Presentation Authors: Michael Witthaus*, Timothy Campbell, Rachel Melnyk, Erin Coppola, Shamrooz Farooq, Katherine Cameron, Tyler Holler, Ashkan Ertefaie, Thomas Frye, Hani Rashid, Guan Wu, Jean Joseph, Ahmed Ghazi, Rochester, NY
Introduction: Surgical education is dependent on live patients for operative exposure and cultivation of surgical technique. Robotic assisted radical prostatectomy is a unique surgery requiring both oncologic and functional outcomes for success. The steep learning curve of nerve-sparing prostatectomy provides a significant need for surgical education outside of the live patient operative room exposure. In our study, we validate a high-fidelity, inanimate robotic assisted nerve-sparing prostatectomy model within a full-immersion simulation environment using Clinically-relevant Performance Metrics (CRPMs).
Methods: Anatomically accurate models of the human pelvis, bladder, prostate, urethra, neurovascular bundle (NVB) and relevant adjacent structures were created form a patients MRI using polyvinyl alcohol (PVA) hydrogels and three-dimensional-printed injection molds. Pertinent steps of the nerve-sparing prostatectomy were simulated: bladder neck dissection, seminal vesicle mobilization, nerve-sparing prostatectomy and urethra-vesical anastomosis. Five experts (>500 caseload) and 10 novices were ( < 50 caseload) completed the simulation. Force trauma applied to the NVB during the dissection was quantified by a novel tension wire sensor system within the NVB. Adequacy of the anastomosis was quantified by a 180cc leak test. The validated objective GEARS scores and RACE score were calculated by 2 blinded surgeons and correlated to forces applied to the NVB and UVA leakage respectively. After resection, margin status was measured grossly and microscopically by prostatic fluorescent dye within each prostatic mold. Robotic Anastomosis Competency Evaluation (RACE) was performed and all anastomosis were leak tested.
Results: Experts achieved faster task specific times: bladder neck dissection (p= 0.003), nerve sparing (p= 0.007) and VUA (p= 0.002). Experts continued to have superior margins (p= 0.011) and VUAs were without leak (p=0.02). Nerve forces applied were significantly lower for experts in maximum force (p=0.011), average force (p=0.011), peak frequency and total energy (p=0.003). Higher force sensitivity (Subcategory of GEARS Score) and Total GEARS Score correlated with lower nerve forces applied with total energy (J) -0.66(0.019) and -0.87(0.000), respectively. VUA leak rate was correlated with RACE score -0.86 (0.000), which was significantly different between novices and experts (p=0.003).
Conclusions: This high-fidelity simulation model for Robot Assisted Radical Prostatectomy, incorporating CRPMs that co-relate with validated objective metrics presents a valid training tool for robotic surgery.