BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

Anisotropic water diffusion in neural fibres such as nerve, white matter in spinal cord, or white matter in brain forms the basis for the utilization of diffusion tensor imaging (DTI) to track fibre pathways. The fact that water diffusion is sensitive to the underlying tissue microstructure provides a unique method of assessing the orientation and integrity of these neural fibres, which may be useful in assessing a number of neurological disorders. The purpose of this review is to characterize the relationship of nuclear magnetic resonance measurements of water diffusion and its anisotropy (i.e. directional dependence) with the underlying microstructure of neural fibres. The emphasis of the review will be on model neurological systems both in vitro and in vivo. A systematic discussion of the possible sources of anisotropy and their evaluation will be presented followed by an overview of various studies of restricted diffusion and compartmentation as they relate to anisotropy. Pertinent pathological models, developmental studies and theoretical analyses provide further insight into the basis of anisotropic diffusion and its potential utility in the nervous system.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/nbm.782

The basis of anisotropic water diffusion in the nervous system – a technical review

The state of the art of reconstruction of the axonal tracts in the central nervous system (CNS) using diffusion tensor imaging (DTI) is reviewed. This relatively new technique has generated much enthusiasm and high expectations because it presently is the only approach available to non-invasively study the three-dimensional architecture of white matter tracts. While there is no doubt that DTI fiber tracking is providing exciting new opportunities to study CNS anatomy, it is very important to understand its limitations. In this review we therefore assess the basic principles and the assumptions that need to be made for each step of the study, including both data acquisition and the elaborate fiber reconstruction algorithms. Special attention is paid to situations where complications may arise, and possible solutions are reviewed. Validation issues and potential future directions and improvements are also discussed.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/nbm.781

Fiber tracking: Principles and strategies - A technical review

Because of their wide use in molecular modeling, methods to compute molecular surfaces have received a lot of interest in recent years. However, most of the proposed algorithms compute the analytical representation of only the solvent-accessible surface. There are a few programs that compute the analytical representation of the solvent-excluded surface, but they often have problems handling singular cases of self-intersecting surfaces and tend to fail on large molecules (more than 10,000 atoms). We describe here a program called MSMS, which is shown to be fast and reliable in computing molecular surfaces. It relies on the use of the reduced surface that is briefly defined here and from which the solvent-accessible and solvent-excluded surfaces are computed. The four algorithms composing MSMS are described and their complexity is analyzed. Special attention is given to the handling of self-intersecting parts of the solvent-excluded surface called singularities. The program has been compared with Connolly's program PQMS [M.L. Connolly (1993) Journal of Molecular Graphics, Vol. 11, pp. 139-141] on a set of 709 molecules taken from the Brookhaven Data Base. MSMS was able to compute topologically correct surfaces for each molecule in the set. Moreover, the actual time spent to compute surfaces is in agreement with the theoretical complexity of the program, which is shown to be O[n log(n)] for n atoms. On a Hewlett-Packard 9000/735 workstation, MSMS takes 0.73 s to produce a triangulated solvent-excluded surface for crambin (1 crn, 46 residues, 327 atoms, 4772 triangles), 4.6 s for thermolysin (3tln, 316 residues, 2437 atoms, 26462 triangles), and 104.53 s for glutamine synthetase (2gls, 5676 residues, 43632 atoms, 476665 triangles).

Reduced surface: An efficient way to compute molecular surfaces

Two- and three-dimensional (3D) white matter atlases were created on the basis of high-spatial-resolution diffusion tensor magnetic resonance (MR) imaging and 3D tract reconstruction. The 3D trajectories of 17 prominent white matter tracts could be reconstructed and depicted. Tracts were superimposed on coregistered anatomic MR images to parcel the white matter. These parcellation maps were then compared with coregistered diffusion tensor imaging color maps to assign visible structures. The results showed (a) which anatomic structures can be identified on diffusion tensor images and (b) where these anatomic units are located at each section level and orientation. The atlas may prove useful for educational and clinical purposes. © RSNA, 2003

Fiber tract-based atlas of human white matter anatomy.

Toward a machine learning approach for classifying user goals from user interactions.

Multiple sclerosis (MS) is a chronic disease of the central nervous system that predominantly affects young adults during their most productive years. Pathologically, MS is characterized by the presence of areas of demyelination and T-cell predominant perivascular inflammation in the brain white matter. In order to study the effect of MS lesion on the white matter, we acquire diffusion tensor imaging (DTI) data on MS patients and employ streamtubes and streamsurfaces to visualize the DTI data. We also register structural data sets with DTI data sets and generate isosurfaces of the MS lesions and the ventricles. The simultaneous visualization of all the models has the potential to elucidate the complex relationship between the MS lesions, the white matter neural fibers and the affected gray matter regions.

/pdf/visualization-of-the-interaction-of-multiple-sclerosis-3cnz1qd6gl.pdf

Visualization of the Interaction of Multiple Sclerosis Lesions with Adjacent White Matter Fibers Using Streamtubes and Streamsurfaces

We visualize gene co-regulation patterns by creating 2D embeddings from microarray data corresponding to complete gene sets from the mouse genome, across large numbers of cell types. We use google maps and client-side graphics to disseminate pre-rendered such visualizations with a small but intuitive set of interactions. We conduct an anecdotal evaluation with domain specialists and demonstrate that biologists appreciate this approach because it facilitates low-overhead access to readily analyzable perspectives of unfamiliar datasets and because it offers a convenient way of disseminating large datasets in visual form.

Visualizing gene co-expression as google maps

P2-232 Diffusion-tensor imaging: linear, planar, and spherical diffusion in cadasil

We demonstrate a method for visualizing contact areas and ligament paths in articular joints. Contact areas define the cortical surface where bones articulate with each other. Visualization of contact areas and ligament paths has the potential to non-invasively highlight subtle but important differences between injured and uninjured joints. Animations of these visualizations are particularly helpful for understanding changes in relationships among bones. We applied our technique to the distal radioulnar joint of a volunteer diagnosed with malunited distal radial fracture in one forearm. Our approach highlights modifications in injured forearm kinematics previously undetected.

/pdf/visualization-of-contact-areas-and-ligament-paths-in-joints-rgemzf5ysu.pdf

David H. Laidlaw

Papers

Toward a machine learning approach for classifying user goals from user interactions.

Visualization of the Interaction of Multiple Sclerosis Lesions with Adjacent White Matter Fibers Using Streamtubes and Streamsurfaces

Visualizing gene co-expression as google maps

P2-232 Diffusion-tensor imaging: linear, planar, and spherical diffusion in cadasil

Visualization of Contact Areas and Ligament Paths in Joints