High fidelity simulation of the endoscopic transsphenoidal approach: Validation of the UpSurgeOn TNS Box

Automated surgical skill assessment in endoscopic pituitary surgery using real-time instrument tracking on a high-fidelity bench-top phantom

Improved surgical skill is generally associated with improved patient outcomes, although assessment is subjective, labour intensive, and requires domain-specific expertise. Automated data-driven metrics can alleviate these difficulties, as demonstrated by existing machine learning instrument tracking models. However, these models are tested on limited datasets of laparoscopic surgery, with a focus on isolated tasks and robotic surgery. Here, a new public dataset is introduced: the nasal phase of simulated endoscopic pituitary surgery. Simulated surgery allows for a realistic yet repeatable environment, meaning the insights gained from automated assessment can be used by novice surgeons to hone their skills on the simulator before moving to real surgery. Pituitary Real-time INstrument Tracking Network (PRINTNet) has been created as a baseline model for this automated assessment. Consisting of DeepLabV3 for classification and segmentation, StrongSORT for tracking, and the NVIDIA Holoscan for real-time performance, PRINTNet achieved 71.9% multiple object tracking precision running at 22 frames per second. Using this tracking output, a multilayer perceptron achieved 87% accuracy in predicting surgical skill level (novice or expert), with the 'ratio of total procedure time to instrument visible time' correlated with higher surgical skill. The new publicly available dataset can be found at https://doi.org/10.5522/04/26511049.

Pilot Validation of a 3-Dimensional Printed Pituitary Adenoma, Vascular Injury, and Cerebrospinal Fluid Leak Surgical Simulator

BACKGROUND AND OBJECTIVES

Endoscopic skull base surgery is a subspecialty field which would benefit significantly from high-fidelity surgical simulators. Giving trainees the opportunity to flatten their learning curve by practicing a variety of procedures on surgical simulators will inevitably improve patient outcomes.

METHODS

Four neurosurgeons, 8 otolarynologists, and 6 expert course faculty agreed to participate. All participants were asked to perform a transsphenoidal exposure and resection of a pituitary adenoma, repair a cerebrospinal fluid (CSF) leak, control a carotid injury, and repair a skull base defect. The content, face, and construct validity of the 3-dimensional printed model was examined.

RESULTS

The heart rate of the participants significantly increased from baseline when starting the carotid injury simulation (mean 90 vs 121, P = .029) and significantly decreased once the injury was controlled (mean 121 vs 110, P = .033, respectively). The participants reported a significant improvement in anxiety in facing a major vascular injury, as well as an increase in their confidence in management of major vascular injury, resecting a pituitary adenoma and repair of a CSF leak using a 5-point Likert scale (mean 4.42 vs 3.58 P = .05, 2 vs 3.25 P < .001, 2.36 vs 4.27 P < .001 and 2.45 vs 4.0 P = .001, respectively). The mean Objective Structured Assessment of Technical Skills score for experienced stations was 4.4, significantly higher than the Objective Structured Assessment of Technical Skills score for inexperienced stations (mean 3.65, P = .016).

CONCLUSION

We have demonstrated for the first time a validated 3-dimensional printed surgical simulator for endoscopic pituitary surgery that allows surgeons to practice a transsphenoidal approach, surgical resection of a pituitary adenoma, repair of a CSF leak in the diaphragma sellae, control of a carotid injury, and repair of skull base defect.

Video-Based Performance Analysis in Pituitary Surgery - Part 2: Artificial Intelligence Assisted Surgical Coaching

BACKGROUND

Superior surgical skill improves surgical outcomes in endoscopic pituitary adenoma surgery. Video-based coaching programs, pioneered in professional sports, have shown promise in surgical training. In this study, we developed and assessed a video-based coaching program using artificial intelligence (AI) assistance.

METHODS

An AI-assisted video-based surgical coaching was implemented over 6 months with the pituitary surgery team. The program consisted of 1) monthly random video analysis and review; and 2) quarterly 2-hour educational meetings discussing these videos and learning points. Each video was annotated for surgical phases and steps using AI, which improved video interactivity and allowed the calculation of quantitative metrics. Primary outcomes were program feasibility, acceptability, and appropriateness. Surgical performance (via modified Objective Structured Assessment of Technical Skills) and early surgical outcomes were recorded for every case during the 6-month coaching period, and a preceding 6-month control period. Beta and logistic regression were used to assess the change in modified Objective Structured Assessment of Technical Skills scores and surgical outcomes after the coaching program implementation.

RESULTS

All participants highly rated the program's feasibility, acceptability, and appropriateness. During the coaching program, 63 endoscopic pituitary adenoma cases were included, with 41 in the control group. Surgical performance across all operative phases improved during the coaching period (P < 0.001), with a reduction in new postoperative anterior pituitary hormone deficit (P = 0.01).

CONCLUSIONS

We have developed a novel AI-assisted video surgical coaching program for endoscopic pituitary adenoma surgery - demonstrating its viability and impact on surgical performance. Early results also suggest improvement in patient outcomes. Future studies should be multicenter and longer term.

Assessment of High-fidelity Anatomical Models for Performing Pterional Approach: A Practical Clinic in American Association of Neurological Surgeons Meeting 2024

BACKGROUND

Over the last decade, simulation models have been increasingly applied as an adjunct for surgical training in neurosurgery. We aim through a practical course at a national neurosurgical conference to evaluate 3D non-cadaveric simulation models along with augmented reality for learning and practicing the pterional craniotomy approach among a wide variety of participants including medical students, neurosurgery residents, and attending neurosurgeons.

METHODS

Our course was conducted during an international neurosurgery meeting with 93 participants but the course surveys (pre- and post-course) were completed by 42 participants.

RESULTS

Most participants were medical students (31; 73.8%). Participants with no experience (the majority) in cadaver lab dissections, craniotomy as first operator, and as second operator represented 12 (27.9%), 29 (69%), and 22 (52.4%), respectively. Participants with moderate experience in cadaver lab dissections were 23 (53.5%). Post-course survey respondents noted positive feedback in most items queried including enhancement of familiarity and acquiring skills, confidence with neurosurgery instruments, confidence with microscope, part of standard training, traditional training, and lifelong training.

CONCLUSIONS

Simulation model combining augmented reality with physical simulation for hybrid experience can be a promising and valuable tool especially for medical students or early career neurosurgical residents.

Video-Based Performance Analysis in Pituitary Surgery-Part 1: Surgical Outcomes

BACKGROUND

Endoscopic pituitary adenoma surgery has a steep learning curve, with varying surgical techniques and outcomes across centers. In other surgeries, superior performance is linked with superior surgical outcomes. This study aimed to explore the prediction of patient-specific outcomes using surgical video analysis in pituitary surgery.

METHODS

Endoscopic pituitary adenoma surgery videos from a single center were annotated by experts for operative workflow (3 surgical phases and 15 surgical steps) and operative skill (using modified Objective Structured Assessment of Technical Skills [mOSATS]). Quantitative workflow metrics were calculated, including phase duration and step transitions. Poisson or logistic regression was used to assess the association of workflow metrics and mOSATS with common inpatient surgical outcomes.

RESULTS

100 videos from 100 patients were included. Nasal phase mean duration was 24 minutes and mean mOSATS was 21.2/30. Mean duration was 34 minutes and mean mOSATS was 20.9/30 for the sellar phase, and 11 minutes and 21.7/30, respectively, for the closure phase. The most common adverse outcomes were new anterior pituitary hormone deficiency (n = 26), dysnatremia (n = 24), and cerebrospinal fluid leak (n = 5). Higher mOSATS for all 3 phases and shorter operation duration were associated with decreased length of stay (P = 0.003 &P < 0.001). Superior closure phase mOSATS were associated with reduced postoperative cerebrospinal fluid leak (P < 0.001), and superior sellar phase mOSATS were associated with reduced postoperative visual deterioration (P = 0.041).

CONCLUSIONS

Superior surgical skill and shorter surgical time were associated with superior surgical outcomes, at a generic and phase-specific level. Such video-based analysis has promise for integration into data-driven training and service improvement initiatives.

Advancing Neurosurgical Skills: A Comparative Study of Training Models for Intra-Extracranial Cerebral Bypass

BACKGROUND

Training in anastomosis is fundamental in neurosurgery due to the precision and dexterity required. Biological models, although realistic, present limitations such as availability, ethical concerns, and the risk of biological contamination. Synthetic models, on the other hand, offer durability and standardized conditions, although they sometimes lack anatomical realism. This study aims to evaluate and compare the efficiency of anastomosis training models in the intra-extracranial cerebral bypass procedure, identifying those characteristics that enhance optimal microsurgical skill development and participant experience.

METHODS

A neurosurgery workshop was held from March 2024 to June 2024 with 5 vascular techniques and the participation of 22 surgeons. The models tested were the human placenta, the Wistar rat, the chicken wing artery, the nasogastric feeding tube, and the UpSurgeOn Mycro simulator. The scales used to measure these models were the Main Characteristics Score and the Evaluation Score. These scores allowed us to measure, qualitatively and quantitatively, durability, anatomical similarity, variety of simulation scenarios, risk of biological contamination, ethical considerations and disadvantages with specific infrastructure.

RESULTS

The human placenta model, Wistar rat model, and UpSurgeOn model were identified as the most effective for training. The human placenta and Wistar rat models were highly regarded for anatomical realism, while the UpSurgeOn model excelled in durability and advanced simulation scenarios. Ethical and cost implications were also considered.

CONCLUSIONS

The study identifies the human placenta and UpSurgeOn models as optimal for training in intra-extracranial bypass procedures, emphasizing the need for diverse and effective training models in neurosurgery.

Handheld robotic device for endoscopic neurosurgery: system integration and pre-clinical evaluation

The Expanded Endoscopic Endonasal Approach, one of the best examples of endoscopic neurosurgery, allows access to the skull base through the natural orifice of the nostril. Current standard instruments lack articulation limiting operative access and surgeon dexterity, and thus, could benefit from robotic articulation. In this study, a handheld robotic system with a series of detachable end-effectors for this approach is presented. This system is comprised of interchangeable articulated 2/3 degrees-of-freedom 3 mm instruments that expand the operative workspace and enhance the surgeon's dexterity, an ergonomically designed handheld controller with a rotating joystick-body that can be placed at the position most comfortable for the user, and the accompanying control box. The robotic instruments were experimentally evaluated for their workspace, structural integrity, and force-delivery capabilities. The entire system was then tested in a pre-clinical context during a phantom feasibility test, followed up by a cadaveric pilot study by a cohort of surgeons of varied clinical experience. Results from this series of experiments suggested enhanced dexterity and adequate robustness that could be associated with feasibility in a clinical context, as well as improvement over current neurosurgical instruments.

Blood Harmonisation of Endoscopic Transsphenoidal Surgical Video Frames on Phantom Models

Physical phantom models have been integral to surgical training, yet they lack realism and are unable to replicate the presence of blood resulting from surgical actions. Existing domain transfer methods aim to enhance realism, but none facilitate blood simulation. This study investigates the overlay of blood on images acquired during endoscopic transsphenoidal pituitary surgery on phantom models. The process involves employing manual techniques using the GIMP image manipulation application and automated methods using pythons Blend Modes module. We then approach this as an image harmonisation task to assess its practicality and feasibility. Our evaluation uses Structural Similarity Index Measure and Laplacian metrics. The results we obtained emphasize the significance of image harmonisation, offering substantial insights within the surgical field. Our work is a step towards investigating data-driven models that can simulate blood for increased realism during surgical training on phantom models.

Mapping patient education encounters in elective surgery: a cohort study and cross-sectional survey

OBJECTIVE

Develop a process map of when patients learn about their proposed surgery and what resources patients use to educate themselves.

DESIGN

A mixed methods design, combining semistructured stakeholder interviews, quantitative validation using electronic healthcare records (EHR) in a retrospective cohort and a cross-sectional patient survey.

SETTING

A single surgical centre in the UK.

PARTICIPANTS

Fourteen members of the spinal multidisciplinary team were interviewed to develop the process map.This process map was validated using the EHR of 50 patients undergoing elective spine surgery between January and June 2022. Postprocedure, feedback was gathered from 25 patient surveys to identify which resources they used to learn about their spinal procedure. Patients below the age of 18 or who received emergency surgery were excluded.

INTERVENTIONS

Elective spine surgery and patient questionnaires given postoperatively either on the ward or in follow-up clinic.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome was the percentage of the study cohort that was present at encounters on the process map. Key timepoints were defined if >80% of patients were present. The secondary outcome was the percentage of the study cohort that used educational resources listed in the patient questionnaire.

RESULTS

There were 342 encounters which occurred across the cohort, with 16 discrete event categories identified. The initial surgical clinic (88%), anaesthetic preoperative assessment (96%) and admission for surgery (100%) were identified as key timepoints. Surveys identified that patients most used verbal information from their surgeon (100%) followed by written information from their surgeon (52%) and the internet (40%) to learn about their surgery.

CONCLUSIONS

Process mapping is an effective method of illustrating the patient pathway. The initial surgical clinic, anaesthetic preoperative assessment and surgical admission are key timepoints where patients receive information. This has future implications for guiding patient education interventions to focus at key timepoints.

Latex vascular injection as method for enhanced neurosurgical training and skills

Background

Tridimensional medical knowledge of human anatomy is a key step in the undergraduate and postgraduate medical education, especially in surgical fields. Training simulation before real surgical procedures is necessary to develop clinical competences and to minimize surgical complications.

Methods

Latex injection of vascular system in brain and in head-neck segment is made after washing out of the vascular system and fixation of the specimen before and after latex injection.

Results

Using this latex injection technique, the vascular system of 90% of brains and 80% of head-neck segments are well-perfused. Latex-injected vessels maintain real appearance compared to silicone, and more flexible vessels compared to resins. Besides, latex makes possible a better perfusion of small vessels.

Conclusions

Latex vascular injection technique of the brain and head-neck segment is a simulation model for neurosurgical training based on real experiencing to improve surgical skills and surgical results.

3-Dimensionally Printed Affordable Nose Model: A Reliable Start in Endoscopic Training for Young Neurosurgeons

BACKGROUND

Training neurosurgical skills is one of the most important tasks of a residency program. Techniques' complexity and pathology rarity define a long learning curve for mastering different surgical skills for which simulation on anatomic samples is extremely important. For this purpose, cadaver laboratory training is the most reliable tool. However, since access to cadaveric specimens is limited, due to costs and availability, surgical skills could be developed using inanimate models. This work aimed to develop a printable 3-dimensional model of the nasal cavity and sellar floor using an open-source downloadable file, to give residents the opportunity to improve their endoscopic surgical skills in a low-risk atmosphere with little cost.

METHODS

The 3D model was realized taking as a sample a real-case CT scan imaging from which the sellar floor was removed. A quail egg was placed underneath the printed model covering the sellar floor opening. Under endoscopic visualization, the "sellar floor" was drilled by each participant with the goal of sparing the egg's inner membrane. Once the task was achieved, surgeons were asked to participate in a satisfaction survey.

RESULTS

The total cost for printing was 6.31€ (6,72$). A satisfaction survey showed technical improvement (90%), increased confidence (80%), and bringing learned skills into the operating room (70%), leading to a 100% agreement in introducing this project into residency programs.

CONCLUSIONS

Training on affordable anatomic models represents a useful tool in technical skills improvement. We believe this model could help residents bring their technical capabilities to more sophisticated levels.

Neurosurgical Education Using Cadaver-Free Brain Models and Augmented Reality: First Experiences from a Hands-On Simulation Course for Medical Students

Background and Objectives: Neurosurgery has been underrepresented in the medical school curriculum. Advances in augmented reality and 3D printing have opened the way for early practical training through simulations. We assessed the usability of the UpSurgeOn simulation-based training model and report first experiences from a hands-on neurosurgery course for medical students. Materials and Methods: We organized a two-day microneurosurgery simulation course tailored to medical students. On day one, three neurosurgeons demonstrated anatomical explorations with the help of life-like physical simulators (BrainBox, UpSurgeOn). The surgical field was projected onto large high-definition screens by a robotic-assisted exoscope (RoboticScope, BHS Technologies). On day two, the students were equipped with microsurgical instruments to explore the surgical anatomy of the pterional, temporal and endoscopic retrosigmoid approaches. With the help of the RoboticScope, they simulated five clipping procedures using the Aneurysm BrainBox. All medical students filled out a digital Likert-scale-based questionnaire to evaluate their experiences. Results: Sixteen medical students participated in the course. No medical students had previous experience with UpSurgeOn. All participants agreed that the app helped develop anatomical orientation. They unanimously agreed that this model should be part of residency training. Fourteen out of sixteen students felt that the course solidified their decision to pursue neurosurgery. The same fourteen students rated their learning experience as totally positive, and the remaining two rated it as rather positive. Conclusions: The UpSurgeOn educational app and cadaver-free models were perceived as usable and effective tools for the hands-on neuroanatomy and neurosurgery teaching of medical students. Comparative studies may help measure the long-term benefits of UpSurgeOn-assisted teaching over conventional resources.

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.

Image-guidance in endoscopic pituitary surgery: an in-silico study of errors involved in tracker-based techniques

Background

Endoscopic endonasal surgery is an established minimally invasive technique for resecting pituitary adenomas. However, understanding orientation and identifying critical neurovascular structures in this anatomically dense region can be challenging. In clinical practice, commercial navigation systems use a tracked pointer for guidance. Augmented Reality (AR) is an emerging technology used for surgical guidance. It can be tracker based or vision based, but neither is widely used in pituitary surgery.

Methods

This pre-clinical study aims to assess the accuracy of tracker-based navigation systems, including those that allow for AR. Two setups were used to conduct simulations: (1) the standard pointer setup, tracked by an infrared camera; and (2) the endoscope setup that allows for AR, using reflective markers on the end of the endoscope, tracked by infrared cameras. The error sources were estimated by calculating the Euclidean distance between a point's true location and the point's location after passing it through the noisy system. A phantom study was then conducted to verify the in-silico simulation results and show a working example of image-based navigation errors in current methodologies.

Results

The errors of the tracked pointer and tracked endoscope simulations were 1.7 and 2.5 mm respectively. The phantom study showed errors of 2.14 and 3.21 mm for the tracked pointer and tracked endoscope setups respectively.

Discussion

In pituitary surgery, precise neighboring structure identification is crucial for success. However, our simulations reveal that the errors of tracked approaches were too large to meet the fine error margins required for pituitary surgery. In order to achieve the required accuracy, we would need much more accurate tracking, better calibration and improved registration techniques.

The use of advanced technology for preoperative planning in cranial surgery - A survey by the EANS Young Neurosurgeons Committee

Introduction

Technological advancements provided several preoperative tools allowing for precise preoperative planning in cranial neurosurgery, aiming to increase the efficacy and safety of surgery. However, little data are available regarding if and how young neurosurgeons are trained in using such technologies, how often they use them in clinical practice, and how valuable they consider these technologies.

Research question

How frequently these technologies are used during training and clinical practice as well as to how their perceived value can be qualitatively assessed.

Materials and methods

The Young Neurosurgeons' Committee (YNC) of the European Association of Neurosurgical Societies (EANS) distributed a 14-items survey among young neurosurgeons between June 1st and August 31st, 2022.

Results

A total of 441 responses were collected. Most responders (42.34%) received "formal" training during their residency. Planning techniques were used mainly in neuro-oncology (90.86%), and 3D visualization of patients' DICOM dataset using open-source software was the most frequently used (>20 times/month, 20.34% of responders). Software for 3D visualization of patients' DICOM dataset was the most valuable technology, especially for planning surgical approach (42.03%). Conversely, simulation based on augmented/mixed/virtual reality was considered the less valuable tool, being rated below sufficiency by 39.7% of responders.

Discussion and conclusion

Training for using preoperative planning technologies in cranial neurosurgery is provided by neurosurgical residency programs. Software for 3D visualization of DICOM datasets is the most valuable and used tool, especially in neuro-oncology. Interestingly, simulation tools based on augmented/virtual/mixed reality are considered less valuable and, therefore, less used than other technologies.