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Spatial-temporal Pharmacokinetic Model Based Registration of 4D Brain PET Data

机译:基于时空药代动力学模型的4D脑PET数据配准

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In dynamic positron emission tomography (PET), where scan durations often exceed 1 hour, registration of motion-corrupted dynamic PET images is necessary in order to maintain the integrity of the physiological/pharmacological/biochemical information derived from the tracer kinetic analysis of the scan. A pharmacokinetic model, which is traditionally used to analyse PET data following any registration, was incorporated into the registration process itself in order to allow for a groupwise registration of the temporal time frames. The new method achieved smaller registration errors and improved kinetic parameter estimates on validation data sets as compared with the traditional image based similarity registration approach. When applied to measured clinical data from 10 healthy subjects scanned with [~(11)C]-(+)-PHNO (a dopamine D3/D2 receptor tracer), it reduced the intra-class variability on the tracer kinetics, suggesting a successful registration. Our new method which incorporates a generic tracer kinetic model could be applied widely to dynamic PET data as part of an automated tool to remove motion artefacts and increase the integrity and statistical power of these data.
机译:在扫描时间通常超过1小时的动态正电子发射断层扫描(PET)中,必须记录运动受损的动态PET图像,以保持从扫描示踪剂动力学分析得出的生理/药理/生化信息的完整性。传统上用于在任何配准后分析PET数据的药代动力学模型已合并到配准过程本身中,以允许对时间范围进行逐组配准。与传统的基于图像的相似性配准方法相比,该新方法在验证数据集上实现了较小的配准误差并改进了动力学参数估计。当将其应用到用[〜(11)C]-(+)-PHNO(多巴胺D3 / D2受体示踪剂)扫描的10位健康受试者的测量临床数据中时,它减少了示踪剂动力学上的类内变异性,表明成功登记。我们的新方法结合了通用的示踪剂动力学模型,可以作为自动工具的一部分广泛应用于动态PET数据,以消除运动伪像并提高这些数据的完整性和统计能力。

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