Preparing for the future of cardiothoracic surgery with virtual reality simulation and surgical planning:a narrative review

Background and Objective: Virtual reality (VR) technology in cardiothoracic surgery has been an area of interest for almost three decades, but computational limitations had restricted its implementation. Recent advances in computing power have facilitated the creation of high-fidelity VR simulations and anatomy visualisation tools. We undertook a non-systematic narrative review of literature on VR simulations and preoperative planning tools in cardiothoracic surgery and present the state-of-the-art, and a future outlook. Methods: A comprehensive search through MEDLINE database was performed in November 2022 for all publications that describe the use of VR in cardiothoracic surgery regarding training purposes, education, simulation, and procedural planning. We excluded papers that were not in English or Dutch, and that used two-dimensional (2D) screens, augmented, and simulated reality. Key Content and Findings: Results were categorised as simulators and preoperative planning tools. Current surgical simulators include the lobectomy module in the LapSim for video assisted thorascopic surgery which has been extensively validated, and the more recent robotic assisted lobectomy simulators from Robotix Mentor and Da Vinci SimNow, which are increasingly becoming integrated into the robotic surgery curriculum. Other perioperative simulators include the CardioPulmonary VR Resuscitation simulator for advanced life support after cardiac surgery, and the VR Extracorporeal Circulation (ECC) simulator for perfusionists to simulate the use of a heart-lung machine (HLM). For surgical planning, there are many small-scale tools available, and many case/pilot studies have been published utilising the visualisation possibilities provided by VR, including congenital cardiac, congenital thoracic, adult cardiac, and adult thoracic diseases. Conclusions: There are many promising tools becoming available to leverage the immersive power of VR in cardiothoracic surgery. The path to validate these simulators is well described, but large-scale trials producing high-level evidence for their efficacy are absent as of yet. Our view is that these tools will become increasingly integral parts of daily practice in this field in the coming decade.</p

Evaluation of a Patient-Specific, Low-Cost, 3-Dimensional–Printed Transesophageal Echocardiography Human Heart Phantom

Simulation based education has been shown to increase the task-specific capability of medical trainees. Transesophageal echocardiography training greatly benefits from the use of simulators. They allow real time scanning of a beating heart and generation of ultrasound images side by side with anatomically accurate virtual model. These simulators are costly and have many limitations. 3D printing technologies have enabled the creation of bespoke phantoms capable of being used as task-trainers. This study aims to compare the ease of use and accuracy of a low-cost patient-specific, Computer-tomography based, 3D printed, echogenic TEE phantom compared to a commercially available echocardiography training mannequin. We hypothesized that a low-cost, 3D printed custom-made, cardiac phantom has comparable image quality, accuracy and usability as existing commercially available echocardiographic phantoms. After Institutional Ethic Research Board approval, we recruited ten American Board – Certified cardiac anesthesiologists and conducted a blinded comparative study divided into two stages. Stage one consisted of image assessment. A set of basic TEE views obtained from the 3D printed and commercial phantom were presented to the participants on a computer screen in random order. For each image, participants will be asked to identify the view, identify the quality of the image on a 1-5 Likert scale compared to the corresponding human view and guess with which phantom it was acquired (1 not at all realistic to patients view and 5 realistic to patients view). Stage two, participants will be asked to use the 3D printed and the commercially available phantom to obtain basic TEE views. In a maximum of 30 minutes. Each view was recorded and assessed for accuracy by two certified echocardiographers. Time needed to acquire each basic view and number of correct views was recorded. Overall usability of the phantoms was assessed through a questionnaire. For all continuous variables, we will calculate mean, median and standard deviation. We use Wilcoxon Signed-Rank test to assess significant differences in the rating of each phantom. All ten participants completed all part of the study. All participants could recognize all of the standard views. The average Likert scale was 3.2 for the 3D printed and 2.9 for the commercial Phantom with no significant difference. The average time to obtain views was 24.5 and 30 sec for the 3D printed and the commercial phantoms respectively statistically significantly in favor of the 3D printed phantom. The qualitative user assessment for ease to obtain the views, probe manipulation, image quality and overall experience were in great favor of the 3D printed phantom. Our Study suggest that the quality of TEE images obtained on the 3D printed phantom are not significantly different from those obtained on the commercial Phantom. The ease of use and time required to complete a basic TEE exam were in favor of the 3D Printed phantom.:Table of Content 1. Bibliographic Description 3 2. Introduction 4 2.1. Perioperative transesophageal echocardiography 4 2.2. Transesophageal echocardiography training 5 2.3. Transesophageal echocardiography simulation 6 2.4. 3D Heart Printing 13 2.5. 3D Segmentation 16 2.6. Development of the study phantom 17 2.7. Study Rationale 18 3. Publication 22 4. Summary 30 5. References 33 6. Appendices 37 6.1. Darstellung des eigenes Beitrags 38 6.2. Erklärung über die eigenständige Abfassung der Arbeit 39 6.3. Lebenslauf 40 6.4. Publikationen und Vorträge 44 6.5. Danksagung 61

Real-Time Ultrasound Simulation for Medical Training and Standardized Patient Assessment

With the increasing role played by ultrasound in clinical diagnostics, ultrasound training in medical education has become more and more important. The clinical routine for ultrasound training is on real patients; therefore monitored and guided examinations involving medical students are quite time-constrained. Furthermore, standardized patients (SPs), who are increasingly used in medical school for teaching and assessing medical students, need to be augmented. These SPs are typically healthy individuals who can not accurately portray the variety of abnormalities that are needed for training especially when medical examinations involve instrument interactions. To augment SPs in a realistically effective way and also address the resourced time constraints for sonography training, a computerized ultrasound simulation is essential for medical education. In this dissertation, I investigate a real-time ultrasound simulation methodology based on a virtual 3-dimentional (3-D) mesh organ. This research has developed the simulation technology to augment SPs with synthetic ultrasound images. I present this methodology and its use in simulating echocardiography. This simulated echocardiogram displays the various oriented sonographs in real time according to the placement of a mock transducer without the need of an actual patient

Position-based dynamics simulator of vessel deformations for path planning in robotic endovascular catheterization

A major challenge during autonomous navigation in endovascular interventions is the complexity of operating in a deformable but constrained workspace with an instrument. Simulation of deformations for it can provide a cost-effective training platform for path planning. Aim of this study is to develop a realistic, auto-adaptive, and visually plausible simulator to predict vessels’ global deformation induced by the robotic catheter’s contact and cyclic heartbeat motion. Based on a Position-based Dynamics (PBD) approach for vessel modeling, Particle Swarm Optimization (PSO) algorithm is employed for an auto-adaptive calibration of PBD deformation parameters and of the vessels movement due to a heartbeat. In-vitro experiments were conducted and compared with in-silico results. The end-user evaluation results were reported through quantitative performance metrics and a 5-Point Likert Scale questionnaire. Compared with literature, this simulator has an error of 0.23±0.13% for deformation and 0.30±0.85mm for the aortic root displacement. In-vitro experiments show an error of 1.35±1.38mm for deformation prediction. The end-user evaluation results show that novices are more accustomed to using joystick controllers, and cardiologists are more satisfied with the visual authenticity. The real-time and accurate performance of the simulator make this framework suitable for creating a dynamic environment for autonomous navigation of robotic catheters

Virtual Reality simulator for dental anesthesia training in the inferior alveolar nerve block

Objectives This study shows the development and validation of a dental anesthesia-training simulator, specifically for the inferior alveolar nerve block (IANB). The system developed provides the tactile sensation of inserting a real needle in a human patient, using Virtual Reality (VR) techniques and a haptic device that can provide a perceived force feedback in the needle insertion task during the anesthesia procedure. Material and Methods To simulate a realistic anesthesia procedure, a Carpule syringe was coupled to a haptic device. The Volere method was used to elicit requirements from users in the Dentistry area; Repeated Measures Two-Way ANOVA (Analysis of Variance), Tukey post-hoc test and averages for the results’ analysis. A questionnaire-based subjective evaluation method was applied to collect information about the simulator, and 26 people participated in the experiments (12 beginners, 12 at intermediate level, and 2 experts). The questionnaire included profile, preferences (number of viewpoints, texture of the objects, and haptic device handler), as well as visual (appearance, scale, and position of objects) and haptic aspects (motion space, tactile sensation, and motion reproduction). Results The visual aspect was considered appropriate and the haptic feedback must be improved, which the users can do by calibrating the virtual tissues’ resistance. The evaluation of visual aspects was influenced by the participants’ experience, according to ANOVA test (F=15.6, p=0.0002, with

Augmented reality in medical education: a systematic review

Introduction: The field of augmented reality (AR) is rapidly growing with many new potential applications in medical education. This systematic review investigated the current state of augmented reality applications (ARAs) and developed an analytical model to guide future research in assessing ARAs as teaching tools in medical education. Methods: A literature search was conducted using PubMed, Embase, Web of Science, Cochrane Library, and Google Scholar. This review followed PRISMA guidelines and included publications from January 1, 2000 to June 18, 2018. Inclusion criteria were experimental studies evaluating ARAs implemented in healthcare education published in English. Our review evaluated study quality and determined whether studies assessed ARA validity using criteria established by the GRADE Working Group and Gallagher et al., respectively. These findings were used to formulate an analytical model to assess the readiness of ARAs for implementation in medical education. Results: We identified 100,807 articles in the initial literature search; 36 met inclusion criteria for final review and were categorized into three categories: Surgery (23), Anatomy (9), and Other (4). The overall quality of the studies was poor and no ARA was tested for all five stages of validity. Our analytical model evaluates the importance of research quality, application content, outcomes, and feasibility of an ARA to gauge its readiness for implementation. Conclusion: While AR technology is growing at a rapid rate, the current quality and breadth of AR research in medical training is insufficient to recommend the adoption into educational curricula. We hope our analytical model will help standardize AR assessment methods and define the role of AR technology in medical education

Automated speckle tracking algorithm to aid on-axis imaging in echocardiography

Obtaining a “correct” view in echocardiography is a subjective process in which an operator attempts to obtain images conforming to consensus standard views. Real-time objective quantification of image alignment may assist less experienced operators, but no reliable index yet exists. We present a fully automated algorithm for detecting incorrect medial/lateral translation of an ultrasound probe by image analysis. The ability of the algorithm to distinguish optimal from sub-optimal four-chamber images was compared to that of specialists—the current “gold-standard.” The orientation assessments produced by the automated algorithm correlated well with consensus visual assessments of the specialists (r=0.87r=0.87) and compared favourably with the correlation between individual specialists and the consensus, 0.82±0.09. Each individual specialist’s assessments were within the consensus of other specialists, 75±14% of the time, and the algorithm’s assessments were within the consensus of specialists 85% of the time. The mean discrepancy in probe translation values between individual specialists and their consensus was 0.97±0.87  cm, and between the automated algorithm and specialists’ consensus was 0.92±0.70  cm. This technology could be incorporated into hardware to provide real-time guidance for image optimisation—a potentially valuable tool both for training and quality control