Immersive Visualization in Biomedical Computational Fluid Dynamics and Didactic Teaching and Learning

Virtual reality (VR) can stimulate active learning, critical thinking, decision making and improved performance. It requires a medium to show virtual content, which is called a virtual environment (VE). The MARquette Visualization Lab (MARVL) is an example of a VE. Robust processes and workflows that allow for the creation of content for use within MARVL further increases the userbase for this valuable resource. A workflow was created to display biomedical computational fluid dynamics (CFD) and complementary data in a wide range of VE’s. This allows a researcher to study the simulation in its natural three-dimensional (3D) morphology. In addition, it is an exciting way to extract more information from CFD results by taking advantage of improved depth cues, a larger display canvas, custom interactivity, and an immersive approach that surrounds the researcher. The CFD to VR workflow was designed to be basic enough for a novice user. It is also used as a tool to foster collaboration between engineers and clinicians. The workflow aimed to support results from common CFD software packages and across clinical research areas. ParaView, Blender and Unity were used in the workflow to take standard CFD files and process them for viewing in VR. Designated scripts were written to automate the steps implemented in each software package. The workflow was successfully completed across multiple biomedical vessels, scales and applications including: the aorta with application to congenital cardiovascular disease, the Circle of Willis with respect to cerebral aneurysms, and the airway for surgical treatment planning. The workflow was completed by novice users in approximately an hour. Bringing VR further into didactic teaching within academia allows students to be fully immersed in their respective subject matter, thereby increasing the students’ sense of presence, understanding and enthusiasm. MARVL is a space for collaborative learning that also offers an immersive, virtual experience. A workflow was created to view PowerPoint presentations in 3D using MARVL. A resulting Immersive PowerPoint workflow used PowerPoint, Unity and other open-source software packages to display the PowerPoint presentations in 3D. The Immersive PowerPoint workflow can be completed in under thirty minutes

Research on real-time physics-based deformation for haptic-enabled medical simulation

This study developed a multiple effective visuo-haptic surgical engine to handle a variety of surgical manipulations in real-time. Soft tissue models are based on biomechanical experiment and continuum mechanics for greater accuracy. Such models will increase the realism of future training systems and the VR/AR/MR implementations for the operating room

Real-time hybrid cutting with dynamic fluid visualization for virtual surgery

It is widely accepted that a reform in medical teaching must be made to meet today's high volume training requirements. Virtual simulation offers a potential method of providing such trainings and some current medical training simulations integrate haptic and visual feedback to enhance procedure learning. The purpose of this project is to explore the capability of Virtual Reality (VR) technology to develop a training simulator for surgical cutting and bleeding in a general surgery

Design and development of a VR system for exploration of medical data using haptic rendering and high quality visualization

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Multimodality in VR: A survey

Virtual reality (VR) is rapidly growing, with the potential to change the way we create and consume content. In VR, users integrate multimodal sensory information they receive, to create a unified perception of the virtual world. In this survey, we review the body of work addressing multimodality in VR, and its role and benefits in user experience, together with different applications that leverage multimodality in many disciplines. These works thus encompass several fields of research, and demonstrate that multimodality plays a fundamental role in VR; enhancing the experience, improving overall performance, and yielding unprecedented abilities in skill and knowledge transfer

Augmented reality (AR) for surgical robotic and autonomous systems: State of the art, challenges, and solutions

Despite the substantial progress achieved in the development and integration of augmented reality (AR) in surgical robotic and autonomous systems (RAS), the center of focus in most devices remains on improving end-effector dexterity and precision, as well as improved access to minimally invasive surgeries. This paper aims to provide a systematic review of different types of state-of-the-art surgical robotic platforms while identifying areas for technological improvement. We associate specific control features, such as haptic feedback, sensory stimuli, and human-robot collaboration, with AR technology to perform complex surgical interventions for increased user perception of the augmented world. Current researchers in the field have, for long, faced innumerable issues with low accuracy in tool placement around complex trajectories, pose estimation, and difficulty in depth perception during two-dimensional medical imaging. A number of robots described in this review, such as Novarad and SpineAssist, are analyzed in terms of their hardware features, computer vision systems (such as deep learning algorithms), and the clinical relevance of the literature. We attempt to outline the shortcomings in current optimization algorithms for surgical robots (such as YOLO and LTSM) whilst providing mitigating solutions to internal tool-to-organ collision detection and image reconstruction. The accuracy of results in robot end-effector collisions and reduced occlusion remain promising within the scope of our research, validating the propositions made for the surgical clearance of ever-expanding AR technology in the future

Machine learning and interactive real-time simulation for training on relevant total hip replacement skills.

Virtual Reality simulators have proven to be an excellent tool in the medical sector to help trainees mastering surgical abilities by providing them with unlimited training opportunities. Total Hip Replacement (THR) is a procedure that can benefit significantly from VR/AR training, given its non-reversible nature. From all the different steps required while performing a THR, doctors agree that a correct fitting of the acetabular component of the implant has the highest relevance to ensure successful outcomes. Acetabular reaming is the step during which the acetabulum is resurfaced and prepared to receive the acetabular implant. The success of this step is directly related to the success of fitting the acetabular component. Therefore, this thesis will focus on developing digital tools that can be used to assist the training of acetabular reaming. Devices such as navigation systems and robotic arms have proven to improve the final accuracy of the procedure. However, surgeons must learn to adapt their instrument movements to be recognised by infrared cameras. When surgeons are initially introduced to these systems, surgical times can be extended up to 20 minutes, maximising surgical risks. Training opportunities are sparse, given the high investment required to purchase these devices. As a cheaper alternative, we developed an Augmented Reality (AR) alternative for training on the calibration of imageless navigation systems (INS). At the time, there were no alternative simulators that using head-mounted displays to train users into the steps to calibrate such systems. Our simulator replicates the presence of an infrared camera and its interaction with the reflecting markers located on the surgical tools. A group of 6 hip surgeons were invited to test the simulator. All of them expressed their satisfaction with the ease of use and attractiveness of the simulator as well as the similarity of interaction with the real procedure. The study confirmed that our simulator represents a cheaper and faster option to train multiple surgeons simultaneously in the use of Imageless Navigation Systems (INS) than learning exclusively on the surgical theatre. Current reviews on simulators for orthopaedic surgical procedures lack objective metrics of assessment given a standard set of design requirements. Instead, most of them rely exclusively on the level of interaction and functionality provided. We propose a comparative assessment rubric based on three different evaluation criteria. Namely immersion, interaction fidelity, and applied learning theories. After our assessment, we found that none of the simulators available for THR provides an accurate interactive representation of resurfacing procedures such as acetabular reaming based on force inputs exerted by the user. This feature is indispensable for an orthopaedics simulator, given that hand-eye coordination skills are essential skills to be trained before performing non-reversible bone removal on real patients. Based on the findings of our comparative assessment, we decided to develop a model to simulate the physically-based deformation expected during traditional acetabular reaming, given the user’s interaction with a volumetric mesh. Current interactive deformation methods on high-resolution meshes are based on geometrical collision detection and do not consider the contribution of the materials’ physical properties. By ignoring the effect of the material mechanics and the force exerted by the user, they become inadequate for training on hand- eye coordination skills transferable to the surgical theatre. Volumetric meshes are preferred in surgical simulation to geometric ones, given that they are able to represent the internal evolution of deformable solids resulting from cutting and shearing operations. Existing numerical methods for representing linear and corotational FEM cuts can only maintain interactive framerates at a low resolution of the mesh. Therefore, we decided to train a machine-learning model to learn the continuum mechanic laws relevant to acetabular reaming and predict deformations at interactive framerates. To the best of our knowledge, no research has been done previously on training a machine learning model on non-elastic FEM data to achieve results at interactive framerates. As training data, we used the results from XFEM simulations precomputed over 5000 frames for plastic deformations on tetrahedral meshes with 20406 elements each. We selected XFEM simulation as the physically-based deformation ground-truth given its accuracy and fast convergence to represent cuts, discontinuities and large strain rates. Our machine learning-based interactive model was trained following the Graph Neural Networks (GNN) blocks. GNNs were selected to learn on tetrahedral meshes as other supervised-learning architectures like the Multilayer perceptron (MLP), and Convolutional neural networks (CNN) are unable to learn the relationships between entities with an arbitrary number of neighbours. The learned simulator identifies the elements to be removed on each frame and describes the accumulated stress evolution in the whole machined piece. Using data generated from the results of XFEM allowed us to embed the effects of non-linearities in our interactive simulations without extra processing time. The trained model executed the prediction task using our tetrahedral mesh and unseen reamer orientations faster per frame than the time required to generate the training FEM dataset. Given an unseen orientation of the reamer, the trained GN model updates the value of accumulated stress on each of the 20406 tetrahedral elements that constitute our mesh during the prediction task. Once this value is updated, the tetrahedrons to be removed from the mesh are identified using a threshold condition. After using each single-frame output as input for the following prediction repeatedly for up to 60 iterations, our model can maintain an accuracy of up to 90.8% in identifying the status of each element given their value of accumulated stress. Finally, we demonstrate how the developed estimator can be easily connected to any game engine and included in developing a fully functional hip arthroplasty simulator

Virtual Reality Simulator for Training in Myringotomy with Tube Placement

Myringotomy refers to a surgical incision in the eardrum, and it is often followed by ventilation tube placement to treat middle-ear infections. The procedure is difficult to learn; hence, the objectives of this work were to develop a virtual-reality training simulator, assess its face and content validity, and implement quantitative performance metrics and assess construct validity. A commercial digital gaming engine (Unity3D) was used to implement the simulator with support for 3D visualization of digital ear models and support for major surgical tasks. A haptic arm co-located with the stereo scene was used to manipulate virtual surgical tools and to provide force feedback. A questionnaire was developed with 14 face validity questions focusing on realism and 6 content validity questions focusing on training potential. Twelve participants from the Department of Otolaryngology were recruited for the study. Responses to 12 of the 14 face validity questions were positive. One concern was with contact modeling related to tube insertion into the eardrum, and the second was with movement of the blade and forceps. The former could be resolved by using a higher resolution digital model for the eardrum to improve contact localization. The latter could be resolved by using a higher fidelity haptic device. With regard to content validity, 64% of the responses were positive, 21% were neutral, and 15% were negative. In the final phase of this work, automated performance metrics were programmed and a construct validity study was conducted with 11 participants: 4 senior Otolaryngology consultants and 7 junior Otolaryngology residents. Each participant performed 10 procedures on the simulator and metrics were automatically collected. Senior Otolaryngologists took significantly less time to completion compared to junior residents. Junior residents had 2.8 times more errors as compared to experienced surgeons. The senior surgeons also had significantly longer incision lengths, more accurate incision angles, and lower magnification keeping both the umbo and annulus in view. All metrics were able to discriminate senior Otolaryngologists from junior residents with a significance of p \u3c 0.002. The simulator has sufficient realism, training potential and performance discrimination ability to warrant a more resource intensive skills transference study

Patient Specific Systems for Computer Assisted Robotic Surgery Simulation, Planning, and Navigation

The evolving scenario of surgery: starting from modern surgery, to the birth of medical imaging and the introduction of minimally invasive techniques, has seen in these last years the advent of surgical robotics. These systems, making possible to get through the difficulties of endoscopic surgery, allow an improved surgical performance and a better quality of the intervention. Information technology contributed to this evolution since the beginning of the digital revolution: providing innovative medical imaging devices and computer assisted surgical systems. Afterwards, the progresses in computer graphics brought innovative visualization modalities for medical datasets, and later the birth virtual reality has paved the way for virtual surgery. Although many surgical simulators already exist, there are no patient specific solutions. This thesis presents the development of patient specific software systems for preoperative planning, simulation and intraoperative assistance, designed for robotic surgery: in particular for bimanual robots that are becoming the future of single port interventions. The first software application is a virtual reality simulator for this kind of surgical robots. The system has been designed to validate the initial port placement and the operative workspace for the potential application of this surgical device. Given a bimanual robot with its own geometry and kinematics, and a patient specific 3D virtual anatomy, the surgical simulator allows the surgeon to choose the optimal positioning of the robot and the access port in the abdominal wall. Additionally, it makes possible to evaluate in a virtual environment if a dexterous movability of the robot is achievable, avoiding unwanted collisions with the surrounding anatomy to prevent potential damages in the real surgical procedure. Even if the software has been designed for a specific bimanual surgical robot, it supports any open kinematic chain structure: as far as it can be described in our custom format. The robot capabilities to accomplish specific tasks can be virtually tested using the deformable models: interacting directly with the target virtual organs, trying to avoid unwanted collisions with the surrounding anatomy not involved in the intervention. Moreover, the surgical simulator has been enhanced with algorithms and data structures to integrate biomechanical parameters into virtual deformable models (based on mass-spring-damper network) of target solid organs, in order to properly reproduce the physical behaviour of the patient anatomy during the interactions. The main biomechanical parameters (Young's modulus and density) have been integrated, allowing the automatic tuning of some model network elements, such as: the node mass and the spring stiffness. The spring damping coefficient has been modeled using the Rayleigh approach. Furthermore, the developed method automatically detect the external layer, allowing the usage of both the surface and internal Young's moduli, in order to model the main parts of dense organs: the stroma and the parenchyma. Finally the model can be manually tuned to represent lesion with specific biomechanical properties. Additionally, some software modules of the simulator have been properly extended to be integrated in a patient specific computer guidance system for intraoperative navigation and assistance in robotic single port interventions. This application provides guidance functionalities working in three different modalities: passive as a surgical navigator, assistive as a guide for the single port placement and active as a tutor preventing unwanted collision during the intervention. The simulation system has beed tested by five surgeons: simulating the robot access port placemen, and evaluating the robot movability and workspace inside the patient abdomen. The tested functionalities, rated by expert surgeons, have shown good quality and performance of the simulation. Moreover, the integration of biomechanical parameters into deformable models has beed tested with various material samples. The results have shown a good visual realism ensuring the performance required by an interactive simulation. Finally, the intraoperative navigator has been tested performing a cholecystectomy on a synthetic patient mannequin, in order to evaluate: the intraoperative navigation accuracy, the network communications latency and the overall usability of the system. The tests performed demonstrated the effectiveness and the usability of the software systems developed: encouraging the introduction of the proposed solution in the clinical practice, and the implementation of further improvements. Surgical robotics will be enhanced by an advanced integration of medical images into software systems: allowing the detailed planning of surgical interventions by means of virtual surgery simulation based on patient specific biomechanical parameters. Furthermore, the advanced functionalities offered by these systems, enable surgical robots to improve the intraoperative surgical assistance: benefitting of the knowledge of the virtual patient anatomy

The matrix revisited: A critical assessment of virtual reality technologies for modeling, simulation, and training

A convergence of affordable hardware, current events, and decades of research have advanced virtual reality (VR) from the research lab into the commercial marketplace. Since its inception in the 1960s, and over the next three decades, the technology was portrayed as a rarely used, high-end novelty for special applications. Despite the high cost, applications have expanded into defense, education, manufacturing, and medicine. The promise of VR for entertainment arose in the early 1990\u27s and by 2016 several consumer VR platforms were released. With VR now accessible in the home and the isolationist lifestyle adopted due to the COVID-19 global pandemic, VR is now viewed as a potential tool to enhance remote education. Drawing upon over 17 years of experience across numerous VR applications, this dissertation examines the optimal use of VR technologies in the areas of visualization, simulation, training, education, art, and entertainment. It will be demonstrated that VR is well suited for education and training applications, with modest advantages in simulation. Using this context, the case is made that VR can play a pivotal role in the future of education and training in a globally connected world