A platform for real-3d visualization and planning of left atrial appendage occlusion through mixed reality

Funding Acknowledgements Type of funding sources: None. Background In left atrial appendage occlusion (LAAO), pre-procedural computed tomography (CT) is pivotal to describe the complex and highly variable LAA anatomy and to guide the operator in accurate planning of the intervention. Multiplanar reconstruction and 3D rendering are used for the navigation and analysis of the 3D datasets but they share some limitations that are due to the use of 2D screens; Mixed Reality (MxR) technology aims at overcoming such limitations by allowing for real-3D visualizations with holographic replicas of anatomical models while preserving a sense of presence within the true physical environment by the operator. Purpose To develop and test a MxR platform that provides a more intuitive and informative tool for the morphological analysis during the planning phase of LAAO. Methods Patients (n = 4) were randomly selected among those referred for a CT scan prior to transcatheter aortic valve replacement, each one characterized by a specific LAA morphology (cauliflower, bilobular, chicken wing, wind-sock). CT scans were performed in diastole at 75% of the R-R interval on a 64-slice scanner, with in-plane resolution 0.38-0.64 mm and slice thickness 0.62 mm. Firstly, the acquisition was cropped to contain the left atrium, the circumflex artery, the left upper pulmonary ridge. Subsequently, an isosurface with high coincidence between the blood cavity border and the endocardium was identified by the user and processed using a marching cube algorithm to obtain the 3D model. Finally, the 3D model was optimized for a MxR platform that allows for moving, zooming and cutting the model, measuring the main LAA linear dimensions and simulating the implant of a virtual replica of a transcatheter occluder. Results The workflow was successfully applied for all the patients independently from the morphology. All the models were successfully uploaded in the MxR platform (Fig 1.a) and for all the patients the morphological analysis was performed (Fig 1.b) in less than 10 minutes. The four different morphologies of the LAA were correctly identified allowing a very detailed holographic modeling of the structure, including the neck, the landing zone, the curvature and the position and size of lobes. For both the identified ostium and landing planes, using a dedicated measuring tool (Fig. 1.c), the operator measured the minimum and maximum diameters, which were later used to define the size of the occluder device to be used in the virtual implant simulation (Fig. 1.d). Conclusions The tested MxR platform suggested the potential to overcome the limits of the standard technologies in planning of LAAO thanks to the real-3D perception, potentially leading to a more accurate and faster planning phase. Furthermore, the use of MxR technology may enhance the ability to predict the optimal device size and position within the anatomy to obtain LAA complete sealing. Abstract Figure.

Using Poisson Disk Sampling to Render Oil Particles at Sea

Fluid simulation is one of the most complex tasks in three-dimensional simulation. Specifically, in the case of oil spills at sea, the oil film constantly interacts and is influenced by the environment, thus making its composition and properties change over time. In this paper, we tackle this problem by using both Lehr's spreading model and Hoult's drifting model to build the oil spill physical model. Unlike previous studies that only applied the Poisson disk algorithm to static and solid objects, we applied it in a three-dimensional space to divide the oil film into fluid particles. The track of oil particles under the influence of waves, wind, and currents is rendered by the Unity3D tool with C# programming language, which vividly and realistically simulates the collision of oil particles on the ocean scene with obstacles such as buoys and small islands. The result of this research can be used to predict oil spill direction, thus providing the solution to respond and minimize the damage caused by oil spills at sea. We also discuss some improvements to our model by using the Marching cube algorithm to render the Metaball model.

Vortex Analysis of Intra-Aneurismal Flow in Cerebral Aneurysms

This study aims to develop an alternative vortex analysis method by measuring structure ofIntracranial aneurysm (IA) flow vortexes across the cardiac cycle, to quantify temporal stability of aneurismal flow. Hemodynamics were modeled in “patient-specific” geometries, using computational fluid dynamics (CFD) simulations. Modified versions of knownλ2andQ-criterion methods identified vortex regions; then regions were segmented out using the classical marching cube algorithm. Temporal stability was measured by the degree of vortex overlap (DVO) at each step of a cardiac cycle against a cycle-averaged vortex and by the change in number of cores over the cycle. No statistical differences exist in DVO or number of vortex cores between 5 terminal IAs and 5 sidewall IAs. No strong correlation exists between vortex core characteristics and geometric or hemodynamic characteristics of IAs. Statistical independence suggests this proposed method may provide novel IA information. However, threshold values used to determine the vortex core regions and resolution of velocity data influenced analysis outcomes and have to be addressed in future studies. In conclusions, preliminary results show that the proposed methodology may help give novel insight toward aneurismal flow characteristic and help in future risk assessment given more developments.

Point Cloud Reconstruction Based on SVR

This paper presents a point cloud reconstruction algorithm which based on SVR(support vector regression) . Firstly, the point cloud data pre-processing, filter out noise points. Then train the point by SVR , and we can get the function of surface expression. Finally, using the Marching Cube algorithm to visualize the implicit function. Experimental results show that the algorithm is more robust and more efficient.