Regularized image reconstruction algorithms for dual-isotope myocardial perfusion SPECT (MPS) imaging using a cross-tracer prior.
Regularized image reconstruction algorithms for dual-isotope myocardial perfusion SPECT (MPS) imaging using a cross-tracer prior.
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DOI：
10.1109/tmi.2010.2087031
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发表时间：
2011-06
影响因子：
10.6
通讯作者：
Frey EC
中科院分区：
文献类型：
--
作者：
He X;Cheng L;Fessler JA;Frey EC
在同时双同位素心肌灌注SPECT（MPS）成像中，同时采集数据以确定两种放射性同位素的分布。这项工作的目标是开发惩罚最大似然（PML）算法的一种新的交叉示踪剂之前，利用这一事实，即从同时双同位素MPS投影数据重建的两个图像在空间中完美注册。我们首先制定了同时双同位素MPS重建问题作为一个联合估计问题。然后提出了一个交叉示踪剂之前，耦合两个图像上的体素值。我们开发了一种迭代算法来重建MPS图像，该算法收敛于基于可分离代理函数的最大后验解。为了加快收敛速度，我们开发了一个快速算法的交叉跟踪先验的基础上完整的数据OS-EM（COSEM）框架。所提出的算法进行了比较，定性和定量的单示踪剂版本的前不包括交叉示踪剂项。定量评价包括平均值和标准差图像的比较以及使用均方误差评估图像保真度。我们还针对三级MPS诊断任务（即，将患者分类为无缺陷、可逆缺陷或固定缺陷。在这项研究中，与传统的有序子集期望最大化（OS-EM）重建后滤波进行了比较。与单一示踪剂之前的比较表明，对于具有大强度变化的图像区域具有相似的分辨率，并且在均匀区域中具有降低的噪声。在恢复图像保真度方面，交叉示踪剂先验也优于单示踪剂版本上级。三级观察者研究的结果表明，提出的交叉示踪剂先验和收敛算法相比，OS-EM提高了双同位素MPS图像的图像质量。
In simultaneous dual-isotope myocardial perfusion SPECT (MPS) imaging, data are simultaneously acquired to determine the distributions of two radioactive isotopes. The goal of this work was to develop penalized maximum likelihood (PML) algorithms for a novel cross-tracer prior that exploits the fact that the two images reconstructed from simultaneous dual-isotope MPS projection data are perfectly registered in space. We first formulated the simultaneous dual-isotope MPS reconstruction problem as a joint estimation problem. A cross-tracer prior that couples voxel values on both images was then proposed. We developed an iterative algorithm to reconstruct the MPS images that converges to the maximum a posteriori solution for this prior based on separable surrogate functions. To accelerate the convergence, we developed a fast algorithm for the cross-tracer prior based on the complete data OS-EM (COSEM) framework. The proposed algorithm was compared qualitatively and quantitatively to a single-tracer version of the prior that did not include the cross-tracer term. Quantitative evaluations included comparisons of mean and standard deviation images as well as assessment of image fidelity using the mean square error. We also evaluated the cross tracer prior using a three-class observer study with respect to the three-class MPS diagnostic task, i.e., classifying patients as having either no defect, reversible defect, or fixed defects. For this study, a comparison with conventional ordered subsets-expectation maximization (OS-EM) reconstruction with postfiltering was performed. The comparisons to the single-tracer prior demonstrated similar resolution for areas of the image with large intensity changes and reduced noise in uniform regions. The cross-tracer prior was also superior to the single-tracer version in terms of restoring image fidelity. Results of the three-class observer study showed that the proposed cross-tracer prior and the convergent algorithms improved the image quality of dual-isotope MPS images compared to OS-EM.