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PURPOSE To introduce a scheme based on a recent technique in computational hemodynamics, known as the lattice Boltzmann methods (LBM), to noninvasively measure pressure gradients in patients with a coarctation of the aorta (CoA). To provide evidence on the accuracy of the proposed scheme, the computed pressure drop values are compared against those obtained using the reference standard method of catheterization. MATERIALS AND METHODS Pre- and posttreatment LBM-based pressure gradients for 12 patients with CoA were simulated for the time point of peak systole using the open source library OpenLB. Four-dimensional (4D) flow-sensitive phase-contrast MRI at 1.5 Tesla was used to acquire flow and to setup the simulation. The vascular geometry was reconstructed using 3D whole-heart MRI. Patients underwent pre- and postinterventional pressure catheterization as a reference standard. RESULTS There is a significant linear correlation between the pretreatment catheter pressure drops and those computed based on the LBM simulation, r=.85, P

Various options are available for the treatment of mitral valve insufficiency, including reconstructive approaches such as annulus correction through ring implants. The correct choice of general therapy and implant is relevant for an optimal outcome. Additional to guidelines, decision support systems (DSS) can provide decision aid by means of virtual intervention planning and predictive simulations. Our approach on virtual downsizing is one of the virtual intervention tools that are part of the DSS workflow. It allows for emulating a ring implantation based on patient-specific lumen geometry and vendor-specific implants. Our approach is fully automatic and relies on a lumen mask and an annulus contour as inputs. Both are acquired from previous DSS workflow steps. A virtual surface- and contour-based model of a vendor-specific ring design (26–40 mm) is generated. For each case, the ring geometry is positioned with respect to the original, patient-specific annulus and additional anatomical landmarks. The lumen mesh is parameterized to allow for a vertex-based deformation with respect to the user-defined annulus. Derived from post-interventional observations, specific deformation schemes are applied to atrium and ventricle and the lumen mesh is altered with respect to the ring location. For quantitative evaluation, the surface distance between the deformed lumen mesh and segmented post-operative echo lumen close to the annulus was computed for 11 datasets. The results indicate a good agreement. An arbitrary subset of six datasets was used for a qualitative evaluation of the complete lumen. Two domain experts compared the deformed lumen mesh with post-interventional echo images. All deformations were deemed plausible. Our approach on virtual downsizing allows for an automatic creation of plausible lumen deformations. As it takes only a few seconds to generate results, it can be added to a virtual intervention toolset without unnecessarily increasing the pipeline complexity.

Various cardiac diseases can be diagnosed by the analysis of myocardial motion. Relevant biomarkers are radial, longitudinal, and rotational velocities of the cardiac muscle computed locally from MR images. We designed a visual encoding that maps these three attributes to glyph shapes according to a barycentric space formed by 3D superquadric glyphs. The glyphs show aggregated myocardial motion information following the AHA model and are displayed in a respective 3D layout.

Morphology of cardiovascular tissue is influenced by the unsteady behavior of the blood flow and vice versa. Therefore, the pathogenesis of several cardiovascular diseases is directly affected by the blood-flow dynamics. Understanding flow behavior is of vital importance to understand the cardiovascular system and potentially harbors a considerable value for both diagnosis and risk assessment. The analysis of hemodynamic characteristics involves qualitative and quantitative inspection of the blood-flow field. Visualization plays an important role in the qualitative exploration, as well as the definition of relevant quantitative measures and its validation. There are two main approaches to obtain information about the blood flow: simulation by computational fluid dynamics, and in-vivo measurements. Although research on blood flow simulation has been performed for decades, many open problems remain concerning accuracy and patient-specific solutions. Possibilities for real measurement of blood flow have recently increased considerably by new developments in magnetic resonance imaging which enable the acquisition of 3D quantitative measurements of blood-flow velocity fields. This chapter presents the visualization challenges for both simulation and real measurements of unsteady blood-flow fields.

Volume rendering allows the direct visualization of scanned volume data, and can reveal vessel abnormalitiesmore faithfully. In this overview, we will present a pipeline model for direct volume rendering systems, which focus on vascular structures. We will cover the fields of data pre-processing, classification of the volume via transfer functions, and finally rendering the volume in 2D and 3D. For each stage in the pipeline, different techniques are discussed to support the diagnosis of vascular diseases. Next to various general methods we will present two case studies, in which the systems are optimized for two different medical issues. At the end, we discuss current trends in volume rendering and their implications for vessel visualization.

Objective: Accurate and high-quality reconstructions of vascular structures are essential for vascular disease diagnosis and blood flow simulations.These applications necessitate a trade-off between accuracy and smoothness. An additional requirement for the volume grid generation for Computational Fluid Dynamics (CFD) simulations is a high triangle quality. We propose a method that produces an accurate reconstruction of the vessel surface with satisfactory surface quality.