Ikoma Yoko, Takano Akihiro, Ito Hiroshi, Kusuhara Hiroyuki, Sugiyama Yuichi, Arakawa Ryosuke, Fukumura Toshimitsu, Nakao Ryuji, Suzuki Kazutoshi, Suhara Tetsuya
Department of Molecular Neuroimaging, Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, Japan.
J Nucl Med. 2006 Sep;47(9):1531-7.
P-glycoprotein in the blood-brain barrier (BBB) has been found to be associated with several types of neurologic damage. (11)C-Verapamil has been used for in vivo imaging of P-glycoprotein function in the BBB by PET, but metabolites in plasma complicate the quantitative analysis of human studies. In this study, we validated the quantification methods of (11)C-verapamil transfer from plasma to the brain in humans.
The transfer rate constant from plasma to the brain, K(1), was estimated by nonlinear least squares (NLS) with a 2-input compartment model, including the permeation of the main metabolite in plasma at the BBB, and with a 1-input compartment model using only 15-min data that contained little metabolite in plasma. K(1) was also estimated by graphical analysis of an integration plot that uses only early-time data, before the appearance of metabolites, and the estimated K(1) was compared with that obtained by the NLS method. In the simulation study, the reliability of parameter estimates in the graphical analysis method was investigated for various values of rate constants, time ranges of parameter estimations, and noise levels.
(11)C-Verapamil in plasma gradually converted to its metabolites, and about 45% of the radioactivity in the plasma specimen was associated with (11)C-verapamil metabolites at 30 min after injection. Although K(1) estimated from graphical analysis was slightly smaller than that by NLS, there was strong correlation among the K(1) values obtained by these 3 methods. In the simulation study, for graphical analysis, the differences between the true and mean of K(1) estimates became larger and the coefficient of variation (COV) of K(1) estimates became smaller as the end time of linear regression became later. The COV of graphical analysis was almost equal to that of NLS with the 1-input compartment model.
The transfer of (11)C-verapamil from plasma to the brain was able to be quantitatively estimated by graphical analysis because this method can provide K(1) from the data of the initial few minutes without considering the effect of the metabolites in plasma.
血脑屏障（BBB）中的P-糖蛋白已被发现与多种类型的神经损伤有关。（11）C-维拉帕米已被用于通过PET对BBB中P-糖蛋白功能进行体内成像，但血浆中的代谢物使人体研究的定量分析变得复杂。在本研究中，我们验证了人体中（11）C-维拉帕米从血浆向脑内转运的定量方法。
采用二输入房室模型，通过非线性最小二乘法（NLS）估计从血浆到脑的转运速率常数K（1），该模型包括血浆中主要代谢物在血脑屏障处的渗透，以及使用仅包含血浆中少量代谢物的15分钟数据的一输入房室模型。K（1）也通过仅使用代谢物出现之前的早期数据的积分图的图形分析来估计，并将估计的K（1）与通过NLS方法获得的K（1）进行比较。在模拟研究中，针对速率常数的各种值、参数估计的时间范围和噪声水平，研究了图形分析方法中参数估计的可靠性。
血浆中的（11）C-维拉帕米逐渐转化为其代谢物，注射后30分钟时，血浆标本中约45%的放射性与（11）C-维拉帕米代谢物相关。虽然通过图形分析估计的K（1）略小于通过NLS估计的K（1），但通过这三种方法获得的K（1）值之间存在很强的相关性。在模拟研究中，对于图形分析，随着线性回归的结束时间变晚，K（1）估计值的真实值与平均值之间的差异变大，K（1）估计值的变异系数（COV）变小。图形分析的COV几乎与一输入房室模型的NLS的COV相等。
（11）C-维拉帕米从血浆到脑的转运能够通过图形分析进行定量估计，因为该方法可以从最初几分钟的数据中提供K（1），而无需考虑血浆中代谢物 的影响。
