Diffusion weighted imaging (DWI) technique has been used to help understand the human brain white matter fiber
structures in vivo. Currently used standard diffusion tensor magnetic resonance imaging (DTI) tractography based on the
second order diffusion tensor model has limitations in its ability to resolve complex fiber tracts. The generalized diffusion
tensor (GDT) imaging technique has been proposed to overcome these limitations associated with the standard second
order tensor model. Based on the GDT model, a generalized partial differential equation (PDE) governing the anisotropic
diffusion process can be derived. For the purpose of solving the PDE and computing the generalized diffusion tensor, we
derive a generalized analytic expression for the high order b matrix in the case of twice-refocused spin echo (TRSE) pulse
sequence which is used in the DWI data acquisition. The TRSE pulse sequence is considered because of its ability to null
the eddy current effect generated during the scanning. The b matrix was computed by integrating the transverse precessing
magnetization between the excitation time and the echo time (TE). In our experiments, we show some computational results
of the generalized b matrix based on the new analytic expression. In addition, comparisons between the generalized b matrix computed using our formula and the second order b matrix given by the MRI machine are presented. The characteristics
of the fomula and the data are discussed at last.
A new fiber tract-oriented quantitative and visual analysis scheme using diffusion tensor imaging (DTI) is developed to study the regional micro structural white matter changes along major fiber bundles which may not be effectively revealed by existing methods due to the curved spatial nature of neuronal paths. Our technique is based on DTI tractography and geodesic path mapping, which establishes correspondences to allow cross-subject evaluation of diffusion properties by parameterizing the fiber pathways as a function of geodesic distance. A novel isonodes visualization scheme is proposed to render regional statistical features along the fiber pathways. Assessment of the technique reveals specific anatomical locations along the genu of the corpus callosum paths with significant diffusion property changes in the amnestic mild cognitive impairment subjects. The experimental results show that this approach is promising and may provide a sensitive technique to study the integrity of neuronal connectivity in human brain.
KEYWORDS: Signal to noise ratio, Spherical lenses, Diffusion, Magnetic resonance imaging, Monte Carlo methods, Optical spheres, Brain, Diffusion tensor imaging, Spatial resolution, Information visualization
Magnetic Resonance Imaging (MRI) techniques have achieved much importance in providing visual and quantitative
information of human body. Diffusion MRI is the only non-invasive tool to obtain information of the
neural fiber networks of the human brain. The traditional Diffusion Tensor Imaging (DTI) is only capable of
characterizing Gaussian diffusion. High Angular Resolution Diffusion Imaging (HARDI) extends its ability to
model more complex diffusion processes. Spherical harmonic series truncated to a certain degree is used in recent
studies to describe the measured non-Gaussian Apparent Diffusion Coefficient (ADC) profile. In this study, we
use the sampling theorem on band-limited spherical harmonics to choose a suitable degree to truncate the spherical
harmonic series in the sense of Signal-to-Noise Ratio (SNR), and use Monte Carlo integration to compute
the spherical harmonic transform of human brain data obtained from icosahedral schema.
Diffusion tensor imaging (DTI) represents a promising tool for the early diagnosis of certain brain diseases. Many
DTI studies have compared differences in local diffusivity in specific region-of- interest (ROI) between patient
and control groups to find possible disease markers. However, local diffusivity results may be influenced by
partial volume effects (PVE), particularly in small white matter tracts that border grey matter tissue. Here, we
investigated the influence of PVE on local diffusivity measurements in a small but critical white matter tract,
the cingulum. Results demonstrated significant variability in PVE that contribute to local diffusivity in the
cingulum. Our results highlight the need for careful consideration of PVE when computing diffusivity of small
tissues.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.