Kameyama Masashi, Murakami Koji, Jinzaki Masahiro
Division of Nuclear Medicine, Department of Radiology, National Center for Global Health and Medicine, 1-21-1 Toyama, Shinjuku-ku, Tokyo, 162-8655, Japan.
Division of Nuclear Medicine, Department of Radiology, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
Ann Nucl Med. 2016 Jul;30(6):445-9. doi: 10.1007/s12149-016-1073-z. Epub 2016 Mar 26.
[(99m)Tc] D,L-hexamethyl-propyeneamine oxime ((99m)Tc-HMPAO), a brain perfusion tracer, suffers significant underestimation of regional cerebral blood flow (rCBF). Lassen et al. developed their linearization algorithm to correct the influence of back-diffusion of the tracer, and proposed their parameter α as 1.5. Based on mathematical modeling and literature review, recently, a new α value of 0.5 has been proposed for Lassen's correction algorithm for (99m)Tc-HMPAO, although correction using the old α value of 1.5 was confirmed to be sufficient. Inugami et al. reported that linearization correction gives a stable correlation coefficient over a wide range of α. Our hypotheses are that statistical noise is the source of the stable correlation coefficient presented by them and that the robustness of the correlation coefficient is the reason why many studies confirmed the value of α as 1.5.
Statistical noise was added in silico to the count, whose relationship with flow was α = 0.5. Then, the count was corrected by Lassen's linearization algorithm with a variety of α.
This study confirmed the hypothesis that smaller α values (strong correction) increase the noise at high flow values, leading to nominal increases in correlation coefficient as α decreases.
Despite this, adoption of the new, smaller α value of 0.5 would be more useful clinically in regaining the contrast between low-flow and high-flow areas of the brain.
脑灌注示踪剂[(99m)Tc]D,L-六甲基丙烯胺肟((99m)Tc-HMPAO)存在对局部脑血流量(rCBF)的显著低估。拉森等人开发了他们的线性化算法来校正示踪剂反向扩散的影响,并提出其参数α为1.5。基于数学建模和文献综述,最近有人针对(99m)Tc-HMPAO的拉森校正算法提出了新的α值0.5,尽管使用旧的α值1.5进行校正已被证实是足够的。犬上等人报告说,线性化校正在很宽的α范围内都能给出稳定的相关系数。我们的假设是,统计噪声是他们所呈现的稳定相关系数的来源,并且相关系数的稳健性是许多研究确认α值为1.5的原因。
在计算机模拟中向与流量关系为α = 0.5的计数中添加统计噪声。然后,用各种α值的拉森线性化算法对计数进行校正。
本研究证实了以下假设:较小的α值(强校正)会在高流量值时增加噪声,导致随着α减小相关系数名义上增加。
尽管如此,采用新的较小α值0.5在临床上对于恢复脑低流量和高流量区域之间的对比度会更有用。