论文标题
轴向和径向轴突扩散性来自单个编码强扩散加权MRI
Axial and radial axonal diffusivities from single encoding strongly diffusion-weighted MRI
论文作者
论文摘要
我们可以从单轴轴向扩散率估计单个编码,强烈扩散加权,脉冲梯度自旋回波数据。此外,与基于球形平均的估计相比,我们改善了每轴径向扩散率的估计。在磁共振成像(MRI)中使用强扩散权重可以将白质信号近似为轴突的贡献之和。同时,球形的平均值通过消除明确说明轴突的未知方向分布的需要,从而导致建模的重大简化。但是,在强扩散权重以轴向扩散率不敏感的情况下,获得的球体平均信号对轴向扩散率不敏感,因此无法估算。在修改了现有理论之后,我们引入了一种新的通用方法,用于基于区域谐波建模的强扩散权重估计两种轴突扩散。我们还展示了这可能导致估计不存在灰质物质的估计。我们测试了MGH成人扩散人类连接项目数据集的公开数据的方法。我们报告基于34名受试者的轴突扩散率的参考值,并得出轴突半径的估计值。我们还从所需的数据预处理的角度,与建模假设,当前局限性和未来可能性有关的偏见的存在来解决估计问题。
We enable the estimation of the per-axon axial diffusivity from single encoding, strongly diffusion-weighted, pulsed gradient spin echo data. Additionally, we improve the estimation of the per-axon radial diffusivity compared to estimates based on spherical averaging. The use of strong diffusion weightings in magnetic resonance imaging (MRI) allows to approximate the signal in white matter as the sum of the contributions from axons. At the same time, spherical averaging leads to a major simplification of the modeling by removing the need to explicitly account for the unknown orientation distribution of axons. However, the spherically averaged signal acquired at strong diffusion weightings is not sensitive to the axial diffusivity, which cannot therefore be estimated. After revising existing theory, we introduce a new general method for the estimation of both axonal diffusivities at strong diffusion weightings based on zonal harmonics modeling. We additionally show how this could lead to estimates that are free from partial volume bias with, for instance, gray matter. We test the method on publicly available data from the MGH Adult Diffusion Human Connectome project dataset. We report reference values of axonal diffusivities based on 34 subjects, and derive estimates of axonal radii. We address the estimation problem also from the angle of the required data preprocessing, the presence of biases related to modeling assumptions, current limitations, and future possibilities.