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An Analysis of Whole Body Tracer Kinetics in Dynamic PET Studies With Application to Image-Based Blood Input Function Extraction

机译:动态PET研究中的全身示踪剂动力学分析及其在基于图像的血液输入功能提取中的应用

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摘要

In a positron emission tomography (PET) study, the local uptake of the tracer is dependent on vascular delivery and retention. For dynamic studies the measured uptake time-course information can be best interpreted when knowledge of the time-course of tracer in the blood is available. This is certainly true for the most established tracers such as 18F-Fluorodeoxyglucose (FDG) and 15O-Water (H2O). Since direct sampling of blood as part of PET studies is increasingly impractical, there is ongoing interest in image-extraction of blood time-course information. But analysis of PET-measured blood pool signals is complicated because they will typically involve a combination of arterial, venous and tissue information. Thus, a careful appreciation of these components is needed to interpret the available data. To facilitate this process, we propose a novel Markov chain model for representation of the circulation of a tracer atom in the body. The model represents both arterial and venous time-course patterns. Under reasonable conditions equilibration of tracer activity in arterial and venous blood is achieved by the end of the PET study—consistent with empirical measurement. Statistical inference for Markov model parameters is a challenge. A penalized nonlinear least squares process, incorporating a generalized cross-validation score, is proposed. Random effects analysis is used to adaptively specify the structure of the penalty function based on historical samples of directly measured blood data. A collection of arterially sampled data from PET studies with FDG and H2O is used to illustrate the methodology. These data analyses are highly supportive of the overall modeling approach. An adaptation of the model to the problem of extraction of arterial blood signals from imaging data is also developed and promising preliminary results for cerebral and thoracic imaging studies with FDG and H2O are obtained.
机译:在正电子发射断层扫描(PET)研究中,示踪剂的局部摄取取决于血管的输送和保留。对于动态研究,当可以获得血液中示踪剂的时程知识时,可以最好地解释测得的摄取时程信息。对于最成熟的示踪剂,例如 18 F-氟去氧葡萄糖(FDG)和 15 O-水(H2O),当然是正确的。由于将血液直接采样作为PET研究的一部分越来越不切实际,因此人们对血液时程信息的图像提取越来越感兴趣。但是,PET测量的血池信号的分析非常复杂,因为它们通常涉及动脉,静脉和组织信息的组合。因此,需要仔细了解这些组件以解释可用数据。为了促进这一过程,我们提出了一种新颖的马尔可夫链模型来表示人体中示踪原子的循环。该模型代表了动脉和静脉的时程模式。在合理的条件下,PET研究结束时,动静脉血中示踪剂活性的平衡得以实现-与经验测量一致。马尔可夫模型参数的统计推断是一个挑战。提出了一种带有广义交叉验证得分的惩罚非线性最小二乘方法。随机效应分析用于根据直接测量的血液数据的历史样本自适应地指定惩罚函数的结构。使用FDG和H2O进行的PET研究的动脉采样数据的收集用于说明该方法。这些数据分析高度支持整体建模方法。还开发了该模型对从成像数据中提取动脉血信号问题的适应性,并获得了利用FDG和H2O进行脑和胸腔成像研究的有希望的初步结果。

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