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一般区室大小分布的核磁共振表征。

NMR characterization of general compartment size distributions.

作者信息

Ozarslan Evren, Shemesh Noam, Koay Cheng Guan, Cohen Yoram, Basser Peter J

机构信息

Section on Tissue Biophysics and Biomimetics, NICHD, National Institutes of Health, 13 South Drive, Bethesda, Maryland, 20892, USA.

出版信息

New J Phys. 2011 Jan;13:15010. doi: 10.1088/1367-2630/13/1/015010.

DOI:10.1088/1367-2630/13/1/015010
PMID:21709780
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3120057/
Abstract

The influence of molecular diffusion on the nuclear magnetic resonance (NMR) signal can be exploited to estimate compartment size distributions in heterogeneous specimens. Theoretical relationships between the NMR signal intensity at long diffusion times and the moments of a general distribution of isolated pores with characteristic shapes (planar, cylindrical or spherical) are established. A numerical method based on expressing a general diffusion-attenuated NMR signal profile in a series of complete orthogonal basis functions is introduced and subsequently employed to estimate the moments of the compartment size distribution. The results on simulated and real data obtained from controlled water-filled microcapillaries demonstrate the power of the approach to create contrast based not only on the mean of the compartment size but also its variance. The technique can be employed to address a variety of problems such as characterizing distributions of droplet sizes in emulsions and of apparent axon diameters in nerve fascicles.

摘要

分子扩散对核磁共振(NMR)信号的影响可用于估计异质样本中的隔室大小分布。建立了长扩散时间下NMR信号强度与具有特征形状(平面、圆柱或球形)的孤立孔隙的一般分布矩之间的理论关系。介绍了一种基于用一系列完全正交基函数表示一般扩散衰减NMR信号轮廓的数值方法,并随后用于估计隔室大小分布的矩。从受控充水微毛细管获得的模拟数据和实际数据结果表明,该方法不仅能够基于隔室大小的均值,还能基于其方差来产生对比度。该技术可用于解决各种问题,如表征乳液中液滴大小的分布以及神经束中表观轴突直径的分布。

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Efficient and robust computation of PDF features from diffusion MR signal.从扩散磁共振信号高效且稳健地计算概率密度函数特征。
Med Image Anal. 2009 Oct;13(5):715-29. doi: 10.1016/j.media.2009.06.004. Epub 2009 Jul 12.
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Neuroimage. 2021 Aug 15;237:118183. doi: 10.1016/j.neuroimage.2021.118183. Epub 2021 May 19.
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