A simple estimate of axon size with diffusion MRI.

A simple estimate of axon size with diffusion MRI.
复制标题

DOI:
10.1016/j.neuroimage.2020.117619
复制
发表时间:
2021-02-15
期刊:
影响因子:
5.7
通讯作者:
Does MD
Does MD
中科院分区:
医学1区
文献类型:
--
作者:
Harkins KD;Beaulieu C;Xu J;Gore JC;Does MD

文献摘要

参考文献

被引文献

相似文献

无创性估计平均轴突直径为探索白质可塑性、发育和病理学提供了新的机会。已经提出了几种扩散加权磁共振成像(DW-MRI)方法来测量白质中的平均轴突直径,但它们通常需要许多扩散编码测量和复杂的数学模型来将信号适配到多个组织间隔,包括轴突内和轴突外间隙。在这里,蒙特卡罗模拟揭示了轴突直径的一个简单的DW-MRI指标:在不同的有效扩散时间ΔD⊥估计的径向表观扩散系数的变化。模拟结果表明,该指标在有效轴突平均直径的相关范围内单调增加,而对轴突外体积分数、轴突直径分布、g比和髓鞘水的影响不敏感。此外,还发现来自轴突内和轴突外的信号之间存在单调关系。随着振荡和脉冲梯度扩散序列扩散时间的不同,ΔD⊥的斜率随有效轴突直径的增加而增大。
Noninvasive estimation of mean axon diameter presents a new opportunity to explore white matter plasticity, development, and pathology. Several diffusion-weighted MRI (DW-MRI) methods have been proposed to measure the average axon diameter in white matter, but they typically require many diffusion encoding measurements and complicated mathematical models to fit the signal to multiple tissue compartments, including intra- and extra-axonal spaces. Here, Monte Carlo simulations uncovered a straightforward DW-MRI metric of axon diameter: the change in radial apparent diffusion coefficient estimated at different effective diffusion times, ΔD⊥. Simulations indicated that this metric increases monotonically within a relevant range of effective mean axon diameter while being insensitive to changes in extra-axonal volume fraction, axon diameter distribution, g-ratio, and influence of myelin water. Also, a monotonic relationship was found to exist for signals coming from both intra- and extra-axonal compartments. The slope in ΔD⊥ with effective axon diameter increased with the difference in diffusion time of both oscillating and pulsed gradient diffusion sequences.
用扩散MRI量化脑微观结构:理论和参数估计。
DOI: 10.1002/nbm.3998
发表时间: 2019-04
期刊: NMR in biomedicine
影响因子: 2.9
作者:
Novikov DS;Fieremans E;Jespersen SN;Kiselev VG
通讯作者: Kiselev VG
DOI: 10.1002/mrm.27463
发表时间: 2019-03
影响因子: 3.3
作者:
Grussu F;Ianuş A;Tur C;Prados F;Schneider T;Kaden E;Ourselin S;Drobnjak I;Zhang H;Alexander DC;Gandini Wheeler-Kingshott CAM
通讯作者: Gandini Wheeler-Kingshott CAM
DOI: 10.1088/0031-9155/61/13/4729
发表时间: 2016-07-07
影响因子: 3.5
作者:
Harkins KD;Does MD
通讯作者: Does MD
DOI: 10.1016/j.neuroimage.2017.12.038
发表时间: 2018-11-15
期刊: NeuroImage
影响因子: 5.7
作者:
Lee HH;Fieremans E;Novikov DS
通讯作者: Novikov DS
DOI: 10.1007/s00429-019-01844-6
发表时间: 2019-05-01
影响因子: 3.1
作者:
Lee, Hong-Hsi;Yaros, Katarina;Fieremans, Els
通讯作者: Fieremans, Els