Direct 4D parametric imaging for linearized models of reversibly binding PET tracers using generalized AB-EM reconstruction.

Direct 4D parametric imaging for linearized models of reversibly binding PET tracers using generalized AB-EM reconstruction.
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DOI:
10.1088/0031-9155/57/3/733
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发表时间:
2012-02-07
影响因子:
3.5
通讯作者:
Wong DF
Wong DF
中科院分区:
工程技术2区
文献类型:
--
作者:
Rahmim A;Zhou Y;Tang J;Lu L;Sossi V;Wong DF

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由于体素动力学中的高噪声水平,可靠的参数成像算法的开发仍然是动态脑PET成像中最活跃的领域之一,在绝大多数情况下,动态脑PET成像涉及可逆结合示踪剂的受体/转运蛋白研究。因此,这项工作的重点是开发一种新的直接4D参数图像重建方案,这样的示踪剂。基于相对平衡(RE)图形分析公式,我们开发了一种封闭形式的4D EM算法,以直接重建血浆输入模型内的分布容积(DV)参数图像,以及参考组织模型方案内的DV比率(DVR)图像(其中,初始重建用于估计参考组织时间-活性曲线)。直接4D EM公式的一个特殊挑战是可逆示踪剂的图形(线性化)分析(例如Logan或RE分析)中的截距参数通常为负(与不可逆示踪剂不同;例如使用Patlak分析)。随后,我们将注意力集中在AB-EM算法上,该算法由允许包含关于图像值的下限(A)和上限(B)的先验信息导出。然后,我们将此算法推广到4D EM框架,从而允许负截距参数。此外,我们的4D AB-EM算法纳入,并强调使用空间变化的下限,以实现增强的性能。作为验证,从55项人体11 C-雷氯必利动态PET研究中估计的参数平均值用于使用数学脑体模进行广泛模拟。图像重建使用传统的间接以及提出的直接参数成像方法。在大脑的各个区域进行噪声与偏差定量测量。直接4D EM重建导致显著的定性和定量准确性提高(在血浆和参考组织输入模型中,噪声降低超过35%,具有匹配的偏差)。即使对于相对低吸收的皮质区域,估计的DV和DVR值的变异系数(COV)也观察到类似的改善,这表明鲁棒参数估计的能力增强。该方法还在高分辨率研究断层扫描仪(HRT)上进行的90分钟11 C-雷氯必利患者研究中进行了测试,其中所提出的方法在多个区域上显示出优于传统方法,在这个意义上,对于给定的DVR值,观察到改善的噪声水平。
Due to high noise levels in the voxel kinetics, development of reliable parametric imaging algorithms remains as one of most active areas in dynamic brain PET imaging, which in the vast majority of cases involves receptor/transporter studies with reversibly binding tracers. As such, the focus of this work has been to develop a novel direct 4D parametric image reconstruction scheme for such tracers. Based on a relative equilibrium (RE) graphical analysis formulation, we developed a closed-form 4D EM algorithm to directly reconstruct distribution volume (DV) parametric images within a plasma input model, as well as DV ratio (DVR) images within a reference tissue model scheme (wherein an initial reconstruction was used to estimate the reference tissue time-activity-curves). A particular challenge with the direct 4D EM formulation is that the intercept parameters in graphical (linearized) analysis of reversible tracers (e.g. Logan or RE analysis) are commonly negative (unlike for irreversible tracers; e.g. using Patlak analysis). Subsequently, we focused our attention on the AB-EM algorithm, derived by to allow inclusion of prior information about the lower (A) and upper (B) bounds for image values. We then generalized this algorithm to the 4D EM framework thus allowing negative intercept parameters. Furthermore, our 4D AB-EM algorithm incorporated, and emphasized the use of spatially varying lower bounds to achieve enhanced performance. As validation, the means of parameters estimated from 55 human 11C-raclopride dynamic PET studies were used for extensive simulations using a mathematical brain phantom. Images were reconstructed using conventional indirect as well as proposed direct parametric imaging methods. Noise vs. bias quantitative measurements were performed in various regions of the brain. Direct 4D EM reconstruction resulted in notable qualitative and quantitative accuracy improvements (over 35% noise reduction, with matched bias, in both plasma and reference-tissue input models). Similar improvements were also observed in the coefficient of variation (COV) of the estimated DV and DVR values even for relatively low uptake cortical regions, suggesting the enhanced ability for robust parameter estimation. The method was also tested on a 90-minute 11C- raclopride patient study performed on the high resolution research tomograph (HRRT) wherein the proposed method was shown across a variety of regions to outperform the conventional method in the sense that for a given DVR value improved noise levels were observed.
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