Gao Chenyu, Yang Qi, Kim Michael E, Khairi Nazirah Mohd, Cai Leon Y, Newlin Nancy R, Kanakaraj Praitayini, Remedios Lucas W, Krishnan Aravind R, Yu Xin, Yao Tianyuan, Zhang Panpan, Schilling Kurt G, Moyer Daniel, Archer Derek B, Resnick Susan M, Landman Bennett A
Vanderbilt University, Department of Electrical and Computer Engineering, Nashville, Tennessee, United States.
Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States.
J Med Imaging (Bellingham). 2024 Jul;11(4):044007. doi: 10.1117/1.JMI.11.4.044007. Epub 2024 Aug 24.
As large analyses merge data across sites, a deeper understanding of variance in statistical assessment across the sources of data becomes critical for valid analyses. Diffusion tensor imaging (DTI) exhibits spatially varying and correlated noise, so care must be taken with distributional assumptions. Here, we characterize the role of physiology, subject compliance, and the interaction of the subject with the scanner in the understanding of DTI variability, as modeled in the spatial variance of derived metrics in homogeneous regions.
We analyze DTI data from 1035 subjects in the Baltimore Longitudinal Study of Aging, with ages ranging from 22.4 to 103 years old. For each subject, up to 12 longitudinal sessions were conducted. We assess the variance of DTI scalars within regions of interest (ROIs) defined by four segmentation methods and investigate the relationships between the variance and covariates, including baseline age, time from the baseline (referred to as "interval"), motion, sex, and whether it is the first scan or the second scan in the session.
Covariate effects are heterogeneous and bilaterally symmetric across ROIs. Inter-session interval is positively related ( ) to FA variance in the cuneus and occipital gyrus, but negatively ( ) in the caudate nucleus. Males show significantly ( ) higher FA variance in the right putamen, thalamus, body of the corpus callosum, and cingulate gyrus. In 62 out of 176 ROIs defined by the Eve type-1 atlas, an increase in motion is associated ( ) with a decrease in FA variance. Head motion increases during the rescan of DTI ( mm per volume).
The effects of each covariate on DTI variance and their relationships across ROIs are complex. Ultimately, we encourage researchers to include estimates of variance when sharing data and consider models of heteroscedasticity in analysis. This work provides a foundation for study planning to account for regional variations in metric variance.
随着大型分析整合跨站点的数据，深入了解数据来源间统计评估的差异对于有效分析至关重要。扩散张量成像（DTI）表现出空间变化且相关的噪声，因此必须谨慎对待分布假设。在此，我们描述生理学、受试者依从性以及受试者与扫描仪的相互作用在理解DTI变异性中的作用，这是通过均匀区域中衍生指标的空间方差建模的。
我们分析了巴尔的摩纵向衰老研究中1035名受试者的DTI数据，年龄范围为22.4岁至103岁。每位受试者最多进行了12次纵向检查。我们评估了由四种分割方法定义的感兴趣区域（ROI）内DTI标量的方差，并研究了方差与协变量之间的关系，包括基线年龄、距基线的时间（称为“间隔”）、运动、性别以及该检查是首次扫描还是第二次扫描。
协变量效应在各ROI间是异质性且双侧对称的。会话间隔与楔叶和枕叶的FA方差呈正相关（ ），但与尾状核的FA方差呈负相关（ ）。男性在右侧壳核、丘脑、胼胝体和扣带回的FA方差显著更高（ ）。在由Eve 1型图谱定义的176个ROI中的62个中，运动增加与FA方差降低相关（ ）。DTI重新扫描期间头部运动增加（每体素 毫米）。
每个协变量对DTI方差的影响及其在各ROI间的关系都很复杂。最终，我们鼓励研究人员在共享数据时纳入方差估计，并在分析中考虑异方差模型。这项工作为研究规划提供了基础，以考虑指标方差的区域差异。
