Design and validation of a low-cost, high-fidelity model for robotic pyeloplasty simulation training

Clinical application values of a novel synthetic training simulator for bulbar urethral anastomosis

Purpose

This study aimed to report a newly developed, high-fidelity synthetic simulator to simulate excision and primary anastomotic (EPA) bulbar urethroplasty and its clinical use for new practitioners in shortening the learning curve.

Material and Methods

The bulbar urethral anastomosis simulator consists of several standardized components created according to the actual size of the male patient. Interns, novice residents, and fellows inexperienced with urethral reconstruction (n = 10, 5, 5) from different medical centres were invited to participate in the training programme. Two reconstructive urology experts monitored each practice. Following the training, three kinds of validity testing were used to assess the simulator: face, content, and construct. In the intern group, the task performance in the first five training sessions and the last five training ones were compared using a self-control approach. In the resident and fellow group, the real surgical data, including estimated blood loss, operative duration, and 6-month post-operative success rate of trainees after training, are plotted, which are compared with that of reconstructive urology experts (n = 5) included retrospectively to study the effectiveness of the simulator in shortening the learning curve.

Results

The overall mean satisfaction rate for the simulators was inspiring and evaluated by experts. In the intern group, significant improvement can be achieved through 10 training sessions (p < 0.05). In clinical practice, the intraoperative indicators and surgical success rate of both the training groups showed the tendency to close or even better than those in the expert group. In terms of the learning curve, training groups performed better compared with experts in the early stages of their careers.

Conclusions

In conclusion, this synthetic training simulator for bulbar urethral anastomosis is novel, effective, and convenient for beginners of different groups. The training course can bridge the gap between preclinical use and actual surgery via this simulator.

Training the Next Generation of Transplant Surgeons With a 3-Dimensional Trainer: A Pilot Study

Background

In the United States, no published guidelines promote exposure to technical variants (ie, living donor or split liver) during transplant fellowship. Simulation with hands-on liver models may improve training in transplantation. This pilot study addressed 3 overall goals (material and model creation tools, recruitment rates and assessment of workload, and protocol adherence).

Methods

A patient-specific hands-on liver model was constructed from clinical imaging, and it needed to be resilient and realistic. Multiple types of materials were tested between January 2020 and August 2022. Participants were recruited stepwise. A left lateral segmentectomy simulation was conducted between August 2022 and December 2022 to assess protocol adherence.

Results

Digital anatomy 3-dimensional printing was considered the best option for the hands-on liver model. The recruitment rate was 100% and 47% for junior attendings and surgical residents, respectively. Ten participants were included and completed all the required surveys. Seven (70%) and 6 (60%) participants "agreed" that the overall quality of the model and the material were acceptable for surgical simulation. Five participants (50%) "agreed" that the training improved their surgical skills. Nine participants (90%) "strongly agreed" that similar sessions should be included in surgical training programs.

Conclusions

Three-dimensional hands-on liver models have the advantage of tactile feedback and were rated favorably as a potential training tool. Study enrollment for further studies is possible with the support of leadership. Rigorous multicenter designs should be developed to measure the actual impact of 3-dimensional hands-on liver models on surgical training.

Emergent robot-to-open conversion - Multidisciplinary simulation training in crisis management

Anticipating and addressing unexpected intraoperative events and anatomies are some of the most challenging aspects of pediatric urologic practice; uncontrolled hemorrhage is one of the most anxiety provoking and precarious. The increasing application of the robotic platform in pediatric urology adds another layer of complexity as surgeons are not immediately at the patient's bedside. Should hemorrhage occur in robotic cases, clear communication and seamless coordination between members of the operating room team are paramount to optimize patient safety and minimize errors. This is especially important in pediatric cases for which the margin of error is narrow. Non-technical skills, including leadership, decision-making, situational awareness, stress management, and team-communication, become increasingly critical. While many programs have focused on robotic training, few prepare the operating room team and surgical trainees to manage these unforeseen, emergent intraoperative scenarios. This review discusses the role of a multidisciplinary, in situ robot-to-open conversion simulation program in addressing this educational gap, ways to approach establishing these programs, and potential barriers.

Measures of performance and proficiency in robotic assisted surgery: a systematic review

Robotic assisted surgery (RAS) has seen a global rise in adoption. Despite this, there is not a standardised training curricula nor a standardised measure of performance. We performed a systematic review across the surgical specialties in RAS and evaluated tools used to assess surgeons' technical performance. Using the PRISMA 2020 guidelines, Pubmed, Embase and the Cochrane Library were searched systematically for full texts published on or after January 2020-January 2022. Observational studies and RCTs were included; review articles and systematic reviews were excluded. The papers' quality and bias score were assessed using the Newcastle Ottawa Score for the observational studies and Cochrane Risk Tool for the RCTs. The initial search yielded 1189 papers of which 72 fit the eligibility criteria. 27 unique performance metrics were identified. Global assessments were the most common tool of assessment (n = 13); the most used was GEARS (Global Evaluative Assessment of Robotic Skills). 11 metrics (42%) were objective tools of performance. Automated performance metrics (APMs) were the most widely used objective metrics whilst the remaining (n = 15, 58%) were subjective. The results demonstrate variation in tools used to assess technical performance in RAS. A large proportion of the metrics are subjective measures which increases the risk of bias amongst users. A standardised objective metric which measures all domains of technical performance from global to cognitive is required. The metric should be applicable to all RAS procedures and easily implementable. Automated performance metrics (APMs) have demonstrated promise in their wide use of accurate measures.

Evaluation of objective tools and artificial intelligence in robotic surgery technical skills assessment: a systematic review

BACKGROUND

There is a need to standardize training in robotic surgery, including objective assessment for accreditation. This systematic review aimed to identify objective tools for technical skills assessment, providing evaluation statuses to guide research and inform implementation into training curricula.

METHODS

A systematic literature search was conducted in accordance with the PRISMA guidelines. Ovid Embase/Medline, PubMed and Web of Science were searched. Inclusion criterion: robotic surgery technical skills tools. Exclusion criteria: non-technical, laparoscopy or open skills only. Manual tools and automated performance metrics (APMs) were analysed using Messick's concept of validity and the Oxford Centre of Evidence-Based Medicine (OCEBM) Levels of Evidence and Recommendation (LoR). A bespoke tool analysed artificial intelligence (AI) studies. The Modified Downs-Black checklist was used to assess risk of bias.

RESULTS

Two hundred and forty-seven studies were analysed, identifying: 8 global rating scales, 26 procedure-/task-specific tools, 3 main error-based methods, 10 simulators, 28 studies analysing APMs and 53 AI studies. Global Evaluative Assessment of Robotic Skills and the da Vinci Skills Simulator were the most evaluated tools at LoR 1 (OCEBM). Three procedure-specific tools, 3 error-based methods and 1 non-simulator APMs reached LoR 2. AI models estimated outcomes (skill or clinical), demonstrating superior accuracy rates in the laboratory with 60 per cent of methods reporting accuracies over 90 per cent, compared to real surgery ranging from 67 to 100 per cent.

CONCLUSIONS

Manual and automated assessment tools for robotic surgery are not well validated and require further evaluation before use in accreditation processes.PROSPERO: registration ID CRD42022304901.

An interactive and realistic phantom for cricothyroidotomy simulation of a patient with obesity through a reusable design using 3D-printing and Arduino

BACKGROUND AND OBJECTIVES

Proper airway management during emergencies can prevent serious complications. However, cricothyroidotomy is challenging in patients with obesity. Since this technique is not performed frequently but at a critical time, the opportunity for trainees is rare. Simulators for these procedures are also lacking. Therefore, we proposed a realistic and interactive cricothyroidotomy simulator.

METHODS

All anatomical structures were modeled based on computed tomography images of a patient with obesity. To mimic the feeling of incision during cricothyroidotomy, the incision site was modeled to distinguish between the skin and fat. To reinforce the educational purpose, capacitive touch sensors were attached to the artery, vein, and thyroid to generate audio feedback. The tensile strength of the silicone-cast skin was measured to verify the similarity of the mechanical properties between humans and our model. The fabrication and assembly accuracies of the phantom between the Standard Tessellation Language and the fabricated model were evaluated. Audio feedback through sensing the anatomy parts and utilization was evaluated.

RESULTS

The body, skull, clavicle, artery, vein, and thyroid were fabricated using fused deposition modeling (FDM) with polylactic acid. A skin mold was fabricated using FDM with thermoplastic polyurethane. A fat mold was fabricated using stereolithography apparatus (SLA) with a clear resin. The airway and tongue were fabricated using SLA with an elastic resin. The tensile strength of the skin using silicone with and without polyester mesh was 2.63 ± 0.68 and 2.46 ± 0.21 MPa. The measurement errors for fabricating and assembling parts of the phantom between the STL and the fabricated models were -0.08 ± 0.19 mm and 0.13 ± 0.64 mm. The measurement errors internal anatomy embodied surfaces in fat part were 0.41 ± 0.89 mm. Audio feedback was generated 100% in all the areas tested. The realism, understanding of clinical skills, and intention to retrain were 7.1, 8.8, and 8.3 average points.

CONCLUSIONS

Our simulator can provide a realistic simulation experience for trainees through a realistic feeling of incision and audio feedback, which can be used for actual clinical education.

Pediatric robotic surgery: issues in management-expert consensus from the Italian Society of Pediatric and Neonatal Anesthesia and Intensive Care (SARNePI) and the Italian Society of Pediatric Surgery (SICP)

BACKGROUND

Pediatric robotic-assisted surgeries have increased in recent years; however, guidance documents are still lacking. This study aimed to develop evidence-based recommendations, or best practice statements when evidence is lacking or inadequate, to assist surgical teams internationally.

METHODS

A joint consensus taskforce of anesthesiologists and surgeons from the Italian Society of Pediatric and Neonatal Anesthesia and Intensive Care (SARNePI) and the Italian Society of Pediatric Surgery (SICP) have identified critical areas and reviewed the available evidence. The taskforce comprised 21 experts representing the fields of anesthesia (n = 11) and surgery (n = 10) from clinical centers performing pediatric robotic surgery in the Italian cities of Ancona, Bologna, Milan, Naples, Padua, Pavia, Perugia, Rome, Siena, and Verona. Between December 2020 and September 2021, three meetings, two Delphi rounds, and a final consensus conference took place.

RESULTS

During the first planning meeting, the panel agreed on the specific objectives, the definitions to apply, and precise methodology. The project was structured into three subtopics: (i) preoperative patient assessment and preparation; (ii) intraoperative management (surgical and anesthesiologic); and (iii) postoperative procedures. Within these phases, the panel agreed to address a total of 18 relevant areas, which spanned preoperative patient assessment and patient selection, anesthesiology, critical care medicine, respiratory care, prevention of postoperative nausea and vomiting, and pain management.

CONCLUSION

Collaboration among surgeons and anesthesiologists will be increasingly important for achieving safe and effective RAS procedures. These recommendations will provide a review for those who already have relevant experience and should be particularly useful for those starting a new program.

A review of simulation training and new 3D computer-generated synthetic organs for robotic surgery education

We conducted a comprehensive review of surgical simulation models used in robotic surgery education. We present an assessment of the validity and cost-effectiveness of virtual and augmented reality simulation, animal, cadaver and synthetic organ models. Face, content, construct, concurrent and predictive validity criteria were applied to each simulation model. There are six major commercial simulation machines available for robot-assisted surgery. The validity of virtual reality (VR) simulation curricula for psychomotor assessment and skill acquisition for the early phase of robotic surgery training has been demonstrated. The widespread adoption of VR simulation has been limited by the high cost of these machines. Live animal and cadavers have been the accepted standard for robotic surgical simulation since it began in the early 2000s. Our review found that there is a lack of evidence in the literature to support the use of animal and cadaver for robotic surgery training. The effectiveness of these models as a training tool is limited by logistical, ethical, financial and infection control issues. The latest evolution in synthetic organ model training for robotic surgery has been driven by new 3D-printing technology. Validated and cost-effective high-fidelity procedural models exist for robotic surgery training in urology. The development of synthetic models for the other specialties is not as mature. Expansion into multiple surgical disciplines and the widespread adoption of synthetic organ models for robotic simulation training will require the ability to engineer scalability for mass production. This would enable a transition in robotic surgical education where digital and synthetic organ models could be used in place of live animals and cadaver training to achieve robotic surgery competency.

Evaluation of skin cancer resection guide using hyper-realistic in-vitro phantom fabricated by 3D printing

Skin cancer usually occurs in the facial area relatively exposed to sunlight. Medical imaging can confirm the invasiveness and metastasis of skin cancer, which is used to establish a surgical plan. However, there is no method of directly marking this information on the patient's skin in the operating room. We evaluated a skin cancer resection guide that marks resection areas including safety margins on the patient's skin based on medical images and in-vitro phantom fabricated via 3D printing. The in-vitro phantom, which includes the skull, skin, and five different cancer locations was designed and fabricated based on a CT image of a patient. Skin cancer resection guides were designed using a CT image of an in-vitro phantom, with a safety margin, and four injection points at each cancer. The guide was used to insert 16 cc intravenous catheters into each cancer of the phantom, which was rescanned by CT. The catheter insertion point and angle were evaluated. The accuracy of the insertion points was 2.09 ± 1.06 mm and cosine similarities was 0.980 ± 0.020. In conclusion, skin cancer resection guides were fabricated to mark surgical plans on the patient's skin in the operating room. They demonstrated reasonable accuracies in actual clinical settings.