DTI Data (dti + data)

Distribution by Scientific Domains


Selected Abstracts


Illustrative White Matter Fiber Bundles

COMPUTER GRAPHICS FORUM, Issue 3 2010
Ron Otten
Abstract Diffusion Tensor Imaging (DTI) has made feasible the visualization of the fibrous structure of the brain white matter. In the last decades, several fiber-tracking methods have been developed to reconstruct the fiber tracts from DTI data. Usually these fiber tracts are shown individually based on some selection criteria like region of interest. However, if the white matter as a whole is being visualized clutter is generated by directly rendering the individual fiber tracts. Often users are actually interested in fiber bundles, anatomically meaningful entities that abstract from the fibers they contain. Several clustering techniques have been developed that try to group the fiber tracts in fiber bundles. However, even if clustering succeeds, the complex nature of white matter still makes it difficult to investigate. In this paper, we propose the use of illustration techniques to ease the exploration of white matter clusters. We create a technique to visualize an individual cluster as a whole. The amount of fibers visualized for the cluster is reduced to just a few hint lines, and silhouette and contours are used to improve the definition of the cluster borders. Multiple clusters can be easily visualized by a combination of the single cluster visualizations. Focus+context concepts are used to extend the multiple-cluster renderings. Exploded views ease the exploration of the focus cluster while keeping the context clusters in an abstract form. Real-time results are achieved by the GPU implementation of the presented techniques. [source]


Addressing a systematic vibration artifact in diffusion-weighted MRI

HUMAN BRAIN MAPPING, Issue 2 2010
Daniel Gallichan
Abstract We have identified and studied a pronounced artifact in diffusion-weighted MRI on a clinical system. The artifact results from vibrations of the patient table due to low-frequency mechanical resonances of the system which are stimulated by the low-frequency gradient switching associated with the diffusion-weighting. The artifact manifests as localized signal-loss in images acquired with partial Fourier coverage when there is a strong component of the diffusion-gradient vector in the left,right direction. This signal loss is caused by local phase ramps in the image domain which shift the apparent k-space center for a particular voxel outside the covered region. The local signal loss masquerades as signal attenuation due to diffusion, severely disrupting the quantitative measures associated with diffusion-tensor imaging (DTI). We suggest a way to improve the interpretation of affected DTI data by including a co-regressor which accounts for the empirical response of regions affected by the artifact. We also demonstrate that the artifact may be avoided by acquiring full k-space data, and that subsequent increases in TE can be avoided by employing parallel acceleration. Hum Brain Mapp, 2010. © 2009 Wiley-Liss, Inc. [source]


Smoothing that does not blur: Effects of the anisotropic approach for evaluating diffusion tensor imaging data in the clinic

JOURNAL OF MAGNETIC RESONANCE IMAGING, Issue 3 2010
Marta Moraschi MS
Abstract Purpose: To compare the effects of anisotropic and Gaussian smoothing on the outcomes of diffusion tensor imaging (DTI) voxel-based (VB) analyses in the clinic, in terms of signal-to-noise ratio (SNR) enhancement and directional information and boundary structures preservation. Materials and Methods: DTI data of 30 Alzheimer's disease (AD) patients and 30 matched control subjects were obtained at 3T. Fractional anisotropy (FA) maps with variable degrees and quality (Gaussian and anisotropic) of smoothing were created and compared with an unsmoothed dataset. The two smoothing approaches were evaluated in terms of SNR improvements, capability to separate differential effects between patients and controls by a standard VB analysis, and level of artifacts introduced by the preprocessing. Results: Gaussian smoothing regionally biased the FA values and introduced a high variability of results in clinical analysis, greatly dependent on the kernel size. On the contrary, anisotropic smoothing proved itself capable of enhancing the SNR of images and maintaining boundary structures, with only moderate dependence of results on smoothing parameters. Conclusion: Our study suggests that anisotropic smoothing is more suitable in DTI studies; however, regardless of technique, a moderate level of smoothing seems to be preferable considering the artifacts introduced by this manipulation. J. Magn. Reson. Imaging 2010;31:690,697. © 2010 Wiley-Liss, Inc. [source]


Conventional DTI vs. slow and fast diffusion tensors in cat visual cortex

MAGNETIC RESONANCE IN MEDICINE, Issue 5 2003
Itamar Ronen
Abstract Diffusion tensor imaging (DTI) uses water diffusion anisotropy in axonal fibers to provide a tool for analyzing and tracking those fibers in brain white matter. In the present work, multidirectional diffusion MRI data were collected from a cat brain and decomposed into slow and fast diffusion tensors and directly compared with conventional DTI data from the same imaging slice. The fractional anisotropy of the slow diffusing component (Dslow) was significantly higher than the anisotropy measured by conventional DTI while reflecting a similar directionality and appeared to account for most of the anisotropy observed in gray matter, where the fiber density is notoriously low. Preliminary results of fiber tracking based on the slow diffusion component are shown. Fibers generated based on the slow diffusion component appear to follow the vertical fibers in gray matter. DslowTI may provide a way for increasing the sensitivity to anisotropic structures in cortical gray matter. Magn Reson Med 49:785,790, 2003. © 2003 Wiley-Liss, Inc. [source]


White matter changes in extremely preterm infants, a population-based diffusion tensor imaging study

ACTA PAEDIATRICA, Issue 6 2010
Béatrice Skiöld
Abstract Aim:, To investigate cerebral white matter (WM) abnormalities (J Pediatr 2003; 143: 171) and diffuse and excessive high signal intensities (DEHSI), (J Pediatr 1999; 135: 351) in a cohort of extremely preterm infants born in Stockholm during a 3-year period, using magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). Methods:, MRI at term-equivalent age was performed in 109 infants and DTI data were acquired in 54 infants. Survival rate in the entire cohort was 67%. Sixteen term-born healthy control infants were scanned for comparison. Results:, No or mild WM abnormalities were seen in 86% of infants and 14% had moderate or severe WM abnormalities. DEHSI were seen in infants with all grades of white matter abnormalities and were present in 56% of infants. In the WM at the level of centrum semiovale, infants with any WM abnormalities or DEHSI had lower Fractional Anisotropy and higher Apparent Diffusion Coefficient compared with control infants. No significant differences in diffusion were seen in infants without DEHSI compared with the controls in this region. Compared with controls, the preterm infants had significantly altered diffusion in the corpus callosum. Conclusion:, Only 14% of the extremely preterm infants had moderate or severe WM abnormalities on MRI. However, the incidence of DEHSI was high. In the DEHSI regions, changes in diffusion parameters were detected, indicating altered WM organization. [source]