Badani, Ketan K.

Abstract Introduction and Objective This study aims to evaluate the learning curve and perioperative outcomes of single‐port extraperitoneal robotic radical prostatectomy (SP‐EP‐RARP) performed by a single surgeon at a high‐volume academic institution. Methods A retrospective review of a prospectively maintained database was conducted for patients who underwent SP‐EP‐RARP from September 2023 to August 2025. Key metrics included operative time, estimated blood loss, conversion rate, nerve‐sparing status, pathological margin status and continence (0–1 pad for safety), and 30‐day complication rate. Descriptive statistics were used, and outcomes were analysed chronologically to assess for trends suggesting a learning curve. Results The cohort included 53 patients who underwent extraperitoneal SP‐EP‐RARP. Median operative time was 213 min (IQR: 145–281). Median estimated blood loss was 100 mL (IQR: 75–125). Nerve‐sparing was attempted in 75.5% of cases. No assist or plus one ports were utilized. Final pathology revealed pT2 disease in 64.1% (34 cases), pT3a in 32.1% (17 cases) and pT3b in 3.7% (2 cases). Overall positive margin rate was 26.4%. Thirty‐day Clavien–Dindo Grades I–II complication rates were 11.3%, and no major complications or 90‐day complications were reported. Continence rates at 6 weeks, 3 months and 6 months were 72%, 72% and 75%, respectively. Stabilization of operative times and intraoperative outcomes occurred after approximately 25–30 cases. Conclusion SP‐EP‐RARP can be safely implemented by a newly graduated fellowship‐trained robotic surgeon with acceptable oncologic and functional outcomes. Initial learning can be estimated at approximately 25–30 cases.

ImportancePlanning complex operations such as robotic-assisted laparoscopic radical prostatectomy (RALP) requires surgeons to review 2-dimensional magnetic resonance imaging (MRI) scans to understand 3-dimensional (3D) patient anatomy. Three-dimensional digital models for planning RALP may allow better understanding of patient anatomy and may lead to better patient outcomes, although data are currently limited.ObjectiveTo determine surgical outcomes after RALP when surgeons reviewed 3D digital models during operative planning.Design, Setting, and ParticipantsThis study was a planned secondary analysis of a multicenter, single-blind, randomized clinical trial conducted at 6 large teaching hospitals in the US. The study was conducted between January 1, 2019, and December 31, 2022, and included patients undergoing RALP. Patients were assessed and recruited at the time of surgical consultation. Final data analysis was conducted between August and December 2023.InterventionPatients were randomized to either a control group undergoing usual preoperative planning with prostate biopsy results and multiparametric MRI only or to an intervention group in which imaging and biopsy results were supplemented with a 3D digital model. This model was viewed on the surgeon’s mobile phone in 3D format and picture-in-picture on the robotic console screen.Main Outcomes and MeasuresThe primary outcome measure for the overall study was oncologic outcomes after RALP, measured as prostate-specific antigen (PSA) detectability. Secondary outcomes were sexual function and urinary function, measured with Sexual Health Inventory for Men (SHIM) scores and rates of urinary incontinence, respectively, as well as use of salvage or adjuvant radiation therapy (RT) or androgen deprivation therapy (ADT). Trifecta outcomes were defined as undetectable PSA without RT or ADT, SHIM score categorically the same or greater than preoperatively, and complete continence. Univariate analysis was performed to compare outcomes between groups.ResultsThis trial included 92 patients undergoing RALP (51 in the control group and 41 in the intervention group). Their mean (SD) age was 62 (7.4) years; 10 patients (10.9%) were Black and 67 (72.8%) were White. At 18 months postsurgery, the intervention group had lower rates of biochemical recurrence (PSA level >0.1 ng/mL, 0 vs 7 [17.9%]; absolute difference, 17.9% [95% CI, 1.8% to 31.8%]; P = .01) and were significantly less likely to undergo adjuvant or salvage RT (1 [3.1%] vs 12 [31.6%]; absolute difference, 28.5% [95% CI, 10.1% to 46.7%]; P = .002) compared with the control group. Sexual function at 18 months postsurgery was significantly better in the intervention group (mean [SD] SHIM score, 16.8 [8.7] vs 9.8 [7.7]; absolute difference, 7.0 [95% CI, 2.6 to 11.4]; P = .002) and urinary function was unchanged (total continence, 22 [78.6%] vs 29 [80.6%]; absolute difference, 2.0% [95% CI, −17.9% to 21.9%]; P = .84) compared with the control group. Trifecta outcomes were achieved for 12 (48.0%) patients in the intervention group and 3 patients (10.0%) in the control group (absolute difference, 38.0% [95% CI, 14.4% to 61.6%]; P = .002).Conclusions and RelevanceIn this secondary analysis of a randomized clinical trial, patients whose surgical planning of RALP involved 3D digital models had better oncologic and functional outcomes. Further work should assess the effect of 3D models in a broader set of patients, physicians, and hospital settings.Trial RegistrationClinicalTrials.gov Identifier: NCT03943368

Purpose: Planning for robotic-assisted partial nephrectomy requires surgeons to review two-dimensional CT or MRI scans to understand three-dimensional (3D) anatomy. We sought to determine the drivers of improvements in key surgical outcomes when using patient-specific 3D virtual reality (VR) models for operative planning. Materials and Methods: A multicenter, randomized, single-blind clinical trial was conducted from January 2019 to December 2020. Patients undergoing robotic-assisted partial nephrectomy were randomly assigned to a control group undergoing usual preoperative planning with CT and/or MRI only or to an intervention group where imaging was supplemented with a 3D VR model. A survey was administered to surgeons after review of the model and after the operation. The primary outcome measure was operative time, and secondary outcomes included clamp time, estimated blood loss, and hospital stay. Results: Qualitative data analysis of 44 cases in the treatment arm was performed. Surgeons reported seeing anatomic details much better in the 3D model 55% of the time and modified their preoperative plan based on anatomy shown in the 3D model 30% of the time. Cases in which the surgeon reported modifying their preoperative plan after viewing the model (30%) had significantly lower operative time, blood loss, and clamp time (P < .05). In addition, increased surgeon confidence after viewing the model significantly lowered operative time, estimated blood loss, and clamp time (P < .05). Conclusions: We demonstrate that surgeons who use 3D VR models for robotic kidney surgery are able to visualize anatomic structures and select the optimal approach, leading to better surgical outcomes. Trial Registration: ClinicalTrials.gov identifier NCT0333434.