Department of Radiology and Radiological Sciences, Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA.
Mol Imaging. 2010 Apr;9(2):76-86.
A relatively simple, almost entirely noninvasive imaging-based method is presented for deriving arterial blood input functions for quantitative [(18)F]2-fluoro-2-deoxy-d-glucose (FDG) positron emission tomographic (PET) studies in rodents. It requires only one venous blood sample at the end of the scan. MicroPET images and arterial blood time-activity curves (TACs) were downloaded from the Mouse Quantitation Program database at the University of California, Los Angeles. Three-dimensional regions of interest were drawn around the blood-pool region of the left ventricle and within the liver to derive their respective TACs. To construct the "hybrid" image-derived input function (IDIF), the initial part of the left ventricle TAC, containing the peak concentration of [(18)F]FDG in the arterial blood, was corrected for spillout (ie, partial-volume effect yielding a recovery coefficient < 1) and then joined to the liver TAC (normalized to the 60-minute arterial blood sample) immediately after it peaks. To validate our method, the [(18)F]FDG influx constant (K(i)) was estimated using a two-tissue compartment model and compared to estimates of K(i) obtained using measured arterial blood TACs. No significant difference in the K(i) estimates was obtained with the arterial blood input function and our hybrid IDIF. We conclude that the normalized hybrid IDIF can be used in practice to obtain reliable K(i) estimates.
本文提出了一种相对简单、几乎完全无创的基于成像的方法,用于从啮齿动物定量 [(18)F]2-氟-2-脱氧-d-葡萄糖(FDG)正电子发射断层扫描(PET)研究中推导出动脉血液输入函数。它只需要在扫描结束时采集一次静脉血样本。MicroPET 图像和动脉血液时间-活性曲线(TAC)从加利福尼亚大学洛杉矶分校的 Mouse Quantitation Program 数据库中下载。在左心室的血池区域和肝脏内绘制三维感兴趣区域,以得出各自的 TAC。为了构建“混合”图像衍生输入函数(IDIF),左心室 TAC 的初始部分包含动脉血液中 [(18)F]FDG 的峰值浓度,经过校正溢出(即部分容积效应导致恢复系数 <1),然后与肝脏 TAC 连接(归一化为 60 分钟的动脉血样本),在其达到峰值后立即连接。为了验证我们的方法,使用两组织室模型估计了 [(18)F]FDG 流入常数(K(i)),并将其与使用测量的动脉血液 TAC 获得的 K(i)估计值进行了比较。使用动脉血液输入函数和我们的混合 IDIF 获得的 K(i)估计值没有显著差异。我们得出结论,归一化的混合 IDIF 可在实践中用于获得可靠的 K(i)估计值。