Radiotherapy Versus Partial Penectomy for T1 Squamous Cell Carcinoma of the Penis.

BACKGROUND: Radiotherapy (RT) represents an alternative treatment option for patients with T1 squamous cell carcinoma of the penis (SCCP), with proven feasibility and tolerability. However, it has never been directly compared with partial penectomy (PP) using cancer-specific mortality (CSM) as an end point. METHODS: In the Surveillance, Epidemiology, and End Results database (2000-2020), T1N0M0 SCCP patients treated with RT or PP were identified. This study relied on 1:4 propensity score-matching (PSM) for age at diagnosis, tumor stage, and tumor grade. Subsequently, cumulative incidence plots as well as multivariable competing risks regression (CRR) models addressed CSM. Additionally, the study accounted for the confounding effect of other-cause mortality (OCM). RESULTS: Of 895 patients with T1N0M0 SCCP, 55 (6.1%) underwent RT and 840 (93.9%) underwent PP. The RT and PP patients had a similar age distribution (median age, 70 vs 70 years) and more frequently harbored grade I or II tumors (67.3% vs 75.8%) as well as T1a-stage disease (67.3% vs 74.3%). After 1:4 PSM, 55 (100%) of the 55 RT patients versus 220 (26.2%) of the 840 PP patients were included in the study. The 10-year CSM derived from the cumulative incidence plots was 25.4% for RT and 14.4% for PP. In the multivariable CRR models, RT independently predicted a higher CSM than PP (hazard ratio, 1.99; 95% confidence interval, 1.05-3.80; p = 0.04). CONCLUSION: For the T1N0M0 SCCP patients treated in the community, RT was associated with nearly a twofold higher CSM than PP. Ideally, a validation study based on tertiary care institution data should be conducted to test whether this CSM disadvantage is operational only in the community or not.

First-in-human validation of a DROP-IN ß-probe for robotic radioguided surgery: defining optimal signal-to-background discrimination algorithm.

PURPOSE: In radioguided surgery (RGS), radiopharmaceuticals are used to generate preoperative roadmaps (e.g., PET/CT) and to facilitate intraoperative tracing of tracer avid lesions. Within RGS, there is a push toward the use of receptor-targeted radiopharmaceuticals, a trend that also has to align with the surgical move toward minimal invasive robotic surgery. Building on our initial ex vivo evaluation, this study investigates the clinical translation of a DROP-IN ß probe in robotic PSMA-guided prostate cancer surgery. METHODS: A clinical-grade DROP-IN ß probe was developed to support the detection of PET radioisotopes (e.g., 68 Ga). The prototype was evaluated in 7 primary prostate cancer patients, having at least 1 lymph node metastases visible on PSMA-PET. Patients were scheduled for radical prostatectomy combined with extended pelvic lymph node dissection. At the beginning of surgery, patients were injected with 1.1 MBq/kg of [68Ga]Ga-PSMA. The ß probe was used to trace PSMA-expressing lymph nodes in vivo. To support intraoperative decision-making, a statistical software algorithm was defined and optimized on this dataset to help the surgeon discriminate between probe signals coming from tumors and healthy tissue. RESULTS: The DROP-IN ß probe helped provide the surgeon with autonomous and highly maneuverable tracer detection. A total of 66 samples (i.e., lymph node specimens) were analyzed in vivo, of which 31 (47%) were found to be malignant. After optimization of the signal cutoff algorithm, we found a probe detection rate of 78% of the PSMA-PET-positive samples, a sensitivity of 76%, and a specificity of 93%, as compared to pathologic evaluation. CONCLUSION: This study shows the first-in-human use of a DROP-IN ß probe, supporting the integration of ß radio guidance and robotic surgery. The achieved competitive sensitivity and specificity help open the world of robotic RGS to a whole new range of radiopharmaceuticals.

Evaluation of margins during radical prostatectomy: confocal microscopy vs frozen section analysis.

OBJECTIVES: To test the performance of ex vivo fluorescence confocal microscopy (FCM; Vivascope 2500M-G4), as compared to intra-operative frozen section (IFS) analysis, to evaluate surgical margins during robot-assisted radical prostatectomy (RARP), with final pathology as the reference standard. METHODS: Overall, 54 margins in 45 patients treated with RARP were analysed with: (1) ex vivo FCM; (2) IFS analysis; and (3) final pathology. FCM margins were evaluated by two different pathologists (experienced [M.I.: 10 years] vs highly experienced [G.R.: >30 years]) as strongly negative, probably negative, doubtful, probably positive, or strongly positive. First, inter-observer agreement (Cohen's κ) between pathologists was tested. Second, we reported the sensitivity, specificity, positive predictive (PPV) and negative predictive value (NPV) of ex vivo FCM. Finally, agreement between ex vivo FCM and IFS analysis (Cohen's κ) was reported. For all analyses, four combinations of FCM results were evaluated. RESULTS: At ex vivo FCM, the inter-observer agreement between pathologists ranged from moderate (κ = 0.74) to almost perfect (κ = 0.90), according to the four categories of results. Indeed, at ex vivo FCM, the highly experienced pathologist reached the best balance between sensitivity (70.5%) specificity (91.8%), PPV (80.0%) and NPV (87.1%). Conversely, on IFS analysis, the sensitivity, specificity, PPV and NPV were, respectively, 88.2% vs 100% vs 100% vs 94.8%. The agreement between the ex vivo FCM and IFS analyses ranged from moderate (κ = 0.62) to strong (κ = 0.86), according to the four categories of results. CONCLUSION: Evaluation of prostate margins at ex vivo FCM appears to be feasible and reliable. The agreement between readers encourages its widespread use in daily practice. Nevertheless, as of today, the performance of FCM seems to be sub-par when compared to the established standard of care (IFS analysis).

Extreme-hypofractionated RT with concomitant boost to the DIL in PCa: a 5-year update on oncological and patient-reported outcomes for the phase II trial "GIVE ME FIVE".

AIM: The present work reports updated oncological results and patients-reported outcomes at 5 years of phase II trial "Short-term high precision RT for early prostate cancer with SIB to the dominant intraprostatic lesion (DIL) for patients with early-stage PCa". METHODS: Data from patients enrolled within AIRC IG-13218 (NCT01913717) trial were analyzed. Clinical and GU/GI toxicity assessment and PSA measurements were performed every 3 months for at least 2 years after RT end. QoL of enrolled patients was assessed by IPSS, EORTC QLQ-C30, EORTC QLQ-PR25, and IIEF-5. Patients' score changes were calculated at the end of RT and at 1, 12, and 60 months after RT. RESULTS: A total of 65 patients were included. At a median follow-up of 5 years, OS resulted 86%. Biochemical and clinical progression-free survival at 5 years were 95%. The median PSA at baseline was 6.07 ng/ml, while at last follow-up resulted 0.25 ng/ml. IPSS showed a statistically significant variation in urinary function from baseline (p = 0.002), with the most relevant deterioration 1 month after RT, with a recovery toward baseline at 12 months (p ≤ 0.0001). A numerical improvement in QoL according to the EORTC QLQ-C30 has been reported although not statistically significant. No change in sexual activity was recorded after RT. CONCLUSIONS: The study confirms that extreme hypofractionation with a DIL boost is safe and effective, with no severe effects on the QoL. The increasing dose to the DIL does not worsen the RT toxicity, thus opening the possibility of an even more escalated treatment.

Survival benefit of nephroureterectomy in systemic therapy exposed metastatic upper tract urinary urothelial carcinoma patients.

BACKGROUND: It is unknown whether the stage of the primary may influence the survival (OS) of metastatic upper tract urothelial carcinoma (mUTUC) patients treated with nephroureterectomy (NU) and systemic therapy (ST). We tested this hypothesis within a large-scale North American cohort. METHODS: Within Surveillance Epidemiology and End Results database 2000-2020, all mUTUC patients treated with ST+NU or with ST alone were identified. Kaplan-Maier plots depicted OS. Multivariable Cox regression (MCR) models tested for differences between ST+NU and ST alone predicting overall mortality (OM). All analyses were performed in localized (T1-T2) and then repeated in locally advanced (T3-T4) patients. RESULTS: Of all 728 mUTUC patients, 187 (26%) harbored T1-T2 vs 541 (74%) harbored T3-T4. In T1-T2 patients, the median OS was 20 months in ST+NU vs 10 months in ST alone. Moreover, in MCR analyses that also relied on 3 months' landmark analyses, the combination of ST+NU independently predicted lower OM (HR 0.37, p < 0.001). Conversely, in T3-T4 patients, the median OS was 12 in ST+NU vs 10 months in ST alone. Moreover, in MCR analyses that also relied on 3 months' landmark analyses, the combination of ST+NU was not independently associated with lower OM (HR 0.85, p = 0.1). CONCLUSIONS: In mUTUC patients, treated with ST, NU drastically improved survival in T1-T2 patients, even after strict methodological adjustments (multivariable and landmark analyses). However, this survival benefit did not apply to patients with locally more advanced disease (T3-T4).

Can we predict pathology without surgery? Weighing the added value of multiparametric MRI and whole prostate radiomics in integrative machine learning models.

OBJECTIVE: To test the ability of high-performance machine learning (ML) models employing clinical, radiological, and radiomic variables to improve non-invasive prediction of the pathological status of prostate cancer (PCa) in a large, single-institution cohort. METHODS: Patients who underwent multiparametric MRI and prostatectomy in our institution in 2015-2018 were considered; a total of 949 patients were included. Gradient-boosted decision tree models were separately trained using clinical features alone and in combination with radiological reporting and/or prostate radiomic features to predict pathological T, pathological N, ISUP score, and their change from preclinical assessment. Model behavior was analyzed in terms of performance, feature importance, Shapley additive explanation (SHAP) values, and mean absolute error (MAE). The best model was compared against a naïve model mimicking clinical workflow. RESULTS: The model including all variables was the best performing (AUC values ranging from 0.73 to 0.96 for the six endpoints). Radiomic features brought a small yet measurable boost in performance, with the SHAP values indicating that their contribution can be critical to successful prediction of endpoints for individual patients. MAEs were lower for low-risk patients, suggesting that the models find them easier to classify. The best model outperformed (p ≤ 0.0001) clinical baseline, resulting in significantly fewer false negative predictions and overall was less prone to under-staging. CONCLUSIONS: Our results highlight the potential benefit of integrative ML models for pathological status prediction in PCa. Additional studies regarding clinical integration of such models can provide valuable information for personalizing therapy offering a tool to improve non-invasive prediction of pathological status. CLINICAL RELEVANCE STATEMENT: The best machine learning model was less prone to under-staging of the disease. The improved accuracy of our pathological prediction models could constitute an asset to the clinical workflow by providing clinicians with accurate pathological predictions prior to treatment. KEY POINTS: • Currently, the most common strategies for pre-surgical stratification of prostate cancer (PCa) patients have shown to have suboptimal performances. • The addition of radiological features to the clinical features gave a considerable boost in model performance. Our best model outperforms the naïve model, avoiding under-staging and resulting in a critical advantage in the clinic. •Machine learning models incorporating clinical, radiological, and radiomics features significantly improved accuracy of pathological prediction in prostate cancer, possibly constituting an asset to the clinical workflow.

Contemporary conditional cancer-specific survival rates in surgically treated nonmetastatic primary urethral carcinoma.

BACKGROUND: We examined the effect of disease-free interval (DFI) duration on cancer-specific mortality (CSM)-free survival, otherwise known as the effect of conditional survival, in radical urethrectomy nonmetastatic primary urethral carcinoma (PUC) patients. METHODS: Using the Surveillance, Epidemiology, and End Results (SEER) database 2000-2020, patient (age, sex, race/ethnicity, and marital status) and tumor (stage and histology) characteristics, as well as systemic therapy exposure status of nonmetastatic PUC patients were tabulated. Conditional survival estimates at 5-year were assessed based on DFI duration and according to stage at presentation (T1 -2N0 vs. T3-4N0-2). RESULTS: Of all 512 radical urethrectomy PUC patients, 278 (54%) harbored T1-2N0 stage versus 234 (46%) harbored T3-4N0-2 stage. In 512 PUC patients, 5-year CSM-free survival at initial diagnosis was 61.8%. Provided a DFI duration of 36 months, 5-year CSM-free survival was 85.6%. In 278 T1-2N0 PUC patients, 5-year CSM-free survival at initial diagnosis was 68.4%. Provided a DFI duration of 36 months, 5-year CSM-free survival was 86.9%. In 234 T3-4N0-2 PUC patients, 5-year CSM-free survival at initial diagnosis was 53.8%. Provided a DFI duration of 36 months, 5-year CSM-free survival was 83.6%. CONCLUSIONS: Although intuitively, clinicians and patients are well aware of the concept that increasing DFI duration improves survival probability, only a few clinicians can accurately estimate the magnitude of survival improvement, as was done within the current study. Such information is crucial to survivors, especially in those diagnosed with rare malignancies, where the survival estimation according to DFI duration is even more challenging.

Survival of stage III non-seminoma testis cancer patients versus simulated controls, according to race/ethnicity.

BACKGROUND: It is unknown whether 5-year overall survival (OS) differs and to what extent between the American Joint Committee on Cancer stage III non-seminoma testicular germ cell tumor (NS-TGCT) patients and simulated age-matched male population-based controls, according to race/ethnicity groups. METHODS: We identified newly diagnosed (2004-2014) stage III NS-TGCT patients within the Surveillance Epidemiology and End Results database 2004-2019. For each case, we simulated an age-matched male control (Monte Carlo simulation), relying on Social Security Administration (SSA) Life Tables with 5 years of follow-up. We compared OS rates between stage III NS-TGCT patients and simulated age-matched male population-based controls, according to race/ethnicity groups (Caucasian, Hispanic, Asian/Pacific Islander and African American). Both, cancer-specific mortality (CSM) and other-cause mortality (OCM) were computed. RESULTS: Of 2054 stage III NS-TGCT patients, 60% were Caucasians versus 33% Hispanics versus 4% Asians/Pacific Islanders versus 3% African Americans. The 5-year OS difference between stage III NS-TGCT patients versus simulated age-matched male population-based controls was highest in Asians/Pacific Islanders (64 vs. 99%, Δ = 35%), followed by African Americans (66 vs. 97%, Δ = 31%), Hispanics (72 vs. 99%, Δ = 27%), and Caucasians (76 vs. 98%, Δ = 22%). The 5-year CSM rate was highest in Asians/Pacific Islanders (32%), followed by African Americans (26%), Hispanics (25%), and Caucasians (20%). The 5-year OCM rate was highest in African Americans (8%), followed by Caucasians (4%), Asians/Pacific Islanders (4%), and Hispanics (2%). CONCLUSION: Relative to SSA Life Tables, the highest 5-year OS disadvantage applied to stage III NS-TGCT Asian/Pacific Islander race/ethnicity group, followed by African American, Hispanic and Caucasian, in that order.

Association between mpMRI detected tumor apparent diffusion coefficient and 5-year biochemical recurrence risk after radical prostatectomy.

PURPOSE: To assess the ability of tumor apparent diffusion coefficient (ADC) values obtained from multiparametric magnetic resonance imaging (mpMRI) to predict the risk of 5-year biochemical recurrence (BCR) after radical prostatectomy (RP). MATERIALS AND METHODS: This retrospective analysis included 1207 peripheral and 232 non-peripheral zone prostate cancer (PCa) patients who underwent mpMRI before RP (2012-2015), with the outcome of interest being 5-year BCR. ADC was evaluated as a continuous variable and as categories: low (< 850 µm2/s), intermediate (850-1100 µm2/s), and high (> 1100 µm2/s). Kaplan-Meier curves with log-rank testing of BCR-free survival, multivariable Cox proportional hazard regression models were formed to estimate the risk of BCR. RESULTS: Among the 1439 males with median age 63 (± 7) years, the median follow-up was 59 months, and 306 (25%) patients experienced BCR. Peripheral zone PCa patients with BCR had lower tumor ADC values than those without BCR (874 versus 1025 µm2/s, p < 0.001). Five-year BCR-free survival rates were 52.3%, 74.4%, and 87% for patients in the low, intermediate, and high ADC value categories, respectively (p < 0.0001). Lower ADC was associated with BCR, both as continuously coded variable (HR: 5.35; p < 0.001) and as ADC categories (intermediate versus high ADC-HR: 1.56, p = 0.017; low vs. high ADC-HR; 2.36, p < 0.001). In the non-peripheral zone PCa patients, no association between ADC and BCR was observed. CONCLUSION: Tumor ADC values and categories were found to be predictive of the 5-year BCR risk after RP in patients with peripheral zone PCa and may serve as a prognostic biomarker.

Multiparametric MRI-based 5-year Risk Prediction Model for Biochemical Recurrence of Prostate Cancer after Radical Prostatectomy.

Background Current predictive tools to estimate the risk of biochemical recurrence (BCR) after treatment of prostate cancer do not consider multiparametric MRI (mpMRI) information. Purpose To develop a risk prediction tool that considers mpMRI findings to assess the risk of 5-year BCR after radical prostatectomy. Materials and Methods In this retrospective single-center analysis in 1459 patients with prostate cancer who underwent mpMRI before radical prostatectomy (in 2012-2015), the outcome of interest was 5-year BCR (two consecutive prostate-specific antigen [PSA] levels > 0.2 ng/mL [0.2 µg/L]). Patients were randomly divided into training (70%) and test (30%) sets. Kaplan-Meier plots were applied to the training set to estimate survival probabilities. Multivariable Cox regression models were used to test the relationship between BCR and different sets of exploratory variables. The C-index of the final model was calculated for the training and test sets and was compared with European Association of Urology, University of California San Francisco Cancer of the Prostate Risk Assessment, Memorial Sloan-Kettering Cancer Center, and Partin risk tools using the partial likelihood ratio test. Five risk categories were created. Results The median duration of follow-up in the whole cohort was 59 months (IQR, 32-81 months); 376 of 1459 (25.8%) patients had BCR. A multivariable Cox regression model (referred to as PIPEN, and composed of PSA density, International Society of Urological Pathology grade group, Prostate Imaging Reporting and Data System category, European Society of Urogenital Radiology extraprostatic extension score, nodes) fitted to the training data yielded a C-index of 0.74, superior to that of other predictive tools (C-index 0.70 for all models; P ≤ .01) and a median higher C-index on 500 test set replications (C-index, 0.73). Five PIPEN risk categories were identified with 5-year BCR-free survival rates of 92%, 84%, 71%, 56%, and 26% in very low-, low-, intermediate-, high-, and very high-risk patients, respectively (all P < .001). Conclusion A five-item model for predicting the risk of 5-year BCR after radical prostatectomy for prostate cancer was developed and internally verified, and five risk categories were identified. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Aguirre and Ortegón in this issue.

External validation of the computerized analysis of TRUS of the prostate with the ANNA/C-TRUS system: a potential role of artificial intelligence for improving prostate cancer detection.

PURPOSE: Prostate cancer (PCa) imaging has been revolutionized by the introduction of multi-parametric Magnetic Resonance Imaging (mpMRI). Transrectal ultrasound (TRUS) has always been considered a low-performance modality. To overcome this, a computerized artificial neural network analysis (ANNA/C-TRUS) of the TRUS based on an artificial intelligence (AI) analysis has been proposed. Our aim was to evaluate the diagnostic performance of the ANNA/C-TRUS system and its ability to improve conventional TRUS in PCa diagnosis. METHODS: We retrospectively analyzed data from 64 patients with PCa and scheduled for radical prostatectomy who underwent TRUS followed by ANNA/C-TRUS analysis before the procedure. The results of ANNA/C-TRUS analysis with whole mount sections from final pathology. RESULTS: On a per-sectors analysis, sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV) and accuracy were 62%, 81%, 80%, 64% and 78% respectively. The values for the detection of clinically significant prostate cancer were 69%, 77%, 88%, 50% and 75%. The diagnostic values for high grade tumours were 70%, 74%, 91%, 41% and 74%, respectively. Cancer volume (≤ 0.5 or greater) did not influence the diagnostic performance of the ANNA/C-TRUS system. CONCLUSIONS: ANNA/C-TRUS represents a promising diagnostic tool and application of AI for PCa diagnosis. It improves the ability of conventional TRUS to diagnose prostate cancer, preserving its simplicity and availability. Since it is an AI system, it does not hold the inter-observer variability nor a learning curve. Multicenter biopsy-based studies with the inclusion of an adequate number of patients are needed to confirm these results.

Diagnosis of prostate cancer with magnetic resonance imaging in men treated with 5-alpha-reductase inhibitors.

PURPOSE: The primary aim of this study was to evaluate if exposure to 5-alpha-reductase inhibitors (5-ARIs) modifies the effect of MRI for the diagnosis of clinically significant Prostate Cancer (csPCa) (ISUP Gleason grade ≥ 2). METHODS: This study is a multicenter cohort study including patients undergoing prostate biopsy and MRI at 24 institutions between 2013 and 2022. Multivariable analysis predicting csPCa with an interaction term between 5-ARIs and PIRADS score was performed. Sensitivity, specificity, and negative (NPV) and positive (PPV) predictive values of MRI were compared in treated and untreated patients. RESULTS: 705 patients (9%) were treated with 5-ARIs [median age 69 years, Interquartile range (IQR): 65, 73; median PSA 6.3 ng/ml, IQR 4.0, 9.0; median prostate volume 53 ml, IQR 40, 72] and 6913 were 5-ARIs naïve (age 66 years, IQR 60, 71; PSA 6.5 ng/ml, IQR 4.8, 9.0; prostate volume 50 ml, IQR 37, 65). MRI showed PIRADS 1-2, 3, 4, and 5 lesions in 141 (20%), 158 (22%), 258 (37%), and 148 (21%) patients treated with 5-ARIs, and 878 (13%), 1764 (25%), 2948 (43%), and 1323 (19%) of untreated patients (p < 0.0001). No difference was found in csPCa detection rates, but diagnosis of high-grade PCa (ISUP GG ≥ 3) was higher in treated patients (23% vs 19%, p = 0.013). We did not find any evidence of interaction between PIRADS score and 5-ARIs exposure in predicting csPCa. Sensitivity, specificity, PPV, and NPV of PIRADS ≥ 3 were 94%, 29%, 46%, and 88% in treated patients and 96%, 18%, 43%, and 88% in untreated patients, respectively. CONCLUSIONS: Exposure to 5-ARIs does not affect the association of PIRADS score with csPCa. Higher rates of high-grade PCa were detected in treated patients, but most were clearly visible on MRI as PIRADS 4 and 5 lesions. TRIAL REGISTRATION: The present study was registered at ClinicalTrials.gov number: NCT05078359.

Comparison of automated segmentation techniques for magnetic resonance images of the prostate.

BACKGROUND: Contouring of anatomical regions is a crucial step in the medical workflow and is both time-consuming and prone to intra- and inter-observer variability. This study compares different strategies for automatic segmentation of the prostate in T2-weighted MRIs. METHODS: This study included 100 patients diagnosed with prostate adenocarcinoma who had undergone multi-parametric MRI and prostatectomy. From the T2-weighted MR images, ground truth segmentation masks were established by consensus from two expert radiologists. The prostate was then automatically contoured with six different methods: (1) a multi-atlas algorithm, (2) a proprietary algorithm in the Syngo.Via medical imaging software, and four deep learning models: (3) a V-net trained from scratch, (4) a pre-trained 2D U-net, (5) a GAN extension of the 2D U-net, and (6) a segmentation-adapted EfficientDet architecture. The resulting segmentations were compared and scored against the ground truth masks with one 70/30 and one 50/50 train/test data split. We also analyzed the association between segmentation performance and clinical variables. RESULTS: The best performing method was the adapted EfficientDet (model 6), achieving a mean Dice coefficient of 0.914, a mean absolute volume difference of 5.9%, a mean surface distance (MSD) of 1.93 pixels, and a mean 95th percentile Hausdorff distance of 3.77 pixels. The deep learning models were less prone to serious errors (0.854 minimum Dice and 4.02 maximum MSD), and no significant relationship was found between segmentation performance and clinical variables. CONCLUSIONS: Deep learning-based segmentation techniques can consistently achieve Dice coefficients of 0.9 or above with as few as 50 training patients, regardless of architectural archetype. The atlas-based and Syngo.via methods found in commercial clinical software performed significantly worse (0.855[Formula: see text]0.887 Dice).

What is the best time for postoperative radiation therapy in pN1 prostate cancer?

We retrospectively compared long-term biochemical recurrence rates (BCR) in pN1 PCa patients that underwent adjuvant radiotherapy (aRT) vs. no aRT/early salvage (esRT) after robot-assisted radical prostatectomy and extended pelvic lymphadenectomy. All PCa pN1 M0 patients treated at a single high-volume center between 2010 and 2020 were analyzed. Patients with <10 LNs yield, or >10 positive LNs, or persistently detectable PSA after RARP were excluded. Kaplan-Meier (KM) plots depicted BCR rates. Multivariable Cox regression models (MCRMs) focused on predictors of BCR. The cumulative incidence plot depicted BCR rates after propensity score (PS) matching (ratio 1:1). 220 pN1 patients were enrolled, 133 (60.4%) treated with aRT and 87 (39.6%) with no-aRT/esRT. aRT patients were older, with higher rates of postoperative ISUP grade group 4-5, and higher rates of pT3b stage. The actuarial BCR was similar (aRT 39.8% vs. no-aRT/esRT 40.2%; p=1). Median time to BCR was 62 vs. 38 months in aRT vs. no-aRT/esRT patients (p=0.001). In MCRMs, patients managed with no-aRT/esRT were associated with higher rates of BCR over time (hazard ratio [HR]: 3.27, p<0.001). ISUP grade group 5 (HR: 2.18, p<0.01) was an independent predictor of BCR. In PS-matched cumulative incidence plots, the BCR rate was significantly higher in the aRT group (76.4 vs. 40.4%; p<0.01). Patients managed with no-aRT/esRT experienced BCR approximately two years before the aRT group. Despite, the important BCR benefit after aRT, this treatment strategy is underused in daily practice.

Radiogenomics in Renal Cancer Management-Current Evidence and Future Prospects.

Renal cancer management is challenging from diagnosis to treatment and follow-up. In cases of small renal masses and cystic lesions the differential diagnosis of benign or malignant tissues has potential pitfalls when imaging or even renal biopsy is applied. The recent artificial intelligence, imaging techniques, and genomics advancements have the ability to help clinicians set the stratification risk, treatment selection, follow-up strategy, and prognosis of the disease. The combination of radiomics features and genomics data has achieved good results but is currently limited by the retrospective design and the small number of patients included in clinical trials. The road ahead for radiogenomics is open to new, well-designed prospective studies, with large cohorts of patients required to validate previously obtained results and enter clinical practice.

Repeat MRI during active surveillance: natural history of prostatic lesions and upgrading rates.

OBJECTIVES: To assess upgrading rates in patients on active surveillance (AS) for prostate cancer (PCa) after serial multiparametric magnetic resonance imaging (mpMRI). METHODS: We conducted a retrospective analysis of 558 patients. Five different criteria for mpMRI progression were used: 1) a Prostate Imaging Reporting and Data System (PI-RADS) score increase; 2) a lesion size increase; 3) an extraprostatic extension score increase; 4) overall mpMRI progression; and 5) the number of criteria met for mpMRI progression (0 vs 1 vs 2-3). In addition, two definitions of PCa upgrading were evaluated: 1) International Society of Urological Pathology Grade Group (ISUP GG) ≥2 with >10% of pattern 4 and 2) ISUP GG ≥ 3. Estimated annual percent changes methodology was used to show the temporal trends of mpMRI progression criteria. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of mpMRI progression criteria were also analysed. Multivariable logistic regression models tested PCa upgrading rates. RESULTS: Lower rates over time for all mpMRI progression criteria were observed. The NPV of serial mpMRI scans ranged from 90.5% to 93.5% (ISUP GG≥2 with >10% of pattern 4 PCa upgrading) and from 98% to 99% (ISUP GG≥3 PCa upgrading), depending on the criteria used for mpMRI progression. A prostate-specific antigen density (PSAD) threshold of 0.15 ng/mL/mL was used to substratify those patients who would be able to skip a prostate biopsy. In multivariable logistic regression models assessing PCa upgrading rates, all five mpMRI progression criteria achieved independent predictor status. CONCLUSION: During AS, approximately 27% of patients experience mpMRI progression at first repeat MRI. However, the rates of mpMRI progression decrease over time at subsequent mpMRI scans. Patients with stable mpMRI findings and with PSAD < 0.15 ng/mL/mL could safely skip surveillance biopsies. Conversely, patients who experience mpMRI progression should undergo a prostate biopsy.

Association between previous negative biopsies and lower rates of progression during active surveillance for prostate cancer.

PURPOSE: To test any-cause discontinuation and ISUP GG upgrading rates during Active Surveillance (AS) in patients that underwent previous negative biopsies (PNBs) before prostate cancer (PCa) diagnosis vs. biopsy naive patients. METHODS: Retrospective analysis of 961 AS patients (2008-2020). Three definitions of PNBs were used: (1) PNBs status (biopsy naïve vs. PNBs); (2) number of PNBs (0 vs. 1 vs. ≥ 2); (3) histology at last PNB (no vs. negative vs. HGPIN/ASAP). Kaplan-Meier plots and multivariable Cox models tested any-cause and ISUP GG upgrading discontinuation rates. RESULTS: Overall, 760 (79.1%) vs. 201 (20.9%) patients were biopsy naïve vs. PNBs. Specifically, 760 (79.1%) vs. 138 (14.4%) vs. 63 (6.5%) patients had 0 vs. 1 vs. ≥ 2 PNBs. Last, 760 (79.1%) vs. 134 (13.9%) vs. 67 (7%) patients had no vs. negative PNB vs. HGPIN/ASAP. PNBs were not associated with any-cause discontinuation rates. Conversely, PNBs were associated with lower rates of ISUP GG upgrading: (1) PNBs vs. biopsy naïve (HR:0.6, p = 0.04); (2) 1 vs. 0 PNBs (HR:0.6, p = 0.1) and 2 vs. 0 PNBs, (HR:0.5, p = 0.1); (3) negative PNB vs. biopsy naïve (HR:0.7, p = 0.3) and HGPIN/ASAP vs. biopsy naïve (HR:0.4, p = 0.04). However, last PNB ≤ 18 months (HR:0.4, p = 0.02), but not last PNB > 18 months (HR:0.8, p = 0.5) were associated with lower rates of ISUP GG upgrading. CONCLUSION: PNBs status is associated with lower rates of ISUP GG upgrading during AS for PCa. The number of PNBs and time from last PNB to PCa diagnosis (≤ 18 months) appear also to be critical for patient selection.

Active surveillance for prostate cancer: comparison between incidental tumors vs. tumors diagnosed at prostate biopsies.

PURPOSE: To test discontinuation rates during Active Surveillance (AS) in patients diagnosed with incidental prostate cancers (IPCa) vs. tumors diagnosed at prostate biopsies (BxPCa). METHODS: Retrospective single center analysis of 961 vs. 121 BxPCa vs. IPCa patients (2008-2020). Kaplan-Meier plots and multivariable Cox regression models tested four different outcomes: (1) any-cause discontinuation; (2) discontinuation due to ISUP GG upgrading; (3) biopsy discontinuation due to ISUP GG upgrading or > 3 positive cores; (4) biopsy discontinuation or suspicious extraprostatic extension at surveillance mpMRI. Then, multivariable logistic regression models tested rates of clinically significant PCa (csPCa) (ISUP GG ≥ 3 or pT ≥ 3a or pN1) after radical prostatectomy (RP). RESULTS: Median time follow-up was 35 (19-64) months. IPCa patients were at lower risk of any-cause (3-year survival: 79.3 vs. 66%; HR: 0.5, p = 0.001) and biopsy/MRI AS discontinuation (3-year survival: 82.3 vs. 72.7%; HR: 0.5, p = 0.001), compared to BxPCa patients. Conversely, IPCa patients exhibited same rates of biopsy discontinuation and ISUP GG upgrading over time, relative to BxPCa. In multivariable logistic regression models, IPCa patients were associated with higher rates of csPCa at RP (OR: 1.4, p = 0.03), relative to their BxPCa counterparts. CONCLUSION: AS represents a safe management strategy for IPCa. Compared to BxPCa, IPCa patients are less prone to experience any-cause and biopsy/MRI AS discontinuation. However, the two mentioned groups present similar rates of biopsy discontinuation and ISUP GG upgrading over time. In consequence, tailored AS protocols with scheduled repeated surveillance biopsies should be offered to all newly diagnosed IPCa patients.

Correlation between radiological and biological features and clinical outcomes in early prostate cancer: an exploratory subgroup analysis.

PTEN deletion and Ki-67 expression are two of the most promising biomarkers in prostate cancer (PCa). In the same manner, multiparametric magnetic resonance imaging (mp-MRI) guided core biopsy is a powerful tool for PCa detection and staging. The aim of the study is to assess whether a correlation can be identified between the pathological stage defined by an mp-MRI-guided core biopsy and Ki-67 expression and PTEN deletion. Such correlation might be useful for staging and treatment personalization in PCa. This investigation was conducted in the context of phase II clinical study "Short-term radiotherapy for early prostate cancer with a concomitant boost to the dominant lesion" (AIRC IG-13218), ClinicalTrials.gov identifier: NCT01913717. Nineteen patients underwent a further in-bore MRI-targeted core biopsy (MRI-TBx) on the dominant intraprostatic lesion (DIL); on this basis, an additional Gleason Score (GS) was determined. PTEN loss and Ki-67 expression on these samples were analyzed and correlated with both risk categories modifications and oncological outcomes (overall survival, biochemical and clinical relapse). GS was upgraded in 5 cases, with 4 patients re-classified as intermediate-risk and 1 patient as high-risk. The latter experienced a clinical local relapse. No correlations between up/down-staging, PTEN deletion, and Ki-67 expression were observed in this cohort. Further investigations are needed towards the identification of a pattern in the tumor aggressiveness-response in PCa treated with ultra-hypofractionated radiotherapy. Moreover, a possible relationship between biomarker analysis and imaging textural features could be explored.

Increased Body Mass Index Is a Risk Factor for Poor Clinical Outcomes after Radical Prostatectomy in Men with International Society of Urological Pathology Grade Group 1 Prostate Cancer Diagnosed with Systematic Biopsies.

INTRODUCTION: The association between obesity and clinically significant prostate cancer (PCa) is still a matter of debate. In this study, we evaluated the effect of body mass index (BMI) on the prediction of pathological unfavorable disease (UD), positive surgical margins (PSMs), and biochemical recurrence (BCR) in patients with clinically localized (≤cT2c) International Society of Urological Pathology (ISUP) grade group 1 PCa at biopsy. METHODS: 427 patients with ISUP grade group 1 PCa who have undergone radical prostatectomy and BMI evaluation were included. The outcome of interest was the presence of UD (defined as ISUP grade group ≥3 and pT ≥3a), PSM, and BCR. RESULTS: Statistically significant differences resulted in comparing BMI with prostate-specific antigen (PSA) and serum testosterone levels (both p < 0.0001). Patients with UD and PSM had higher BMI values (p < 0.0001 and p = 0.006, respectively). BCR-free survival was significantly decreased in patients with higher BMI values (p < 0.0001). BMI was an independent risk factor for BCR and PSM. Receiver-operating characteristic analysis testing PSA accuracy in different BMI groups, showed that PSA had a reduced predictive value (area under the curve [AUC] = 0.535; 95% confidence interval [CI] = 0.422-0.646), in obese men compared to overweight (AUC = 0.664; 95% CI = 0.598-0.725) and normal weight patients (AUC = 0.721; 95% CI = 0.660-0.777). CONCLUSION: Our findings show that increased BMI is a significant predictor of UD and PSM at RP in patients with preoperative low-to intermediate-risk diseases, suggesting that BMI evaluation may be useful in a clinical setting to identify patients with favorable preoperative disease characteristics harboring high-risk PCa.