Kameyama Masashi
Division of Nuclear Medicine, Department of Radiology, School of Medicine, Keio University, 35, Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan.
J Cereb Blood Flow Metab. 2014 Jul;34(7):1157-61. doi: 10.1038/jcbfm.2014.64. Epub 2014 Apr 16.
Brain perfusion tracers like [(99m)Tc] d,l-hexamethyl-propyeneamine oxime ((99m)Tc-HMPAO) and [(99m)Tc] ethyl-cysteinate dimer ((99m)Tc-ECD) underestimate regional cerebral blood flow (rCBF) at high flow values. To improve linearity between tracer accumulation and rCBF, two different models have been proposed. One is Lassen's correction algorithm for back-diffusion of tracer, and the other is based on the permeability-surface (PS) model for correction of low first-pass extraction. Although both these models have the same goal, they have completely different forms of equation. It was demonstrated that mathematical approximation of the PS model equation leads to Lassen's equation. In this process, the relationship between PS, CBF values and Lassen's parameter was acquired, and how to correct both the back-diffusion and low first-pass extraction was also demonstrated. A computer simulation confirmed that the two models provided similar consequences when the parameter value is chosen according to the relationship found. Lassen's equation can be used to correct not only back-diffusion but also low first-pass extraction. To perform overall correction, the parameter value we have been using for decades may be too weak. I estimated that the parameter value for overall correction of HMPAO would be around 0.5, and that of ECD would be around 0.65.
像[(99m)Tc] d,l - 六甲基丙烯胺肟((99m)Tc - HMPAO)和[(99m)Tc] 乙基半胱氨酸二聚体((99m)Tc - ECD)这样的脑灌注示踪剂在高流量值时会低估局部脑血流量(rCBF)。为了改善示踪剂积聚与rCBF之间的线性关系,已经提出了两种不同的模型。一种是用于示踪剂反向扩散的拉森校正算法,另一种基于通透表面(PS)模型用于校正低首过提取率。尽管这两种模型有相同的目标,但它们的方程形式完全不同。结果表明,PS模型方程的数学近似会得到拉森方程。在此过程中,获得了PS、CBF值与拉森参数之间的关系,并且还展示了如何校正反向扩散和低首过提取率。计算机模拟证实,当根据所发现的关系选择参数值时,这两种模型会产生相似的结果。拉森方程不仅可用于校正反向扩散,还可用于校正低首过提取率。为了进行全面校正,我们几十年来一直在使用的参数值可能太弱了。我估计,HMPAO全面校正的参数值约为0.5,ECD的约为0.65。