Training to acquire psychomotor skills for endoscopic endonasal surgery using a personal webcam trainer

Pilot Analysis of Surgeon Instrument Utilization Signatures Based on Shannon Entropy and Deep Learning for Surgeon Performance Assessment in a Cadaveric Carotid Artery Injury Control Simulation

BACKGROUND AND OBJECTIVES

Assessment and feedback are critical to surgical education, but direct observational feedback by experts is rarely provided because of time constraints and is typically only qualitative. Automated, video-based, quantitative feedback on surgical performance could address this gap, improving surgical training. The authors aim to demonstrate the ability of Shannon entropy (ShEn), an information theory metric that quantifies series diversity, to predict surgical performance using instrument detections generated through deep learning.

METHODS

Annotated images from a publicly available video data set of surgeons managing endoscopic endonasal carotid artery lacerations in a perfused cadaveric simulator were collected. A deep learning model was implemented to detect surgical instruments across video frames. ShEn score for the instrument sequence was calculated from each surgical trial. Logistic regression using ShEn was used to predict hemorrhage control success.

RESULTS

ShEn scores and instrument usage patterns differed between successful and unsuccessful trials (ShEn: 0.452 vs 0.370, P < .001). Unsuccessful hemorrhage control trials displayed lower entropy and less varied instrument use patterns. By contrast, successful trials demonstrated higher entropy with more diverse instrument usage and consistent progression in instrument utilization. A logistic regression model using ShEn scores (78% accuracy and 97% average precision) was at least as accurate as surgeons' attending/resident status and years of experience for predicting trial success and had similar accuracy as expert human observers.

CONCLUSION

ShEn score offers a summative signal about surgeon performance and predicted success at controlling carotid hemorrhage in a simulated cadaveric setting. Future efforts to generalize ShEn to additional surgical scenarios can further validate this metric.

Training models and simulators for endoscopic transsphenoidal surgery: a systematic review

Endoscopic transsphenoidal surgery is a novel surgical technique requiring specific training. Different models and simulators have been recently suggested for it, but no systematic review is available. To provide a systematic and critical literature review and up-to-date description of the training models or simulators dedicated to endoscopic transsphenoidal surgery. A search was performed on PubMed and Scopus databases for articles published until February 2023; Google was also searched to document commercially available. For each model, the following features were recorded: training performed, tumor/arachnoid reproduction, assessment and validation, and cost. Of the 1199 retrieved articles, 101 were included in the final analysis. The described models can be subdivided into 5 major categories: (1) enhanced cadaveric heads; (2) animal models; (3) training artificial solutions, with increasing complexity (from "box-trainers" to multi-material, ct-based models); (4) training simulators, based on virtual or augmented reality; (5) Pre-operative planning models and simulators. Each available training model has specific advantages and limitations. Costs are high for cadaver-based solutions and vary significantly for the other solutions. Cheaper solutions seem useful only for the first stages of training. Most models do not provide a simulation of the sellar tumor, and a realistic simulation of the suprasellar arachnoid. Most artificial models do not provide a realistic and cost-efficient simulation of the most delicate and relatively common phase of surgery, i.e., tumor removal with arachnoid preservation; current research should optimize this to train future neurosurgical generations efficiently and safely.

A systematic review on classification and assessment of surgical skill levels for simulation-based training programs

BACKGROUND

Nowadays, advances in medical informatics have made minimally invasive surgery (MIS) procedures the preferred choice. However, there are several problems with the education programs in terms of surgical skill acquisition. For instance, defining and objectively measuring surgical skill levels is a challenging process. Accordingly, the aim of this study is to conduct a literature review for an investigation of the current approaches for classifying the surgical skill levels and for identifying the skill training tools and measurement methods.

MATERIALS AND METHODS

In this research, a search is conducted and a corpus is created. Exclusion and inclusion criteria are applied by limiting the number of articles based on surgical education, training approximations, hand movements, and endoscopic or laparoscopic operations. To satisfy these criteria, 57 articles are included in the corpus of this study.

RESULTS

Currently used surgical skill assessment approaches have been summarized. Results show that various classification approaches for the surgical skill level definitions are being used. Besides, many studies are conducted by omitting particularly important skill levels in between. Additionally, some inconsistencies are also identified across the skill level classification studies.

CONCLUSION

In order to improve the benefits of simulation-based training programs, a standardized interdisciplinary approach should be developed. For this reason, specific to each surgical procedure, the required skills should be identified. Additionally, appropriate measures for assessing these skills, which can be defined in simulation-based MIS training environments, should be refined. Finally, the skill levels gained during the developmental stages of these skills, with their threshold values referencing the identified measures, should be redefined in a standardized manner.

Simulation training in endoscopic skull base surgery: A scoping review

Objective

Methods

Results

Conclusions

Defining competence profiles of different medical specialties with the requirement-tracking questionnaire - a pilot study to provide a framework for medial students' choice of postgraduate training

BACKGROUND

The medical specialties are characterised by a great diversity in their daily work which requires different sets of competences. A requirement analysis would help to establish competence profiles of the different medical specialities. The aim of this pilot study was to define competence profiles for individual medical specialties. This could provide a framework as support for medical graduates who wish to choose a medical specialty for their postgraduate training.

METHODS

In February 2020, physicians were invited via the State Chamber of Physicians' monthly journal to electronically fill out the requirement tracking (R-Track) questionnaire. It contains 63 aspects assigned to six areas of competence: "Mental abilities", "Sensory abilities", "Psychomotor and multitasking abilities", "Social interactive competences", "Motivation", and "Personality traits". The expression of the different aspects was assessed on a 5-point Likert scale (1: "very low" to 5: "very high"). Sociodemographic data and information about the current workplace (hospital or practice) were also collected.

RESULTS

In total, 195 practicing physicians from 19 different specialities followed the invitation by the State Chamber of Physicians to participate in this survey. For almost all medical specialties, the competence area "Motivation" reached rank 1. "Psychomotor and multitasking abilities" received high ranks among specialties performing surgical activities, while "Social interactive competences" and "Personality traits" were highly rated by specialties with an intense level of patient-physician-interaction. "Mental abilities" were only rated highly by radiologists (rank 2) and physiologists (rank 3) while "Sensory abilities" were generally rated very low with the expression (rank 4) for anaesthesiology and ENT.

CONCLUSIONS

In this pilot study, a first outline of competences profiles for 17 medical specialties were defined. The specific "Motivation" for a medical specialty seemed to play the greatest role for most specialties. This first specialty specific competence framework could provide a first insight into specific competences required by medical specialties and could serve medical graduate as a decision aid when looking for a medical specialty for their postgraduate training.

WITHDRAWN: Simulation-based training in endoscopic endonasal surgery: Assessment of the cyrano simulator

Cet article a du être retiré conformément à la ligne de conduite d'Elsevier concernant le retrait d'articles. Vous pouvez consulter le site (https://www.elsevier.com/about/our-business/policies/article-withdrawal) pour de plus amples renseignements. L'éditeur vous prie d'accepter ses excuses pour ce désagrément.

Three-dimensional endoscopy: The future of nasoendoscopic training

OBJECTIVES/HYPOTHESIS

Three-dimensional (3D) endoscopy is an emerging tool in surgery that provides real-time depth perception. Its benefits have been investigated in surgical training, but the current literature lacks significant objective outcome data. We aimed to objectively compare the efficacy of two-dimensional (2D) versus 3D high-definition endoscopes in novice users.

STUDY DESIGN

Prospective, randomized crossover study.

METHODS

Ninety-two novice medical students who used both 2D and 3D endoscopes to complete two validated tasks in a box trainer participated in the study. Time taken and error rates were measured, and subjective data were collected.

RESULTS

Wilcoxon tests showed 3D technology was significantly faster than 2D (78 vs. 95 seconds, P = .004), and errors per task were significantly lower (3 vs. 5, P < .001). Sixty-nine percent of participants preferred the 3D endoscope.

CONCLUSIONS

3D high-definition endoscopy could be instrumental in training the next generation of endoscopic surgeons. Further research is required in a clinical setting.

LEVEL OF EVIDENCE

2b Laryngoscope, 129:1280-1285, 2019.

Injury of the Carotid Artery during Endoscopic Endonasal Surgery: Surveys of Skull Base Surgeons

Objectives  This study aimed to review endoscopic skull base surgeon experience with internal carotid artery (ICA) injuries during endoscopic endonasal surgery (EES) to provide an estimate of the incidence of ICA injury, the associated factors and identify the best training modalities for the management of this complication. Design  Anonymous electronic survey of past participants at a well-established endoscopic skull base surgery course and a global online community of skull base surgeons. Main Outcome Measures  Relative incidence of ICA injuries during EES, associated anatomic and intraoperative factors, and surgeon experience. Results  At least 20% of surgeons in each surveyed population experienced a carotid artery injury. Reported carotid artery injuries were most common during tumor exposure and removal (48%). The parasellar carotid artery was the most commonly injured segment (39%). Carotid artery injuries were more common in high-volume surgeons, but only statistically significant in one of the two populations. Attendance at a skull base course or courses did not change the incidence of carotid artery injury in either surveyed population. In both surveys, respondents preferred live surgeries or active (not computer simulated) training models. Conclusions  ICA injury is underreported and most common when manipulating the parasellar carotid artery for exposure and tumor dissection. Given the high morbidity and mortality associated with these injuries, vascular injury management should be prioritized and taught in a graduated approach by modern endoscopic skull base courses.

Indigenous Inexpensive Practice Models for Skill Development in Neuroendoscopy

Introduction:

Neurosurgery is a branch having a tough learning curve. Residents generally get very less hands-on exposure for advanced procedures like neuroendoscopy. With the limited number of cadavers available and ethical issues associated with animal models, practice models, and simulators are becoming the able alternative. Most of these simulators are very costly. We tried to build indigenous inexpensive practice models that can help in developing most of the skills of neuroendoscopy.

Materials and Methods:

Models were built for learning hand-eye coordination, dexterity, instrument manipulation, cutting, fine dissection, keyhole concept, drilling, and simulation of laminectomy and ligamentum flavum resection. These were shown in the neuroendoscopic fellowship program conducted in authors' institute, and trainees' responses were recorded.

Results:

Both novice and experienced neuroendoscopic surgeons validated the models. There was no significant difference between their responses (P = 0.791).

Conclusion:

Indigenous innovative models can be used to learn and teach neuroendoscopic skills. The presented models were reliable, valid, eco-friendly, highly cost-effective, portable, easily made and can be kept in one's chamber for practicing.

Design and Validation of an Open-Source, Partial Task Trainer for Endonasal Neuro-Endoscopic Skills Development: Indian Experience

BACKGROUND

Box trainers are ideal simulators, given they are inexpensive, accessible, and use appropriate fidelity.

OBJECTIVE

The development and validation of an open-source, partial task simulator that teaches the fundamental skills necessary for endonasal skull-base neuro-endoscopic surgery.

METHODS

We defined the Neuro-Endo-Trainer (NET) SkullBase-Task-GraspPickPlace with an activity area by analyzing the computed tomography scans of 15 adult patients with sellar suprasellar parasellar tumors. Four groups of participants (Group E, n = 4: expert neuroendoscopists; Group N, n =19: novice neurosurgeons; Group R, n = 11: neurosurgery residents with multiple iterations; and Group T, n = 27: neurosurgery residents with single iteration) performed grasp, pick, and place tasks using NET and were graded on task completion time and skills assessment scale score.

RESULTS

Group E had lower task completion times and greater skills assessment scale scores than both Group N and R (P ≤ 0.03, 0.001). The performance of Groups N and R was found to be equivalent; in self-assessing neuro-endoscopic skill, the participants in these groups were found to have equally low pretraining scores (4/10) with significant improvement shown after NET simulation (6, 7 respectively). Angled scopes resulted in decreased scores with tilted plates compared with straight plates (30° P ≤ 0.04, 45° P ≤ 0.001). With tilted plates, decreased scores were observed when we compared the 0° with 45° endoscope (right, P ≤ 0.008; left, P ≤ 0.002).

CONCLUSIONS

The NET, a face and construct valid open-source partial task neuroendoscopic trainer, was designed. Presimulation novice neurosurgeons and neurosurgical residents were described as having insufficient skills and preparation to practice neuro-endoscopy. Plate tilt and endoscope angle were shown to be important factors in participant performance. The NET was found to be a useful partial-task trainer for skill building in neuro-endoscopy.

Endoscopic endonasal cranial base surgery simulation using an artificial cranial base model created by selective laser sintering

Mastery of the expanded endoscopic endonasal approach (EEA) requires anatomical knowledge and surgical skills; the learning curve for this technique is steep. To a great degree, these skills can be gained by cadaveric dissections; however, ethical, religious, and legal considerations may interfere with this paradigm in different regions of the world. We assessed an artificial cranial base model for the surgical simulation of EEA and compared its usefulness with that of cadaveric specimens. The model is made of both polyamide nylon and glass beads using a selective laser sintering (SLS) technique to reflect CT-DICOM data of the patient's head. It features several artificial cranial base structures such as the dura mater, venous sinuses, cavernous sinuses, internal carotid arteries, and cranial nerves. Under endoscopic view, the model was dissected through the nostrils using a high-speed drill and other endonasal surgical instruments. Anatomical structures around and inside the sphenoid sinus were accurately reconstructed in the model, and several important surgical landmarks, including the medial and lateral optico-carotid recesses and vidian canals, were observed. The bone was removed with a high-speed drill until it was eggshell thin and the dura mater was preserved, a technique very similar to that applied in patients during endonasal cranial base approaches. The model allowed simulation of almost all sagittal and coronal plane EEA modules. SLS modeling is a useful tool for acquiring the anatomical knowledge and surgical expertise for performing EEA while avoiding the ethical, religious, and infection-related problems inherent with use of cadaveric specimens.