ロボット支援インプラント手術システムの研修医における学習曲線：in vitro研究

This study investigated the accuracy and learning curve of dental postgraduate trainees in robot-assisted implant surgery (r-CAIS) and examined the characteristics of learning curve.

After receiving comprehensive training, eleven dental trainees used r-CAIS to place three implants, 3 trials per day over four experimental days, with each experimental day occurring every 72 h. Trueness was assessed by comparing postoperative model scans with preoperative planning. The total time was recorded during the experiment and subsequently categorized into preparation and surgery times.

The average deviations for platform, apex, and angular were 0.91 ± 0.39 mm, 0.93 ± 0.38 mm, and 1.38 ± 0.61°, respectively. The mean total time, preparation time, and surgery time were 954.36 ± 222.69 s, 321.36 ± 119.30 s, and 632.53 ± 140.30 s, respectively. Analysis indicated that there were no statistically significant differences in trueness between different experimental days and trials for platform, apex, and angular (p-values: Day: 0.0924, 0.2735, 0.3223; Trial: 0.6647, 0.7873, 0.5270). However, all time measures (total, preparation, and surgery time) showed significant reductions as days and trials increased (p-values < 0.0001 for all). Additionally, there was a significant interaction between days and trials for surgery time (p = 0.0123). Normality tests revealed that the trueness data and surgery time were not normally distributed on day 1, but conformed to a normal distribution on the rest days.

The results demonstrated stability in trueness during the learning phase of r-CAIS, although there could still be a learning curve in terms of time metrics. Additionally, the accumulation of experience may exert varying influences during the preparation and surgical phases.

The r-CAIS can enable dental trainees to achieve high trueness during their initial exposure to surgical procedures. Understanding the differing learning processes associated with various r-CAIS procedures can help develop more effective training programs and promote the broader clinical applications of r-CAIS.