T.H.J.M. Peeters

Diffusion tensor imaging of left ventricular remodeling in response to myocardial infarction in the mouse

The cardiac muscle architecture lies at the basis of the mechanical and electrical properties of the heart, and dynamic alterations in fiber structure are known to be of prime importance in healing and remodeling after myocardial infarction. In this study, left ventricular remodeling was characterized using diffusion tensor imaging (DTI) in a mouse model of myocardial infarction. Myocardial infarction was induced in mice by permanent ligation of the left anterior descending coronary artery. Serial ex vivo DTI measurements were performed 7, 14, 28, and 60 days after ligation. Apparent diffusion coefficient, fractional anisotropy, the three eigenvalues of the diffusion tensor, and the myofiber disarray served as readout parameters. After myocardial infarction, the mouse hearts displayed extreme wall thinning in the infarcted area, which covered large parts of the apex and extended into the free wall up to the equator. Average heart mass increased by 70% 7–60 days after infarction. Histological analysis showed that the infarct at 7 days consisted of unstructured tissue with residual necrosis and infiltration of macrophages and myofibroblasts. At 14 days after infarction, the necrotic tissue had disappeared and collagen fibers were starting to appear. From 28 to 60 days, the infarct had fully developed into a mature scar. DTI parameters showed dynamic changes as a function of time after infarction. The apparent diffusion coefficient in the infarcted region was lower than in remote regions and increased as a function of time after infarction. The fractional anisotropy was higher in the infarcted region and was maximum at 28 days, which was attributed to the development of structured collagen fibers. Myofiber disarray, which was analyzed by considering the alignment of fibers in neighboring voxels, was significantly higher in infarcted regions. DTI provides a valuable non‐destructive tool for characterizing structural remodeling in diseased myocardium. Copyright

Analysis of distance/similarity measures for diffusion tensor imaging

Many different measures have been proposed to compute similarities and distances between diffusion tensors. These measures are commonly used for algorithms such as segmentation, registration, and quantitative analysis of Diffusion Tensor Imaging data sets. The results obtained from these algorithms are extremely dependent on the chosen measure. The measures presented in literature can be of complete different nature, and it is often difficult to predict the behavior of a given measure for a specific application. In this chapter, we classify and summarize the different measures that have been presented in literature. We also present a framework to analyze and compare the behavior of the measures according to several selected properties. We expect that this framework will help in the initial selection of a measure for a given application and to identify when the generation of a new measure is needed. This framework will also allow the comparison of new measures with existing ones.

Fused DTI/HARDI Visualization

High-angular resolution diffusion imaging (HARDI) is a diffusion weighted MRI technique that overcomes some of the decisive limitations of its predecessor, diffusion tensor imaging (DTI), in the areas of composite nerve fiber structure. Despite its advantages, HARDI raises several issues: complex modeling of the data, nonintuitive and computationally demanding visualization, inability to interactively explore and transform the data, etc. To overcome these drawbacks, we present a novel, multifield visualization framework that adopts the benefits of both DTI and HARDI. By applying a classification scheme based on HARDI anisotropy measures, the most suitable model per imaging voxel is automatically chosen. This classification allows simplification of the data in areas with single fiber bundle coherence. To accomplish fast and interactive visualization for both HARDI and DTI modalities, we exploit the capabilities of modern GPUs for glyph rendering and adopt DTI fiber tracking in suitable regions. The resulting framework, allows user-friendly data exploration of fused HARDI and DTI data. Many incorporated features such as sharpening, normalization, maxima enhancement and different types of color coding of the HARDI glyphs, simplify the data and enhance its features. We provide a qualitative user evaluation that shows the potentials of our visualization tools in several HARDI applications.

Fast and sleek glyph rendering for interactive HARDI data exploration

High angular resolution diffusion imaging (HARDI) is an emerging magnetic resonance imaging (MRI) technique that overcomes some decisive limitations of its predecessor diffusion tensor imaging (DTI). HARDI can resolve locally more than one direction in the diffusion pattern of water molecules and thereby opens up the opportunity to display and track crossing fibers. Showing the local structure of the reconstructed, angular probability profiles in a fast, detailed, and interactive way can improve the quality of the research in this area and help to move it into clinical application. In this paper we present a novel approach for HARDI glyph visualization or, more generally, for the visualization of any function that resides on a sphere and that can be expressed by a Laplace series. Our GPU-accelerated glyph rendering improves the performance of the traditional way of HARDI glyph visualization as well as the visual quality of the reconstructed data, thus offering interactive HARDI data exploration of the local structure of the white brain matter in-vivo. In this paper we exploit the capabilities of modern GPUs to overcome the large, processor-intensive and memory-consuming data visualization.

GPU-Based Ray-Casting of Spherical Functions Applied to High Angular Resolution Diffusion Imaging

Abstract-Any sufficiently smooth, positive, real-valued function ψ : S2 → K+ on a sphere S2 can be expanded by a Laplace expansion into a sum of spherical harmonics. Given the Laplace expansion coefficients, we provide a CPU and GPU-based algorithm that renders the radial graph of ψ in a fast and efficient way by ray-casting the glyph of ψ in the fragment shader of a GPU. The proposed rendering algorithm has proven highly useful in the visualization of high angular resolution diffusion imaging (HARDI) data. Our implementation of the rendering algorithm can display simultaneously thousands of glyphs depicting the local diffusivity of water. The rendering is fast enough to allow for interactive manipulation of large HARDI data sets.

Case study: visualization of annotated DNA sequences

DNA sequences and their annotations form ever expanding data sets. Proper explorations of such data sets require new tools for visualization and analysis. In this case study, we have defined the requirements for a visualization tool for annotated DNA sequences. We have implemented these requirements in a new and flexible tool for browsing and comparing annotated DNA sequences interactively and in real-time. The use of standard information visualization techniques, such as linked windows, perspective walls, and smooth interaction, enables genome researchers to obtain better insight in large DNA data sets in an effective, efficient, and attractive way.

Interactive Fibre Structure Visualization of the Heart

The heart consists of densely packed muscle fibres. The orientation of these fibres can be acquired by using Diffusion Tensor Imaging (DTI) ex vivo. A good way to visualize the fibre structure in a cross section of the heart is by showing short line segments originating from the cross section and aligned with the local direction of the fibres. If the line segments are placed dense enough, one can see how the fibre orientations change. However, generation of the line segments takes time and thus the user has to wait for new geometry to be generated when the plane defining the cross section is changed. We present a new direct rendering method for the visualization of the 3D vector field in a 2D user‐definable cross section of a heart. On the intersection of the plane with the vector field, the full 3D vectors are rendered as 3D line segments with a local ray casting approach. No preprocessing of the data is needed and no geometry is generated. This technique allows a fast inspection of the data to identify interesting areas where further analysis is necessary (e.g. quantification or generation of streamlines). We also show how the technique is generalized to other glyph shapes than line segments by implementing ellipsoids.