Transformation of neurosurgical training from “see one, do one, teach one” to AR/VR & simulation – A survey by the EANS Young Neurosurgeons

Augmented reality technology shortens aneurysm surgery learning curve for residents

OBJECTIVES

We aimed to prospectively investigate the benefit of using augmented reality (AR) for surgery residents learning aneurysm surgery.

MATERIALS AND METHODS

Eight residents were included, and divided into an AR group and a control group (4 in each group). Both groups were asked to locate an aneurysm with a blue circle on the same screenshot after their viewing of surgery videos from both AR and non-AR tests. Only the AR group was allowed to inspect and manipulate an AR holographic representation of the aneurysm in AR tests. The actual location of the aneurysm was defined by a yellow circle by an attending physician after each test. Localization deviation was determined by the distance between the blue and yellow circle.

RESULTS

Localization deviation was lower in the AR group than in the control group in the last 2 tests (AR Test 2: 2.7 ± 1.0 mm vs. 5.8 ± 4.1 mm, p = 0.01, non-AR Test 2: 2.1 ± 0.8 mm vs. 5.9 ± 5.8 mm, p < 0.001). The mean deviation was lower in non-AR Test 2 as compared to non-AR Test 1 in both groups (AR: p < 0.001, control: p = 0.391). The localization deviation of the AR group decreased from 8.1 ± 3.8 mm in Test 2 to 2.7 ± 1.0 mm in AR Test 2 (p < 0.001).

CONCLUSION

AR technology provides an effective and interactive way for neurosurgery training, and shortens the learning curve for residents in aneurysm surgery.

Intraoperative teaching methods, models, and frameworks: A scoping review for surgical resident education

BACKGROUND

This review aimed to consolidate the existing literature on intraoperative teaching strategies and highlight areas for future research.

OBJECTIVE

The objective is to review the research conducted regarding the implementation of various teaching frameworks for surgical learners and to present their feasibility, benefits, and limitations within surgical residencies, as well as areas for future research.

METHODS

Two independent investigators searched MEDLINE, EMBASE, and ERIC and reviewed articles on intraoperative teaching strategies for surgical resident education.

RESULTS

3050 abstracts were reviewed, and 66 studies (2.2%) were included. The most common study type was single cohort studies (33%), followed by survey studies (17%). The majority of articles were carried out in General Surgery (50%), or a combination of surgical specialties (17%).

CONCLUSIONS

The BID model encompasses perioperative teaching time points and suggests a universal organizational approach to intraoperative teaching that would likely be compatible with documented competency assessments for residents.

Intraoperative Videogrammetry and Photogrammetry for Photorealistic Neurosurgical 3-Dimensional Models Generated Using Operative Microscope: Technical Note

BACKGROUND AND OBJECTIVES

Intraoperative orientation during microsurgery has a prolonged learning curve among neurosurgical residents. Three-dimensional (3D) understanding of anatomy can be facilitated with realistic 3D anatomic models created from photogrammetry, where a series of 2-dimensional images is converted into a 3D model. This study implements an algorithm that can create photorealistic intraoperative 3D models to exemplify important steps of the operation, operative corridors, and surgical perspectives.

METHODS

We implemented photograph-based and video-based scanning algorithms for uptakes using the operating room (OR) microscope, targeted for superficial structures, after surgical exposure, and deep operative corridors, in cranial microsurgery. The algorithm required between 30-45 photographs (superficial scanning), 45-65 photographs (deep scanning), or approximately 1 minute of video recording of the entire operative field to create a 3D model. A multicenter approach in 3 neurosurgical departments was applied to test reproducibility and refine the method.

RESULTS

Twenty-five 3D models were created of some of the most common neurosurgical approaches-frontolateral, pterional, retrosigmoid, frontal, and temporal craniotomy. The 3D models present important steps of the surgical approaches and allow rotation, zooming, and panning of the model, enabling visualization from different surgical perspectives. The superficial and medium depth structures were consistently presented through the 3D models, whereas scanning of the deepest structures presented some technical challenges, which were gradually overcome with refinement of the image capturing process.

CONCLUSION

Intraoperative photogrammetry is an accessible method to create 3D educational material to show complex anatomy and demonstrate concepts of intraoperative orientation. Detailed interactive 3D models, displaying stepwise surgical case-based anatomy, can be used to help understand details of the operative corridor. Further development includes refining or automatization of image acquisition intraoperatively and evaluation of other applications of the resulting 3D models in training and surgical planning.

Can AI pass the written European Board Examination in Neurological Surgery? - Ethical and practical issues

Introduction

Artificial intelligence (AI) based large language models (LLM) contain enormous potential in education and training. Recent publications demonstrated that they are able to outperform participants in written medical exams.

Research question

We aimed to explore the accuracy of AI in the written part of the EANS board exam.

Material and methods

Eighty-six representative single best answer (SBA) questions, included at least ten times in prior EANS board exams, were selected by the current EANS board exam committee. The questions' content was classified as 75 text-based (TB) and 11 image-based (IB) and their structure as 50 interpretation-weighted, 30 theory-based and 6 true-or-false. Questions were tested with Chat GPT 3.5, Bing and Bard. The AI and participant results were statistically analyzed through ANOVA tests with Stata SE 15 (StataCorp, College Station, TX). P-values of <0.05 were considered as statistically significant.

Results

The Bard LLM achieved the highest accuracy with 62% correct questions overall and 69% excluding IB, outperforming human exam participants 59% (p = 0.67) and 59% (p = 0.42), respectively. All LLMs scored highest in theory-based questions, excluding IB questions (Chat-GPT: 79%; Bing: 83%; Bard: 86%) and significantly better than the human exam participants (60%; p = 0.03). AI could not answer any IB question correctly.

Discussion and conclusion

AI passed the written EANS board exam based on representative SBA questions and achieved results close to or even better than the human exam participants. Our results raise several ethical and practical implications, which may impact the current concept for the written EANS board exam.

Augmented reality simulation as training model of ventricular puncture: Evidence in the improvement of the quality of punctures

BACKGROUND

Ventricular puncture is a common procedure in neurosurgery and the first that resident must learn. Ongoing education is critical to improving patient outcomes. However, training at the expense of potential risk to patients warrants new and safer training methods for residents.

METHODS

An augmented reality (AR) simulator for the practice of ventricular punctures was designed. It consists of a navigation system with a virtual 3D projection of the anatomy over a 3D-printed patient model. Forty-eight participants from neurosurgery staff performed two free-hand ventricular punctures before and after a training session.

RESULTS

Participants achieved enhanced accuracy in reaching the target at the Monro foramen after practicing with the system. Additional metrics revealed significantly better trajectories after the training.

CONCLUSION

The study confirms the feasibility of AR as a training tool. This motivates future work towards standardising new educative methodologies in neurosurgery.

Photogrammetry Applied to Neurosurgery: A Literature Review

Photogrammetry refers to the process of creating 3D models and taking measurements through the use of photographs. Photogrammetry has many applications in neurosurgery, such as creating 3D anatomical models and diagnosing and evaluating head shape and posture deformities. This review aims to summarize the uses of the technique in the neurosurgical practice and showcase the systems and software required for its implementation. A literature review was done in the online database PubMed. Papers were searched using the keywords "photogrammetry", "neurosurgery", "neuroanatomy", "craniosynostosis" and "scoliosis". The identified articles were later put through primary (abstracts and titles) and secondary (full text) screening for eligibility for inclusion. In total, 86 articles were included in the review from 315 papers identified. The review showed that the main uses of photogrammetry in the field of neurosurgery are related to the creation of 3D models of complex neuroanatomical structures and surgical approaches, accompanied by the uses for diagnosis and evaluation of patients with structural deformities of the head and trunk, such as craniosynostosis and scoliosis. Additionally, three instances of photogrammetry applied for more specific aims, namely, cervical spine surgery, skull-base surgery, and radiosurgery, were identified. Information was extracted on the software and systems used to execute the method. With the development of the photogrammetric method, it has become possible to create accurate 3D models of physical objects and analyze images with dedicated software. In the neurosurgical setting, this has translated into the creation of anatomical teaching models and surgical 3D models as well as the evaluation of head and spine deformities. Through those applications, the method has the potential to facilitate the education of residents and medical students and the diagnosis of patient pathologies.

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.