MRI-based computational hemodynamics in patients with aortic coarctation using the lattice Boltzmann methods: Clinical validation study.

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<.001. The bias was -0.58 ± 4.1 mmHg and was not significant ( P=0.64) with a 95% confidence interval (CI) of -3.22 to 2.06. For the posttreatment results, the bias was larger and at -2.54 ± 3.53 mmHg with a 95% CI of -0.17 to -4.91 mmHg. CONCLUSION: The results indicate a reasonable agreement between the simulation results and the catheter measurements. LBM-based computational hemodynamics can be considered as an alternative to more traditional computational fluid dynamics schemes for noninvasive pressure calculations and can assist in diagnosis and therapy planning. LEVEL OF EVIDENCE: 3 J. Magn. Reson. Imaging 2017;45:139-146.

Interactive editing of virtual chordae tendineae for the simulation of the mitral valve in a decision support system.

PURPOSE: Decision support systems for mitral valve disease are an important step toward personalized surgery planning. A simulation of the mitral valve apparatus is required for decision support. Building a model of the chordae tendineae is an essential component of a mitral valve simulation. Due to image quality and artifacts, the chordae tendineae cannot be reliably detected in medical imaging. METHODS: Using the position-based dynamics framework, we are able to realistically simulate the opening and closing of the mitral valve. Here, we present a heuristic method for building an initial chordae model needed for a successful simulation. In addition to the heuristic, we present an interactive editor to refine the chordae model and to further improve pathology reproduction as well as geometric approximation of the closed valve. RESULTS: For evaluation, five mitral valves were reconstructed based on image sequences of patients scheduled for mitral valve surgery. We evaluated the approximation of the closed valves using either just the heuristic chordae model or a manually refined model. Using the manually refined models, prolapse was correctly reproduced in four of the five cases compared to two of the five cases when using the heuristic. In addition, using the editor improved the approximation in four cases. CONCLUSIONS: Our approach is suitable to create realistically parameterized mitral valve apparatus reconstructions for the simulation of normally and abnormally closing valves in a decision support system.

Virtual downsizing for decision support in mitral valve repair.

PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Extraction of open-state mitral valve geometry from CT volumes.

PURPOSE: The importance of mitral valve therapies is rising due to an aging population. Visualization and quantification of the valve anatomy from image acquisitions is an essential component of surgical and interventional planning. The segmentation of the mitral valve from computed tomography (CT) acquisitions is challenging due to high variation in appearance and visibility across subjects. We present a novel semi-automatic approach to segment the open-state valve in 3D CT volumes that combines user-defined landmarks to an initial valve model which is automatically adapted to the image information, even if the image data provide only partial visibility of the valve. METHODS: Context information and automatic view initialization are derived from segmentation of the left heart lumina, which incorporates topological, shape and regional information. The valve model is initialized with user-defined landmarks in views generated from the context segmentation and then adapted to the image data in an active surface approach guided by landmarks derived from sheetness analysis. The resulting model is refined by user landmarks. RESULTS: For evaluation, three clinicians segmented the open valve in 10 CT volumes of patients with mitral valve insufficiency. Despite notable differences in landmark definition, the resulting valve meshes were overall similar in appearance, with a mean surface distance of [Formula: see text] mm. Each volume could be segmented in 5-22 min. CONCLUSIONS: Our approach enables an expert user to easily segment the open mitral valve in CT data, even when image noise or low contrast limits the visibility of the valve.

Interactive virtual stent planning for the treatment of coarctation of the aorta.

PURPOSE: The coarctation of the aorta (CoA), a local narrowing of the aortic arch, accounts for 7 % of all congenital heart defects. Stenting is a recommended therapy to reduce the pressure gradient. This procedure is associated with complications such as the development of adverse flow conditions. A computer-aided treatment planning based on flow simulations can help to predict possible complications. The virtual stent planning is an important, intermediate step in the treatment planning pipeline. We present a novel approach that automatically suggests a stent setup and provides a set of intuitive parameters that allow for an interactive adaption of the suggested stent placement and induced deformation. METHODS: A high-quality mesh and a centerline are automatically generated. The stent-induced deformation is realized through a deformation of the centerline and a vertex displacement with respect to the deformed centerline and additional stent parameters. The parameterization is automatically derived from the underlying data and can be optionally altered through a condensed set of clinically sound parameters. RESULTS: The automatic deformation can be generated in about 25 s on a consumer system. The interactive adaption can be performed in real time. Compared with manual expert reconstructions of the stented vessel section, the mean difference of vessel path and diameter is below 1 mm. CONCLUSION: Our approach enables a medical user to easily generate a plausibly deformed vessel mesh which is necessary as input for a simulation-based treatment planning of CoA.

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.