Ostergaard L, Weisskoff R M, Chesler D A, Gyldensted C, Rosen B R
Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown.
Magn Reson Med. 1996 Nov;36(5):715-25. doi: 10.1002/mrm.1910360510.
The authors review the theoretical basis of determination of cerebral blood flow (CBF) using dynamic measurements of nondiffusible contrast agents, and demonstrate how parametric and nonparametric deconvolution techniques can be modified for the special requirements of CBF determination using dynamic MRI. Using Monte Carlo modeling, the use of simple, analytical residue models is shown to introduce large errors in flow estimates when actual, underlying vascular characteristics are not sufficiently described by the chosen function. The determination of the shape of the residue function on a regional basis is shown to be possible only at high signal-to-noise ratio. Comparison of several nonparametric deconvolution techniques showed that a nonparametric deconvolution technique (singular value decomposition) allows estimation of flow relatively independent of underlying vascular structure and volume even at low signal-to-noise ratio associated with pixel-by-pixel deconvolution.
作者回顾了使用非扩散性造影剂的动态测量来测定脑血流量（CBF）的理论基础，并展示了如何针对使用动态MRI测定CBF的特殊要求对参数和非参数反卷积技术进行修改。通过蒙特卡洛建模表明，当所选函数不能充分描述实际的潜在血管特征时，使用简单的解析残差模型会在血流估计中引入较大误差。仅在高信噪比时才有可能在区域基础上确定残差函数的形状。几种非参数反卷积技术的比较表明，一种非参数反卷积技术（奇异值分解）即使在与逐像素反卷积相关的低信噪比情况下，也能相对独立于潜在血管结构和体积来估计血流。
