Single-voxel delay map from long-axial field-of-view PET scans

Frederik Bay Nielsen, Ulrich Lindberg, Heloisa N. Bordallo, C. B. Johnbeck, Ian Law, B. M. Fischer, F. L. Andersen, T. L. Andersen
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Abstract

We present an algorithm to estimate the delay between a tissue time activity curve and a blood input curve at a single-voxel level tested on whole-body data from a long-axial field-of-view scanner with tracers of different noise characteristics.Whole-body scans of 15 patients divided equally among three tracers: [15O]H2O, [18F]FDG and [64Cu]Cu-DOTATATE, were used in development and testing of the algorithm. Delay time were estimated by fitting the cumulatively summed input function and tissue time activity curve with special considerations for noise. To evaluate the performance of the algorithm, it was compared against two other algorithms also commonly applied in delay estimation, name cross-correlation and a one-tissue compartment model with incorporated delay. All algorithms were tested on both synthetic time activity curves produced with the one-tissue compartment model with increasing levels of noise and delays between the tissue activity curve and the blood input curve. Whole-body delay maps were also calculated for each of the three tracers with data acquired on a long-axial field-of-view scanner with high time resolution.Our proposed model performs better for low signal-to-noise ratio time activity curves compared to both cross-correlation and the one-tissue compartment models for non-[15O]H2O tracers. Testing on synthetically produced time activity curves it displays only a small and even residual delay, while the one-tissue compartment model with included delay showed varying residual delays.The algorithm is robust to noise and proves applicable on a range of tracers as tested on [15O]H2O, [18F]FDG and [64Cu]Cu-DOTATATE, and hence is a viable option offering the ability for delay correction across various organs and tracers in use with kinetic modeling.
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长轴视场 PET 扫描的单体素延迟图
我们介绍了一种在单象素水平上估算组织时间活动曲线与血液输入曲线之间延迟的算法,该算法在长轴视场扫描仪的全身数据上进行了测试,并使用了具有不同噪声特性的示踪剂:算法的开发和测试使用了[15O]H2O、[18F]FDG和[64Cu]Cu-DOTATATE三种示踪剂。延迟时间是通过拟合累积总和输入函数和组织时间活动曲线估算出来的,并特别考虑了噪声。为了评估该算法的性能,还将其与其他两种通常应用于延迟估计的算法进行了比较,即名称交叉相关算法和包含延迟的单组织区室模型。所有算法都在使用单组织区室模型生成的合成时间活动曲线上进行了测试,测试中的噪声和组织活动曲线与血液输入曲线之间的延迟水平都在不断增加。与交叉相关模型和非[15O]H2O示踪剂的单组织室模型相比,我们提出的模型在低信噪比时间活动曲线上表现更好。在对合成的时间活动曲线进行测试时,它只显示出很小且均匀的残余延迟,而包含延迟的单组织区室模型则显示出不同的残余延迟。该算法对噪声很稳健,在对[15O]H2O、[18F]FDG和[64Cu]Cu-DOTATATE进行测试时,证明适用于一系列示踪剂,因此是一种可行的选择,能够在使用动力学建模时对各种器官和示踪剂进行延迟校正。
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