Tristán-Vega Antonio, París Guillem, de Luis-García Rodrigo, Aja-Fernández Santiago
Laboratorio de Procesado de Imagen (LPI), Universidad de Valladolid, Valladolid, Spain.
Magn Reson Med. 2022 Feb;87(2):1028-1035. doi: 10.1002/mrm.28997. Epub 2021 Aug 31.
To accurately estimate the partial volume fraction of free water in the white matter from diffusion MRI acquisitions not demanding strong sensitizing gradients and/or large collections of different b-values. Data sets considered comprise 32-64 gradients near plus 6 gradients near .
The spherical means of each diffusion MRI set with the same b-value are computed. These means are related to the inherent diffusion parameters within the voxel (free- and cellular-water fractions; cellular-water diffusivity), which are solved by constrained nonlinear least squares regression.
The proposed method outperforms those based on mixtures of two Gaussians for the kind of data sets considered. W.r.t. the accuracy, the former does not introduce significant biases in the scenarios of interest, while the latter can reach a bias of 5%-7% if fiber crossings are present. W.r.t. the precision, a variance near , compared to 15%, can be attained for usual configurations.
It is possible to compute reliable estimates of the free-water fraction inside the white matter by complementing typical DTI acquisitions with few gradients at a lowb-value. It can be done voxel-by-voxel, without imposing spatial regularity constraints.
在不要求强敏感梯度和/或大量不同b值采集数据的情况下，通过扩散磁共振成像（MRI）准确估计白质中自由水的部分体积分数。所考虑的数据集包括32 - 64个接近[具体值1]的梯度加上6个接近[具体值2]的梯度。
计算具有相同b值的每个扩散MRI数据集的球均值。这些均值与体素内的固有扩散参数（自由水和细胞水分数；细胞水扩散率）相关，通过约束非线性最小二乘回归求解。
对于所考虑的数据集类型，所提出的方法优于基于两个高斯混合的方法。在准确性方面，前者在感兴趣的场景中不会引入显著偏差，而如果存在纤维交叉，后者可能会达到5% - 7%的偏差。在精度方面，对于通常的配置，与15%相比，可以达到接近[具体方差值]的方差。
通过在低b值下用少量梯度补充典型的扩散张量成像（DTI）采集数据，可以逐体素地计算白质内自由水分数的可靠估计值，而无需施加空间正则性约束。
