Extraprostatic Extension Research Articles

Development and Validation of MRI Imaging Biomarkers for Prostate Cancer Using Deep Learning.

Given the increasing number of treatment options for patients with localized prostate cancer (PCa), there is a need for biomarkers to aid in risk stratification. Specifically, novel biomarkers can aid in the identification of high-risk phenotypes among similar patients in traditional NCCN risk groupings. One promising area for development is using pre-treatment prostate MRI to identify imaging biomarkers to identify prostate cancer patients at highest risk for recurrence. We hypothesized that deep learning could be leveraged to identify imaging biomarkers of aggressive PCa from pre-treatment prostate MRIs. Our study included 1,020 patients treated at our institution between 2010-2022. Given pathologic extraprostatic extension (EPE) and seminal vesicle invasion (SVI) are associated with higher risk of treatment failure, we hypothesized that deep learning models which identified radiographic EPE and SVI would provide non-invasive imaging biomarkers associated with PCa prognosis. We trained two separate deep learning models using convolutional neural networks to predict SVI and EPE respectively. The model inputs were T2W prostate MRIs (n = 894) and models consisted of 8 convolutional layers. Dropout, L2 regularization, and data augmentation were used to improve model generalizability and reduce overfitting. Discriminatory ability of each model was measured using AUC on a blinded external test set of 221 patients. To assess the clinical utility of our imaging biomarkers, log-rank tests were used to evaluate biochemical free survival (BFS) for patients classified as high risk to patients classified as low risk. Biochemical failure was defined as post-treatment PSA >0.1 for patients who underwent radical prostatectomy (RP) or PSA >2ng/ml above nadir for patients receiving radiation therapy. Within our cohort of 1,020 patients the median age was 66 with a median follow up of 4 years. 49.3% (n = 503) underwent RP and 50.7% (n = 517) received EBRT. 4% (n = 41) were low risk, 62.4% (n = 636) were intermediate risk, and 33% (n = 337) were high risk based on NCCN criteria. Deep learning models showed good discriminatory ability for both EPE (AUC 0.66) and SVI (AUC 0.74). Both imaging biomarkers showed prognostic ability to identify high risk prostate phenotypes. Patients deemed high risk based on EPE classifier had worse BFS (median 5 vs 9 years, p<.001). Similarly, patients classified as high risk based on SVI also showed worse BFS (median 5 vs 9 years, p = 0.024). Among intermediate risk patients, EPE biomarker showed an ability to identify high risk phenotypes (median 6 vs 9 years, p = 0.024). Deep learning classifiers of prostate MRIs demonstrated the ability to stratify high-risk prostate cancer phenotypes beyond traditional risk paradigms. Imaging biomarkers represent a non-invasive method to help aid in the personalization of treatment for patients with localized prostate cancer and identify patients who potentially require treatment escalation.

Integration of Multiparameter MRI into Conventional Pretreatment Risk Factors to Predict Adverse Features after Radical Prostatectomy.

The purpose of this study was to Integration of Multiparameter MRI into conventional pretreatment risk factors to develop nomogram for the prediction of adverse features (i.e., positive margin (PM) or extra-prostatic extension (EPE)) indicated for postoperative radiotherapy in patients with prostate cancer. We analyzed 203 histologically proven prostate cancer patients underwent preoperative 3T multiparametric MRI including high b value (0, 1500 s/mm2) diffusion-weighted imaging between 2019 and 2022 at our hospital. Patients with a history of neoadjuvant hormonal therapy, or patients whose surgeon's experience was ≤3 years were excluded. Age, surgical technique, serum PSA level, PSA density, clinical T stage, and biopsy Gleason score were clinical predictors. MRI parameters include prostate volume, tumor size, ECE score, seminal vesicle invasion score, tumor location (apex, peripheral region, or bladder neck), apparent diffusion coefficient (ADC), tumor contact length (TCL), PI-RADS score. Predictors were used in nomograms developed from multivariable logistic regression analysis to estimate the probability of positive margin (PM) or extra-prostatic extension (EPE) after RP. The nomogram's predictive accuracy and discriminative ability were determined by the concordance index with calibration and receiver operating characteristic (ROC) curves. (1) Patient characters: Table 1 lists the MRI characteristics of the patients. Median PSA level is 17.6ng/ml. All patients received extra-fascial resection. 44% of the patients underwent robotic surgery. 24% of the patients had positive margins. In 226 patients who was clinically confined to the prostate, 100 (44%) had a postoperative pathological upgrade of pT3a or above. 46 (29%) of the 158 patients with biopsy grade group (GG)1 was confirmed GG3-5 after RP. Using mpMRI parameters and clinicopathological information, we produced nomograms that may accurately predict adverse Features that are indications for postoperative radiotherapy after RP, which may help individualize treatment decision-making.

Post-Prostatectomy Risk Stratification of Biochemical Recurrence Using Transfer Learning-Based Multi-Modal Artificial Intelligence

For patients undergoing radical prostatectomy for prostate cancer (PCa), accurate risk stratification is essential to guide post-prostatectomy therapeutic decision making. Recently, there has been success in the use of multi-modal artificial intelligence models for men after prostate biopsy to aid in risk stratification. Herein, we trained and tested a TRansfer learning-based multi-modal Artificial InteLligence model (TRAIL) for biochemical recurrence (BCR) risk stratification following radical prostatectomy. Patients contained within a prospective PCa registry at a single institution were utilized. Digital pathology slides from the diagnostic biopsies prior to radical prostatectomy for patients with clinically localized PCa were scanned at 20x resolution. Features were extracted for the TRAIL model from pathology slides via two transfer learning steps: (1) InceptionResNetv2 that first determines a heatmap of tumor areas, and (2) A ResNet18 that extracts representative features from the high tumor probability areas. Least Absolute Shrinkage and Selection Operator (LASSO) was used for feature selection from the pathology-extracted features. Finally, TRAIL combines the clinical and pathology-extracted features via a classification ensemble model based on weak tree learners to predict 2- and 5-year BCR defined as two consecutive serum PSA levels ≥0.2 ng/mL. TRAIL training was performed on 250 patients and was then locked and applied to the test set of 125 patients. Accuracy and the area under the curve (AUC) were calculated. Comparison to CAPRA-S and to clinical-only features were assessed. A total of 818 digital whole pathology biopsy slides from 375 patients treated with subsequent radical prostatectomy were included. Surgical margins were positive in 29% of the patients, and 41% had extra-prostatic extension. The median follow-up was 48 months (Range: 1-132 months). The rates of 2-and 5-year BCR were 11% and 18% respectively. A total of 19 digital pathology-driven features were included in TRAIL. Clinical factors included age, ISUPG, Gleason score, PSA, pathological T and N stages, surgical margin involvement, and the presence of extra-prostatic extension. On the testing set, TRAIL achieved a 2-year BCR AUC of 0.76 and accuracy of 0.87, and was superior to CAPRA-S (AUC = 0.57) and clinical-only features (AUC 0.50, accuracy 0.14). For 5-year BCR, TRAIL achieved an AUC of 0.69 and accuracy of 0.78, and performed better than CAPRA-S (AUC = 0.58), and clinical only features (AUC = 0.50, accuracy = 0.23). Through a combination of deep and ensemble learning, TRAIL incorporates clinical and histopathology features, enabling an improved BCR risk stratification post-prostatectomy when compared to the currently used clinicopathologic models. Future work with larger datasets with metastatic events is warranted to further optimize the model for clinical use.

Transperineal template saturation and conventional biopsy for stage prediction in prostate cancer.

To evaluate the performance of risk calculators (RCs) predicting lymph node invasion (LNI) and extraprostatic extension (EPE) in men undergoing transperineal magnetic resonance imaging/transrectal ultrasound (TRUS)-fusion template saturation biopsy (TTSB) and conventional systematic TRUS-guided biopsy (SB). The RCs were tested in a consecutive cohort of 645 men undergoing radical prostatectomy with extended pelvic LN dissection between 2005 and 2019. TTSB was performed in 230 (35.7%) and SB in 415 (64.3%) men. Risk of LNI and EPE was calculated using the available RCs. Discrimination, calibration, and clinical usefulness stratified by different biopsy techniques were assessed. Lymph node invasion was observed in 23 (10%) and EPE in 73 (31.8%) of cases with TTSB and 53 (12.8%) and 158 (38%) with SB, respectively. RCs showed an excellent discrimination and acceptable calibration for prediction of LNI based on TTSB (area under the curve [AUC]/risk estimation: Memorial Sloan Kettering Cancer Center [MSKCC]-RC 0.79/-4%, Briganti (2012)-RC 0.82/-4%, Gandaglia-RC 0.81/+6%). These were comparable in SB (MSKCC-RC 0.78/+2%; Briganti (2012)-RC 0.77/-3%). Decision curve analysis (DCA) revealed a net benefit at threshold probabilities between 3% and 6% when TTSB was used. For prediction of EPE based on TTSB an inferior discrimination and variable calibration were observed (AUC/risk estimation: MSKCC-RC 0.71/+8% and Martini (2018)-RC 0.69/+2%) achieving a net benefit on DCA only at risk thresholds of >17%. Performance of RCs for prediction of LNI and EPE based on SB showed comparable results with a better performance in the DCA for LNI (risk thresholds 1-2%) and poorer performance for EPE (risk threshold >20%). This study is limited by its retrospective single-institution design. The potentially more accurate grading ability of TTSB did not result in improved performance of preoperative RCs. Prediction tools for LNI proved clinical usefulness while RCs for EPE did not.

Prostat Adenokarsinomlarında Morfolojik Tümör Heterojenitesinin Lenf Nodu Metastazı ile İlişkisi

Aim:The aim of our study isto investigate effect of prostatic carcinoma histopathological subtypes to the lymph node metastasis (LNM).&#x0D; Materials- Methods:A total of 102 patients who underwent radical prostatectomy (RP) and pelvic lymph node disection were included in the study. Tumor grades, accompanying intraductal carcinoma (IDC-P)/ductal adenocarcinoma (PDA), LNM, extraprostatic extension (EPE) and seminal vesicle invasion (SVI) were recorded.&#x0D; Results: While 76 of the tumors had pure acinar adenocarcinoma (AC) histology, IDC-P accompanied AC in 17 and PDA in 9 cases. The tumors accompanying IDC-P and PDA were all stage 3 and stage 4. In pure AC cases, a statistically significant relationship was observed between the increased tumor grade and advanced stage. The positive relationship was determined between high GG with LNM, SVI and EPE in pure AC cases. LNM was observed in 11 of 17 cases accompanied by IDC-P, SVI in 10, and EPE in 16 cases. All 9 cases with PDA accompanying the tumor had EPE, 8 of the cases had LNM and SVI. A statistically significant relationship was observed between presence of LNM, SVI, EPE and accompanying IDC-P/PDA. When high graded tumors were examined, similar to results mentioned above, it was observed that IDC-P/PDA has accompanied AC thus, the risk of having LNM increased.&#x0D; Conclusion: In our study, it was noted that the presence of IDC-P/PDA accompanying the tumor significantly increased the risk of LNM, and it was thought that considering both these data in LNM risk analysis may provide a more accurate approach in treatment planning.

Relative impact of lymph-node metastasis and seminal vesical invasion on oncologic outcomes following radical prostatectomy.

While both seminal vesicle (SVI) and lymph-node invasion (LNI) have been identified as adverse prognostic variables among men undergoing radical prostatectomy (RP), the relative impact of each of these features on subsequent oncologic outcomes has not been well defined. We assessed the impact of LNI on long-term oncologic outcomes among patients with SVI at RP. We reviewed 19,519 patients who underwent RP and identified 2043 with SVI. Metastasis-free (MFS), cancer-specific (CSS), and overall survival (OS) were estimated for patients with SVI, stratified by the presence and number of pelvic lymph node metastases. Cox proportional hazards models were used to evaluate the independent association of the number of metastatic nodes and lymph node density with oncologic outcomes among patients with SVI, controlling for age, year of surgery, margin status, preoperative PSA, pathologic Gleason score, extraprostatic extension, and use of adjuvant therapies. At a median follow up of 12.1 years (IQR 7.0,18.6), 548 patients developed metastatic disease and 1331 died, including 406 who died from prostate cancer (PCa). We found that, among patients with SVI, the presence of a single positive lymph node was not associated with incrementally adverse oncologic outcomes compared to no nodal metastasis at RP, with 10-year MFS, CSS, and OS rates of 81.3% versus 78.3%(p = 0.18), 86.5% versus 89.8%(p = 0.32), and 72.8% versus 76.7%(p = 0.53), respectively. In contrast, on multivariable analyses, the presence of ≥2 metastatic nodes and a 20% lymph-node density cut off remained independently associated with worse survival. SVI represents an adverse pathologic feature such that the presence of a single positive pelvic lymph node did not further adversely impact prognosis. Meanwhile, a significant number of involved nodes was associated with decreased survival. These findings may aid in risk-stratification as well as clinical trial design for such high-risk patients following surgery.

Allelic variants and immunostaining profile in CXCL12/CXCR4 axis: An investigation of association with prognosis in prostate cancer

Prostate cancer (PCa) is the malignant neoplasm that most commonly affects men and is an important cause of death. It can be detected by changes in serum levels of Prostate Specific Antigen (PSA) and digital rectal examination, but often symptoms do not appear until advanced stages and metastases. The C-X-C Motif Chemokine Ligand 12/C-X-C Motif Chemokine Receptor 4 (CXCL12/CXCR4) axis acts in cell migration and may be involved in the metastatic process. In this context, the aim of this study was to evaluate the allelic variants rs1801157 (CXCL12) and rs2228014 (CXCR4) and the immunostaining of CXCR4 protein as candidates for prognostic markers in PCa. Samples (n = 60) were divided according to prognostic parameters (with and without metastasis at diagnosis) in tree groups: better prognosis, worse prognosis with metastasis at diagnosis and worse prognosis without metastasis at diagnosis, and immunostaining was evaluated by indirect immunohistochemistry, considering tumoral and adjacent tissues from the same patient (n = 120). A significant association was found between the C allele of rs2228014 (CXCR4) and the extraprostatic extension. For CXCR4 immunostaining a weak labeling and a cytoplasmic localization predominated, as well as a significant difference between malignant versus adjacent tissue, with higher protein expression in the malignant tissue. A significant association was found between CXCR4 tumor immunostaining with TNM staging (T2b-T2c) and PSA level (> 20 ng/mL). None of the allelic variants affected CXCR4 immunostaining. Prognostic groups did not differ in allelic variant frequency or immunostaining profile. Findings suggest that CXCR4 receptor may be one of the ways to worsen the prognosis of prostatic cancer.

Detection of extraprostatic extension by transperineal multiparametric magnetic resonance imaging-ultrasound fusion targeted combined with systemic template prostate biopsy

BackgroundExtraprostatic extension (EPE) of prostate cancer (PCa) on transrectal (TR) needle core biopsy (Bx) is a rare histopathological finding that can help in clinical decision-making. The detection efficiency of the transperineal (TP) approach is yet to be explored.MethodsWe retrospectively reviewed 2848 PCa cases using concomitant systemic template biopsy (SBx) and multiparametric magnetic resonance imaging (MRI)-ultrasound fusion-targeted biopsy (TBx) using the TR (n = 1917) or TP (n = 931) approach at our institution between January 2015 and July 2022. We assessed and compared clinical, MRI, and biopsy characteristics using different approaches (TP and TR) and methods (SBx and TBx).ResultsIn total, 40 EPE cases were identified (40/2848, 1.4%). TP showed a significantly higher EPE detection rate compared to TR in SBx (TR:0.7% vs. TP:1.6%; p = 0.028) and TBx (TR:0.5% vs. TP:1.2%; p = 0.033), as well as the combined methods (2.1% vs. 1.1%, p = 0.019). A significantly higher incidence of EPEs was found at non-base sites in TP than in TR (76.7% vs. 50%, p = 0.038). SBx showed a higher EPE detection rate than TBx; however, the difference was not statistically significant. TP showed higher prostate-specific antigen density (0.35 vs. 0.17, p = 0.005), higher frequency of GG4-5 in the cores with EPE (65.0% vs. 50.0%, p = 0.020), and more PCa-positive SBx cores (10 vs. 8, p = 0.023) compared to the TR.ConclusionsTP may improve EPE detection compared with TR and should be applied to patients with adverse pre-biopsy features.

Poster 15 - Extraprostatic extension is significantly associated with Gleason grade score upgrading: A retrospective cohort study from a Tertiary Teaching Institution

Poster 15 - Extraprostatic extension is significantly associated with Gleason grade score upgrading: A retrospective cohort study from a Tertiary Teaching Institution

Role of 68Ga-PSMA PET/CT in Initial Staging of Prostate Cancer and Correlation with PSA and Gleason Score

Background Prostate cancer is the second most common male malignancy. Its prognosis depends on the tumor stage as well as its aggressiveness; expressed histopathologically by Gleason scores. Furthermore, optimal patient management depends on the tumor stage. 68Ga PSMA PET/CT has a wide spectrum of uses in prostate malignancy, some of them are comprehensively studied while others are still under investigation. The most widely accepted use is the accurate initial staging of cancer prostate as well as predicting the long-term outcome, with SUVmax being a promising prognostic parameter correlating significantly with other established prognostic parameters, including the Gleason score and the PSA levels. Objective To evaluate the role of 68GA- PSMA PET/CT in initial staging of prostate cancer and correlate with PSA level and Gleason score. Methods A prospective descriptive study over the course of 6 months. It included patients with pathologically proven prostate cancer referred for a PSMA PET/CT scan for initial staging without any treatment or interventions. Results 68Ga-PSMA PET/CT scans of 36 patients were evaluated for local staging (primary prostatic lesions, extra-prostatic spread, and seminal vesicle invasion), regional nodal staging, and metastatic spread (extra-regional lymph nodes, osseous lesions, and visceral lesions). PET/CT findings as well as the SUVmax of the most avid lesions were correlated with PSA level, Gleason scores, as well as Gleason grade risk groups. A statistically significant relationship was found between PSA level and SUVmax of prostatic lesion as well as that of the most avid metastatic regional lymph node, the presence of extra-regional lymph nodal spread, the presence of osseous metastatic lesions, the presence of seminal vesicle invasion, extra-prostatic extension, and the presence of PSMA-avid regional lymph nodal spread. On the other hand, a statistically significant relationship was found between Gleason scores and the presence of regional lymph nodal spread and osseous metastatic lesions. Lastly, a statistically significant relationship was found between Gleason grading risk groups and the presence of regional lymph nodal spread and osseous metastatic lesions. Conclusion 68Ga-PSMA PET/CT is a powerful staging and stratifying tool for the majority of prostate cancer patients, being significantly correlated with PSA level and Gleason scores. However, patients with low PSA scores still pose a dilemma as they showed significantly low PSMA uptake, rendering the use of 68Ga-PSMA PET/CT for staging in such patients controversial. 68Ga-PSMA PET/CT based imaging findings should ideally be supported with histopathological documentation and/or follow-up imaging results in order to confirm the nature of detected lesions and help establish accurate sensitivity and specificity of 68Ga-PSMA PET/CT.

The diagnostic accuracy of radiolabeled PSMA-ligand PET for tumour staging in newly diagnosed prostate cancer patients compared to histopathology: a systematic review and meta-analysis.

The current clinical recommendations posit the deployment of specific approved radiolabeled prostate-specific membrane antigen-ligand positron emission tomography (PSMA PET) for detecting metastatic prostate cancer during primary staging. Nevertheless, the precise efficacy of such ligands in localizing intraprostatic tumours (index tumour) and T-staging is not well established. Consequently, the objective of this inquiry is to ascertain the diagnostic accuracy of PSMA-PET in the tumour staging of newly diagnosed prostate cancer by means of a meta-analysis that integrates studies utilizing histological confirmation as the reference standard. In this study, we conducted a systematic literature search of the PubMed, Embase, Web of Science, and Cochrane Library databases using a predefined collection of search terms. These terms included 'PSMA PET', 'primary staging', and 'prostate cancer'. Subsequently, two independent reviewers evaluated all the studies based on predetermined inclusion criteria, extracted pertinent data, and assessed the quality of evidence. Any disparities were resolved by a third reviewer. A random effects Sidik-Jonkman model was applied to conduct a meta-analysis and estimate the diagnostic accuracy on a per-patient basis, along with 95% confidence intervals. Moreover, an appraisal regarding the likelihood of publication bias and the impact of small-study effects was performed utilizing both Egger's test and a graphical examination of the funnel plot. The present analysis comprised a total of twenty-three scientific papers encompassing 969 patients and involved their analysis by both qualitative and quantitative approaches. The results of this study demonstrated that the estimated diagnostic accuracy of PSMA PET/CT and PSMA PET/MRI, for the detection of intraprostatic tumours, regardless of the type of PSMA-ligand, was 86% (95% CI: 76-96%) and 97% (95% CI: 94-100%), respectively. Furthermore, the diagnostic accuracy for the detection of extraprostatic extension (EPE) was 73% (95% CI: 64-82%) and 77% (95% CI: 69-85%), while the diagnostic accuracy for the detection of seminal vesicle involvement (SVI) was 87% (95% CI: 80-93) and 90% (95% CI: 82-99%), respectively. The present investigation has demonstrated that PSMA PET/MRI surpasses currently recommended multiparametric magnetic resonance imaging (mpMRI) in terms of diagnostic accuracy as inferred from a notable data trajectory, whereas PSMA-PET/CT exhibited comparable diagnostic accuracy for intraprostatic tumour detection and T-staging compared to mpMRI. Nevertheless, the analysis has identified certain potential limitations, such as small-study effects and a potential for publication bias, which may impact the overall conclusions drawn from this study.

Predictors of Extraprostatic Extension in Patients with Prostate Cancer.

To identify effective factors predicting extraprostatic extension (EPE) in patients with prostate cancer (PCa). This retrospective cohort study recruited 898 consecutive patients with PCa treated with robot-assisted laparoscopic radical prostatectomy. The patients were divided into EPE and non-EPE groups based on the analysis of whole-mount histopathologic sections. Histopathological analysis (ISUP biopsy grade group) and magnetic resonance imaging (MRI) (PI-RADS v2.1 scores [1-5] and the Mehralivand EPE grade [0-3]) were used to assess the prediction of EPE. We also assessed the clinical usefulness of the prediction model based on decision-curve analysis. Of 800 included patients, 235 (29.3%) had EPE, and 565 patients (70.7%) did not (non-EPE). Multivariable logistic regression analysis showed that the biopsy ISUP grade, PI-RADS v2.1 score, and Mehralivand EPE grade were independent risk factors for EPE. In the regression assessment of the models, the best discrimination (area under the curve of 0.879) was obtained using the basic model (age, serum PSA, prostate volume at MRI, positive biopsy core, clinical T stage, and D'Amico risk group) and Mehralivand EPE grade 3. Decision-curve analysis showed that combining Mehralivand EPE grade 3 with the basic model resulted in superior net benefits for predicting EPE. Mehralivand EPE grades and PI-RADS v2.1 scores, in addition to basic clinical and demographic information, are potentially useful for predicting EPE in patients with PCa.

The Prostate Is Not a Pill and Therefore Has No Capsule

Tumor staging of prostate cancer is a fundamental principle in management and therapy, with a hallmark being tumor growth beyond the organ boundary. Often, this is referred to as “capsule penetration”, suggesting the existence of a true prostatic capsule that would facilitate the determination of tumor penetration. In fact, the prostate does not have a true capsule and, depending on the anatomic area, it blends with the surrounding fibrous, adipose and muscular tissue. This makes it sometimes difficult or impossible to unequivocally identify extraprostatic tumor extension. It is necessary to appreciate this difficulty in order to better understand the significance of extraprostatic tumor extension.

Comprehensive analysis of predictive factors for upstaging in intraprostatic cancer after radical prostatectomy: Different patterns of spread exist in lesions at different locations.

Accurate assessment of the clinical staging is crucial for determining the need for radical prostatectomy (RP) in prostate cancer (PCa). However, the current methods for PCa staging may yield incorrect results. This study aimed to comprehensively analyze independent predictors of postoperative upstaging of intraprostatic cancer. We conducted a retrospective analysis of data from intraprostatic cancer patients who underwent radical surgery between March 2019 and December 2022. Intraprostatic cancer was defined as a lesion confined to the prostate, excluding cases where multiparameter magnetic resonance imaging (mpMRI) showed the lesion in contact with the prostatic capsule. We assessed independent predictors of extraprostatic extension (EPE) and analyzed their association with positive surgical margin (PSM) status. In addition, based on the distance of the lesion from the capsule on mpMRI, we divided the patients into non-transition zone and transition zone groups for further analysis. A total of 500 patients were included in our study. Logistic regression analysis revealed that biopsy Gleason grade group (GG) (odds ratio, OR: 1.370, 95% confidence interval, CI: 1.093-1.718) and perineural invasion (PNI) (OR: 2.746, 95% CI: 1.420-5.309) were predictive factors for postoperative EPE. Both biopsy GG and PNI were associated with lateral (GG: OR: 1.270, 95% CI: 1.074-1.501; PNI: OR: 2.733, 95% CI: 1.521-4.911) and basal (GG: OR: 1.491, 95% CI: 1.194-1.862; PNI: OR: 3.730, 95% CI: 1.929-7.214) PSM but not with apex PSM (GG: OR: 1.176, 95% CI: 0.989-1.399; PNI: OR: 1.204, 95% CI: 0.609-2.381) after RP. Finally, PNI was an independent predictor of EPE in the transition zone (OR: 11.235, 95% CI: 2.779-45.428) but not in the non-transition zone (OR: 1.942, 95% CI: 0.920-4.098). PNI and higher GG may indicate upstaging of tumors in patients with intraprostatic carcinoma. These two factors are associated with PSM in locations other than the apex of the prostate. Importantly, cancer in the transition zone of the prostate is more likely to spread externally through nerve invasion than cancer in the non-transition zone.

Impact of Multiparametric Magnetic Resonance Imaging for the Prediction of Extraprostatic Extension According to the National Comprehensive Cancer Network Risk Stratification in Prostate Cancer

Purpose: The accuracy of extraprostatic extension (EPE) on multiparametric magnetic resonance imaging (mpMRI) for the preoperative staging of prostate cancer (PCa) remains controversial. This study aimed to determine the effect of mpMRI for EPE prediction in the final pathology after radical prostatectomy (RP) according to the National Comprehensive Cancer Network (NCCN) risk stratification in patients with clinically localized PCa.Materials and Methods: This retrospective study analyzed 340 consecutive patients diagnosed with clinically localized PCa who underwent RP with preoperative mpMRI between March 2020 and December 2021. They were stratified according to the NCCN risk stratification into low (LR), favorable intermediate (FIR), unfavorable intermediate (UIR), and high risk (HR) groups to assess final pathological EPE. The accuracy of staging mpMRI was assessed in each group. Univariate and multivariate analyses evaluated the predictors of EPE in the final pathology after RP.Results: Preoperative mpMRI showed suspicious EPE in 87 patients (25.6%), whereas postoperative pathological evaluation revealed EPE in 137 patients (40.3%). The LR group showed relatively low sensitivity and positive predictive value compared with other groups. In the multivariate analysis, suspicious EPE on mpMRI was a significant predictive factor for EPE in the final pathology in the FIR, UIR, and HR groups (p=0.012, p=0.011, and p=0.001, respectively), whereas no correlation was observed in the LR group (p=0.711).Conclusions: A strong correlation was observed between suspicious EPE on mpMRI and EPE in the final pathology in the FIR, UIR, and HR groups but not in the LR group.

MR image quality in local staging of prostate cancer: Role of PI-QUAL in the detection of extraprostatic extension

PurposeTo assess the impact of prostate MRI image quality by means of the Prostate Imaging Quality (PI-QUAL) score, on the identification of extraprostatic extension of disease (EPE), predicted using the EPE Grade Score, Likert Scale Score (LSS) and a clinical nomogram (MSKCCn). MethodsWe retrospectively included 105 patients with multiparametric prostate MRI prior to prostatectomy. Two radiologists evaluated image quality using PI-QUAL (≥4 was considered high quality) in consensus. All cases were also scored using the EPE Grade, the LSS, and the MSKCCn (dichotomized). Inter-rater reproducibility for each score was also assessed. Accuracy was calculated for the entire population and by image quality, considering two thresholds for EPE Grade (≥2 and = 3) and LSS (≥3 and ≥ 4) and using McNemar’s test for comparison. ResultsOverall, 66 scans achieved high quality. The accuracy of EPE Grade ranged from 0.695 to 0.743, while LSS achieved values between 0.705 and 0.733. Overall sensitivity for the radiological scores (range = 0.235–0.529) was low irrespective of the PI-QUAL score, while specificity was higher (0.775–0.986). The MSKCCn achieved an AUC of 0.76, outperforming EPE Grade (=3 threshold) in studies with suboptimal image quality (0.821 vs 0.564, p = 0.016). EPE Grade (=3 threshold) accuracy was also better in high image quality studies (0.849 vs 0.564, p = 0.001). Reproducibility was good to excellent overall (95 % Confidence Interval range = 0.782–0.924). ConclusionAssessing image quality by means of PI-QUAL is helpful in the evaluation of EPE, as a scan of low quality makes its performance drop compared to clinical staging tools.

Unravelling the Role of P300 and TMPRSS2 in Prostate Cancer: A Literature Review.

Prostate cancer is one of the most common malignant diseases in men, and it contributes significantly to the increased mortality rate in men worldwide. This study aimed to review the roles of p300 and TMPRSS2 (transmembrane protease, serine 2) in the AR (androgen receptor) pathway as they are closely related to the development and progression of prostate cancer. This paper represents a library-based study conducted by selecting the most suitable, up-to-date scientific published articles from online journals. We focused on articles that use similar techniques, particularly those that use prostate cancer cell lines and immunohistochemical staining to study the molecular impact of p300 and TMPRSS2 in prostate cancer specimens. The TMPRSS2:ERG fusion is considered relevant to prostate cancer, but its association with the development and progression as well as its clinical significance have not been fully elucidated. On the other hand, high p300 levels in prostate cancer biopsies predict larger tumor volumes, extraprostatic extension of disease, and seminal vesicle involvement at prostatectomy, and may be associated with prostate cancer progression after surgery. The inhibition of p300 has been shown to reduce the proliferation of prostate cancer cells with TMPRSS2:ETS (E26 transformation-specific) fusions, and combining p300 inhibitors with other targeted therapies may increase their efficacy. Overall, the interplay between the p300 and TMPRSS2 pathways is an active area of research.

Association of quantifiable prostate MRI parameters with any and large cribriform pattern in prostate cancer patients undergoing radical prostatectomy

PurposeCribriform pattern has recently been recognized as an important independent risk factor for prostate cancer (PCa) outcome. This study aimed to identify the association of quantifiable prostate magnetic resonance imaging (MRI) parameters with any and large cribriform pattern at radical prostatectomy (RP) specimens. MethodsPreoperative prostate MRI’s from 188 men undergoing RP between 2010 and 2018 were retrospectively acquired. RP specimens of the patients were revised for Gleason score (GS), and presence of any and large cribriform pattern. MRI parameters such as MRI visibility, PI-RADS score, lowest apparent diffusion coefficient (ADC) value, lesion size, and radiologic extra-prostatic extension (EPE) were reviewed. The association of prostate MRI parameters for presence of any and large cribriform pattern at RP was analysed using logistic regression. Results116/188 (61.7%) PCa patients had any cribriform and 36/188 (19.1%) large cribriform pattern at RP. 171/188 (91.0%) men had MRI-visible lesions; 111/116 (95.7%) tumours with any and 36/36 (100%) with large cribriform pattern were visible at MRI. PCa with any and large cribriform pattern both had lower ADC values than those without (p < 0.001). In adjusted analysis, lowest ADC value was as an independent predictor for any cribriform (Odds Ratio (OR) 0.2, 95% Confidence Interval (CI) 0.1–0.8; p = 0.01) and large cribriform pattern (OR 0.2, 95% CI 0.1–0.7; p = 0.01), while other parameters were not. ConclusionsThe majority of PCa with cribriform pattern at RP were visible at MRI, and lowest ADC value was an independent predictor for both any and large cribriform pattern.

Redefining 18F DCFPyl PSMA-PET detected local recurrence from radical prostatectomy histopathology.

18F-DCFPyL PET localises tumour recurrence in patients with biochemical recurrence post-radical prostatectomy. Correlations exist between disease recurrence and poor histopathological parameters such as the presence of extra prostatic extension (EPE) and positive surgical margins. We aim to assess topographic concordance between these histopathological features and the location of the PSMA PET local recurrences, qualitatively and quantitatively. Our cohort was selected from the 100 men who received a 18F-DCFPyL PET scan through IMPPORT trial, a prospective non-randomised study completed by GenesisCare Victoria. Eligibility included patients with a rising PSA (>0.2 ng/mL) post radical prostatectomy and PSMA PET detected local recurrence. Histopathological parameters collated included the location of tumour, EPE and positive margins. Criteria for the location and 'concordance' between histopathological features and local recurrences were predefined. 24 patients were eligible, median age was 71 years old, median PSA 0.37ng/ml and time between prostatectomy and PSMA PET was 2.6 years. 15 patients had recurrences within the vesicourethral anastomotic region and 9 within the lateral surgical margins. 100% concordance in the left to right plane between tumour location and local recurrence was found, with 79% of these lesions concordant three-dimensionally; across cranio-caudal, left-right and anterior-posterior planes. 10/16 (63%) patients' with EPE and 5/9 (55.5%) of patients' with positive margins had three-dimensional concordance between their pathology and their local recurrence. In quantitative assessment, 17 of the 24 patients, had local recurrences that correlated with the location of their original tumour in the cranio-caudal plane. Local recurrence is highly concordant with the position of the tumour within the prostate. Predicting the location of local recurrence using the location of the EPE and positive margins is less helpful. Further investigation into this field, could impact surgical technique and salvage radiotherapy clinical target volume.

Quality assessment of prostate MRI by PI-QUAL score: Inter-reader agreement and impact on prostate cancer local staging at 3 Tesla

PurposeTo evaluate whether the Prostate Imaging Quality (PI-QUAL) score impacts prostate cancer (PCa) staging on MRI. The secondary goal was to test inter-reader agreement among radiologists experienced in prostate imaging. MethodA retrospective, single-center study with patients who underwent 3 Tesla prostate MRI scans and were submitted to radical prostatectomy (RP) between January 2018 and November 2021 and were eligible for our study. Extraprostatic extension (EPE) data were collected from original MR reports (EPEm) and pathological reports of RP specimens (EPEp). Three expert prostate radiologists (ESUR/ESUI criteria R1, R2, R3) independently evaluated all MRI exams according to PI-QUAL score for image quality (1 to 5; 1: poor, 5: excellent), blinded to original imaging reports and clinical data. We studied the diagnostic performance of MRI using pooled data from PI-QUAL scores (≤3 vs. ≥4). We also performed univariate and multivariate analyses to assess the PI-QUAL score impact on local PCa staging. Cohen’s K and Tau-b Kendall tests were used to assess the inter-reader agreement for PI-QUAL score, T2WI, DWI, and DCE. ResultsOur final cohort included 146 patients, of which 27.4% presented EPE on pathology. We observed no impact of imaging quality on accuracy for EPE prediction: AUC of 0.750 (95% CI 0.26-1) for PI-QUAL ≤ 3 and 0.705 (95% CI 0.618–0.793) for PI-QUAL ≥ 4. The multivariate analysis demonstrated a correlation of EPEm (OR 3.25, p 0.001) and ISUP grade group (OR 1.89, p 0.012) to predict EPEp. The inter-reader agreement was moderate to substantial (0.539 for R1-R2, 0.522 for R2-R3, and 0.694 for R1-R3). ConclusionOur clinical impact evaluation showed no direct correlation between MRI quality by PI-QUAL score and accuracy in detecting EPE in patients undergoing RP. Additionally, we had moderate to a substantial inter-reader agreement for the PI-QUAL score.