Using Real-time Feedback To Improve Surgical Performance on a Robotic Tissue Dissection Task

Laca, Jasper; Kocielnik, Rafał; Nguyen, Jessica; You, Jonathan; Tsang, Ryan; Wong, Elyssa Y.; Shtulman, Andrew; Anandkumar, Anima; Hung, Andrew J.

doi:10.1016/j.euros.2022.09.015

Cited by 8 publications

(5 citation statements)

References 7 publications

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“…Unfortunately, these forms and measures of time and motion efficiency (i.e., instrument handling), provide limited quantitative information on the effect that these instruments have on the tissue. GEARS might be suitable to detect improvement of basic skills over time in inexperience trainees [ 41 , 42 ]. However, there is no association between laparoscopic experience and robotic-assisted suturing performance, according to OSATS scores, and there is evidence that assessment forms are not be suitable for the assessment of robotic technical skills and to differentiate between levels of expertise [ 43 , 44 ].…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2023

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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.

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Section: Discussionmentioning

confidence: 99%

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

et al. 2023

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“…They were then given real-time audio and visual feedback which was shown to improve dissection skills in underperformers [ 37 ]. Wong et al [ 38 ] have also developed a classification system for feedback delivered to trainees intraoperatively which lays the groundwork for determining what types of feedback are most optimal for surgical training [ 38 ]. Together, these studies are setting the stage for AI modeling that can understand a trainee’s weak points and deliver high-quality feedback for each trainee’s specific learning stage (Fig.…”

Section: Ai In Robotic Surgical Assessment and Feedbackmentioning

confidence: 99%

Clinical applications of artificial intelligence in robotic surgery

Knudsen,

Ghaffar,

et al. 2024

J Robotic Surg

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Artificial intelligence (AI) is revolutionizing nearly every aspect of modern life. In the medical field, robotic surgery is the sector with some of the most innovative and impactful advancements. In this narrative review, we outline recent contributions of AI to the field of robotic surgery with a particular focus on intraoperative enhancement. AI modeling is allowing surgeons to have advanced intraoperative metrics such as force and tactile measurements, enhanced detection of positive surgical margins, and even allowing for the complete automation of certain steps in surgical procedures. AI is also Query revolutionizing the field of surgical education. AI modeling applied to intraoperative surgical video feeds and instrument kinematics data is allowing for the generation of automated skills assessments. AI also shows promise for the generation and delivery of highly specialized intraoperative surgical feedback for training surgeons. Although the adoption and integration of AI show promise in robotic surgery, it raises important, complex ethical questions. Frameworks for thinking through ethical dilemmas raised by AI are outlined in this review. AI enhancements in robotic surgery is some of the most groundbreaking research happening today, and the studies outlined in this review represent some of the most exciting innovations in recent years.

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“…Other essential training aspects include feedback and autonomy, as both live feedback and autonomy have enhanced residents' confidence and facilitated their transition to independent practice. 25,26,27 There is little knowledge on the optimal balance between patient safety and resident autonomy or the described "safe struggle." However, graded increases in resident autonomy, such as chief resident services, are essential to address gaps in confidence and preparation for independent practice.…”

confidence: 99%

Graduating resident and fellow readiness for general urologic practice during the COVID-19 pandemic

Waisanen,

Hennig,

Lutnick

et al. 2024

CUAJ

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Introduction: Our goal was to compare the perceived readiness of graduating urologic residents and fellows to program directors (PDs) in U.S.-based postgraduate training programs. Additionally, we set out to assess the impact of COVID-19 on postgraduation plans to pursue fellowship training. Methods: Graduating residents, fellows, and PDs of accredited residency/fellowship programs in the U.S. were surveyed. The ranked preparedness of trainees to perform common urologic procedures was measured using a Likert scale from 1 (not comfortable) to 5 (fully proficient). The impact of COVID-19 was measured using a three-point Likert scale. Chi-squared and Kruskal-Wallis analyses were used to compare the groups. Results: From 93 responders, 21 were residents, 19 were fellows, 24 were residency PDs, and 29 were fellowship PDs. The median levels of comfort for transurethral resection of the prostate, hydrocelectomy, vasectomy, and urethral sling were at or above (≥3) moderate for both PDs and trainees. PDs were more likely to report underperformance for hypospadias repair (60% vs. 39%), penile prosthesis implantation (39% vs. 26%), and orthotopic neobladder formation (57% vs. 18%) than the trainees. Fifty-three (57.0%) of the surveyors felt that COVID-19 did not impact the trainees’ comfort in performing general urologic procedures. COVID-19 influenced trainees' decision to pursue a fellowship or opt to practice as general urologists (p=0.002). Conclusions: Our study suggests there may be a self-reported discrepancy between graduating trainees and their PDs regarding trainees’ comfort levels performing general urologic procedures.

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Using Real-time Feedback To Improve Surgical Performance on a Robotic Tissue Dissection Task

Cited by 8 publications

References 7 publications

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

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

Clinical applications of artificial intelligence in robotic surgery

Graduating resident and fellow readiness for general urologic practice during the COVID-19 pandemic

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