Joint Reconstruction of Activity and Attenuation in Time-of-Flight PET: A Quantitative Analysis
Joint Reconstruction of Activity and Attenuation in Time-of-Flight PET: A Quantitative Analysis
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DOI：
10.2967/jnumed.117.204156
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发表时间：
2018-10-01
影响因子：
9.3
通讯作者：
Nuyts, Johan
中科院分区：
文献类型：
--
作者：
Rezaei, Ahmadreza;Deroose, Christophe M.;Nuyts, Johan
用于飞行时间（TOF）PET数据的关节活动重建和衰减重建的方法在没有（或不完整或不准确）关于衰减的信息可用时提供衰减校正的有效解决方案。限制这些方法在临床实践中使用的主要障碍之一是它们缺乏在相对较大的患者数据库中的验证。在这方面的贡献，我们的目标是验证重建与最大似然活动重建和衰减登记（MLRR）在全身患者数据集。此外，还提供了用最大似然活动和衰减（MLAA）执行的重建的部分验证（因为现在避免了算法的尺度问题）。我们提出了这2种关节重建方法和当前临床金标准，最大似然期望最大化（MLEM）与基于CT的衰减校正之间的定量比较。研究方法：将每个患者数据集的全身TOF PET发射数据作为一个整体进行处理，以重建覆盖所有采集床位置的活动体积，有助于将MLAA中每个床位置的标度问题减少到整个活动体积的全局标度。使用了三种重建算法：MLEM、MLRR和MLAA。最大似然缩放的单散射模拟估计的排放数据被用于散射校正。然后分析了各个感兴趣区域的重建结果。结果如下：在患者或器官运动导致PET和CT未对准的情况下，全身患者数据集的关节重建提供了比金标准更好的量化。我们的定量分析显示，MLRR和MLEM之间的差异为-4.2% +/- 2.3%，MLAA和MLEM之间的差异为-7.5% +/- 4.6%，在所有感兴趣区域内平均。结论：当基于CT的衰减图像受到未对准或不可用时，活动和衰减的联合重建提供了一种有用的手段来估计示踪剂分布。通过准确估计发射测量中的散射贡献，TOF PET数据的联合重建在临床可接受的精度内。
Methods for joint activity reconstruction and attenuation reconstruction of time-of-flight (TOF) PET data provide an effective solution to attenuation correction when no (or incomplete or inaccurate) information on attenuation is available. One of the main barriers limiting use of these methods in clinical practice is their lack of validation in a relatively large patient database. In this contribution, we aim to validate reconstruction performed with maximum-likelihood activity reconstruction and attenuation registration (MLRR) in a whole-body patient dataset. Furthermore, a partial validation (because the scale problem of the algorithm is avoided for now) of reconstruction performed with maximum-likelihood activity and attenuation (MLAA) is also provided. We present a quantitative comparison between these 2 methods of joint reconstruction and the current clinical gold standard, maximum-likelihood expectation maximization (MLEM) with CT-based attenuation correction. Methods: The whole-body TOF PET emission data of each patient dataset were processed as a whole to reconstruct an activity volume covering all the acquired bed positions, helping reduce the problem of a scale per bed position in MLAA to a global scale for the entire activity volume. Three reconstruction algorithms were used: MLEM, MLRR, and MLAA. A maximum-likelihood scaling of the single-scatter simulation estimate to the emission data was used for scatter correction. The reconstruction results for various regions of interest were then analyzed. Results: The joint reconstructions of the whole-body patient dataset provided better quantification than the gold standard in cases of PET and CT misalignment caused by patient or organ motion. Our quantitative analysis showed a difference of -4.2% +/- 2.3% between MLRR and MLEM and a difference of -7.5% +/- 4.6% between MLAA and MLEM, averaged over all regions of interest. Conclusion: Joint reconstruction of activity and attenuation provides a useful means to estimate tracer distribution when CTbased- attenuation images are subject to misalignment or are not available. With an accurate estimate of the scatter contribution in the emission measurements, the joint reconstructions of TOF PET data are within clinically acceptable accuracy.