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IMAGING D2-DOPAMINE RECEPTOR CONCENTRATION IN NON-HUMAN PRIMATE BRAIN USING 18{sup left}F-FALLYPRIDE

机译:使用18 {sup left} f-blyplyprimed ulligallige的非人灵长类大脑中的成像D2-多巴胺受体浓度

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In this paper, we demonstrate how to form images of D2-dopamine receptor concentration in the brain with positron emission tomography (PET). Quantification of receptor sites within the brain is required to understand aging, diseases such as Alzheimer, and drug addiction. This quantification is performed by acquiring dynamic PET data and analyzing the tracer kinetics from the reconstructed emission data. The signal-to-noise ratio (SNR) of the reconstructed dynamic PET data is generally so low that region of interest (ROI) analysis is required to have accurate quantification. ROI analysis produces a single value of receptor concentration for each region in the brain. We recently show that it is possible to form parametric images directly from the acquired sinogram data [1]. Elimination of intermediate steps and direct reconstruction of parameters from sinograms allowed us to form dense images of parameters of interest. In this paper, we applied the direct parametric reconstruction algorithm to form images of D2-dopamine receptor concentration within monkey brain using 18{sup left}F-fallypride radiotracer. Our initial investigations show that our D2 receptor images are consistent with the results of the classical ROI analysis.
机译:在本文中,我们展示了如何用正电子发射断层扫描(PET)在大脑中形成D2-多巴胺受体浓度的图像。需要大脑内的受体位点的定量来理解老化,疾病,如阿尔茨海默和吸毒。通过获取动态PET数据并从重建的发射数据分析示踪动力学来执行该量化。重建动态PET数据的信噪比(SNR)通常如此低,所以感兴趣区域(ROI)分析需要准确定量。 ROI分析为大脑中每个区域产生的受体浓度的单一值。我们最近表明可以直接从所获取的Sinogram数据[1]形成参数图像。消除中间步骤和来自Sinogram的参数的直接重建使我们能够形成感兴趣的参数的密集图像。在本文中,我们应用了使用18 {sup左} F-芳丙烯酸脲酰胺在猴脑内形成D2-多巴胺受体浓度的图像的直接参数重建算法。我们的初步调查表明,我们的D2受体图像与经典ROI分析的结果一致。

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