首页> 外文会议>Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2011 IEEE >Activity estimation in small volumes with non-uniform radiotracer uptake using a local projection-based fitting approach
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Activity estimation in small volumes with non-uniform radiotracer uptake using a local projection-based fitting approach

机译:使用基于局部投影的拟合方法以不均匀的放射性示踪剂吸收量进行小剂量活动估算

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We have previously evaluated a local projection-based approach that provides robust estimates of activity concentration in small volumes-of-interest (VOI) affected by partial volume and tissue crosstalk in clinical SPECT imaging. The approach requires local segmentation of functionally distinct tissues within a VOI from a registered, high-resolution anatomical image of the object. Measured projection data are fitted to a statistical model of segmented-tissue projections. The resulting linear equations are solved to recover corrected values of tissue-activity concentration. In this work, we extended the approach to incorporate models of non-uniform radiotracer uptake into the fitting procedure. We evaluated the modified method using 25 independent noise realizations of simulated torso phantoms, each containing 20 identical, spherical “tumors” within a homogenous activity background. Radially varying quadratic functions were used to simulate two degrees (50% and 90%) of reduced central uptake inside the tumors (e.g., from necrosis), with an average integrated tumor-to-background concentration ratio of 7∶1. Tumor-activity estimates were obtained by fitting projection data to models that assumed either uniform tracer uptake (UF) or radially varying non-uniform uptake (NUF). The sensitivity of the approach to registration errors was investigated by simulating a 1-pixel misspecification of the locations of the VOI. The NUF approach achieved better than 1% bias and 12% precision for total tumor-activity estimates. Increasing the degree of central count loss from 50% to 90% did not significantly affect the NUF bias. In comparison, the UF method yielded 16% bias and 1% precision (48% bias, 5% precision) for 50% (90%) central count loss. The simulated registration error did not affect the UF estimates, but degraded the accuracy (and precision) of NUF estimates to 11% (and 13%). Despite slightly inferior precision, NUF may permit improved assessment of-inhomogeneous tumor uptake.
机译:我们之前已经评估了一种基于局部投影的方法,该方法可以在临床SPECT成像中受部分体积和组织串扰影响的小体积感兴趣样品(VOI)中提供可靠的活性浓度估算。该方法需要从对象的已注册的高分辨率解剖图像中对VOI中功能不同的组织进行局部分割。测得的投影数据适合分段组织投影的统计模型。求解所得的线性方程,以恢复组织活性浓度的校正值。在这项工作中,我们扩展了将非均匀放射性示踪剂吸收模型纳入拟合过程的方法。我们使用模拟躯干体模的25个独立噪声实现评估了修改后的方法,每个体模在同质活动背景中均包含20个相同的球形“肿瘤”。使用径向变化的二次函数来模拟肿瘤内部(例如,来自坏死)的中心摄取减少两个程度(50%和90%),肿瘤与背景的平均集成浓度比为7∶1。通过将投影数据拟合到假定均一的示踪剂摄入量(UF)或径向变化的不均一摄入量(NUF)的模型来获得肿瘤活性估计值。通过模拟VOI位置的1像素错误指定,研究了配准错误方法的敏感性。对于总的肿瘤活性估计,NUF方法获得了优于1%的偏倚和12%的精确度。将中心计数丢失的程度从50%增加到90%不会显着影响NUF偏差。相比之下,超滤方法产生了16%的偏差和1%的精度(48%的偏差,5%的精度),中心计数损失为50%(90%)。模拟的配准误差不会影响UF估计,但是会将NUF估计的准确性(和精度)降低到11%(和13%)。尽管精度略逊一筹,但NUF仍可以改善对不均匀肿瘤吸收的评估。

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