Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
Magn Reson Med. 2011 Mar;65(3):725-31. doi: 10.1002/mrm.22649. Epub 2010 Nov 30.
MRI can measure several important hemodynamic parameters but might not yet have reached its full potential. The most common MRI method for the assessment of flow is phase-contrast MRI velocity mapping that estimates the mean velocity of a voxel. This estimation is precise only when the intravoxel velocity distribution is symmetric. The mean velocity corresponds to the first raw moment of the intravoxel velocity distribution. Here, a generalized MRI framework for the quantification of any moment of arbitrary velocity distributions is described. This framework is based on the fact that moments in the function domain (velocity space) correspond to differentials in the Fourier transform domain (kv-space). For proof-of-concept, moments of realistic velocity distributions were estimated using finite difference approximations of the derivatives of the MRI signal. In addition, the framework was applied to investigate the symmetry assumption underlying phase-contrast MRI velocity mapping; we found that this assumption can substantially affect phase-contrast MRI velocity estimates and that its significance can be reduced by increasing the velocity encoding range.
MRI 可以测量几个重要的血流动力学参数,但可能尚未充分发挥其潜力。评估血流的最常用 MRI 方法是相位对比 MRI 速度测绘,该方法估计体素的平均速度。只有当体素内速度分布对称时,这种估计才是精确的。平均速度对应于体素内速度分布的第一原始矩。这里描述了一种用于量化任意速度分布的任何阶矩的通用 MRI 框架。该框架基于函数域(速度空间)中的矩对应于傅立叶变换域(kv 空间)中的微分的事实。作为概念验证,使用 MRI 信号导数的有限差分逼近来估计实际速度分布的矩。此外,该框架还被应用于研究相位对比 MRI 速度测绘中所基于的对称假设;我们发现,该假设会显著影响相位对比 MRI 速度估计,并且可以通过增加速度编码范围来降低其重要性。