The Impact of Force Feedback in the dV5 Robotic Surgical System on Learning Curve and Safety in Robot-Assisted Radical Prostatectomy - A Prospective, Single-Center, Investigator-Initiated Clinical Trial

This single-center, investigator-initiated prospective clinical study aims to evaluate the impact of the Force Feedback function of the da Vinci 5 (dV5) robotic surgical system on surgical skill acquisition and intraoperative safety during robot-assisted radical prostatectomy (RARP). Although robotic surgery is well established in urology, the absence of tactile sensation remains a major limitation of previous systems. The new dV5 platform incorporates real-time haptic (force) feedback, potentially reducing excessive tissue traction and improving surgical precision. A total of 60 patients with clinically localized prostate cancer will be enrolled at Samsung Medical Center. Two surgeons (one faculty and one trainee) will each perform 30 RARP cases, with Force Feedback ON/OFF randomly assigned for each case. The primary endpoints are (1) mean traction force and (2) total instrument path length during seminal vesicle dissection. Secondary endpoints include surgical performance metrics (time, clutch counts), intraoperative safety, postoperative complications, and patient-reported outcomes (IPSS, IIEF-5, EPIC-CP, ICIQ-UI SF). Data will be analyzed using mixed-effects models accounting for surgeon-level random effects. This study seeks to provide quantitative evidence on how Force Feedback enhances surgical learning efficiency, precision, and patient safety in next-generation robotic prostate surgery.

This prospective, single-institution, investigator-initiated clinical trial investigates how the Force Feedback (haptic sensing) technology in the da Vinci 5 (dV5) robotic surgery platform influences technical skill acquisition and safety in robot-assisted radical prostatectomy (RARP). The study is conducted at Samsung Medical Center (Seoul, Korea) under the supervision of Professor Seong Soo Jeon and Dr. Jiwoong Yu from the Department of Urology. Robotic-assisted surgery has revolutionized minimally invasive prostate cancer treatment, but conventional robotic systems (e.g., da Vinci Xi) lack tactile feedback, forcing surgeons to rely solely on visual cues. This limitation may lead to excessive force application and increase the risk of tissue injury. The dV5 system introduces a Force Feedback mechanism that allows surgeons to feel real-time resistance transmitted through the robotic arms. Preclinical reports suggest this reduces applied forces by up to 40-50% and improves precision, especially during the learning phase. However, objective clinical data quantifying these benefits are limited. The present trial will enroll 60 patients diagnosed with clinically localized prostate cancer (cT1-T3a, N0, M0) eligible for RARP. Two surgeons-a senior faculty (expert) and a urology resident (trainee)-will each perform 30 RARP cases. For each surgery, the Force Feedback function will be randomly assigned (ON vs. OFF) while maintaining identical operative conditions. The seminal vesicle dissection step is chosen as the standardized assessment phase since it is technically demanding yet safe for educational evaluation. Primary endpoints are: Mean traction force applied to tissue (N) Total instrument path length (m) during seminal vesicle dissection Secondary endpoints include: Surgical performance metrics: operative time, clutch counts, peak force, efficiency indicators, and cumulative sum (CUSUM) learning curves. Safety parameters: estimated blood loss, complications (graded by Clavien-Dindo), hospital stay, and biochemical recurrence. Patient-reported outcomes: urinary, sexual, and overall quality of life assessed by validated questionnaires (IPSS, IIEF-5, EPIC-CP, ICIQ-UI SF). Procedural efficiency metrics such as lens-cleaning frequency and suction count. All operations will be video-recorded and digitally logged using dV5 Case Insight software, which captures objective performance indicators (OPIs) including instrument trajectory, applied force, and clutch frequency. Statistical analysis will use linear mixed-effects models with Force Feedback status and case sequence as fixed effects, and surgeon ID as a random effect, allowing adjustment for intra-surgeon correlations and learning effects. Safety monitoring follows institutional IRB and KGCP guidelines. All adverse events (AEs) and device deficiencies will be documented, with serious adverse events (SAEs) reported within 24 hours. Standard perioperative management and intraoperative supervision by experienced faculty will ensure patient safety. This study is designed as a pilot exploratory analysis that integrates human performance data, haptic sensor output, and clinical outcomes. Findings will offer the first objective evidence on how haptic feedback influences both novice and expert robotic surgeons in terms of force modulation, precision, efficiency, and safety. The results may guide the optimization of training curricula and inform the development of future robotic platforms incorporating tactile intelligence.