David M. Weinstein

White matter tractography using diffusion tensor deflection

Diffusion tensor MRI provides unique directional diffusion information that can be used to estimate the patterns of white matter connectivity in the human brain. In this study, the behavior of an algorithm for white matter tractography is examined. The algorithm, called TEND, uses the entire diffusion tensor to deflect the estimated fiber trajectory. Simulations and imaging experiments on in vivo human brains were performed to investigate the behavior of the tractography algorithm. The simulations show that the deflection term is less sensitive than the major eigenvector to image noise. In the human brain imaging experiments, estimated tracts were generated in corpus callosum, corticospinal tract, internal capsule, corona radiata, superior longitudinal fasciculus, inferior longitudinal fasciculus, fronto‐occipital fasciculus, and uncinate fasciculus. This approach is promising for mapping the organizational patterns of white matter in the human brain as well as mapping the relationship between major fiber trajectories and the location and extent of brain lesions. Hum. Brain Mapping 18:306–321, 2003.

Influence of tissue conductivity anisotropy on EEG/MEG field and return current computation in a realistic head model: a simulation and visualization study using high-resolution finite element modeling.

To achieve a deeper understanding of the brain, scientists, and clinicians use electroencephalography (EEG) and magnetoencephalography (MEG) inverse methods to reconstruct sources in the cortical sheet of the human brain. The influence of structural and electrical anisotropy in both the skull and the white matter on the EEG and MEG source reconstruction is not well understood. In this paper, we report on a study of the sensitivity to tissue anisotropy of the EEG/MEG forward problem for deep and superficial neocortical sources with differing orientation components in an anatomically accurate model of the human head. The goal of the study was to gain insight into the effect of anisotropy of skull and white matter conductivity through the visualization of field distributions, isopotential surfaces, and return current flow and through statistical error measures. One implicit premise of the study is that factors that affect the accuracy of the forward solution will have at least as strong an influence over solutions to the associated inverse problem. Major findings of the study include (1) anisotropic white matter conductivity causes return currents to flow in directions parallel to the white matter fiber tracts; (2) skull anisotropy has a smearing effect on the forward potential computation; and (3) the deeper a source lies and the more it is surrounded by anisotropic tissue, the larger the influence of this anisotropy on the resulting electric and magnetic fields. Therefore, for the EEG, the presence of tissue anisotropy both for the skull and white matter compartment substantially compromises the forward potential computation and as a consequence, the inverse source reconstruction. In contrast, for the MEG, only the anisotropy of the white matter compartment has a significant effect. Finally, return currents with high amplitudes were found in the highly conducting cerebrospinal fluid compartment, underscoring the need for accurate modeling of this space.

Optimization of MicroCT Imaging and Blood Vessel Diameter Quantitation of Preclinical Specimen Vasculature with Radiopaque Polymer Injection Medium

Vascular networks within a living organism are complex, multi-dimensional, and challenging to image capture. Radio-angiographic studies in live animals require a high level of infrastructure and technical investment in order to administer costly perfusion mediums whose signals metabolize and degrade relatively rapidly, diminishing within a few hours or days. Additionally, live animal specimens must not be subject to long duration scans, which can cause high levels of radiation exposure to the specimen, limiting the quality of images that can be captured. Lastly, despite technological advances in live-animal specimen imaging, it is quite difficult to minimize or prevent movement of a live animal, which can cause motion artifacts in the final data output. It is demonstrated here that through the use of postmortem perfusion protocols of radiopaque silicone polymer mediums and ex-vivo organ harvest, it is possible to acquire a high level of vascular signal in preclinical specimens through the use of micro-computed tomographic (microCT) imaging. Additionally, utilizing high-order rendering algorithms, it is possible to further derive vessel morphometrics for qualitative and quantitative analysis.

Practical Vessel Imaging by Computed Tomography in Live Transgenic Mouse Models for Human Tumors

Contrast-enhanced small-animal computed tomography is an economical and highly quantitative tool for serially examining tumor development in situ, for analyzing the network of blood vessels that nourish them, and for following the response of tumors to preclinical therapeutic intervention(s). We present practical considerations for visualizing the vascular network of transgenic mouse tumors. Using a long-acting iodinated triglyceride blood-pool contrast agent, we present optimized scanner acquisition parameters and volume-rendering techniques for examining the intermediate and large vessels of complex spontaneous tumors (e.g., alveolar rhabdomyosarcomas) in transgenic mice. Our findings indicate that multiple-frame, 360–720 view acquisitions were mandatory for clarifying bone and soft tissue from vessel contrast. This finding was consistent in visualizations using a one-dimensional transfer function where voxel color and opacity was assigned in proportion to CT value and a two-dimensional transfer function where voxel color and opacity was assigned in proportion to CT value and gradient magnitude. This study lays a groundwork for the qualitative and quantitative assessment of anti-angiogenesis preclinical studies using transgenic mice.

Biomedical computing and visualization software environments

Problem-solving environments and advanced visualization take on the complexity of biomedical computing, improving its utility to scientists and clinicians alike.

Optimization of Volumetric Computed Tomography for Skeletal Analysis of Model Genetic Organisms

Forward and reverse genetics now allow researchers to understand embryonic and postnatal gene function in a broad range of species. Although some genetic mutations cause obvious morphological change, other mutations can be more subtle and, without adequate observation and quantification, might be overlooked. For the increasing number of genetic model organisms examined by the growing field of phenomics, standardized but sensitive methods for quantitative analysis need to be incorporated into routine practice to effectively acquire and analyze ever-increasing quantities of phenotypic data. In this study, we present platform-independent parameters for the use of microscopic x-ray computed tomography (microCT) for phenotyping species-specific skeletal morphology of a variety of different genetic model organisms. We show that microCT is suitable for phenotypic characterization for prenatal and postnatal specimens across multiple species.

Three-dimensional Propagation in Mathematic Models: Integrative Model of the Mouse Heart

Computer models have been used to study cardiac conduction since the late 1970s. 1 At that time, computational power limited investigations to simple geometries corresponding to single fibers or monolayer sheets of cells. With the evolution of computer technologies, computational models of the heart have become three-dimensional and increasingly more realistic, 2 3 4 allowing a wider range of investigations to elucidate fundamental relations of a set of biophysic parameters and the underlying potential distributions and current flow.

Visualization of anatomic covariance tensor fields

The computation, visualization, and interpretation of brain variability remains a significant challenge in computational neuroanatomy. Current deformable registration methods can generate, for each vertex of a polygonal mesh modeling the cortical surface, a distribution of displacement vectors between the individual models and their average, which can be summarized as a covariance tensor. While analysis of anatomical covariance tensor fields promises insight into the structural components of aging and disease, basic understanding of the tensor field structure is hampered by the lack of effective methods to create informative and interactive visualizations. We describe a novel application of superquadric tensor glyphs to anatomic covariance tensor fields, supplemented by colormaps of important tensor attributes. The resulting visualizations support a more detailed characterization of population variability of brain structure than possible with previous methods, while also suggesting directions for subsequent quantitative analysis.

A Volumetric Method for Quantifying Atherosclerosis in Mice by Using MicroCT: Comparison to En Face

Precise quantification of atherosclerotic plaque in preclinical models of atherosclerosis requires the volumetric assessment of the lesion(s) while maintaining in situ architecture. Here we use micro-computed tomography (microCT) to detect ex vivo aortic plaque established in three dyslipidemic mouse models of atherosclerosis. All three models lack the low-density lipoprotein receptor (Ldlr−/−), each differing in plaque severity, allowing the evaluation of different plaque volumes using microCT technology. From clearly identified lesions in the thoracic aorta from each model, we were able to determine plaque volume (0.04–3.1 mm3), intimal surface area (0.5–30 mm2), and maximum plaque (intimal-medial) thickness (0.1–0.7 mm). Further, quantification of aortic volume allowed calculation of vessel occlusion by the plaque. To validate microCT for future preclinical studies, we compared microCT data to intimal surface area (by using en face methodology). Both plaque surface area and plaque volume were in excellent correlation between microCT assessment and en face surface area (r2 = 0.99, p<0.0001 and r2 = 0.95, p<0.0001, respectively). MicroCT also identified internal characteristics of the lipid core and fibrous cap, which were confirmed pathologically as Stary type III-V lesions. These data validate the use of microCT technology to provide a more exact empirical measure of ex vivo plaque volume throughout the entire intact aorta in situ for the quantification of atherosclerosis in preclinical models.

Evaluation of different meshing algorithms in the computation of defibrillation thresholds in children

In this paper we evaluate different meshing schemes to solve for the bioelectric fields that arise in the human body due to the defibrillation shock generated by an Implantable Cardiac Defibrillator, with particular emphasis on implantation in children. For children, the question of relative performance of different electrode locations remains open. Computational simulation is a critical tool to address this question, and mesh design is a critical component of such simulations. We use the SCIRun software package to address this simulation problem because it combines the powerful numeric tools required with interactive flexibility allowing easy comparison of both algorithms and electrode orientation. We describe a pipeline that starts with segmented CT-images and produces clinically useful parameters. Using this framework we report below that a meshing scheme using regularly spaced hexahedral elements which are locally refined around the electrodes constitute a quick and relatively accurate way of solving this problem.