Pediatric Thoracoscopic Surgical Simulation Using a Rapid-Prototyped Chest Model and Motion Sensors Can Better Identify Skilled Surgeons Than a Conventional Box Trainer.
OBJECTIVE
We previously developed a pediatric thoracoscopic surgical simulator and showed its construct validity. In this study, the same skill assessment experiments were conducted in an additional 31 surgeons and the results of 53 surgeons in total were analyzed.


METHODS
A suture pad with force sensors was placed in a rapid-prototyped pediatric chest model of a 1-year-old patient. Participants completed the endoscopic intracorporeal suturing and knot-tying task, both in the pediatric chest model setup and in a box trainer setup. The task was evaluated using eight metrics: the 29-point checklist score, error score, number of manipulations, task completion time, force index, width of the pad's slit after suturing, and right and left tool paths.


RESULTS
The 53 participants included skilled surgeons certified by the Endoscopic Surgical Skill Qualification (ESSQ) system (n = 8) and unskilled surgeons without the certification (n = 45). The skilled surgeons showed significantly better performance than the unskilled surgeons in six metrics in the pediatric chest model setup. In contrast, no significant differences between the two groups were observed in the box trainer setup. Upon comparison between the setups, the unskilled surgeons showed worse results in six metrics in the pediatric chest model than in the box trainer, whereas the skilled surgeons showed equivalent performance in both setups.


CONCLUSIONS
Our pediatric thoracoscopic surgical simulator was superior to the conventional box trainer for identifying skilled surgeons. The skilled surgeons showed excellent performance even in the intricate pediatric chest model, providing quantified targets for young pediatric surgeons' training.
1 Department of Pediatric Surgery, The University of Tokyo Hospital , Tokyo, Japan .|2 Department of Pediatric Surgery, Gunma Children's Medical Center , Shibukawa, Japan .
Shinya
S
Takazawa
1 Department of Pediatric Surgery, The University of Tokyo Hospital , Tokyo, Japan .
Tetsuya
T
Ishimaru
3 School of Engineering, The University of Tokyo , Tokyo, Japan .
Kanako
K
Harada
1 Department of Pediatric Surgery, The University of Tokyo Hospital , Tokyo, Japan .
Kyoichi
K
Deie
1 Department of Pediatric Surgery, The University of Tokyo Hospital , Tokyo, Japan .
Jun
J
Fujishiro
3 School of Engineering, The University of Tokyo , Tokyo, Japan .
Naohiko
N
Sugita
3 School of Engineering, The University of Tokyo , Tokyo, Japan .
Mamoru
M
Mitsuishi
1 Department of Pediatric Surgery, The University of Tokyo Hospital , Tokyo, Japan .|4 Saitama Children's Medical Center , Saitama, Japan .
Tadashi
T
Iwanaka
D057189:Checklist; D002983:Clinical Competence; D006801:Humans; D007223:Infant; D000066908:Simulation Training / Q000379:methods*; D013536:Suture Techniques / Q000193:education / Q000592:standards*; D013537:Sutures; D013906:Thoracoscopy / Q000193:education / Q000592:standards*; D013909:Thorax; D014159:Transducers