Semi-automatic vortex extraction in 4D PC-MRI cardiac blood flow data using line predicates.

Cardiovascular diseases (CVD) are the leading cause of death worldwide. Their initiation and evolution depends strongly on the blood flow characteristics. In recent years, advances in 4D PC-MRI acquisition enable reliable and time-resolved 3D flow measuring, which allows a qualitative and quantitative analysis of the patient-specific hemodynamics. Currently, medical researchers investigate the relation between characteristic flow patterns like vortices and different pathologies. The manual extraction and evaluation is tedious and requires expert knowledge. Standardized, (semi-)automatic and reliable techniques are necessary to make the analysis of 4D PC-MRI applicable for the clinical routine. In this work, we present an approach for the extraction of vortex flow in the aorta and pulmonary artery incorporating line predicates. We provide an extensive comparison of existent vortex extraction methods to determine the most suitable vortex criterion for cardiac blood flow and apply our approach to ten datasets with different pathologies like coarctations, Tetralogy of Fallot and aneurysms. For two cases we provide a detailed discussion how our results are capable to complement existent diagnosis information. To ensure real-time feedback for the domain experts we implement our method completely on the GPU.

Recommendations for accurate numerical blood flow simulations of stented intracranial aneurysms.

The number of scientific publications dealing with stented intracranial aneurysms is rapidly increasing. Powerful computational facilities are now available; an accurate computational modeling of hemodynamics in patient-specific configurations is, however, still being sought. Furthermore, there is still no general agreement on the quantities that should be computed and on the most adequate analysis for intervention support. In this article, the accurate representation of patient geometry is first discussed, involving successive improvements. Concerning the second step, the mesh required for the numerical simulation is especially challenging when deploying a stent with very fine wire structures. Third, the description of the fluid properties is a major challenge. Finally, a founded quantitative analysis of the simulation results is obviously needed to support interventional decisions. In the present work, an attempt has been made to review the most important steps for a high-quality computational fluid dynamics computation of virtually stented intracranial aneurysms. In consequence, this leads to concrete recommendations, whereby the obtained results are not discussed for their medical relevance but for the evaluation of their quality. This investigation might hopefully be helpful for further studies considering stent deployment in patient-specific geometries, in particular regarding the generation of the most appropriate computational model.

The FLOWLENS: a focus-and-context visualization approach for exploration of blood flow in cerebral aneurysms.

Blood flow and derived data are essential to investigate the initiation and progression of cerebral aneurysms as well as their risk of rupture. An effective visual exploration of several hemodynamic attributes like the wall shear stress (WSS) and the inflow jet is necessary to understand the hemodynamics. Moreover, the correlation between focus-and-context attributes is of particular interest. An expressive visualization of these attributes and anatomic information requires appropriate visualization techniques to minimize visual clutter and occlusions. We present the FLOWLENS as a focus-and-context approach that addresses these requirements. We group relevant hemodynamic attributes to pairs of focus-and-context attributes and assign them to different anatomic scopes. For each scope, we propose several FLOWLENS visualization templates to provide a flexible visual filtering of the involved hemodynamic pairs. A template consists of the visualization of the focus attribute and the additional depiction of the context attribute inside the lens. Furthermore, the FLOWLENS supports local probing and the exploration of attribute changes over time. The FLOWLENS minimizes visual cluttering, occlusions, and provides a flexible exploration of a region of interest. We have applied our approach to seven representative datasets, including steady and unsteady flow data from CFD simulations and 4D PC-MRI measurements. Informal user interviews with three domain experts confirm the usefulness of our approach.