Robotic hepaticojejunostomy training in novices using robotic simulation and dry-lab suturing (ROSIM): randomized controlled crossover trial.

BACKGROUND: Robotic suturing training is in increasing demand and can be done using suture-pads or robotic simulation training. Robotic simulation is less cumbersome, whereas a robotic suture-pad approach could be more effective but is more costly. A training curriculum with crossover between both approaches may be a practical solution. However, studies assessing the impact of starting with robotic simulation or suture-pads in robotic suturing training are lacking. METHODS: This was a randomized controlled crossover trial conducted with 20 robotic novices from 3 countries who underwent robotic suturing training using an Intuitive Surgical® X and Xi system with the SimNow (robotic simulation) and suture-pads (dry-lab). Participants were randomized to start with robotic simulation (intervention group, n = 10) or suture-pads (control group, n = 10). After the first and second training, all participants completed a robotic hepaticojejunostomy (HJ) in biotissue. Primary endpoint was the objective structured assessment of technical skill (OSATS) score during HJ, scored by two blinded raters. Secondary endpoints were force measurements and a qualitative analysis. After training, participants were surveyed regarding their preferences. RESULTS: Overall, 20 robotic novices completed both training sessions and performed 40 robotic HJs. After both trainings, OSATS was scored higher in the robotic simulation-first group (3.3 ± 0.9 vs 2.5 ± 0.8; p = 0.049), whereas the median maximum force (N) (5.0 [3.2-8.0] vs 3.8 [2.3-12.8]; p = 0.739) did not differ significantly between the groups. In the survey, 17/20 (85%) participants recommended to include robotic simulation training, 14/20 (70%) participants preferred to start with robotic simulation, and 20/20 (100%) to include suture-pad training. CONCLUSION: Surgical performance during robotic HJ in robotic novices was significantly better after robotic simulation-first training followed by suture-pad training. A robotic suturing curriculum including both robotic simulation and dry-lab suturing should ideally start with robotic simulation.

Training in robotic-assisted surgery: a systematic review of training modalities and objective and subjective assessment methods.

INTRODUCTION: The variety of robotic surgery systems, training modalities, and assessment tools within robotic surgery training is extensive. This systematic review aimed to comprehensively overview different training modalities and assessment methods for teaching and assessing surgical skills in robotic surgery, with a specific focus on comparing objective and subjective assessment methods. METHODS: A systematic review was conducted following the PRISMA guidelines. The electronic databases Pubmed, EMBASE, and Cochrane were searched from inception until February 1, 2022. Included studies consisted of robotic-assisted surgery training (e.g., box training, virtual reality training, cadaver training and animal tissue training) with an assessment method (objective or subjective), such as assessment forms, virtual reality scores, peer-to-peer feedback or time recording. RESULTS: The search identified 1591 studies. After abstract screening and full-texts examination, 209 studies were identified that focused on robotic surgery training and included an assessment tool. The majority of the studies utilized the da Vinci Surgical System, with dry lab training being the most common approach, followed by the da Vinci Surgical Skills Simulator. The most frequently used assessment methods included simulator scoring system (e.g., dVSS score), and assessment forms (e.g., GEARS and OSATS). CONCLUSION: This systematic review provides an overview of training modalities and assessment methods in robotic-assisted surgery. Dry lab training on the da Vinci Surgical System and training on the da Vinci Skills Simulator are the predominant approaches. However, focused training on tissue handling, manipulation, and force interaction is lacking, despite the absence of haptic feedback. Future research should focus on developing universal objective assessment and feedback methods to address these limitations as the field continues to evolve.

Design and evaluation of a smart passive dynamic arm support for robotic-assisted laparoscopic surgery.

Surgeons performing robotic-assisted laparoscopic surgery experience physical stress and overuse of shoulder muscles due to sub-optimal arm support during surgery. The objective is to present a novel design and prototype of a dynamic arm support for robotic laparoscopic surgery to evaluate its ergonomics and performance on the AdLap-VR simulation training device. The prototype was designed using the mechanical engineering design process: Technical requirements, concept creation, concept selection, 3D-design and built of the prototype. A crossover study was performed on a marble sorting task on the AdLap-VR. The first group performed four trials without the arm support, followed by four trials with the arm support, and the other group executed the sequence vice versa. The performance parameters used were time to complete (s), path length (mm), and the number of collisions. Afterward, the participants filled out a questionnaire on the ergonomic experience regarding both situations. 20 students executed 160 performed trials on the AdLap-VR Significant decreases in the subjective comfort parameters mental demand, physical demand, effort and frustration were observed as a result of introducing the novel arm support. Significant decreases in the objective performance parameters path length and the number of collisions were also observed during the tests. The newly developed dynamic arm support was found to improve comfort and enhance performance through increased stability on the robotic surgery skills simulator AdLap-VR.

Objective measurement of retention of laparoscopic skills: a prospective cohort study.

INTRODUCTION: There has been an overall growth of 462% in laparoscopic procedures performed by surgical residents between 2000 and 2018. Therefore, training courses in laparoscopic surgery are advocated in many postgraduate programs. While the immediate effect is determined in some cases, the retention of acquired skills is rarely investigated. The objective of this study was to objectively measure the retention of laparoscopic technical skills to offer a more personalized training program. METHODS: First year general surgery residents performed two fundamental laparoscopic skills tasks (Post and Sleeve and the ZigZag loop) on the Lapron box trainer. Assessment was performed before, directly after, and 4 months after completing the basic laparoscopy course. Force, motion, and time were the measured variables. RESULTS: A total of 29 participants were included from 12 Dutch training hospitals and 174 trials were analyzed. The 4 months assessment of the Post and Sleeve showed a significant improvement in force ( P= 0.004), motion ( P ≤0.001), and time ( P ≤0.001) compared to the baseline assessment. The same was true for the ZigZag loop: force ( P ≤0.001), motion ( P= 0.005), and time ( P ≤0.001).Compared to the 4 months assessment, skill deterioration was present for the Post and Sleeve in the mean force ( P= 0.046), max impulse ( P= 0.12), and time ( P= 0.002). For the ZigZag loop, skill decay was observed for force ( P= 0.021), motion ( P= 0.015), and time ( P ≤0.001) parameters. CONCLUSION: Acquired laparoscopic technical skills decreased 4 months after the basic laparoscopy course. Compared to baseline performance, participants showed significant improvement, however deterioration was observed compared to postcourse measurements. To preserve acquired laparoscopic skills, it is recommended to incorporate maintenance training, preferably with objective parameters, in training curricula.

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

INTRODUCTION: Robot-assisted surgery is often performed by experienced laparoscopic surgeons. However, this technique requires a different set of technical skills and surgeons are expected to alternate between these approaches. The aim of this study is to investigate the crossover effects when switching between laparoscopic and robot-assisted surgery. METHODS: An international multicentre crossover study was conducted. Trainees with distinctly different levels of experience were divided into three groups (novice, intermediate, expert). Each trainee performed six trials of a standardized suturing task using a laparoscopic box trainer and six trials using the da Vinci surgical robot. Both systems were equipped with the ForceSense system, measuring five force-based parameters for objective assessment of tissue handling skills. Statistical comparison was done between the sixth and seventh trial to identify transition effects. Unexpected changes in parameter outcomes after the seventh trial were further investigated. RESULTS: A total of 720 trials, performed by 60 participants, were analysed. The expert group increased their tissue handling forces with 46% (maximum impulse 11.5 N/s to 16.8 N/s, p = 0.05), when switching from robot-assisted surgery to laparoscopy. When switching from laparoscopy to robot-assisted surgery, intermediates and experts significantly decreased in motion efficiency (time (sec), resp. 68 vs. 100, p = 0.05, and 44 vs. 84, p = 0.05). Further investigation between the seventh and ninth trial showed that the intermediate group increased their force exertion with 78% (5.1 N vs. 9.1 N, p = 0.04), when switching to robot-assisted surgery. CONCLUSION: The crossover effects in technical skills between laparoscopic and robot-assisted surgery are highly depended on the prior experience with laparoscopic surgery. Where experts can alternate between approaches without impairment of technical skills, novices and intermediates should be aware of decay in efficiency of movement and tissue handling skills that could impact patient safety. Therefore, additional simulation training is advised to prevent from undesired events.

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

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 N3 p = 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 N3 p = 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.

Prediction of laparoscopic skills: objective learning curve analysis.

INTRODUCTION: Prediction of proficiency of laparoscopic skills is essential to establish personalized training programs. Objective assessment of laparoscopic skills has been validated in a laparoscopic box trainer with force, motion and time recognition. The aim of this study is to investigate whether acquiring proficiency of laparoscopic skills can be predicted based on performance in such a training box. METHODS: Surgical residents in their first year of training performed six different tasks in the Lapron box trainer. Force, motion and time data, three objective measures of tissue manipulation and instrument handling, were collected and analyzed for the six different tasks. Linear regression tests were used to predict the learning curve and the number of repetitions required to reach proficiency. RESULTS: A total of 6010 practice sessions performed by 42 trainees from 13 Dutch hospitals were assessed and included for analysis. Proficiency level was determined as a mean result of seven experts performing 42 trials. Learning curve graphs and prediction models for each task were calculated. A significant relationship between force, motion and time during six different tasks and prediction of proficiency was present in 17 out of 18 analyses. CONCLUSION: The learning curve of proficiency of laparoscopic skills can accurately be predicted after three repetitions of six tasks in a training box with force, path length and time recognition. This will facilitate personalized training programs in laparoscopic surgery.