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 <i>b</i> 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 <i>b</i> 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 <i>b</i> matrix based on the new analytic expression. In addition, comparisons between the generalized <i>b</i> matrix computed using our formula and the second order <i>b</i> 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.
Proc. SPIE. 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging
KEYWORDS: Signal to noise ratio, Optical spheres, Magnetic resonance imaging, Diffusion, Monte Carlo methods, Spatial resolution, Spherical lenses, Information visualization, Diffusion tensor imaging, Brain
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.