Force-based assessment of tissue handling skills in simulation training for robot-assisted surgery

Abstract

Introduction Although robotic-assisted surgery is increasingly performed, objective assessment of technical skills is lacking. The aim of this study is to provide validity evidence for objective assessment of technical skills for robotic-assisted surgery. Methods An international multicenter study was conducted with participants from the academic hospitals Heidelberg University Hospital (Germany, Heidelberg) and the Amsterdam University Medical Centers (The Netherlands, Amsterdam). Trainees with distinctly different levels of robotic surgery experience were divided into three groups (novice, intermediate, expert) and enrolled in a training curriculum. Each trainee performed six trials of a standardized suturing task using the da Vinci Surgical System. Using the ForceSense system, five force-based parameters were analyzed, for objective assessment of tissue handling skills. Mann–Whitney U test and linear regression were used to analyze performance differences and the Wilcoxon signed-rank test to analyze skills progression. Results A total of 360 trials, performed by 60 participants, were analyzed. Significant differences between the novices, intermediates and experts were observed regarding the total completion time (41 s vs 29 s vs 22 s p = 0.003), mean non zero force (29 N vs 33 N vs 19 N p = 0.032), maximum impulse (40 Ns vs 31 Ns vs 20 Ns p = 0.001) and force volume (38 N3 vs 32 N3 vs 22 N3p = 0.018). Furthermore, the experts showed better results in mean non-zero force (22 N vs 13 N p = 0.015), maximum impulse (24 Ns vs 17 Ns p = 0.043) and force volume (25 N3 vs 16 N3p = 0.025) compared to the intermediates (p ≤ 0.05). Lastly, learning curve improvement was observed for the total task completion time, mean non-zero force, maximum impulse and force volume (p ≤ 0.05). Conclusion Construct validity for force-based assessment of tissue handling skills in robot-assisted surgery is established. It is advised to incorporate objective assessment and feedback in robot-assisted surgery training programs to determine technical proficiency and, potentially, to prevent tissue trauma.

The development of tissue handling skills is sufficient and comparable after training in virtual reality or on a surgical robotic system: a prospective randomized trial

“…Our findings are supported by a recent study that demonstrated similar reductions in force and time for a repeated robotic suturing task, but without comparison with VR training. In addition, the range of the peak and mean non-zero forces observed by Rahimi et al was comparable to our measurements [ 16 ].…”

“…To increase comparability, the participants were purposefully chosen to be naïve to RAS. In particular, the distinction in surgical experience based on the respective tissue handling skills in RAS has been observed previously [ 16 ].…”

“…The primary endpoint was tissue handling, represented by the mean non-zero force [N] and the peak force [N] exerted during the trial tasks in the Baseline, Midterm, and Final tests [ 15 , 16 ]. The force parameters were measured using a force-measuring device (ForceTrap®, MediShield B.V., Delft, The Netherlands).…”

Crossover-effects in technical skills between laparoscopy and robot-assisted surgery

“…This was also concluded by our previous work regarding the use of objective force-based parameters to assess technical skills during laparoscopic skills training [29,30,48]. Following force-based assessment tools for LS, validity evidence for objective assessment tools for RAS in accumulating [15,16,[49][50][51][52]. A recent construct validation study by our group confirmed the potential for force-based parameters in assessment of tissue handling skills in RAS training [51].…”

Review of robotic surgery platforms and end effectors

“…There is always an important trade-off between the device’s capabilities and the time the surgeons need to learn and operate. The level of training and support offered is important to optimize the surgeon’s learning curve [ 4 – 6 ]. The surgical platforms may have different purchase and operating costs.…”