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Human White Matter (human + white_matter)

Distribution by Scientific Domains

Medical Sciences	80%

Selected Abstracts

MRI atlas of human white matter

CONCEPTS IN MAGNETIC RESONANCE, Issue 2 2006
Philip R. Szeszko
No abstract is available for this article. [source]

MRI atlas of human white matter

CONCEPTS IN MAGNETIC RESONANCE, Issue 2 2006
Chan Ling Ling M.D.
No abstract is available for this article. [source]

Generalized Diffusion Tensor Imaging (GDTI): A Method for Characterizing and Imaging Diffusion Anisotropy Caused by Non-Gaussian Diffusion

ISRAEL JOURNAL OF CHEMISTRY, Issue 1-2 2003
Chunlei Liu
For non-Gaussian distributed random displacement, which is common in restricted diffusion, a second-order diffusion tensor is incapable of fully characterizing the diffusion process. The insufficiency of a second-order tensor is evident in the limited capability of diffusion tensor imaging (DTI) in resolving multiple fiber orientations within one voxel of human white matter. A generalized diffusion tensor imaging (GDTI) method was recently proposed to solve this problem by generalizing Fick's law to a higher-order partial differential equation (PDE). The relationship between the higher-order tensor coefficients of the PDE and the higher-order cumulants of the random displacement can be derived. The statistical property of the diffusion process was fully characterized via the higher-order tensor coefficients by reconstructing the probability density function (PDF) of the molecular random displacement. Those higher-order tensor coefficients can be measured using conventional diffusion-weighted imaging or spectroscopy techniques. Simulations demonstrated that this method was capable of quantitatively characterizing non-Gaussian diffusion and accurately resolving multiple fiber orientations. It can be shown that this method is consistent with the q-space approach. The second-order approximation of GDTI was shown to be DTI. [source]

Ground truth hardware phantoms for validation of diffusion-weighted MRI applications

JOURNAL OF MAGNETIC RESONANCE IMAGING, Issue 2 2010
Pim Pullens MSc
Abstract Purpose: To quantitatively validate diffusion-weighted MRI (DW-MRI) applications, a hardware phantom containing crossing fibers at a sub-voxel level is presented. It is suitable for validation of a large spectrum of DW-MRI applications from acquisition to fiber tracking, which is an important recurrent issue in the field. Materials and Methods: Phantom properties were optimized to resemble properties of human white matter in terms of anisotropy, fractional anisotropy, and T2. Sub-voxel crossings were constructed at angles of 30, 50, and 65 degrees, by wrapping polyester fibers, with a diameter close to axon diameter, into heat shrink tubes. We show our phantoms are suitable for the acquisition of DW-MRI data using a clinical protocol. Results: The phantoms can be used to succesfully estimate both the diffusion tensor and non-Gaussian diffusion models, and perform streamline fiber tracking. DOT (Diffusion Orientation Transform) and q-ball reconstruction of the diffusion profiles acquired at b = 3000 s/mm2 and 132 diffusion directions reveal multimodal diffusion profiles in voxels containing crossing yarn strands. Conclusion: The highly purpose adaptable phantoms provide a DW-MRI validation platform: applications include optimisation of acquisition schemes, validation of non-Gaussian diffusion models, comparison and validation of fiber tracking algorithms, and quality control in multi-center DWI studies. J. Magn. Reson. Imaging 2010;32:482,488. © 2010 Wiley-Liss, Inc. [source]

Optimal acquisition schemes for in vivo quantitative magnetization transfer MRI

MAGNETIC RESONANCE IN MEDICINE, Issue 4 2006
Mara Cercignani
Abstract This paper uses the theory of Cramer-Rao lower bounds (CRLB) to obtain optimal acquisition schemes for in vivo quantitative magnetization transfer (MT) imaging, although the method is generally applicable to any multiparametric MRI technique. Quantitative MT fits a two-pool model to data collected at different sampling points or settings of amplitude and offset frequency in the MT saturation pulses. Here we use simple objective functions based on the CRLB to optimize sampling strategies for multiple parameters simultaneously, and use simulated annealing to minimize these objective functions with respect to the sampling configuration. Experiments compare optimal schemes derived for quantitative MT in the human white matter (WM) at 1.5T with previously published schemes using both synthetic and human-brain data. Results show large reductions in error of the fitted parameters with the new schemes, which greatly increases the clinical potential of in vivo quantitative MT. Since the sampling-scheme optimization requires specific settings of the MT parameters, we also show that the optimum schemes are robust to these settings within the range of MT parameters observed in the brain. Magn Reson Med, 2006. © 2006 Wiley-Liss, Inc. [source]