Initial Evaluation of Direct 4D Parametric Reconstruction with Human PET Data.

Jianhua Yan, Beata Planeta-Wilson, Jean-Dominique Gallezot, Richard E Carson
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Abstract

Previously, we presented a direct EM method for producing kinetic parameter images from list mode PET data, where the time-activity curve for each voxel is described by a one-tissue compartment model (1T). The initial evaluations were performed with simulations, without motion, randoms, or scatter effects included. By extension of our previous frame-based physics correction methods, a practical direct 4D parametric reconstruction algorithm is now proposed and implemented for human data. Initial evaluations were performed using 3 human subjects with the serotonin transporter tracer [(11)C]AFM. Comparisons with the 2-step approach (frame-based reconstruction followed by voxel-by-voxel parameter estimation) provided encouraging initial results. Regional analysis showed that the 2-step and 4D methods have similar K(1) and V(T) values, but with a consistent difference. Visual analysis showed some noise reduction in 4D. These initial results suggest that direct 4D parametric reconstruction can be performed with real data, and offers the potential for improved accuracy and precision over the 2-step frame method.

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使用人体 PET 数据进行直接 4D 参数化重建的初步评估。
在此之前,我们提出了一种直接 EM 方法,用于从列表模式 PET 数据中生成动力学参数图像,其中每个体素的时间-活动曲线由单组织区室模型(1T)描述。最初的评估是在不包含运动、随机或散射效应的情况下模拟进行的。通过扩展我们之前基于帧的物理校正方法,现在提出了一种实用的直接 4D 参数重建算法,并针对人体数据进行了实施。初步评估使用了 3 名人体受试者的血清素转运示踪剂 [(11)C]AFM。与两步法(基于帧的重建,然后逐体素进行参数估计)进行比较后,得出了令人鼓舞的初步结果。区域分析显示,两步法和 4D 法的 K(1) 和 V(T) 值相似,但存在一致的差异。目视分析显示,4D 方法的噪声有所降低。这些初步结果表明,直接四维参数重建可以通过真实数据进行,并有可能比两步框架法提高准确性和精确度。
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