Motion analysis for better understanding of psychomotor skills in laparoscopy: objective assessment-based simulation training using animal organs

Surg Endosc. 2021 Aug;35(8):4399-4416. doi: 10.1007/s00464-020-07940-7. Epub 2020 Sep 9.

Abstract

Background: Our aim was to characterize the motions of multiple laparoscopic surgical instruments among participants with different levels of surgical experience in a series of wet-lab training drills, in which participants need to perform a range of surgical procedures including grasping tissue, tissue traction and dissection, applying a Hem-o-lok clip, and suturing/knotting, and digitize the level of surgical competency.

Methods: Participants performed tissue dissection around the aorta, dividing encountered vessels after applying a Hem-o-lok (Task 1), and renal parenchymal closure (Task 2: suturing, Task 3: suturing and knot-tying), using swine cadaveric organs placed in a box trainer under a motion capture (Mocap) system. Motion-related metrics were compared according to participants' level of surgical experience (experts: 50 ≤ laparoscopic surgeries, intermediates: 10-49, novices: 0-9), using the Kruskal-Wallis test, and significant metrics were subjected to principal component analysis (PCA).

Results: A total of 15 experts, 12 intermediates, and 18 novices participated in the training. In Task 1, a shorter path length and faster velocity/acceleration/jerk were observed using both scissors and a Hem-o-lok applier in the experts, and Hem-o-lok-related metrics markedly contributed to the 1st principal component on PCA analysis, followed by scissors-related metrics. Higher-level skills including a shorter path length and faster velocity were observed in both hands of the experts also in tasks 2 and 3. Sub-analysis showed that, in experts with 100 ≤ cases, scissors moved more frequently in the "close zone (0 ≤ to < 2.0 cm from aorta)" than those with 50-99 cases.

Conclusion: Our novel Mocap system recognized significant differences in several metrics in multiple instruments according to the level of surgical experience. "Applying a Hem-o-lok clip on a pedicle" strongly reflected the level of surgical experience, and zone-metrics may be a promising tool to assess surgical expertise. Our next challenge is to give completely objective feedback to trainees on-site in the wet-lab.

Keywords: Laparoscopic surgery; Motion capture; Simulation training; Surgical education.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animal Structures
  • Animals
  • Clinical Competence
  • Laparoscopy*
  • Simulation Training*
  • Surgical Instruments
  • Sutures
  • Swine