa) was defined as International Society of Urological Pathology (ISUP) grade group ≥2. csPCa detection was compared between dominant (i.e., no upgrade rule applied) and upgraded lesions. Decision curve analysis was used to compare the net benefit, considering the tradeoff of csPCa detection and biopsy avoidance, of MRI-directed pathways in scenarios considering and disregarding PI-RADS upgrading rules. These included biopsy-all pathway, MRI-focused pathway (no biopsy for PI-RADS ≤2), and risk-based pathway (use of PSA density ≥0.15 to select patients with PI-RADS ≤3 for biopsy). Results: The sample comprised 716 patients (mean age, 64.9 years; 93 with a PI-RADS ≤2 examination, 623 with total of 780 PI-RADS ≥3 lesions). Frequencies of csPCa were not significantly different between dominant and upgraded PI-RADS 3 transition zone lesions (20% vs 19%), dominant and upgraded PI-RADS 4 transition zone lesions (33% vs 26%), and dominant and upgraded PI-RADS 4 peripheral zone lesions (58% vs 45%) (p>.05). In the biopsy-all, per-guideline MRI-focused, MRI-focused disregarding upgrading rules, per-guideline risk-based, and risk-based disregarding upgrading rules pathways, csPCa frequency was 53%, 52%, 51%, 52%, and 48%, and biopsy avoidance was 0%, 13%, 16%, 19%, and 25%, respectively. Disregarding upgrading rules yielded 5.5 and 1.9 biopsies avoided per missed csPca for MRI-focused and risk-based pathways, respectively. At probability thresholds for biopsy selection of 7.5-30%, net benefit was highest for the per-guideline risk-based pathway. Conclusion: Disregarding PI-RADS upgrading rules reduced net clinical benefit of the risk-based MRI-directed diagnostic pathway when considering tradeoffs between csPCa detection and biopsy avoidance. Clinical Impact: This study supports the application of PI-RADS upgrading rules to optimize biopsy selection, particularly in risk-based pathways.

Analytical performance validation of aPROMISE platform for prostate tumor burden, index and dominant tumor assessment with 18F-DCFPyL PET/CT. A pilot study

To validate the performance of automated Prostate Cancer Molecular Imaging Standardized Evaluation (aPROMISE) in quantifying total prostate disease burden with 18F-DCFPyL PET/CT and to evaluate the interobserver and histopathologic concordance in the establishment of dominant and index tumor. Patients with a recent diagnosis of intermediate/high-risk prostate cancer underwent 18F-DCFPyL-PET/CT for staging purpose. In positive-18F-DCFPyL-PET/CT scans, automated prostate tumor segmentation was performed using aPROMISE software and compared to an in-house semiautomatic-manual guided segmentation procedure. SUV and volume related variables were obtained with two softwares. A blinded evaluation of dominant tumor (DT) and index tumor (IT) location was assessed by both groups of observers. In histopathological analysis, Gleason, International Society of Urological Pathology (ISUP) group, DT and IT location were obtained. We compared all the obtained variables by both software packages using intraclass correlation coefficient (ICC) and Cohen’s kappa coefficient (k) for the concordance analysis. Fifty-four patients with a positive 18F-DCFPyL PET/CT were evaluated. The ICC for the SUVmax, SUVpeak, SUVmean, tumor volume (TV) and total lesion activity (TLA) was: 1, 0.833, 0.615, 0.494 and 0.950, respectively (p < 0.001 in all cases). For DT and IT detection, a high agreement was observed between both softwares (k = 0.733; p < 0.001 and k = 0.812; p < 0.001, respectively) although the concordances with histopathology were moderate (p < 0001). The analytical validation of aPROMISE showed a good performance for the SUVmax, TLA, DT and IT definition in comparison to our in-house method, although the concordance was moderate with histopathology for DT and IT.