Abstract
BACKGROUND: Robotic surgery systems were introduced to overcome the disadvantages of endoscopic surgery. The goal of this study was to assess whether robot assistance could support endoscopic surgeons in performing a complex endoscopic task.
METHODS: Five experienced endoscopic surgeons performed end-to-end anastomosis on post-mortem porcine small intestine. The procedure was performed both with standard endoscopic techniques and with robotic assistance (da Vinci system, Intuitive Surgical, Sunny vale, CA). It was performed in three different working directions with a horizontal, vertical, and diagonal position of the bowel. Anastomosis time, number of stitches, knots, time per stitch, suture ruptures, and the number of stitch errors were recorded. Also, an action analysis was performed.
RESULTS: Anastomosis time, number of stitches, and the number of knots did not differ significantly between the two groups. The time needed per stitch was significantly shorter with robot assistance (81.4 sec/stitch vs 95.9 sec/stitch, p = 0.005). More suture ruptures occurred in the robot group (0 (0-2) vs 0 (0-0), p = 0.003). In the standard group more stitch errors were found (2 (0-5) vs 0 (0-3), p = 0.017). These results were comparable for three different working directions. The action analysis, however, showed significant benefits of robotic assistance. The benefits were greatest in a vertical bowel position.
CONCLUSION: Robot assistance might offer added value to experienced endoscopic surgeons in the performance of a small-bowel anastomosis in an experimental setup, even though total anastomosis time could not be demonstrated to be shorter and some suture tears occurred due to the lack of force feedback.
Original language | English |
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Pages (from-to) | 1249-1252 |
Number of pages | 4 |
Journal | Surgical Endoscopy |
Volume | 18 |
Issue number | 8 |
DOIs | |
Publication status | Published - Aug 2004 |
Keywords
- Anastomosis, Surgical
- Animals
- Endoscopy, Gastrointestinal
- Intestine, Small
- Robotics
- Suture Techniques
- Task Performance and Analysis