The deconstructed procedural description in robotic colorectal surgery

Increasing robotic surgical utilisation in colorectal surgery internationally has strengthened the need for standardised training. Deconstructed procedural descriptions identify components of an operation that can be integrated into proficiency-based progression training. This approach allows both access to skill level appropriate training opportunities and objective and comparable assessment. Robotic colorectal surgery has graded difficulty of operative procedures lending itself ideally to component training. Developing deconstructed procedural descriptions may assist in the structure and progression components in robotic colorectal surgical training. There is no currently published guide to procedural descriptions in robotic colorectal surgical or assessment of their training utility. This scoping review was conducted in June 2022 following the PRISMA-ScR guidelines to identify which robotic colorectal surgical procedures have available component-based procedural descriptions. Secondary aims were identifying the method of development of these descriptions and how they have been adapted in a training context. 20 published procedural descriptions were identified covering 8 robotic colorectal surgical procedures with anterior resection the most frequently described procedure. Five publications included descriptions of how the procedural description has been utilised for education and training. From these publications terminology relating to using deconstructed procedural descriptions in robotic colorectal surgical training is proposed. Development of deconstructed robotic colorectal procedural descriptions (DPDs) in an international context may assist in the development of a global curriculum of component operating competencies supported by objective metrics. This will allow for standardisation of robotic colorectal surgical training and supports a proficiency-based training approach.

Assessing the efficacy of dissection gestures in robotic surgery

Our group previously defined a dissection gesture classification system that deconstructs robotic tissue dissection into its most elemental yet meaningful movements. The purpose of this study was to expand upon this framework by adding an assessment of gesture efficacy (ineffective, effective, or erroneous) and analyze dissection patterns between groups of surgeons of varying experience. We defined three possible gesture efficacies as ineffective (no meaningful effect on the tissue), effective (intended effect on the tissue), and erroneous (unintended disruption of the tissue). Novices (0 prior robotic cases), intermediates (1-99 cases), and experts (≥ 100 cases) completed a robotic dissection task in a dry-lab training environment. Video recordings were reviewed to classify each gesture and determine its efficacy, then dissection patterns between groups were analyzed. 23 participants completed the task, with 9 novices, 8 intermediates with median caseload 60 (IQR 41-80), and 6 experts with median caseload 525 (IQR 413-900). For gesture selection, we found increasing experience associated with increasing proportion of overall dissection gestures (p = 0.009) and decreasing proportion of retraction gestures (p = 0.009). For gesture efficacy, novices performed the greatest proportion of ineffective gestures (9.8%, p < 0.001), intermediates commit the greatest proportion of erroneous gestures (26.8%, p < 0.001), and the three groups performed similar proportions of overall effective gestures, though experts performed the greatest proportion of effective retraction gestures (85.6%, p < 0.001). Between groups of experience, we found significant differences in gesture selection and gesture efficacy. These relationships may provide insight into further improving surgical training.

Development and validation of the metric-based assessment of a robotic vessel dissection, vessel loop positioning, clip applying and bipolar coagulation task on an avian model

The evolution of robotic technology and its diffusion does not seem to have been adequately accompanied by the development and implementation of surgeon training programs that ensure skilled and safe device use at the start of the learning curve. The objective of the study is to develop and validate performance metrics for vessel dissection, vessel loop positioning, clip applying and bipolar coagulation using an avian model. Three robotic surgeons and a behavioral scientist characterized the performance metrics of the task according to the proficiency-based progression methodology. Fourteen experienced robotic surgeons from different European countries participated in a modified online Delphi consensus. Eight experienced surgeons and eight novices performed the robotic task twice. In the Delphi meeting, 100% consensus was reached on the performance metrics. Novice surgeons took 26 min to complete the entire task on trial 1 and 20 min on trial 2. Experts took 10.1 min and 9.5 min. On average the Expert Group completed the task 137% faster than the Novice Group. The amount of time to reach the vessel part of the task was also calculated. Novice surgeons took 26 min on trial 1 and 20 min on trial 2. Experts took 5.5 min and 4.8 min. On average the experts reached the vessel 200% faster than the novices. The Expert Group made 155% fewer performance errors than the Novice Group. The mean IRR of video-recorded performance assessments for all metrics was 0.96 (95% confidence intervals (CI) lower = 0.94-upper = 0.98). We report the development and validation for a standard and replicable basic robotic vessel dissection, vessel loop positioning, clip applying and bipolar coagulation task on an avian model. The development of objective performance metrics, based on a transparent and fair methodology (i.e., PBP), is the first fundamental step toward quality assured training. This task developed on the avian model proved to have good results in the validation study.

A Standardized Robotic Training Curriculum in a General Surgery Program

Background and Objectives:

The general surgery residency at the University of Illinois College of Medicine at Peoria has a long tradition of integrating robotic surgery into training since 2002. The purpose of this paper is to investigate our curriculum and evaluation system, which was designed to achieve a standardized format for education in general robotic surgery.

Methods:

The curriculum consists of two phases: phase 1 (PGY 1–2): Complete 4 robotic surgery training modules; read two assigned robotic surgery articles; and practice simulation modules on the robot. phase 2 (PGY 3–5): Refresh training modules, score >90% on the simulator modules every 6 months; bedside assist minimum of 4 robotic procedures; and act as console surgeon for a minimum of 10 procedures with 2 separate attending surgeons. The required simulator modules were specially selected to incorporate all of the skills categories documented in the simulator. The faculty evaluate the resident's operative performance using the Global Evaluative Assessment of Robotic Skills validated rubric.

Results:

Since the curriculum was instituted in June 2017, 73 evaluations from 8 surgeons have been collected. We examined data from 6 residents who had at least 5 Global Evaluative Assessment of Robotic Skills assessments completed. Correlation coefficient scores showed a positive correlation ranging from 0.476 to 0.862 for average skills and 0.334 to 0.866 for overall performance scores.

Discussion:

The preliminary results suggest an improvement of resident robotic surgical skills through tailored education. This curriculum is designed to enhance robotic general surgery education that could potentially produce general surgeons able to operate robotically without needing a robotic/MIS (Minimally Invasive Surgery) fellowship.

Using objective robotic automated performance metrics and task-evoked pupillary response to distinguish surgeon expertise

PURPOSE

In this study, we investigate the ability of automated performance metrics (APMs) and task-evoked pupillary response (TEPR), as objective measures of surgeon performance, to distinguish varying levels of surgeon expertise during generic robotic surgical tasks. Additionally, we evaluate the association between APMs and TEPR.

METHODS

Participants completed ten tasks on a da Vinci Xi Surgical System (Intuitive Surgical, Inc.), each representing a surgical skill type: EndoWrist^® manipulation, needle targeting, suturing/knot tying, and excision/dissection. Automated performance metrics (instrument motion tracking, EndoWrist^® articulation, and system events data) and TEPR were recorded by a systems data recorder (Intuitive Surgical, Inc.) and Tobii Pro Glasses 2 (Tobii Technologies, Inc.), respectively. The Kruskal-Wallis test determined significant differences between groups of varying expertise. Spearman's rank correlation coefficient measured associations between APMs and TEPR.

RESULTS

Twenty-six participants were stratified by robotic surgical experience: novice (no prior experience; n = 9), intermediate (< 100 cases; n = 9), and experts (≥ 100 cases; n = 8). Several APMs differentiated surgeon experience including task duration (p < 0.01), time active of instruments (p < 0.03), linear velocity of instruments (p < 0.04), and angular velocity of dominant instrument (p < 0.04). Task-evoked pupillary response distinguished surgeon expertise for three out of four task types (p < 0.04). Correlation trends between APMs and TEPR revealed that expert surgeons move more slowly with high cognitive workload (ρ < - 0.60, p < 0.05), while novices move faster under the same cognitive experiences (ρ > 0.66, p < 0.05).

CONCLUSIONS

Automated performance metrics and TEPR can distinguish surgeon expertise levels during robotic surgical tasks. Furthermore, under high cognitive workload, there can be a divergence in robotic movement profiles between expertise levels.

Training in Robotic Surgery-an Overview

PURPOSE OF REVIEW

There has been a rapid and widespread adoption of the robotic surgical system with a lag in the development of a comprehensive training and credentialing framework. A literature search on robotic surgical training techniques and benchmarks was conducted to provide an evidence-based road map for the development of a robotic surgical skills for the novice robotic surgeon.

RECENT FINDINGS

A structured training curriculum is suggested incorporating evidence-based training techniques and benchmarks for progress. This usually involves sequential progression from observation, case assisting, acquisition of basic robotic skills in the dry and wet lab setting along with achievement of individual and team-based non-technical skills, modular console training under supervision, and finally independent practice. Robotic surgical training must be based on demonstration of proficiency and safety in executing basic robotic skills and procedural tasks prior to independent practice.