Cai Teddy X, Williamson Nathan H, Ravin Rea, Basser Peter J
Section on Quantitative Imaging and Tissue Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, 20892, MD, USA.
Celoptics, Inc., Rockville, 20850, MD, USA.
bioRxiv. 2024 Aug 6:2024.08.05.606620. doi: 10.1101/2024.08.05.606620.
Water exchange is increasingly recognized as an important biological process that can affect the study of biological tissue using diffusion MR. Methods to measure exchange, however, remain immature as opposed to those used to characterize restriction, with no consensus on the optimal pulse sequence(s) or signal model(s). In general, the trend has been towards data-intensive fitting of highly parameterized models. We take the opposite approach and show that a judicious sub-sample of diffusion exchange spectroscopy (DEXSY) data can be used to robustly quantify exchange, as well as restriction, in a data-efficient manner. This sampling produces a ratio of two points per mixing time: (i) one point with equal diffusion weighting in both encoding periods, which gives maximal exchange contrast, and (ii) one point with the same diffusion weighting in just the first encoding period, for normalization. We call this quotient the Diffusion EXchange Ratio (DEXR). Furthermore, we show that it can be used to probe time-dependent diffusion by estimating the velocity autocorrelation function (VACF) over intermediate to long times (~ 2-500 ms). We provide a comprehensive theoretical framework for the design of DEXR experiments in the case of static or constant gradients. Data from Monte Carlo simulations and experiments acquired in fixed and viable neonatal mouse spinal cord using a permanent magnet system are presented to test and validate this approach. In viable spinal cord, we report the following apparent parameters from just 6 data points: , , , and , which correspond to the exchange time, restricted or non-Gaussian signal fraction, an effective spherical radius, and permeability, respectively. For the VACF, we report a long-time, power-law scaling with , which is approximately consistent with disordered domains in 3-D. Overall, the DEXR method is shown to be highly efficient, capable of providing valuable quantitative diffusion metrics using minimal MR data.
水交换日益被认为是一种重要的生物学过程，它会影响使用扩散磁共振成像（MR）对生物组织的研究。然而，与用于表征受限情况的方法相比，测量交换的方法仍不成熟，对于最佳脉冲序列或信号模型尚无共识。总体而言，趋势一直是朝着对高度参数化模型进行数据密集型拟合。我们采用相反的方法，表明扩散交换光谱学（DEXSY）数据的明智子样本可用于以数据高效的方式稳健地量化交换以及受限情况。这种采样在每个混合时间产生两个点的比率：（i）一个点在两个编码期具有相等的扩散加权，可提供最大的交换对比度；（ii）一个点仅在第一个编码期具有相同的扩散加权，用于归一化。我们将这个商称为扩散交换比（DEXR）。此外，我们表明它可用于通过估计中长时间（约2 - 500毫秒）的速度自相关函数（VACF）来探测时间依赖性扩散。我们为静态或恒定梯度情况下的DEXR实验设计提供了一个全面的理论框架。展示了来自蒙特卡罗模拟的数据以及使用永磁系统在固定和存活的新生小鼠脊髓中获取的实验数据，以测试和验证这种方法。在存活的脊髓中，我们仅从6个数据点报告了以下表观参数： 、 、 和 ，它们分别对应于交换时间、受限或非高斯信号分数、有效球形半径和渗透率。对于VACF，我们报告了长时间的幂律缩放 ，这与三维中的无序域大致一致。总体而言，DEXR方法被证明是高效的，能够使用最少的MR数据提供有价值的定量扩散指标。
