A novel model for minimally invasive left ventricular assist device implantation training.

Background: Significant advances in minimally invasive implantation of mechanical circulatory support devices have been made. These approaches are technically challenging and associated with a learning curve. Simulation and training opportunities in these techniques are limited. We developed a high-fidelity novel model for minimally invasive left ventricular assist device implantation.Material and methods: Using a modified inanimate simulator (LSI SOLUTIONS®) and an animal tissue model, a hybrid simulator was created, with a porcine ex vivo heart secured within the inanimate simulator in the normal anatomic position. Key components of the minimally invasive left ventricular assist device implantation were performed, including left ventricular apical coring, attachment of the apical ring, attachment of the assist device, and creation of the aortic-outflow graft anastomosis.Results: A novel composite inanimate and tissue model for minimally invasive left ventricular assist device implantation was successfully developed. These simulation techniques were reproducible, and the model demonstrated ability to successfully simulate key components of the procedure.Conclusions: This high-fidelity, reproducible hybrid model allows for crucial components of minimally invasive LVAD implantation to be performed. This model has the potential to be used as an adjunct to surgical training, providing a safe and controlled learning environment for trainees to acquire skills in minimally invasive LVAD implantation.

Using difference intervals for time-varying isosurface visualization.

We present a novel approach to out-of-core time-varying isosurface visualization. We attempt to interactively visualize time-varying datasets which are too large to fit into main memory using a technique which is dramatically different from existing algorithms. Inspired by video encoding techniques, we examine the data differences between time steps to extract isosurface information. We exploit span space extraction techniques to retrieve operations necessary to update isosurface geometry from neighboring time steps. Because only the changes between time steps need to be retrieved from disk, I/O bandwidth requirements are minimized. We apply temporal compression to further reduce disk access and employ a point-based previewing technique that is refined in idle interaction cycles. Our experiments on computational simulation data indicate that this method is an extremely viable solution to large time-varying isosurface visualization. Our work advances the state-of-the-art by enabling all isosurfaces to be represented by a compact set of operations.