New modeling and experimental framework to characterize hindered and restricted water diffusion in brain white matter

被引:393
作者
Assaf, Y [1 ]
Freidlin, RZ
Rohde, GK
Basser, PJ
机构
[1] Tel Aviv Sourasky Med Ctr, Dept Radiol, Wohl Inst Adv Imaging, Funct Brain Imaging Unit, IL-64239 Tel Aviv, Israel
[2] Tel Aviv Univ, Sch Chem, IL-69978 Tel Aviv, Israel
[3] NIH, Telemed & Appl Imaging Sect, Computat Biosci & Engn Lab, Ctr Informat Technol, Bethesda, MD 20892 USA
[4] NICHHD, Sect Tissue Biophys & Biomimet, Lab Integrat & Med Biophys, NIH, Bethesda, MD 20892 USA
关键词
MRI; white matter; DTI; q-space;
D O I
10.1002/mrm.20274
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
To characterize anisotropic water diffusion in brain white matter, a theoretical framework is proposed that combines hindered and restricted models of water diffusion (CHARMED) and an experimental methodology that embodies features of diffusion tensor and q-space MRI. This model contains a hindered extra-axonal compartment, whose diffusion properties are characterized by an effective diffusion tensor, an an intra-axonal compartment, whose diffusion properties are characterized by a restricted model of diffusion within cylinders. The hindered model primarily explains the Gaussian signal attenuation observed at low b values; the restricted non-Gaussian model does so at high b. Both high and low b data obtained along different directions are required to estimate various microstructural parameters of the composite model, such as the nerve fiber orientation(s), the T-2-weighted extra- and intra-axonal volume fractions, and principal diffusivities. The proposed model provides a description of restricted diffusion in 3D given by a 3D probability distribution (average propagator), which is obtained by 3D Fourier transformation of the estimated signal attenuation profile. The new model is tested using synthetic phantoms and validated on excised spinal cord tissue. This framework shows promise in determining the orientations of two or more fiber compartments more precisely and accurately than with diffusion tensor imaging. Published 2004 Wiley-Liss, Inc(dagger).
引用
收藏
页码:965 / 978
页数:14
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