Learning Experiences in Robotic-Assisted Laparoscopic Surgery

Novel workflow analysis of robot-assisted hysterectomy through objective performance indicators: a pilot study

Introduction

The curriculum for a da Vinci surgeon in gynecology requires special training before a surgeon performs their first independent case, but standardized, objective assessments of a trainee's workflow or skills learned during clinical cases are lacking. This pilot study presents a methodology to evaluate intraoperative surgeon behavior in hysterectomy cases through standardized surgical step segmentation paired with objective performance indicators (OPIs) calculated directly from robotic data streams. This method can provide individual case analysis in a truly objective capacity.

Materials and methods

Surgical data from six robot-assisted total laparoscopic hysterectomies (rTLH) performed by two experienced surgeons was collected prospectively using an Intuitive Data Recorder. Each rTLH video was annotated and segmented into specific, functional surgical steps based on the recorded video. Once annotated, OPIs were compared through workflow analysis and across surgeons during two critical surgical steps: colpotomy and vaginal cuff closure.

Results

Through visualization of the individual steps over time, we observe workflow consistencies and variabilities across individual surgeons of a similar experience level at the same hospital, creating unique surgeon behavior signatures across each surgical case. OPI differences across surgeons were observed for both the colpotomy and vaginal cuff closure steps, specifically reflecting camera movement, energy usage and clutching behaviors. Comparing colpotomy and vaginal cuff closure time needed for the step and the events of energy use were significantly different (p < 0.001). For the comparison between the two surgeons only the event count for camera movement during colpotomy showed significant differences (p = 0.03).

Conclusion

This pilot study presents a novel methodology to analyze and compare individual rTLH procedures with truly objective measurements. Through collection of robotic data streams and standardized segmentation, OPI measurements for specific rTLH surgery steps can be reliably calculated and compared to those of other surgeons. This provides opportunity for critical standardization to the gynecology field, which can be integrated into individualized training plans in the future. However, more studies are needed to establish context surrounding these metrics in gynecology.

Robot-Assisted Surgery in Gynecology

The advancement of robotics-based procedures in the medical industry is the subject of this review article. The purpose of the surgical robot is to increase surgical abilities and address human shortcomings. The robot's success has been predicated on its ability to accurately and consistently repeat tasks. The following are a few objectives and quantifiable benefits of robotic technology improving surgical maneuverability and physical capabilities. In 2005, the FDA granted gynecological surgery approval for the Da Vinci surgical system. It has been quickly embraced and has already taken on a significant role at many of the locations where it is offered. It consists of a cart with robotic branches next to the patient and a high-resolution three-dimensional (3D) vision system. This study covers laparoscopy via robots in benign gynecological surgeries, myomectomy surgery, hysterectomies, endometriosis, tubal anastomosis, and sacrocolpopexy. The appropriate published studies were evaluated after a PubMed search was conducted. Additionally, procedures that may be used in the future are highlighted. In benign gynecological illness, most currently available research does not show a substantial benefit over traditional laparoscopic surgery. Robotics, however, does provide help in more complicated operations. Compared to laparoscopy, robotic assistance has a lower conversion rate to open procedures. Endo wrist movement of an automated machine during myomectomy surgery can perform proper and better suturing than traditional laparoscopy. The automated program is a noticeable improvement over laparoscopic surgery and, if price issues are resolved, can gain popularity among gynecological surgeons around the globe.

The role of the bedside assistant in robot-assisted surgery: A critical synthesis

INTRODUCTION

Robot-assisted surgery has grown exponentially since its inception and first approval in the United States in the year 2000. The surgeon operating with the assistance of the robot sits remotely to the patient and another practitioner assists at the bedside. The role of the bedside assistant and the training that is required to undertake this role are understudied topics.

AIM

To explore the functions, training and professional development of the bedside assistant in robot-assisted surgery and propose the necessary foundations for the safe enactment of the role in the United Kingdom.

METHODS

Through critical interpretative synthesis, relevant literature was systematically searched and analysed to inform integration of evidence.

RESULTS

Seventy-three studies were retrieved from the literature, across several health care disciplines and surgical specialities. These were critically analysed to inform a theoretically sound account grounded on evidence.

CONCLUSION

The role, functions and skills of the bedside assistant in robot-assisted surgery vary across contexts. These were analysed and critically synthetised to produce several keys to the success of bedside assistants in robot-assisted surgery in the context of the United Kingdom and of its national regulations.

A Cross-Sectional Study of Resident Training in Robotic Surgery in India

Background

The widespread implementation of robotic surgery in the Indian subcontinent has received mixed reactions from residents and mentors alike. To date, however, no study has documented the perception of Indian surgical trainees on the effect of robotic surgery on surgical training. Therefore, we conducted a questionnaire-based study on Indian surgical residents to assess their views about robotic surgery and the effect, they believe, it might have on resident training.

Materials and methods

Questionnaires were distributed to 300 surgical residents from programs that do not have surgical robots. All other residents, faculty, medical students, and interns were excluded from the study. The responses were collected and analyzed using appropriate statistical methods.

Results

Overall, 210 surgical residents responded to the survey. A majority of them (57.72%) reported low levels of knowledge regarding robotic surgery. While 88.10% of the study participants reported that the use of robotic surgery will continue to rise in India, an equal proportion (88%) believed that procuring a robot in their program will impair their training in open and laparoscopic surgeries.

Conclusions

The introduction of robotic surgery into surgical residency programs is seen, by most residents, as a threat to training in traditional surgical methods. This calls for the effective incorporation of robotic training into residency training with equal distribution of resident training cases in programs across the country.

Needle-Tissue Interaction Force State Estimation for Robotic Surgical Suturing

Robotically Assisted Minimally Invasive Surgery (RAMIS) offers many advantages over manual surgical techniques. Most of the limitations of RAMIS stem from its non-intuitive user interface and costs. One way to mitigate some of the limitations is to automate surgical subtasks (e.g. suturing) such that they are performed faster while allowing the surgeon to plan the next step of the procedure. One component of successful suture automation is minimizing the internal tissue deformation forces generated by driving a needle through tissue. Minimizing the internal tissue forces requires segmenting the tissue deformation forces from other components of the needle tissue interaction (e.g. friction force). This paper proposes an Unscented Kalman Filter which can successfully model the force components, in particular the internal deformation force, generated by a needle as it is driven through a sample of tissue.