Logan Jean, Fowler Joanna S, Ding Yu-Shin, Franceschi Dinko, Wang Gene-Jack, Volkow Nora D, Felder Christoph, Alexoff David
Chemistry Department, Brookhaven National Laboratory, Upton, New York 11973, USA.
J Cereb Blood Flow Metab. 2002 Nov;22(11):1367-76. doi: 10.1097/01.WCB.0000040947.67415.e1.
The construction of parametric positron emission tomography images of enzyme or receptor concentration obtained using irreversibly binding radiotracers presents problems not usually encountered with reversibly binding radiotracers. Difficulties are most apparent in brain regions having low blood flow and/or high enzyme or receptor concentration and are exacerbated with noisy data. This is especially true when minimal doses of radiotracer are administered. A comparison was recently reported of the irreversible monoamine oxidase A (MAO A) radiotracers [11C]clorgyline (CLG) and deuterium-substituted [11C]clorgyline (CLG-D) in the human brain using region of interest (ROI) analysis in which the authors observed an unexpected loss of image contrast with CLG-D compared with CLG. In order to more fully investigate patterns of binding of these irreversibly binding radiotracers, a strategy was devised to reduce noise in the generation of parametric images of the model term related to enzyme or receptor concentration. The generalized linear least squares (GLLS) method of Feng et al. (1995), a rapid linear method that is unbiased, was used for image-wide parameter estimation. Since GLLS can fail in the presence of large amounts of noise, local voxels were grouped within the image to increase the signal, and the GLLS method was combined with the standard nonlinear estimation methods when necessary. Voxels were grouped together depending on their proximity and whether they fell within a specified range of the time-integrated image. It was assumed that voxels meeting both criteria are functionally related. Simulations reflecting varying enzyme concentrations were performed to assess precision and accuracy of parameter estimates in the presence of varying amounts of noise. Using this approach, images were generated of the combination parameter lambdak3 (lambda = K1/k2, where K1 and k2 are plasma-to-tissue and tissue-to-plasma transport constants, respectively) that is related to enzyme concentration as well as images of the transport constant K1 for individual subjects. Reasonably high-quality images of both K1 and lambdak3 were obtained for CLG and CLG-D for individual subjects even with low injected doses averaging 6 mCi. While there were no differences in the K1 images, the lambdak3 images revealed the loss of contrast previously reported for CLG-D using the ROI analysis. This method should be generalizable to other tracers and should facilitate the analysis of group differences.
使用不可逆结合放射性示踪剂获得酶或受体浓度的参数正电子发射断层扫描图像的构建存在一些通常在可逆结合放射性示踪剂中不会遇到的问题。这些困难在血流低和/或酶或受体浓度高的脑区最为明显,并且在数据有噪声时会加剧。当给予最小剂量的放射性示踪剂时尤其如此。最近有报道使用感兴趣区域(ROI)分析对人脑内不可逆单胺氧化酶A(MAO A)放射性示踪剂[11C]氯吉兰(CLG)和氘取代的[11C]氯吉兰(CLG-D)进行了比较,作者观察到与CLG相比,CLG-D的图像对比度意外降低。为了更全面地研究这些不可逆结合放射性示踪剂的结合模式,设计了一种策略来减少与酶或受体浓度相关的模型项的参数图像生成中的噪声。Feng等人(1995年)的广义线性最小二乘法(GLLS)是一种快速、无偏的线性方法,用于全图像参数估计。由于GLLS在存在大量噪声时可能失败,因此将图像中的局部体素分组以增加信号,并在必要时将GLLS方法与标准非线性估计方法相结合。根据体素的接近程度以及它们是否落在时间积分图像的指定范围内将体素分组在一起。假设满足这两个标准的体素在功能上相关。进行了反映不同酶浓度的模拟,以评估在存在不同量噪声时参数估计的精度和准确性。使用这种方法,生成了与酶浓度相关的组合参数λk3(λ = K1/k2,其中K1和k2分别是血浆到组织和组织到血浆的转运常数)的图像以及个体受试者的转运常数K1的图像。即使平均注射剂量低至6毫居里,对于个体受试者,CLG和CLG-D的K1和λk3图像质量也相当高。虽然K1图像没有差异,但λk3图像显示了先前使用ROI分析报道的CLG-D的对比度降低。该方法应可推广到其他示踪剂,并应有助于分析组间差异。