Afzali Maryam, Pieciak Tomasz, Jones Derek K, Schneider Jürgen E, Özarslan Evren
Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom.
Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.
Front Neuroimaging. 2022 Aug 17;1:958680. doi: 10.3389/fnimg.2022.958680. eCollection 2022.
Diffusion MR is sensitive to the microstructural features of a sample. Fine-scale characteristics can be probed by employing strong diffusion gradients while the low -value regime is determined by the cumulants of the distribution of particle displacements. A signal representation based on the cumulants, however, suffers from a finite convergence radius and cannot represent the 'localization regime' characterized by a stretched exponential decay that emerges at large gradient strengths. Here, we propose a new representation for the diffusion MR signal. Our method provides not only a robust estimate of the first three cumulants but also a meaningful extrapolation of the entire signal decay.
扩散磁共振对样本的微观结构特征敏感。通过采用强扩散梯度可以探测精细尺度特征，而低值区域由粒子位移分布的累积量决定。然而，基于累积量的信号表示存在有限的收敛半径，无法表示在大梯度强度下出现的以拉伸指数衰减为特征的“定位区域”。在此，我们提出一种新的扩散磁共振信号表示方法。我们的方法不仅能对前三个累积量进行稳健估计，还能对整个信号衰减进行有意义的外推。
