Proving the Effectiveness of the Fundamentals of Robotic Surgery (FRS) Skills Curriculum: A Single-blinded, Multispecialty, Multi-institutional Randomized Control Trial

Next-generation robotics in gastrointestinal surgery

The global numbers of robotic gastrointestinal surgeries are increasing. However, the evidence base for robotic gastrointestinal surgery does not yet support its widespread adoption or justify its cost. The reasons for its continued popularity are complex, but a notable driver is the push for innovation - robotic surgery is seen as a compelling solution for delivering on the promise of minimally invasive precision surgery - and a changing commercial landscape delivers the promise of increased affordability. Novel systems will leverage the robot as a data-driven platform, integrating advances in imaging, artificial intelligence and machine learning for decision support. However, if this vision is to be realized, lessons must be heeded from current clinical trials and translational strategies, which have failed to demonstrate patient benefit. In this Perspective, we critically appraise current research to define the principles on which the next generation of gastrointestinal robotics trials should be based. We also discuss the emerging commercial landscape and define existing and new technologies.

Demonstrating the effectiveness of the fundamentals of robotic surgery (FRS) curriculum on the RobotiX Mentor Virtual Reality Simulation Platform

Fundamentals of robotic surgery (FRS) is a proficiency-based progression curriculum developed by robotic surgery experts from multiple specialty areas to address gaps in existing robotic surgery training curricula. The RobotiX Mentor is a virtual reality training platform for robotic surgery. Our aims were to determine if robotic surgery novices would demonstrate improved technical skills after completing FRS training on the RobotiX Mentor, and to compare the effectiveness of FRS across training platforms. An observational, pre-post design, multi-institutional rater-blinded trial was conducted at two American College of Surgeons Accredited Education Institutes-certified simulation centers. Robotic surgery novices (n = 20) were enrolled and trained to expert-derived benchmarks using FRS on the RobotiX Mentor. Participants' baseline skill was assessed before (pre-test) and after (post-test) training on an avian tissue model. Tests were video recorded and graded by blinded raters using the Global Evaluative Assessment of Robotic Skills (GEARS) and a 32-criteria psychomotor checklist. Post hoc comparisons were conducted against previously published comparator groups. On paired-samples T tests, participants demonstrated improved performance across all GEARS domains (p < 0.001 to p = 0.01) and for time (p < 0.001) and errors (p = 0.003) as measured by psychometric checklist. By ANOVA, improvement in novices' skill after FRS training on the RobotiX Mentor was not inferior to improvement reported after FRS training on previously published platforms. Completion of FRS on the RobotiX Mentor resulted in improved robotic surgery skills among novices, proving effectiveness of training. These data provide additional validity evidence for FRS and support use of the RobotiX Mentor for robotic surgery skill acquisition.

Concurrent, face, content, and construct validity of the RobotiX Mentor simulator for robotic basic skills

OBJECTIVES

To assess several criteria, such as concurrent, face, content, and construct validity of the RobotiX Mentor (RXM) simulator for basic robotic skills and to compare virtual and actual dry lab dome.

METHODS

A prospective study was conducted from December 2017 to May 2018 using RXM and a da Vinci Si robot. 37 subjects, divided into three groups according to their initial surgical training (expert, intermediate, and novice), were evaluated in terms of six representative exercises of basic robotic specific skills as recommended by the fundamentals of robotic surgery.

RESULTS

There was a correlation between the automatic data from the RXM and the subjective evaluation with the robot. The face and content validity, which were evaluated by the experts, were generally considered high (71.5% and 62.5%, respectively). Three levels (analysis of variance [ANOVA]; P = .01) and two levels (P = .001) of experience were clearly identified by the simulator.

CONCLUSION

Our study proves the concurrent validity and confirms the face, content, and construct validity of the RXM.

A video anchored rating scale leads to high inter-rater reliability of inexperienced and expert raters in the absence of rater training

BACKGROUND

Our objective was to assess the impact of incorporating videos in a behaviorally anchored performance rating scale on the inter-rater reliability (IRR) of expert, intermediate and novice raters.

METHODS

The Intra-corporeal Suturing Assessment Tool (ISAT) was modified to include short video clips demonstrating poor, average, and expert performances. Blinded raters used this tool to assess videos of trainees performing suturing on a porcine model. Three attending surgeons, 4 residents, and 4 novice raters participated; no rater training was provided. The IRR was then compared among rater groups.

RESULTS

The IRR using the modified ISAT was high at 0.80 (p < 0.001). Ratings were significantly correlated with trainee objective suturing scores for all rater groups (experts: R = 0.84, residents: R = 0.81, and novices: R = 0.69; p < 0.001).

CONCLUSIONS

Incorporating video anchors (to define performance) in the ISAT led to high IRR and enabled novices to achieve similar consistency in their ratings as experts.

Visual behaviour in robotic surgery-Demonstrating the validity of the simulated environment

BACKGROUND

Eye metrics provide insight into surgical behaviour allowing differentiation of performance, however have not been used in robotic surgery. This study explores eye metrics of robotic surgeons in training in simulated and real tissue environments.

METHODS

Following the Fundamentals of Robotic Surgery (FRS), training curriculum novice robotic surgeons were trained to expert-derived benchmark proficiency using real tissue on the da Vinci Si and the da Vinci skills simulator (dVSS) simulator. Surgeons eye metrics were recorded using eye-tracking glasses when both "novice" and "proficient" in both environments. Performance was assessed using Global Evaluative Assessment of Robotic skills (GEARS) and numeric psychomotor test score (NPMTS) scores.

RESULTS

Significant (P ≤ .05) correlations were seen between pupil size, rate of change and entropy, and associated GEARS/NPMTS in "novice" and "proficient" surgeons. Only number of blinks per minute was significantly different between pupilometrics in the simulated and real tissue environments.

CONCLUSIONS

This study illustrates the value of eye tracking as an objective physiological tool in the robotic setting. Pupilometrics significantly correlate with established assessment methods and could be incorporated into robotic surgery assessments.

Artificial intelligence and robotics: a combination that is changing the operating room

PURPOSE

The aim of the current narrative review was to summarize the available evidence in the literature on artificial intelligence (AI) methods that have been applied during robotic surgery.

METHODS

A narrative review of the literature was performed on MEDLINE/Pubmed and Scopus database on the topics of artificial intelligence, autonomous surgery, machine learning, robotic surgery, and surgical navigation, focusing on articles published between January 2015 and June 2019. All available evidences were analyzed and summarized herein after an interactive peer-review process of the panel.

LITERATURE REVIEW

The preliminary results of the implementation of AI in clinical setting are encouraging. By providing a readout of the full telemetry and a sophisticated viewing console, robot-assisted surgery can be used to study and refine the application of AI in surgical practice. Machine learning approaches strengthen the feedback regarding surgical skills acquisition, efficiency of the surgical process, surgical guidance and prediction of postoperative outcomes. Tension-sensors on the robotic arms and the integration of augmented reality methods can help enhance the surgical experience and monitor organ movements.

CONCLUSIONS

The use of AI in robotic surgery is expected to have a significant impact on future surgical training as well as enhance the surgical experience during a procedure. Both aim to realize precision surgery and thus to increase the quality of the surgical care. Implementation of AI in master-slave robotic surgery may allow for the careful, step-by-step consideration of autonomous robotic surgery.

Ergonomics Analysis for Subjective and Objective Fatigue Between Laparoscopic and Robotic Surgical Skills Practice Among Surgeons

Introduction. Our aim was to determine how self-reported and objectively measured fatigue of upper limb differ between laparoscopic and robotic surgical training environments. Methods. Surgeons at the 2016 SAGES Conference Learning Center and at our institution were enrolled. Two standardized surgical tasks (peg transfer [PT] and needle passing [NP]) were performed twice in each surgical skills practical environments: (1) laparoscopic training-box environment (Fundamentals of Laparoscopic Surgery [FLS]) and (2) Mimic dV-trainer (MIMIC). Muscle activation of upper trapezius (UT), anterior deltoid (AD), flexor carpi radialis, and extensor digitorum were recorded using surface electromyography (EMG; Trigno, Delsys, Inc, Natick, MA). Subjective fatigue was self-reported using Piper Fatigue Scale-12. Analysis was done using SPSS v25.0, α = .05. Results. Demographics were similar between FLS (N = 14) and MIMIC (N = 12). For PT, MIMIC had a significant increase in EMG_RMS of UT (P < .001) and AD (P < .001). Conversely, FLS led to significant decreased muscle fatigue in UT (P = .015). For NP, MIMIC had a significant increase in EMG_RMS for UT (P = .034) and AD (P = .031), but FLS induced more muscle fatigue for AD (P = .004). There was significant decrease in self-reported fatigue after performing FLS tasks (P = .030) but not after MIMIC (P = .663). Conclusion. Our results showed that practice with MIMIC resulted in greater activation of shoulder muscles, while FLS caused more significant muscle fatigue in the same muscles. This could be due to ergonomic disadvantages and nonoptimal ergonomic settings. Further studies are needed to understand the optimal ergonomics and its impact on fatigue and muscle activation during use of both the FLS and MIMIC training systems.

Developing an intelligent tutoring system for robotic-assisted surgery instruction

BACKGROUND

Robotic-assisted laparoscopic surgery (RALS) is an operative innovation that has sparked global interest. Over the last decade, RALS cases have rapidly increased with over 750 000 robotic procedures completed in 2017. Until recently, Intuitive's da Vinci surgical system has been the only Food and Drug Administration (FDA)-approved robotic-assisted surgical device for human procedures. Robotic procedures with the da Vinci require a specific, dedicated training due to the introduction of the technological components and psychomotor skills needed to successfully utilize this system. When a surgeon becomes interested in learning robotics, there are limited avenues for training. Surgeons typically receive instruction on the necessary psychomotor and Operation Room (OR) communication skills in isolation from the cognitive and perceptual skills and may only perform these skills in an integrated manner during a 1- or 2-day course.

METHODS

This paper discusses the development of a computer-based intelligent tutoring system (ITS) to train the cognitive and procedural skills needed to complete basic robotic suturing to novice robotic surgeons. The system was developed using the generalized intelligent framework for tutoring framework of tools. This information was captured as video, instruction sets, and flowcharts, which were reviewed for accuracy by surgeons and then encoded into an ITS using the generalized intelligent framework for tutoring tools.

CONCLUSION

The purpose of this paper was threefold-(a) explain the process used to obtain the critical data behind a basic robotic task, (b) develop an entry-level ITS to train the cognitive process and procedural steps behind multiple fundamental robotic surgery skills, and (c) provide future novice ITS developers lessons learned and future recommendations beyond the initial ITS prototype.

The safety of urologic robotic surgery depends on the skills of the surgeon

PURPOSE

To assess the available literature evidence that discusses the effect of surgical experience on patient outcomes in robotic setting. This information is used to help understand how we can develop a learning process that allows surgeons to maximally accommodate patient safety.

METHODS

A literature search of the MEDLINE/PubMed and Scopus database was performed. Original and review articles published in the English language were included after an interactive peer-review process of the panel.

RESULTS

Robotic surgical procedures require high level of experience to guarantee patient safety. This means that, for some procedures, the learning process might be longer than originally expected. In this context, structured training programs that assist surgeons to improve outcomes during their learning processes were extensively discussed. We identified few structured robotic curricula and demonstrated that for some procedures, curriculum trained surgeons can achieve outcomes rates during their initial learning phases that are at least comparable to those of experienced surgeons from high-volume centres. Finally, the importance of non-technical skills on patient safety and of their inclusion in robotic training programs was also assessed.

CONCLUSION

To guarantee safe robotic surgery and to optimize patient outcomes during the learning process, standardized and validated training programs are instrumental. To date, only few structured validated curricula exist for standardized training and further efforts are needed in this direction.