Development and evaluation of rhinoplasty spreader graft suture simulator for novice surgeons

Hand Motion Analysis Using Accelerometer-Based Sensors and Sheep's Head Model for Basic Training in Functional Endoscopic Sinus Surgery

INTRODUCTION

 Motion analysis, the study of movement patterns to evaluate performance, plays a crucial role in surgical training. It provides objective data that can be used to assess and improve trainee's precision, efficiency, and overall surgical technique. The primary aim of this study is to employ accelerometer-based sensors placed on the wrist to analyze hand motions during endoscopic sinus surgery training using the sheep's head. By capturing detailed movement data, the study seeks to quantify the motion characteristics that distinguish different levels of surgical expertise. This approach seeks to quantify motion characteristics indicative of surgical expertise and enhance the objectivity and effectiveness of surgical training feedback mechanisms.

MATERIALS AND METHODS

 Twenty-four participants were divided into three groups based on their experience with endoscopic endonasal surgery. Each participant was tasked with performing specified procedures on an individual sheep's head, concentrating on exploring both nasal passages. A single Bluetooth Accelerometer WitMotion sensor was mounted on the dorsal surface of each hand. This facilitates the evaluation of efficiency parameters such as time, path length, and acceleration during the training procedures. Accelerometer data were collected and imported in CSV format (comma-separated values) for each group of surgeons-senior, specialist, and resident-mean values and standard deviations were computed. The Shapiro-Wilk Test assessed the normality of the distribution. The Kruskal-Wallis test was employed to compare procedural time, acceleration, and path length differences across the three surgeon experience levels.

RESULTS

 For the procedural time, statistical significance appears in all surgical steps (p<0.001), with the biggest difference in the septoplasty group in favor of the senior group. A clear difference can be observed between the resulting acceleration of the dominant hands (instrument hand) and the non-dominant hand (endoscopic hand) and between the study groups. The difference between groups reaches statistical significance with a p-value <0.001. A statistically significant difference can be seen between the paths covered by each hand of every participant (p<0.001). Also, senior doctors covered significantly less movement with both hands than the specialists and the resident doctors (p<0.001).

CONCLUSIONS

 The data show a clear learning curve from resident to senior, with residents taking more time and using more hand movements to complete the same tasks. Specialists are in the intermediate phase, showing signs of honing their technique towards efficiency. This comprehensive data set can help tailor training programs to focus on both efficiency (quicker procedures) and economy of motion (reduced path length and acceleration), especially in more complex procedures where the difference in performance is more pronounced.

Development and Evaluation of a High-Fidelity Rhinoplasty Simulator

SUMMARY

Rhinoplasty is a challenging procedure with a steep learning curve. Surgical simulators provide a safe platform to gain hands-on experience without compromising patient outcomes. Therefore, rhinoplasty is an ideal procedure to benefit from an effective surgical simulator. A high-fidelity rhinoplasty simulator was developed using three-dimensional computer modeling, three-dimensional printing, and polymer techniques. The simulator was tested by six surgeons with experience in rhinoplasty to assess realism, anatomic accuracy, and value as a training tool. The surgeons performed common rhinoplasty techniques and were provided a Likert-type questionnaire assessing the anatomic features of the simulator. A variety of surgical techniques were performed successfully using the simulator, including open and closed approaches. Bony techniques performed included endonasal osteotomies and rasping. Submucous resection with harvest of septal cartilage, cephalic trim, and tip suturing, as well as grafting techniques including alar rim, columellar strut, spreader, and shield grafts, were performed successfully. Overall, there was agreement on the simulator's anatomic accuracy of bony and soft-tissue features. There was strong agreement on the simulator's overall realism and value as a training tool. The simulator provides a high-fidelity, comprehensive training platform to learn rhinoplasty techniques to augment real operating experience without compromising patient outcomes.

Surgical Training Simulators for Rhinoplasty: A Systematic Review

Rhinoplasty training currently follows an apprenticeship model that is largely observational. Trainees have limited experience in performing maneuvers of this complex surgery. Rhinoplasty simulators can address this issue by providing trainees with the opportunity to gain surgical simulator experience that could improve technical competences in the operating room. This review amalgamates the collective understanding of rhinoplasty simulators described to date. In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, PubMed, OVID Embase, OVID Medline, and Web of Science databases were all searched for original research on surgical simulators for rhinoplasty education and reviewed by independent reviewers. Articles underwent title and abstract screening, and then relevant articles underwent full-text review to extract simulator data. Seventeen studies, published between 1984 and 2021, were included for final analysis. Study participant numbers ranged from 4 to 24, and included staff surgeons, fellows, residents (postgraduate year 1-6), and medical students. Cadaveric surgical simulators comprised eight studies, of which three were with human cadavers, one study was a live animal simulator, two were virtual simulators, and six were three-dimensional (3D) models. Both animal and human-based simulators increased the confidence of trainees significantly. Significant improvement in various aspects of rhinoplasty knowledge occurred with implementation of a 3D-printed model in rhinoplasty education. Rhinoplasty simulators are limited by a lack of an automated method of evaluation and a large reliance on feedback from experienced rhinoplasty surgeons. Rhinoplasty simulators have the potential to provide trainees with the opportunity for hands-on training to improve skill and develop competencies without putting patients in harm's way. Current literature on rhinoplasty simulators largely focuses on simulator development, with few simulators being validated and assessed for utility. For wider implementation and acceptance, further refinement of simulators, validation, and assessment of outcomes is required.

Inanimate 3D printed model for thoracoscopic repair of esophageal atresia with tracheoesophageal fistula

Background

Thoracoscopic repair of esophageal atresia (EA) and tracheoesophageal fistula (TEF) poses significant technical challenges. This study aimed to develop an inexpensive, reusable, high-fidelity synthetic tissue model for simulating EA/TEF repairs and to assess the validity of the simulator.

Methods

By using 3D printing and silicone casting, we designed an inexpensive and reusable inanimate model for training in thoracoscopic EA/TEF repair. The objective was to validate the model using a 5-point Likert scale and the Objective Structured Assessment of Technical Skills (OSATS) to evaluate participants' surgical proficiency.

Results

A total of 18 participants (7 medical students, 4 pediatric surgery trainees, and 7 experienced surgeons), after being instructed and trained, were asked to perform TEF ligation, dissection, as well as esophageal anastomosis using six sliding knots on the EA/TEF simulator. All participants in the expert group completed the task within the 120-minute time limit, however only 4 (57%) participants from the novice/intermediate completed the task within the time limit. There was a statistically significant difference in OSATS scores for the "flow of task" (p = 0.018) and scores for the "overall MIS skills" (p = 0.010) task distinguishing between novice and intermediates and experts. The simulator demonstrated strong suitability as a training tool, indicated by a mean score of 4.66. The mean scores for the model's realism and the working environment were 4.25 and 4.5, respectively. Overall, the face validity was scored significantly lower in the expert group compared to the novice/intermediate groups (p = 0.0002).

Conclusions

Our study established good face and content validity of the simulator. Due to its reusability, and suitability for individual participants, our model holds promise as a training tool for thoracoscopic procedures among surgeons. However, novices and trainees struggled with advanced minimally invasive surgical procedures. Therefore, a structured and focused training curriculum in pediatric MIS is needed for optimal utilization of the available training hours.

3D Autonomous Surgeon's Hand Movement Assessment Using a Cascaded Fuzzy Supervisor in Multi-Thread Video Processing

The purpose of the Fundamentals of Laparoscopic Surgery (FLS) training is to develop laparoscopic surgery skills by using simulation experiences. Several advanced training methods based on simulation have been created to enable training in a non-patient environment. Laparoscopic box trainers-cheap, portable devices-have been deployed for a while to offer training opportunities, competence evaluations, and performance reviews. However, the trainees must be under the supervision of medical experts who can evaluate their abilities, which is an expensive and time-consuming operation. Thus, a high level of surgical skill, determined by assessment, is necessary to prevent any intraoperative issues and malfunctions during a real laparoscopic procedure and during human intervention. To guarantee that the use of laparoscopic surgical training methods results in surgical skill improvement, it is necessary to measure and assess surgeons' skills during tests. We used our intelligent box-trainer system (IBTS) as a platform for skill training. The main aim of this study was to monitor the surgeon's hands' movement within a predefined field of interest. To evaluate the surgeons' hands' movement in 3D space, an autonomous evaluation system using two cameras and multi-thread video processing is proposed. This method works by detecting laparoscopic instruments and using a cascaded fuzzy logic assessment system. It is composed of two fuzzy logic systems executing in parallel. The first level assesses the left and right-hand movements simultaneously. Its outputs are cascaded by the final fuzzy logic assessment at the second level. This algorithm is completely autonomous and removes the need for any human monitoring or intervention. The experimental work included nine physicians (surgeons and residents) from the surgery and obstetrics/gynecology (OB/GYN) residency programs at WMU Homer Stryker MD School of Medicine (WMed) with different levels of laparoscopic skills and experience. They were recruited to participate in the peg-transfer task. The participants' performances were assessed, and the videos were recorded throughout the exercises. The results were delivered autonomously about 10 s after the experiments were concluded. In the future, we plan to increase the computing power of the IBTS to achieve real-time performance assessment.

Thinking Beyond the Temporal Bone Lab: A Systematic Process for Expanding Surgical Simulation in Otolaryngology Training

The COVID-19 pandemic led to a temporary lapse in the development of otolaryngology trainee operative skills due to the cancellation of elective procedures and redeployment of trainees and attendings to COVID-19 units. Although transient, this disruption provided an opportunity for otolaryngology programs to develop contingency plans and formalize nascent simulation training curricula. Integration of formal simulation training alongside current didactic and surgical education may offset lost exposure during surgically lean times while providing the framework and resources for enhanced baseline training. Here, we provide an up-to-date overview of surgical simulation models in otolaryngology and identify easily implementable, low-cost, low fidelity models for junior trainees. By taking advantage of rapid advancements in technology and a paradigm shift to a more hands-on approach in medical education, formal simulation training may prove to be a beneficial tool at all stages of residency training, allowing for expanded peer-mentored skill development and providing a safe haven during unforeseen disruptions in surgical case volume.

Objective and automated assessment of surgical technical skills with IoT systems: A systematic literature review

The assessment of surgical technical skills to be acquired by novice surgeons has been traditionally done by an expert surgeon and is therefore of a subjective nature. Nevertheless, the recent advances on IoT (Internet of Things), the possibility of incorporating sensors into objects and environments in order to collect large amounts of data, and the progress on machine learning are facilitating a more objective and automated assessment of surgical technical skills. This paper presents a systematic literature review of papers published after 2013 discussing the objective and automated assessment of surgical technical skills. 101 out of an initial list of 537 papers were analyzed to identify: 1) the sensors used; 2) the data collected by these sensors and the relationship between these data, surgical technical skills and surgeons' levels of expertise; 3) the statistical methods and algorithms used to process these data; and 4) the feedback provided based on the outputs of these statistical methods and algorithms. Particularly, 1) mechanical and electromagnetic sensors are widely used for tool tracking, while inertial measurement units are widely used for body tracking; 2) path length, number of sub-movements, smoothness, fixation, saccade and total time are the main indicators obtained from raw data and serve to assess surgical technical skills such as economy, efficiency, hand tremor, or mind control, and distinguish between two or three levels of expertise (novice/intermediate/advanced surgeons); 3) SVM (Support Vector Machines) and Neural Networks are the preferred statistical methods and algorithms for processing the data collected, while new opportunities are opened up to combine various algorithms and use deep learning; and 4) feedback is provided by matching performance indicators and a lexicon of words and visualizations, although there is considerable room for research in the context of feedback and visualizations, taking, for example, ideas from learning analytics.

Use of Simulation in Plastic Surgery Training

The nationwide focus on patient safety and the health of residents has increased the demand for educational tools outside the operating room. Simulation is a valuable tool for assessing and developing surgical skills in a controlled and safe environment. The use of simulation as a formal component of training has been increasing in various surgical subspecialties. In general surgery, simulation examinations such as the Fundamentals of Laparoscopic Surgery and Fundamentals of Endoscopic Surgery have become a prerequisite to board certification. Although formal simulation examinations in plastic surgery are not universal, there has been an increase in the use of simulation to increase resident competency in the operating room. For now, we will review the current state of simulation in craniofacial, hand, microvascular, and esthetic surgery and discuss applications for the future. We will also discuss the evolving role of artificial intelligence, virtual reality, and augmented reality in plastic surgery training and testing.

Aesthetic Training in Plastic Surgery Residency

Training in aesthetic surgery is a core element in a plastic surgery residency program. Nevertheless, in the past, many studies have shown the lack of resident confidence in aesthetic procedures upon graduation. In recent years, a number of efforts have been made to address this concern, including increasing the required residency aesthetic case requirements and the integration of resident aesthetic clinics to increase exposure and independence in this aspect of training. Numerous studies have been conducted to evaluate the efficacy of these resident-run clinics and have substantiated their value as an important educational tool in residency training and validated their safety in patient care. In fact, survey studies have shown that though residents today show a markedly increased confidence in their training when compared with the past, they still feel there is room for improvement in areas such as facial and minimally invasive surgeries, along with procedures that require higher patient volume to refine. In this article, we review the current state of aesthetic surgery training during plastic surgery residency and discuss future directions in the field.