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Background: In patients treated with partial nephrectomy, prior evidence showed that peri-operative outcomes, such as complications and ischemia time, improved as a function of the surgical experience of the surgeon, but data on functional outcomes after surgery are still scarce. Methods: We retrospectively analyzed data of 4011 patients with a single, unilateral cT1a-b renal mass treated with laparoscopic or robot-assisted partial nephrectomy. The operations were performed by 119 surgeons at 22 participating institutions between 1997 and 2022. Multivariable models investigated the association between surgical experience (number of prior operations) and acute kidney injury (AKI) and recovery of at least 90% of baseline estimated glomerular filtration rate (eGFR) 1 yr after partial nephrectomy. The adjustment for case mix included age, Body Mass Index, preoperative serum creatinine, clinical T stage, PADUA score, warm ischemia time, pathologic tumor size, and year of surgery. Results: A total of 753 (19%) and 3258 (81%) patients underwent laparoscopic and robot-assisted partial nephrectomy, respectively. Overall, 37 (31%) and 55 (46%) surgeons contributed only to laparoscopic and robotic learning curves, respectively, whereas 27 (23%) contributed to the learning curves of both approaches. In the laparoscopic group, 8% and 55% of patients developed AKI and recovered at least 90% of their baseline eGFR, respectively. After adjusting for confounders, we did not find evidence of an association between surgical experience and AKI after laparoscopic partial nephrectomy (odds ratio [OR]: 0.9992; 95% confidence interval [CI]: 0.9963, 1.0022; p = 0.6). Similar results were found when 1-year renal function was the outcome of interest (OR: 0.9996; 95% CI: 0.9988, 1.0005; p = 0.5). Among patients who underwent robot-assisted partial nephrectomy, AKI occurred in 11% of patients, whereas 54% recovered at least 90% of their baseline eGFR. On multivariable analyses, the relationship between surgical experience and AKI after surgery was not statistically significant (OR: 1.0015; 95% CI: 0.9992, 1.0037; p = 0.2), with similar results when the outcome of interest was renal function one year after surgery (OR: 1.0001; 95% CI: 0.9980, 1.0022; p = 0.9). Virtually the same findings were found on sensitivity analyses. Conclusions: In patients treated with laparoscopic or robot-assisted partial nephrectomy, our data suggest that the surgical experience of the operating surgeon might not be a key determinant of functional recovery after surgery. This raises questions about the use of serum markers to assess functional recovery in patients with two kidneys and opens the discussion on what are the key steps of the procedure that allowed surgeons to achieve optimal outcomes since their initial cases.

PI-RADS 3 prostate lesions clinical management is still debated, with high variability among different centers. Identifying clinically significant tumors among PI-RADS 3 is crucial. Radiomics applied to multiparametric MR (mpMR) seems promising. Nevertheless, reproducibility assessment by external validation is required. We retrospectively included all patients with at least one PI-RADS 3 lesion (PI-RADS v2.1) detected on a 3T prostate MRI scan at our Institution (June 2016-March 2021). An MRI-targeted biopsy was used as ground truth. We assessed reproducible mpMRI radiomic features found in the literature. Then, we proposed a new model combining PSA density and two radiomic features (texture regularity (T2) and size zone heterogeneity (ADC)). All models were trained/assessed through 100-repetitions 5-fold cross-validation. Eighty patients were included (26 with GS ≥ 7). In total, 9/20 T2 features (Hector's model) and 1 T2 feature (Jin's model) significantly correlated to biopsy on our dataset. PSA density alone predicted clinically significant tumors (sensitivity: 66%; specificity: 71%). Our model obtained a sensitivity of 80% and a specificity of 76%. Standard-compliant works with detailed methodologies achieve comparable radiomic feature sets. Therefore, efforts to facilitate reproducibility are needed, while complex models and imaging protocols seem not, since our model combining PSA density and two radiomic features from routinely performed sequences appeared to differentiate clinically significant cancers.

Background: To evaluate the accuracy of 68Ga-prostate specific membrane antigen (PSMA) PET/CT in the diagnosis of clinically significant prostate cancer (csPCa) (Grade Group > 2) in men enrolled in Active Surveillance (AS) protocol. Methods: From May 2013 to May 2021, 173 men with very low-risk PCa were enrolled in an AS protocol study. During the follow-up, 38/173 (22%) men were upgraded and 8/173 (4.6%) decided to leave the AS protocol. After four years from confirmatory biopsy (range: 48−52 months), 30/127 (23.6%) consecutive patients were submitted to mpMRI and 68Ga-PSMA PET/CT scan before scheduled repeated biopsy. All the mpMRI (PI-RADS > 3) and 68Ga-PET/TC standardised uptake value (SUVmax) > 5 g/mL index lesions underwent targeted cores (mpMRI-TPBx and PSMA-TPBx) combined with transperineal saturation prostate biopsy (SPBx: median 20 cores). Results: mpMRI and 68Ga-PSMA PET/CT showed 14/30 (46.6%) and 6/30 (20%) lesions suspicious for PCa. In 2/30 (6.6%) men, a csPCa was found; 68Ga-PSMA-TPBx vs. mpMRI-TPBx vs. SPBx diagnosed 1/2 (50%) vs. 1/2 (50%) vs. 2/2 (100%) csPCa, respectively. In detail, mpMRI and 68Ga-PSMA PET/TC demonstrated 13/30 (43.3%) vs. 5/30 (16.7%) false positive and 1 (50%) vs. 1 (50%) false negative results. Conclusion: 68Ga-PSMA PET/CT did not improve the detection for csPCa of SPBx but would have spared 24/30 (80%) scheduled biopsies showing a lower false positive rate in comparison with mpMRI (20% vs. 43.3%) and a negative predictive value of 85.7% vs. 57.1%, respectively.

Background: To explore predictors of positive surgical margins (PSM) after robotic partial nephrectomy (PN) in a large multicenter international observational project, harnessing the Surface-Intermediate-Base (SIB) margin score to report the resection technique after PN in a standardized way. Methods: Data from consecutive patients with cT1-2N0M0 renal masses treated with PN from September 2014 to March 2015 at 16 tertiary referral centers and included in the SIB margin score International Consortium were prospectively collected. For the present study, only patients treated with robotic PN were included. Uni- and multivariable analysis were fitted to explore clinical and surgical predictors of PSMs after PN. Results: Overall, 289 patients were enrolled. Median (IQR) preoperative tumor size was 3.0 (2.3−4.2) cm and median (IQR) PADUA score was 8 (7−9). SIB scores of 0−2 (enucleation), 3−4 (enucleoresection) and 5 (resection) were reported in 53.3%, 27.3% and 19.4% of cases, respectively. A PSM was recorded in 18 (6.2%) patients. PSM rate was 4.5%, 11.4% and 3.6% in case of enucleation, enucleoresection and resection, respectively. Patients with PSMs had tumors with a higher rate of contact with the urinary collecting system (55.6% vs. 27.3%; p < 0.001) and a longer median warm ischemia time (22 vs. 16 min; p = 0.02) compared with patients with negative surgical margins, while no differences emerged between the two groups in terms of other tumor features (i.e., pathological diameter, PADUA score). In multivariable analysis, only enucleoresection (SIB score 3−4) versus enucleation (SIB score 0−2) was found to be an independent predictor of PSM at final pathology (HR: 2.68; 95% CI: 1.25−7.63; p = 0.04), while resection (SIB score 5) was not. Conclusions: In our experience, enucleoresection led to a higher risk of PSMs as compared to enucleation. Further studies are needed to assess the differential impacts of resection technique and surgeon’s experience on margin status after robotic PN.

Objectives: to investigate the accuracy of transurethral resection of bladder tumours (TURBT) in detecting histological variants (BHV) at radical cystectomy (RC) and to evaluate the impact of TURBT before cystectomy on oncological outcomes., Methods: Data of 410 consecutive RCs were assessed. Positive and negative predictive values were used to assess the accuracy of TURBT in detecting BHV. Cohen's Kappa coefficient was used to calculate the agreement grade. Logistic regression analysis predicted features based on the presence of BHV at TURBT. Multivariable backward conditional Cox regression analysis was used to estimate oncological outcomes., Results: A total of 73 patients (17.8%) showed BHV at TURBT as compared to 108 (26.3%) at RC. A moderate agreement in histological diagnosis was found between TURBT and RC (0.58). However, sensitivity and specificity in detecting BHV were 56% and 96%, respectively. Furthermore, positive predictive value (PPV) was 84.7% and negative predictive value (NPV) was 84.6%. Presence of BHV at TURBT was an independent predictor for pathologic upstage, albeit not a predictor for positive nodes or positive surgical margins. However, at multivariable analysis adjusted for all confounders, presence of BHV at TURBT was an independent predictor for recurrence after RC, but not for survival. Conversely, the presence of BHV at RC was an independent predictor for both recurrence and survival., Conclusion: There was a moderate agreement between TURBT and RC histopathological findings. TURBT, alone, could not provide an accurate and definitive histological diagnosis. Detection of BHV in TURBT specimens is not an independent predictor of oncological outcomes; indeed, only pathological features at RC are associated with worse survival. However, BHV presence in cystectomy specimens resulted as an independent predictor of both cancer-specific and overall mortality.