¹⁸F-FDG uptake rate constant K_i is the main physiology parameter measured in dynamic PET studies. A model-independent graphical analysis using Patlak plot with plasma input function (PIF) is a standard approach used to estimate K_i . The PIF is the ¹⁸F-FDG time activity curve (TAC) in plasma that is obtained by serial arterial blood sampling. The purpose of the study is to evaluate a Patlak plot-based optimization approach with reduced blood samples for noninvasive quantification of dynamic ¹⁸F-FDG PET imaging. Eight 60 min rhesus monkey brain dynamic ¹⁸F-FDG PET scans with arterial blood samples were collected. The measured PIF (mPIF) was determined by arterial blood samples. TACs of seven cerebral regions of interest were generated from each study. With a given number of blood samples, the population-based PIF (pPIF) was determined by either interpolation or extrapolation method using scale calibrated population mean of normalized PIF. The optimal sampling scheme with given blood sample size was determined by maximizing the correlations between the K_i estimated from pPIF and those obtained by mPIF. A leave-two-out cross-validation method was used for evaluation. The linear correlations between the K_i estimates from pPIF with optimal sampling schemes and those from mPIF were: K_i (pPIF 1 sample at 40 min)=1.015 K_i (mPIF) − 0.000, R ²=0.974; K_i (pPIF 2 samples at 35 and 50 min)=1.052 K_i (mPIF) − 0.001, R ²=0.976; K_i (pPIF 3 samples at 12, 40, and 50 min)=1.030 K_i (mPIF) − 0.000, R ²=0.985; and K_i (pPIF 4 samples at 10, 20, 40, and 50 min)=1.016 K_i (mPIF)- 0.000, R ²=0.993. As the sample size became greater or equal to 4, the K_i estimates from pPIF with the optimal protocol were almost identical to those from mPIF. The Patlak plot-based optimization approach is a reliable method to estimate PIF for noninvasive quantification of non-human primate dynamic ¹⁸F-FDG PET imaging and is potentially extendable to further translational human studies.

¹⁸ F-FDG 摄取速率常数K _i 是动态 PET 研究中测量的主要生理参数。使用具有等离子体输入函数 (PIF) 的 Patlak 图的与模型无关的图形分析是用于估计K _i 的标准方法。PIF 是通过连续动脉血采样获得的血浆中的^{18 F-FDG 时间活性曲线 (TAC)。}该研究的目的是评估一种基于 Patlak 图的优化方法，该方法减少了血液样本，用于动态¹⁸ F-FDG PET 成像的无创量化。八节60分钟恒河猴大脑动态¹⁸收集了动脉血样本的 F-FDG PET 扫描结果。测量的 PIF (mPIF) 由动脉血样确定。从每项研究中产生了七个感兴趣的大脑区域的 TAC。对于给定数量的血液样本，基于群体的 PIF (pPIF) 是通过使用标准化 PIF 的标度校准总体平均值的内插或外推方法确定的。通过最大化从 pPIF 估计的K _i 与通过 mPIF 获得的 K i之间的相关性来确定具有给定血液样本大小的最佳采样方案。采用留二法交叉验证法进行评价。来自具有最佳采样方案的 pPIF 的K _i 估计值与来自 mPIF 的估计值之间的线性相关性为： K _i (pPIF 1 样品在 40 分钟)=1.015 K _i (mPIF) - 0.000, R ² =0.974；K _i (pPIF 2 样品在 35 和 50 分钟)=1.052 K _i (mPIF) - 0.001, R ² =0.976；K _i (pPIF 3 个样品在 12、40 和 50 分钟)=1.030 K _i (mPIF) - 0.000，R ² =0.985；K _i (pPIF 4 样品在 10、20、40 和 50 分钟)=1.016 K i ₍ mPIF)-0.000，R ² =0.993。当样本量大于或等于 4 时，K _i 采用最佳方案的 pPIF 的估计值几乎与 mPIF 的估计值相同。基于 Patlak 绘图的优化方法是估计 PIF 的可靠方法，用于非人类灵长类动物动态¹⁸ F-FDG PET 成像的无创量化，并且可能可扩展到进一步的人体转化研究。