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Voxel-based estimation of kinetic model parameters of the L-1-11Cleucine PET method for determination of regional rates of cerebral protein synthesis: Validation and comparison with region-of-interest based methods

机译:基于体素的动力学模型参数估计Liucine PET方法用于测定脑蛋白质合成区域率的方法:验证与基于地区的基于区域的方法

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摘要

We adapted and validated a basis function method (BFM) to estimate at the voxel level parameters of the kinetic model of the L-[1-11C]leucine PET method and regional rates of cerebral protein synthesis (rCPS). In simulation at noise levels typical of voxel data, BFM yielded low bias estimates of rCPS; in measured data, BFM and nonlinear least squares parameter estimates were in good agreement. We also examined whether there are advantages to using voxel-level estimates averaged over regions of interest (ROI) in place of estimates obtained by directly fitting ROI time-activity curves (TACs). In both simulated and measured data, fits of ROI TACs were poor, likely due to tissue heterogeneity not taken into account in the kinetic model. In simulation, rCPS determined from fitting ROI TACs was substantially overestimated and BFM-estimated rCPS averaged over all voxels in a ROI was slightly underestimated. In measured data, rCPS determined by regional averaging of voxel estimates was lower than rCPS determined from ROI TACs, consistent with simulation. In both simulated and measured data, intersubject variability of BFM-estimated rCPS averaged over all voxels in a ROI was low. We conclude that voxelwise estimation is preferable to fitting ROI TACs with a homogeneous tissue model.

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