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使用分数阶微积分研究人脑中的异常扩散。

Studies of anomalous diffusion in the human brain using fractional order calculus.

机构信息

Department of Radiology, University of Illinois Medical Center, Chicago, Illinois 60612, USA.

出版信息

Magn Reson Med. 2010 Mar;63(3):562-9. doi: 10.1002/mrm.22285.

DOI:10.1002/mrm.22285
PMID:20187164
Abstract

It is well known that diffusion-induced MR signal loss deviates from monoexponential decay, particularly at high b-values (e.g., >1500 sec/mm(2) for human brain tissues). A number of models have been developed to describe this anomalous diffusion behavior and relate the diffusion measurements to tissue structures. Recently, a new diffusion model was proposed by solving the Bloch-Torrey equation using fractional order calculus with respect to time and space (Magin et al., J Magn Reson 2008;190:255-270; Zhou et al., Proc Int'l Soc Magn Reson Med 2008). Using a spatial Laplacian [symbol: see text], this model yields a new set of parameters to describe anomalous diffusion: diffusion coefficient D, fractional order derivative in space beta, and a spatial parameter mu (in units of microm). In this study, we demonstrate that the fractional calculus model can be successfully applied to analyzing diffusion images of healthy human brain tissues in vivo. Five human volunteers were scanned on a commercial 3-T scanner using a customized single-shot echo-planar imaging diffusion sequence with 15 b values ranging from 0 to 4700 sec/mm(2). The set of images was analyzed using the fractional calculus model, producing spatially resolved maps of D, beta, and mu. The beta and mu maps showed notable contrast between white and gray matter. The contrast has been attributed to the varying degree of complexity of the underlying tissue structures and microenvironment. Although the biophysical basis of beta and mu remains elusive, the potential utility of these parameters to characterize the environment for molecular diffusion, as a complement to apparent diffusion coefficient, may lead to a new way to investigate tissue structural changes in disease progression, intervention, and regression.

摘要

众所周知,扩散诱导的 MR 信号损失偏离单指数衰减,尤其是在高 b 值(例如,人类脑组织 >1500 sec/mm(2))下。已经开发了许多模型来描述这种异常扩散行为,并将扩散测量值与组织结构相关联。最近,通过使用分数阶微积分相对于时间和空间求解 Bloch-Torrey 方程,提出了一种新的扩散模型(Magin 等人,J Magn Reson 2008;190:255-270;Zhou 等人,Proc Int'l Soc Magn Reson Med 2008)。使用空间拉普拉斯算子[符号:见文本],该模型产生了一组新的参数来描述异常扩散:扩散系数 D、空间分数阶导数 beta 和空间参数 mu(单位为微米)。在这项研究中,我们证明分数阶微积分模型可以成功应用于分析健康人类脑组织的体内扩散图像。五名志愿者在商业 3-T 扫描仪上进行扫描,使用具有 15 个 b 值(范围从 0 到 4700 sec/mm(2))的定制单次回波平面成像扩散序列进行扫描。使用分数阶微积分模型对图像集进行分析,生成 D、beta 和 mu 的空间分辨图。beta 和 mu 图显示了白质和灰质之间的显著对比度。这种对比归因于基础组织结构和微环境的复杂程度不同。尽管 beta 和 mu 的生物物理基础仍不清楚,但这些参数在描述分子扩散环境方面的潜在用途,作为表观扩散系数的补充,可能会开辟一种新的方法来研究疾病进展、干预和恢复过程中的组织结构变化。

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