Determining the Magnitude of the Fully Asymmetric Diffusion Tensor from Heteronuclear Relaxation Data in the Absence of Structural Information

1998 ◽  
Vol 120 (19) ◽  
pp. 4889-4890 ◽  
Author(s):  
G. Marius Clore ◽  
Angela M. Gronenborn ◽  
Attila Szabo ◽  
Nico Tjandra
Keyword(s):  
Diffusion Tensor ◽  
Structural Information ◽  
Relaxation Data ◽  
Heteronuclear Relaxation

scholarly journals Finite-Element Extrapolation of Myocardial Structure Alterations Across the Cardiac Cycle in Rats

2015 ◽  
Vol 137 (10) ◽  
Author(s):  
Arnold David Gomez ◽  
David A. Bull ◽  
Edward W. Hsu
Keyword(s):  
Finite Element ◽  
Cardiac Cycle ◽  
Diffusion Tensor ◽  
Structural Information ◽  
Isolated Heart ◽  
Transverse Isotropy ◽  
Radial Strain ◽  
Structural Alteration ◽  
Scan Time ◽  
Subject Specific

Myocardial microstructures are responsible for key aspects of cardiac mechanical function. Natural myocardial deformation across the cardiac cycle induces measurable structural alteration, which varies across disease states. Diffusion tensor magnetic resonance imaging (DT-MRI) has become the tool of choice for myocardial structural analysis. Yet, obtaining the comprehensive structural information of the whole organ, in 3D and time, for subject-specific examination is fundamentally limited by scan time. Therefore, subject-specific finite-element (FE) analysis of a group of rat hearts was implemented for extrapolating a set of initial DT-MRI to the rest of the cardiac cycle. The effect of material symmetry (isotropy, transverse isotropy, and orthotropy), structural input, and warping approach was observed by comparing simulated predictions against in vivo MRI displacement measurements and DT-MRI of an isolated heart preparation at relaxed, inflated, and contracture states. Overall, the results indicate that, while ventricular volume and circumferential strain are largely independent of the simulation strategy, structural alteration predictions are generally improved with the sophistication of the material model, which also enhances torsion and radial strain predictions. Moreover, whereas subject-specific transversely isotropic models produced the most accurate descriptions of fiber structural alterations, the orthotropic models best captured changes in sheet structure. These findings underscore the need for subject-specific input data, including structure, to extrapolate DT-MRI measurements across the cardiac cycle.

scholarly journals A graph neural network framework for causal inference in brain networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
S. Wein ◽  
W. M. Malloni ◽  
A. M. Tomé ◽  
S. M. Frank ◽  
G. -I. Henze ◽  
...  
Keyword(s):  
Neural Network ◽  
Large Scale ◽  
Diffusion Tensor ◽  
Structural Information ◽  
Brain Networks ◽  
Scale Up ◽  
Brain Regions ◽  
Neural Activation ◽  
Dynamic Interactions ◽  
The Brain

AbstractA central question in neuroscience is how self-organizing dynamic interactions in the brain emerge on their relatively static structural backbone. Due to the complexity of spatial and temporal dependencies between different brain areas, fully comprehending the interplay between structure and function is still challenging and an area of intense research. In this paper we present a graph neural network (GNN) framework, to describe functional interactions based on the structural anatomical layout. A GNN allows us to process graph-structured spatio-temporal signals, providing a possibility to combine structural information derived from diffusion tensor imaging (DTI) with temporal neural activity profiles, like that observed in functional magnetic resonance imaging (fMRI). Moreover, dynamic interactions between different brain regions discovered by this data-driven approach can provide a multi-modal measure of causal connectivity strength. We assess the proposed model’s accuracy by evaluating its capabilities to replicate empirically observed neural activation profiles, and compare the performance to those of a vector auto regression (VAR), like that typically used in Granger causality. We show that GNNs are able to capture long-term dependencies in data and also computationally scale up to the analysis of large-scale networks. Finally we confirm that features learned by a GNN can generalize across MRI scanner types and acquisition protocols, by demonstrating that the performance on small datasets can be improved by pre-training the GNN on data from an earlier study. We conclude that the proposed multi-modal GNN framework can provide a novel perspective on the structure-function relationship in the brain. Accordingly this approach appears to be promising for the characterization of the information flow in brain networks.

scholarly journals An ITK Implementation of a Diffusion Tensor Images Resampling Filter

2012 ◽  
Author(s):  
Francois Budin ◽  
Sylvain Bouix ◽  
Martha Shenton ◽  
Martin Styner ◽  
Ipek Oguz
Keyword(s):  
Diffusion Tensor ◽  
Structural Information ◽  
Diffusion Tensor Images ◽  
Vector Images

This paper describes the implementation of a resampling filter for Diffusion Tensor Images (DTI) in the Insight ToolKit (ITK). ITK already contains a filter for resampling scalar and vector images as well as several transformation and interpolation classes. However, due to the directional nature of DT images, using the existing classes would result in losing the structural information of the image. We developed a new resampling filter, specific to DTI, that preserves the structure by applying a rotation directly on the tensors while performing the transformation of the image. New transformation and interpolator classes have also been implemented to handle tensors correctly. The new transformation classes are based on algorithms described by D.C. Alexander et al. Finally, three filters have been written to correct symmetric semi-definite matrices that would no longer be positive after the resampling process and project them into the tensors’ space. In addition, a software based on the new classes has been developed and is provided with this article.

Review of Corpus Callosum Topography, Analysis of Diffusion Values for the Different Callosal Fibers and Sex Differences

2008 ◽  
Vol 21 (6) ◽  
pp. 745-754 ◽  
Author(s):  
F.B. Pizzini ◽  
G. Tassinari ◽  
G. Zoccatelli ◽  
S. Magon ◽  
F. Alessandrini ◽  
...  
Keyword(s):  
Corpus Callosum ◽  
Diffusion Tensor ◽  
Structural Information ◽  
Morphological Evidence ◽  
Cortical Connectivity ◽  
Conventional Mri ◽  
Diffusion Parameters ◽  
Functional Relevance ◽  
Diffusion Tensor Imaging Dti

Conventional MRI shows the morphology of the corpus callosum (CC), but does not reveal cortical connectivity or structural information on the CC. Here, we applied diffusion tensor imaging (DTI) in conjunction with a tract-tracing algorithm to incorporate cortical connectivity information on the CC in 40 subjects and to detect the main area and sex structural differences. CC parcellation was based on trajectories to different cortical (prefrontal, frontal motor/premotor/supplementary motor connections, parieto-occipital, temporal) and sub-cortical areas (capsular/basal ganglia connections). In agreement with recent DTI studies, we found that motor fibers occupy a much larger portion of the CC than previously believed on the basis of anatomical data. Differences in anisotropy values were instead in agreement with previous morphological evidence of smaller fibers in the anterior and posterior portions of the CC. The main sex difference was observed in anisotropy values in frontal fibers that proved to be lower in females than in males. Statistically significant differences in the regional diffusion parameters and between sexes give rise to many important questions regarding fiber organization patterns, CC microstructure and the functional relevance of these differences and provide evidence for the role of DTI, which reaches beyond the information given by morphological analysis.

scholarly journals DWI-Based Neural Fingerprinting Technology: A Preliminary Study on Stroke Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Chenfei Ye ◽  
Heather Ting Ma ◽  
Jun Wu ◽  
Pengfei Yang ◽  
Xuhui Chen ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Diffusion Tensor ◽  
Structural Information ◽  
Region Of Interest ◽  
Clinical Practices ◽  
Stroke Subtype ◽  
Physiological Characterization ◽  
Magnetic Resonance Imaging Mri ◽  
And Diffusion ◽  
Diffusion Tensor Imaging Dti

Stroke is a common neural disorder in neurology clinics. Magnetic resonance imaging (MRI) has become an important tool to assess the neural physiological changes under stroke, such as diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI). Quantitative analysis of MRI images would help medical doctors to localize the stroke area in the diagnosis in terms of structural information and physiological characterization. However, current quantitative approaches can only provide localization of the disorder rather than measure physiological variation of subtypes of ischemic stroke. In the current study, we hypothesize that each kind of neural disorder would have its unique physiological characteristics, which could be reflected by DWI images on different gradients. Based on this hypothesis, a DWI-based neural fingerprinting technology was proposed to classify subtypes of ischemic stroke. The neural fingerprint was constructed by the signal intensity of the region of interest (ROI) on the DWI images under different gradients. The fingerprint derived from the manually drawn ROI could classify the subtypes with accuracy 100%. However, the classification accuracy was worse when using semiautomatic and automatic method in ROI segmentation. The preliminary results showed promising potential of DWI-based neural fingerprinting technology in stroke subtype classification. Further studies will be carried out for enhancing the fingerprinting accuracy and its application in other clinical practices.

Measurement and Reduction of Radiation Damage in Frozen Hydrated Crystalline Specimens

1978 ◽  
Vol 36 (3) ◽  
pp. 70-77 ◽  
Author(s):  
R.M. Glaeser ◽  
S.B. Hayward
Keyword(s):  
Diffraction Pattern ◽  
Structural Information ◽  
Structural Disorder ◽  
Structural Features ◽  
Biological Macromolecules ◽  
Diffraction Intensity ◽  
Object Structure ◽  
Specimen Material ◽  
Unit Cells ◽  
Identical Unit

Highly ordered or crystalline biological macromolecules become severely damaged and structurally disordered after a brief electron exposure. Evidence that damage and structural disorder are occurring is clearly given by the fading and eventual disappearance of the specimen's electron diffraction pattern. The fading and disappearance of sharp diffraction spots implies a corresponding disappearance of periodic structural features in the specimen. By the same token, there is a oneto- one correspondence between the disappearance of the crystalline diffraction pattern and the disappearance of reproducible structural information that can be observed in the images of identical unit cells of the object structure. The electron exposures that result in a significant decrease in the diffraction intensity will depend somewhat upon the resolution (Bragg spacing) involved, and can vary considerably with the chemical makeup and composition of the specimen material.

Direct visualization of phase-separated domains in lipid membranes

1978 ◽  
Vol 36 (2) ◽  
pp. 290-291
Author(s):  
S. W. Hui ◽  
T. P. Stewart
Keyword(s):  
Lipid Membranes ◽  
Structural Information ◽  
Freeze Fracture ◽  
Biological Molecules ◽  
Vacuum Drying ◽  
Direct Visualization ◽  
X Ray Diffraction ◽  
Electron Microscopic ◽  
X Ray ◽  
Hydrocarbon Chains

Direct electron microscopic study of biological molecules has been hampered by such factors as radiation damage, lack of contrast and vacuum drying. In certain cases, however, the difficulties may be overcome by using redundent structural information from repeating units and by various specimen preservation methods. With bilayers of phospholipids in which both the solid and fluid phases co-exist, the ordering of the hydrocarbon chains may be utilized to form diffraction contrast images. Domains of different molecular packings may be recgnizable by placing properly chosen filters in the diffraction plane. These domains would correspond to those observed by freeze fracture, if certain distinctive undulating patterns are associated with certain molecular packing, as suggested by X-ray diffraction studies. By using an environmental stage, we were able to directly observe these domains in bilayers of mixed phospholipids at various temperatures at which their phases change from misible to inmissible states.

High-Resolution Scanning Electron Microscopy of Biological Specimens

1988 ◽  
Vol 46 ◽  
pp. 186-187
Author(s):  
M. Müller ◽  
R. Hermann
Keyword(s):  
High Resolution ◽  
Freeze Drying ◽  
Room Temperature ◽  
Structural Information ◽  
Freeze Substitution ◽  
Critical Point Drying ◽  
Sem Study ◽  
Major Factors ◽  
Structural Preservation ◽  
Preparation Techniques

Three major factors must be concomitantly assessed in order to extract relevant structural information from the surface of biological material at high resolution (2-3nm).Procedures based on chemical fixation and dehydration in graded solvent series seem inappropriate when aiming for TEM-like resolution. Cells inevitably shrink up to 30-70% of their initial volume during gehydration; important surface components e.g. glycoproteins may be lost. These problems may be circumvented by preparation techniques based on cryofixation. Freezedrying and freeze-substitution followed by critical point drying yields improved structural preservation in TEM. An appropriate preservation of dimensional integrity may be achieved by freeze-drying at - 85° C. The sample shrinks and may partially collapse as it is warmed to room temperature for subsequent SEM study. Observations at low temperatures are therefore a necessary prerequisite for high fidelity SEM. Compromises however have been unavoidable up until now. Aldehyde prefixation is frequently needed prior to freeze drying, rendering the sample resistant to treatment with distilled water.

Sign in / Sign up

Export Citation Format

Share Document