The role of surgical simulation and the learning curve in robot-assisted surgery

Revolutionising Breast Surgery: A Comprehensive Review of Robotic Innovations in Breast Surgery and Reconstruction

Robotic innovations in breast surgery have ushered in a new era of precision, safety, and patient-centred care. This comprehensive review explores the multifaceted realm of robotic breast surgery, from preoperative planning to postoperative outcomes, learning curves for surgeons, and the implications for healthcare policies. We examine the ethical considerations, cost-effectiveness, and future directions, including integrating artificial intelligence and telesurgery. Key findings reveal that robotic systems provide improved surgical precision, reduced complications, and enhanced patient satisfaction. Ethical concerns encompass informed consent, resource allocation, and equitable access. The future of breast surgery lies in continued research and development, ensuring that robotics becomes a standard of care accessible to all patients. This technology is reshaping breast surgery and offering new possibilities for minimally invasive, patient-centred care, ultimately redefining the standards of care in this critical field of medicine.

Identifying barriers to resident robotic console time in a general surgery residency through a targeted needs assessment

Robotic-assisted general surgery is experiencing exponential growth. Despite our institution's high volume, residents often graduate with inadequate console experience. Our aim was to identify the educational needs of residents and perceived barriers to residents' console time from both attendings and residents. Separate surveys were created and distributed to robotic surgery faculty and general surgery residents at our institution. Questions were a variety of modalities and focused on the robotic surgery experience at our institution, including barriers to resident console time from both attending surgeon and resident perspectives. Although residents' interest in robotic surgery exceeded that of open and laparoscopic surgery, confidence in their robotic skills was low compared to the other modalities. The top barriers to participating in robotic cases according to residents included minimal or no previous console time with the attending, lack of simulator time, and being required to perform bedside assistant duties. Faculty reported resident preparedness, prior robotic skill demonstration, simulator time, case complexity, and their own confidence as significant factors influencing resident console time. Using these results, we concluded that the design and implementation of a formal robotic surgery curriculum should incorporate simulation-based opportunities for residents to practice their skills, improve confidence, and increase console experience. In addition, simulation opportunities for faculty should also be considered to allow for improvement and maintenance of robotic surgical skills.

Learning curves in robotic neurosurgery: a systematic review

The transition to performing procedures robotically generally entails a period of adjustment known as a learning curve as the surgeon develops a familiarity with the technology. However, no study has comprehensively examined robotic learning curves across the field of neurosurgery. We conducted a systematic review to characterize the scope of literature on robotic learning curves in neurosurgery, assess operative parameters that may involve a learning curve, and delineate areas for future investigation. PubMed, Embase, and Scopus were searched. Following deduplication, articles were screened by title and abstract for relevance. Remaining articles were screened via full text for final inclusion. Bibliographic and learning curve data were extracted. Of 746 resultant articles, 32 articles describing 3074 patients were included, of which 23 (71.9%) examined spine, 4 (12.5%) pediatric, 4 (12.5%) functional, and 1 (3.1%) general neurosurgery. The parameters assessed for learning curves were heterogeneous. In total, 8 (57.1%) of 14 studies found reduced operative time with increased cases, while the remainder demonstrated no learning curve. Six (60.0%) of 10 studies reported reduced operative time per component with increased cases, while the remainder indicated no learning curve. Radiation time, radiation time per component, robot time, registration time, setup time, and radiation dose were assessed by ≤ 4 studies each, with 0-66.7% of studies demonstrated a learning curve. Four (44.4%) of 9 studies on accuracy showed improvement over time, while the others indicated no improvement over time. The number of cases required to reverse the learning curve ranged from 3 to 75. Learning curves are common in robotic neurosurgery. However, existing studies demonstrate high heterogeneity in assessed parameters and the number of cases that comprise the learning curve. Future studies should seek to develop strategies to reduce the number of cases required to reach the learning curve.

A Comparative Human-Centric Analysis of Virtual Reality and Dry Lab Training Tasks on the da Vinci Surgical Platform

There is a growing, widespread trend of adopting robot-assisted minimally invasive surgery (RMIS) in clinical care. Dry lab robot training and virtual reality simulation are commonly used to train surgical residents; however, it is unclear whether both types of training are equivalent or can be interchangeable and still achieve the same results in terms of training outcomes. In this paper, we take the first step in comparing the effects of physical and simulated surgical training tasks on human operator kinematics and physiological response to provide a richer understanding of exactly how the user interacts with the actual or simulated surgical robot. Four subjects, with expertise levels ranging from novice to expert surgeon, were recruited to perform three surgical tasks — Continuous Suture, Pick and Place, Tubes, with three repetitions — on two training platforms: (1) the da Vinci Si Skills Simulator and (2) da Vinci S robot, in a randomized order. We collected physiological response and kinematic movement data through body-worn sensors for a total of 72 individual experimental trials. A range of expertise was chosen for this experiment to wash out inherent differences based on expertise and only focus on inherent differences between the virtual reality and dry lab platforms. Our results show significant differences ([Formula: see text]-[Formula: see text]) between tasks done on the simulator and surgical robot. Specifically, robotic tasks resulted in significantly higher muscle activation and path length, and significantly lower economy of volume. The individual tasks also had significant differences in various kinematic and physiological metrics, leading to significant interaction effects between the task type and training platform. These results indicate that the presence of the robotic system may make surgical training tasks more difficult for the human operator. Thus, the potentially detrimental effects of virtual reality training alone are an important topic for future investigation.

Quantitative Assessment of the Learning Curve for Robotic Thyroid Surgery

With the increased utilization of robot thyroidectomy in recent years, surgical proficiency is the paramount consideration. However, there is no single perfect or ideal method for measuring surgical proficiency. In this study, we evaluated the learning curve of robotic thyroidectomy using various parameters. A total of 172 robotic total thyroidectomies were performed by a single surgeon between March 2014 and February 2018. Cumulative summation analysis revealed that it took 50 cases for the surgeon to significantly improve the operation time. Mean operation time was significantly shorter in the group that included the 51st to the 172nd case, than in the group that included only the first 50 cases (132.8 ± 27.7 min vs. 166.9 ± 29.5 min; p < 0.001). On the other hand, the surgeon was competent after the 75th case when postoperative transient hypoparathyroidism was used as the outcome measure. The incidence of hypoparathyroidism gradually decreased from 52.0%, for the first 75 cases, to 40.2% after the 76th case. These results indicated that the criteria used to assess proficiency greatly influenced the interpretation of the learning curve. Incorporation of the operation time, complications, and oncologic outcomes should be considered in learning curve assessment.

Application of a Perception Neuron® System in Simulation-Based Surgical Training

While multiple studies show that simulation methods help in educating surgical trainees, few studies have focused on developing systems that help trainees to adopt the most effective body motions. This is the first study to use a Perception Neuron^® system to evaluate the relationship between body motions and simulation scores. Ten medical students participated in this study. All completed two standard tasks with da Vinci Skills Simulator (dVSS) and five standard tasks with thyroidectomy training model. This was repeated. Thyroidectomy training was conducted while participants wore a perception neuron. Motion capture (MC) score that indicated how long the tasks took to complete and each participant’s economy-of-motion that was used was calculated. Correlations between the three scores were assessed by Pearson’s correlation analyses. The 20 trials were categorized as low, moderate, and high overall-proficiency by summing the training model, dVSS, and MC scores. The difference between the low and high overall-proficiency trials in terms of economy-of-motion of the left or right hand was assessed by two-tailed t-test. Relative to cycle 1, the training model, dVSS, and MC scores all increased significantly in cycle 2. Three scores correlated significantly with each other. Six, eight, and six trials were classified as low, moderate, and high overall-proficiency, respectively. Low- and high-scoring trials differed significantly in terms of right (dominant) hand economy-of-motion (675.2 mm and 369.4 mm, respectively) (p = 0.043). Perception Neuron^® system can be applied to simulation-based training of surgical trainees. The motion analysis score is related to the traditional scoring system.

Comparison of effective teaching methods to achieve skill acquisition using a robotic virtual reality simulator: Expert proctoring versus an educational video versus independent training

BACKGROUND

To compare the superiority of teaching methods for acquiring a proficient level of surgical skill in a robotic surgery-naïve individual using a robotic virtual reality simulator.

METHODS

This study employed a prospective, randomized study design to assess student's learning curve. We divided 45 subjects into 3 groups: those with expert proctoring (group I), those who watched only an educational video (group II), and those with independent training (group III; n = 15 per group). The task used in this study was the Tube 2 and it imitates a vesicourethral anastomosis in robotic prostatectomy. The effects were analyzed by the time to end the task after overcoming the learning curve which is determined by several performance parameters.

RESULTS

The number of task repetitions required to reach the learning curve plateau was 45, 42, and 37 repetitions in groups I, II, and III, which means that there was continuous improvement in performing the task after 40 repetitions only in groups I and II. The mean time for completing the task during the stabilization period was significantly different between group I and group III and group II and group III, which means that the independent training method was inferior to the other methods (group I vs. group II vs. group III: 187.38 vs. 187.07 vs. 253.47 seconds, P < .001).

CONCLUSIONS

This study's findings showed that an educational video can be as beneficial as expert proctoring, which implies that the development of a standardized educational video would be worthwhile.

Validation of a novel virtual reality simulator for robotic surgery

Objective. With the increase in robotic-assisted laparoscopic surgery there is a concomitant rising demand for training methods. The objective was to establish face and construct validity of a novel virtual reality simulator (dV-Trainer, Mimic Technologies, Seattle, WA) for the use in training of robot-assisted surgery. Methods. A comparative cohort study was performed. Participants (n = 42) were divided into three groups according to their robotic experience. To determine construct validity, participants performed three different exercises twice. Performance parameters were measured. To determine face validity, participants filled in a questionnaire after completion of the exercises. Results. Experts outperformed novices in most of the measured parameters. The most discriminative parameters were “time to complete” and “economy of motion” (P < 0.001). The training capacity of the simulator was rated 4.6 ± 0.5 SD on a 5-point Likert scale. The realism of the simulator in general, visual graphics, movements of instruments, interaction with objects, and the depth perception were all rated as being realistic. The simulator is considered to be a very useful training tool for residents and medical specialist starting with robotic surgery. Conclusions. Face and construct validity for the dV-Trainer could be established. The virtual reality simulator is a useful tool for training robotic surgery.

Virtual reality training improves da Vinci performance: a prospective trial

INTRODUCTION

The DV-Trainer™ (a virtual reality [VR] simulator) (Mimic Technologies, Inc., Seattle, WA) is one of several different robotic surgical training methods. We designed a prospective study to determine whether VR training could improve da Vinci(®) Surgical System (Intuitive Surgical, Inc., Sunnyvale, CA) performance.

SUBJECTS AND METHODS

Surgeons (n=12) were enrolled using a randomized protocol. Groups 1 (VR training) and 2 (control) participated in VR and da Vinci exercises. Participants' time and moving distance were combined to determine a composite score: VR index=1000/(time×moving distance). The da Vinci exercises included needle control and suturing. Procedure time and error were measured. A composite index (DV index) was computed and used to measure da Vinci competency. After the initial trial with both the VR and da Vinci exercises, only Group 1 was trained with the VR simulator following our institutional curriculum for 3 weeks. All members of both groups then participated in the second trial of the VR and da Vinci exercises and were scored in the same way as in the initial trial.

RESULTS

In the initial trial, there was no difference in the VR index (Group 1 versus Group 2, 8.9 ± 3.3 versus 9.4 ± 3.7; P=.832) and the DV index (Group 1 versus Group 2, 3.85 ± 0.73 versus 3.66 ± 0.65; P=.584) scores between the two groups. At the second time point, Group 1 showed increased VR index scores in comparison with Group 2 (19.3 ± 4.5 versus 9.7 ± 4.1, respectively; P=.001) and improved da Vinci performance skills as measured by the DV index (5.80 ± 1.13 versus 4.05 ± 1.03, respectively; P=.028) and by suturing time (7.1 ± 1.54 minutes versus 10.55 ± 1.93 minutes, respectively; P=.018).

CONCLUSIONS

We found that VR simulator training can improve da Vinci performance. VR practice can result in an early plateau in the learning curve for robotic practice under controlled circumstances.

[Robot technology in the Italian Health-CARE system: cost-efficacy economic analysis]

BACKGROUND

Robotic technology is used in multiple fields of surgery, especially radical prostatectomy in patients with prostate cancer. The purpose of this study was to evaluate the introduction of robotic technology in the Italian Public Heath-care context, from the perspective of the Health Technology Assessment (HTA). An economic analysis that compares the costs and effectiveness of the method was developed. Data were compared with those of the most important international literature, analyzing structural and organizational problems related to the method.

MATERIALS AND METHODS

A systematic review of literature on tertiary literature (Health Technology Assessment reports) and secondary (systematic reviews) published since 2002 was conducted. The review was also conducted on more recent primary literature regarding the clinical effectiveness and the economic analysis in the fields of surgery where Da Vinci robot is most promising.

RESULTS

18 studies were selected out of a total of 65 evaluated. The "Break-Even Point" (BEP) is the minimum number of cases needed to be treated in order to achieve a balance between costs and revenues, below which the system is losing money. It was calculated that the total fixed costs are € 378,000 and variable costs are € 3,810 per surgery. Considering that the current value of DRG (Diagnosis-Related Group) refunded by the public Health-care system is actually € 4,553, the BEP would be achieved performing 508 surgeries, so that the robotic technology does not generate neither profit nor loss.

CONCLUSIONS

It is not possible to demonstrate the superiority of robotic surgery in terms of efficacy. The robotic surgery is safe and effective only if performed by surgical teams with relevant experience. Considering the reported case of an Italian University Hospital with public Health-care system refund, the BEP target of 508 radical prostatectomies could be achieved after a few years. The use of the robot in multiple fields on one hand shortens recovery time costs, but on the other hand increases costs due to organizational issues. The value of the DRG refund does not appear adequate to new robotic technology.

Training and learning robotic surgery, time for a more structured approach: a systematic review

BACKGROUND

Robotic assisted laparoscopic surgery is growing rapidly and there is an increasing need for a structured approach to train future robotic surgeons.

OBJECTIVES

To review the literature on training and learning strategies for robotic assisted laparoscopic surgery.

SEARCH STRATEGY

A systematic search of MEDLINE, EMBASE, the Cochrane Library and the Journal of Robotic Surgery was performed.

SELECTION CRITERIA

We included articles concerning training, learning, education and teaching of robotic assisted laparoscopic surgery in any specialism.

DATA COLLECTION AND ANALYSIS

Two authors independently selected articles to be included. We categorised the included articles into: training modalities, learning curve, training future surgeons, curriculum design and implementation.

MAIN RESULTS

We included 114 full text articles. Training modalities such as didactic training, skills training (dry lab, virtual reality, animal or cadaver models), case observation, bedside assisting, proctoring and the mentoring console can be used for training in robotic assisted laparoscopic surgery. Several training programmes in general and specific programmes designed for residents, fellows and surgeons are described in the literature. We provide guidelines for development of a structured training programme.

AUTHORS' CONCLUSIONS

Robotic surgical training consists of system training and procedural training. System training should be formally organised and should be competence based, instead of time based. Virtual reality training will play an import role in the near future. Procedural training should be organised in a stepwise approach with objective assessment of each step. This review aims to facilitate and improve the implementation of structured robotic surgical training programmes.