Temporal Trajectory and Progression Score Estimation from Voxelwise Longitudinal Imaging Measures: Application to Amyloid Imaging.
Temporal Trajectory and Progression Score Estimation from Voxelwise Longitudinal Imaging Measures: Application to Amyloid Imaging.
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时间轨迹和进程得分估计来自体素纵向成像测度：应用于淀粉样蛋白成像。
DOI：
10.1007/978-3-319-19992-4_33
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Prince JL
中科院分区：
文献类型：
--
作者：
Bilgel M;Jedynak B;Wong DF;Resnick SM;Prince JL
皮质β-淀粉样蛋白沉积在阿尔茨海默病(AD)出现任何临床症状的前几年就开始了。因此，在这些早期阶段确定淀粉样蛋白沉积的时间轨迹是很重要的，以便更好地了解它们与进展到AD的关系。提出了一种利用纵向正电子发射断层成像(PET)测量的体状淀粉样蛋白时间轨迹的估计方法。该方法包括根据反映患者淀粉样蛋白进展的正电子发射计算机断层扫描数据估计每次受试者就诊的分数。这种淀粉样蛋白进展评分允许对进展相似的受试者进行比对和分析。使用期望最大化算法进行进展分数和淀粉样蛋白轨迹参数的估计。对淀粉样体素测量之间的相关性进行了建模，以反映PET图像的空间特性。仿真结果表明，该方法在各种噪声和空间相关性水平下都能很好地捕获模型参数。将该方法应用于分别考虑每个大脑半球的纵向淀粉样成像数据。结果在两个半球都是一致的，并与被称为平均皮质DVR的大脑淀粉样蛋白的全球指数一致。与依赖于预先定义的区域的平均皮质DVR不同，该方法提取的进展分数是数据驱动的，并且不对区域纵向变化做出假设。与每个体素的年龄回归相比，使用该方法估计的纵向轨迹斜率显示出更好的局部化纵向变化。
Cortical β-amyloid deposition begins in Alzheimer’s disease (AD) years before the onset of any clinical symptoms. It is therefore important to determine the temporal trajectories of amyloid deposition in these earliest stages in order to better understand their associations with progression to AD. A method for estimating the temporal trajectories of voxelwise amyloid as measured using longitudinal positron emission tomography (PET) imaging is presented. The method involves the estimation of a score for each subject visit based on the PET data that reflects their amyloid progression. This amyloid progression score allows subjects with similar progressions to be aligned and analyzed together. The estimation of the progression scores and the amyloid trajectory parameters are performed using an expectation-maximization algorithm. The correlations among the voxel measures of amyloid are modeled to reflect the spatial nature of PET images. Simulation results show that model parameters are captured well at a variety of noise and spatial correlation levels. The method is applied to longitudinal amyloid imaging data considering each cerebral hemisphere separately. The results are consistent across the hemispheres and agree with a global index of brain amyloid known as mean cortical DVR. Unlike mean cortical DVR, which depends on a priori defined regions, the progression score extracted by the method is data-driven and does not make assumptions about regional longitudinal changes. Compared to regressing on age at each voxel, the longitudinal trajectory slopes estimated using the proposed method show better localized longitudinal changes.