Background: The decision to perform a partial nephrectomy (PN) relies largely upon the complexity of the renal mass and its surrounding anatomy. The presence of adherent perinephric fat (APF) can increase surgical complexity and extend operative times. The accurate prediction of APF may improve surgical planning and aid in decision making for the surgical approach. Objective: We sought to develop and externally validate a score that predicts APF based on preoperative clinical and radiological prognostic factors. Design, setting, and participants: We retrospectively analyzed 495 consecutive patients who underwent open or minimally invasive PN. APF was defined as the presence of "dense," "adherent," or "sticky" perinephric fat at the time of dissection by the surgeon, and this did not require subcapsular dissection. Additionally, we analyzed an independent cohort of 285 patients for external validation. Outcome measurements and statistical analysis: A score model was developed using multivariate logistic regression analysis. Calibration of the fitted model was assessed graphically with a plot of the predicted versus the actual probability of APF, and discrimination was assessed by calculating the area under the receiver operating characteristic curve. Results and limitations: Of the 495 patients, 95 (19%) had APF. Patients with APF had longer operative (p = 0.02) and arterial clamp (p = 0.01) times than non-APF patients. On multivariate analyses, diabetes mellitus (p = 0.009), posterior perinephric fat thickness (p < 0.001), and perinephric stranding (p < 0.001) were predictors of encountering APF in PN. A risk score ranging from 0 to 4 was developed based on these three variables to predict APF. The scoring system demonstrated good discrimination of 0.82 and 0.84 for the development and external validation cohorts, respectively. Conclusions: The APF score can accurately predict the presence of APF in patients with a small renal mass who are planning to undergo PN. This score could aid in pre- and intraoperative planning and impact the surgical approach. Patient summary: The presence of "sticky" fat surrounding the kidney in patients undergoing partial nephrectomy has previously been linked to longer operative times, intraoperative complications, and surgical conversion. In our study, we found that this feature is more often presented in patients with diabetes mellitus, and thicker and more inflammatory fat on renal imaging. Based on these findings, we developed a risk score that can accurately predict this feature before surgery, in order to improve surgical planning and better counsel the patients. (C) 2019 European Association of Urology. Published by Elsevier B.V. All rights reserved.

A 60-year-old man with prostate adenocarcinoma status post radical prostatectomy and bilateral pelvic lymph node dissection referred for restaging F-fluciclovine PET/CT due to rising serum prostate-specific antigen levels (1.1 ng/mL at that time of imaging). PET/CT images were obtained from the proximal thighs to the vertex of the skull approximately 3 to 5 minutes after the IV administration of 347.8 MBq (9.4 mCi) of F-fluciclovine. PET/CT imaging demonstrated a focus of abnormally increased F-fluciclovine uptake at the right ureterovesical junction. Subsequent MRI of the pelvis revealed that this focus corresponded to a benign ureterocele.

497 Background: The decision to perform a partial nephrectomy (PN) relies largely upon the complexity of the renal mass and its surrounding anatomy. An often encountered intraoperative challenge in PN is the adherent perinephric fat (APF). The anticipation of this feature may improve preoperative risk assessment and aid in decision-making for the surgical approach. We sought to develop and externally validate a score that predicts for APF based on preoperative clinical and radiological prognostic factors. Methods: We retrospectively analyzed 495 consecutive patients that underwent open or minimally invasive PN. APF was defined as the presence of “dense”, “adherent”, or “sticky” perinephric fat at time of dissection by the surgeon and this did not required subcapsular dissection for tumor isolation. A score model was developed using multivariate logistic regression analysis. This score was further validated using an external data set with 285 patients. Discrimination and calibration were assessed by calculating the area under the receiver operating characteristic curve (AUC) and the Hosmer–Lemeshow statistic, respectively. Results: Among the 495 patients, 95 (19%) patients presented with APF. On multivariate analyses, diabetes mellitus (p = 0.009), perinephric fat thickness (p < 0.001) and perinephric stranding (p < 0.001) were predictors of encountering APF in PN. A risk score ranging from 0 to 4, was developed based on these three variables to predict for APF. Among the 285 patients in the validation cohort, 41(14.3%) presented with APF. The score demonstrated good discrimination of 0.82 and 0.84 for the development and validation cohort, respectively. The model did not show a statistically significant lack of calibration (p-values = 0.98, 0.35). Moreover, predicted probabilities of APF based on a 0.5 threshold yielded a specificity of 92.3 and 92.2 in the development and validation cohorts, respectively. Conclusions: The score can accurately predict the presence of APF in patients with small renal mass planning to undergo PN. This score could aid current algorithms of preoperative risk assessment and impact surgical approach.