Reply

Simulation-based training improves clinical skills, while minimizing the impact of the educational process on patient care. We present results of a pilot multidisciplinary, simulation-based robotic surgery basic skills training curriculum (BSTC) for robotic novices. A 4-week, simulation-based, robotic surgery BSTC was offered to the Departments of Surgery and Obstetrics & Gynecology (ObGyn) at the University of Toronto. The course consisted of various instructional strategies: didactic lecture, self-directed online-training modules, introductory hands-on training with the da Vinci robot (dVR) (Intuitive Surgical Inc., Sunnyvale, CA), and dedicated training on the da Vinci Skills Simulator (Intuitive Surgical Inc., Sunnyvale, CA) (dVSS). A third of trainees participated in competency-based dVSS training, all others engaged in traditional time-based training. Pre- and post-course skill testing was conducted on the dVR using 2 standardized skill tasks: ring transfer (RT) and needle passing (NP). Retention of skills was assessed at 5 months post-BSTC. A total of 37 participants completed training. The mean task completion time and number of errors improved significantly post-course on both RT (180.6 vs. 107.4 sec, p < 0.01 and 3.5 vs. 1.3 sec, p < 0.01, respectively) and NP (197.1 vs. 154.1 sec, p < 0.01 and 4.5 vs. 1.8 sec, p = 0.04, respectively) tasks. No significant difference in performance was seen between specialties. Competency-based training was associated with significantly better post-course performance. The dVSS demonstrated excellent face validity. The implementation of a pilot multidisciplinary, simulation-based robotic surgery BSTC revealed significantly improved basic robotic skills among novice trainees, regardless of specialty or level of training. Competency-based training was associated with significantly better acquisition of basic robotic skills.

We aim to develop quantitative performance metrics and a deep learning model to objectively assess surgery skills between the novice and the expert surgeons for arthroscopic rotator cuff surgery. These proposed metrics can be used to give the surgeon an objective and a quantitative self-assessment platform. Ten shoulder arthroscopic rotator cuff surgeries were performed by two novices, and fourteen were performed by two expert surgeons. These surgeries were statistically analyzed. Two existing evaluation systems: Basic Arthroscopic Knee Skill Scoring System (BAKSSS) and the Arthroscopic Surgical Skill Evaluation Tool (ASSET), were used to validate our proposed metrics. In addition, a deep learning-based model called Automated Arthroscopic Video Evaluation Tool (AAVET) was developed toward automating quantitative assessments. The results revealed that novice surgeons used surgical tools approximately 10% less effectively and identified and stopped bleeding less swiftly. Our results showed a notable difference in the performance score between the experts and novices, and our metrics successfully identified these at the task level. Moreover, the F1-scores of each class are found as 78%, 87%, and 77% for classifying cases with no-tool, electrocautery, and shaver tool, respectively. We have constructed quantitative metrics that identified differences in the performances of expert and novice surgeons. Our ultimate goal is to validate metrics further and incorporate these into our virtual rotator cuff surgery simulator (ViRCAST), which has been under development. The initial results from AAVET show that the capability of the toolbox can be extended to create a fully automated performance evaluation platform.

Robotic surgical systems quantify human movements in terms of position, velocity, and time span. This information can be used to objectively assess surgical skill. The aim of this study was to test the effects of three-dimensional vs. two-dimensional visualization on performance using the da Vinci Surgical System (Intuitive Surgical, Sunnyvale, CA). The movements of novice and expert surgeons were recorded using the da Vinci Surgical System for a two-handed task in two visual environments (two-dimensional and three-dimensional). Data were analyzed to investigate the effect of visual feedback on performance. Velocities and task completion times were significantly different for novices and experts (P < 0.05) for all velocity parameters in both visual conditions. Additionally, there was a significant difference between two-dimensional and three-dimensional times for novices (P < 0.05). Novices were idle significantly longer in two-dimensional than in three-dimensional visual input (P = 0.037), and overall, novices were idle longer than experts for both visual conditions (P = 0.001). Three-dimensional visual input allows novice surgeons to perform tasks with higher velocities, less idle time, and greater economy of motion. However, three-dimensional visual input provides no significant enhancement of performance for expert surgeons.

Accuracy of robotic-assisted pedicle screw placement comparing junior surgeons with expert surgeons: Can junior surgeons place pedicle screws as accurately as expert surgeons?

The Validation of a Novel Robot-Assisted Radical Prostatectomy Virtual Reality Module

Robotic transthoracic diaphragmatic hernia repair

Optimizing Robotic Simulation Training Among Obstetrics and Gynecology (OBGYN) Residents: A Randomized Pilot Study

Fifth International Consensus Conference: current status of sleeve gastrectomy

Editorial Comment

Author reply

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. 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. 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). 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.

EinleitungDer Einsatz roboterassistierter Operationen verzeichnet in der Viszeralchirurgie gegenwärtig einen stetigen Zuwachs. Im Jahr 2020 hat die COVID-19-Pandemie den klinischen und chirurgischen Alltag unerwartet wesentlich verändert. Wir haben in einer Umfrage den Status der roboterassistierten Viszeralchirurgie in Deutschland sowie die gegenwärtigen Ausbildungskonzepte evaluiert und deren Veränderungen unter dem Einfluss der COVID-19-Pandemie untersucht.Material und MethodenIn einer umfangreichen Recherche wurden 89 Kliniken identifiziert, welche ein Robotersystem für die Viszeralchirurgie 2020 einsetzten. Diese Kliniken wurden über eine webbasierte anonyme Umfrage mit 35 Fragen dreimal kontaktiert. Die Fragen bezogen sich auf die Einsatzgebiete eines Operationsroboters in der Viszeralchirurgie, die dazugehörige klinische Ausbildung und den Einfluss der COVID-19-Pandemie auf das bestehende Programm.ErgebnisseVon den angeschriebenen Kliniken haben 22 (24,7%) eine Rückmeldung gegeben. Hiervon waren 17 (19,1%) Fragebögen auswertbar. Es beteiligten sich 58,8% Universitätsklinika, 17,6% Maximalversorger und 23,5% Schwerpunktkrankenhäuser an der Studie. Der Operationsroboter wurde am oberen Gastrointestinaltrakt (OGIT; 88,2%), am hepatopankreatikobiliären System (HPB; 82,4%) und im kolorektalen Bereich (KRK; 94,1%) sowie bei der Hernienversorgung (35,3%) eingesetzt. Der relative Anteil robotischer Eingriffe am operierten Gesamtkollektiv lag dabei zwischen 0,3% und 15,4%. Die Konversionsraten für 2020 lag im Mittel bei 4,6 ± 3,2%. Die Operationsroboter wurden zum Großteil im interdisziplinären Setting wechselweise mit anderen chirurgischen Disziplinen (82,4%) genutzt. Zu Lehrzwecken stand in sieben Kliniken (41,2%) eine zweite Konsole zur Verfügung. Die Ausbildungsstrukturen waren sehr heterogen und nur 13,2 ± 6,5% der Chirurg*innen pro Klinik waren in das Roboterprogramm involviert. In 82,4% existierten feste Teams, die sich aus Ober‑, Fach- und Assistenzärzt*innen zusammensetzen und in 76,5% wurden Ärzt*innen und Pflegepersonal über klinikinterne Ausbildungsprogramme geschult. Die COVID-19-Pandemie hatte einen Fallzahlrückgang robotischer Eingriffe im Vergleich zu 2019 bei 70% der Kliniken vor allem im zweiten Jahresquartal 2020 (64,7%) zur Folge. Dies wurde auf Personalmangel nichtchirurgischer Disziplinen (Anästhesie 35,3%, OP-Pflege 35,3%, Intensivmedizin 17,6%), interne Regularien (58,8%) und begrenzte Intensiv- oder Überwachungskapazitäten (47,1%) zurückgeführt. Die COVID-19-Pandemie führte in der robotischen Ausbildung teilweise bei der Assistenz am OP-Tisch (23,5%) und der Assistenz an der zweiten Konsole (42,9%) zu einem kompletten Ausbildungsstopp. Ausschlaggebend für diese Entwicklung war überwiegend der Rückgang der Operationszahlen.SchlussfolgerungDie Robotik wird mittlerweile in einem breiten Spektrum der Viszeralchirurgie an Kliniken mit unterschiedlichen Versorgungsschwerpunkten in Deutschland eingesetzt. Der relative Anteil der Eingriffe am Gesamtspektrum ist allerdings noch gering. Roboterassistierte Eingriffe sind expertenfokussiert und es bestehen sehr heterogene Ausbildungskonzepte. Ein Lernerfolg mit konstanten und niedrigen Konversionsraten ist nach wenigen Jahren mit zunehmender Erfahrung zu erkennen. Die COVID-19-Pandemie hatte insgesamt einen negativen Einfluss auf die robotischen OP-Fallzahlen und die damit verbundenen Ausbildungsmöglichkeiten bei freien chirurgischen Personalressourcen. Hier ist eine kreative Gestaltung optimierter Ausbildungsmodalitäten erforderlich.

Editorial Comment

Video-based learning, a form of nonsynchronous imitation, is widely used in robotic surgical training. However, the effectiveness of synchronous imitation, in which trainees replicate expert movements in real time, remains unclear. This study aimed to evaluate the effect of synchronous imitation on robotic surgical skill acquisition. A randomized-controlled trial was conducted with 20 novices in robotic surgery, between April 2023 and March 2024. Participants were stratified by suturing experience and randomly assigned to either the synchronous or nonsynchronous group. The training task was "Thread the Rings" on the da Vinci Skills Simulator. Before each of the 10 trials, participants in the synchronous group watched a recorded expert demonstration and attempted to mimic instrument movements in real time. In contrast, the nonsynchronous group viewed the same video passively without simultaneous imitation. Proficiency scores (0-100) were calculated automatically for each trial. Both groups demonstrated improvement over time; however, mixed-effects regression models showed no significant difference in the rate of score improvement between the two groups (P = 0.88). Synchronous imitation did not lead to superior skill acquisition compared with video-based observations alone. Further research with a larger sample size is warranted to validate these findings.

PurposeLaparoscopy is used in many surgical specialties. Subjective reports have suggested that performing laparoscopic surgery in patients with a high body mass index (BMI) is leading to increased prevalence of musculoskeletal symptoms in surgeons. The aim of this study was to objectively quantify the impact on surgeon upper body kinematics and dynamic workload when performing simulated laparoscopy at different BMI levels.MethodsUpper body kinematics and dynamic workload of novice, intermediate and expert surgeons were calculated based on measurements from inertial measurement units positioned on upper body segments. Varying thicknesses of foam were used to simulate patient BMIs of 20, 30, 40 and 50 kg/m2 during laparoscopic training.ResultsSignificant increases in the jerkiness, angular speed and cumulative displacement of the head, torso and upper arms were found within all experience groups when subject to the 40 and 50 kg/m2 models. Novice surgeons were found to have less controlled kinematics and larger dynamic workloads compared to the more experienced surgeons.ConclusionsOur findings indicate that performing laparoscopic surgery on a high BMI model worsens upper body motion efficiency and efficacy, and increases dynamic workload, producing conditions that are more physically demanding when compared to operating on a 20 kg/m2 model. These findings also suggest that the head, torso, and upper arm segments are especially affected by high BMI models and therefore exposure to patients with high BMIs may increase the risk of musculoskeletal injury when performing laparoscopic surgery.