Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, Canada; Université de Montréal, Montréal, Canada.
Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, Canada.
Neuroimage. 2020 Jan 15;205:116210. doi: 10.1016/j.neuroimage.2019.116210. Epub 2019 Oct 5.
Studies using resting-state functional magnetic resonance imaging (rsfMRI) are increasingly collecting data at multiple sites in order to speed up recruitment or increase sample size. The main objective of this study was to assess the long-term consistency of rsfMRI connectivity maps derived at multiple sites and vendors using the Canadian Dementia Imaging Protocol (CDIP, www.cdip-pcid.ca). Nine to 10 min of functional BOLD images were acquired from an adult cognitively healthy volunteer scanned repeatedly at 13 Canadian sites on three scanner makes (General Electric, Philips and Siemens) over the course of 2.5 years. The consistency (spatial Pearson's correlation) of rsfMRI connectivity maps for seven canonical networks ranged from 0.3 to 0.8, with a negligible effect of time, but significant site and vendor effects. We noted systematic differences in data quality (i.e. head motion, number of useable time frames, temporal signal-to-noise ratio) across vendors, which may also confound some of these results, and could not be disentangled in this sample. We also pooled the long-term longitudinal data with a single-site, short-term (1 month) data sample acquired on 26 subjects (10 scans per subject), called HNU1. Using randomly selected pairs of scans from each subject, we quantified the ability of a data-driven unsupervised cluster analysis to match two scans of the same subjects. In this "fingerprinting" experiment, we found that scans from the Canadian subject (Csub) could be matched with high accuracy intra-site (>95% for some networks), but that the accuracy decreased substantially for scans drawn from different sites and vendors, even falling outside of the range of accuracies observed in HNU1. Overall, our results demonstrate good multivariate stability of rsfMRI measures over several years, but substantial impact of scanning site and vendors. How detrimental these effects are will depend on the application, yet our results demonstrate that new methods for harmonizing multisite analysis represent an important area for future work.
使用静息态功能磁共振成像 (rsfMRI) 的研究越来越多地在多个地点收集数据，以加快招募速度或增加样本量。本研究的主要目的是评估使用加拿大痴呆成像协议 (CDIP，www.cdip-pcid.ca) 从多个地点和供应商获得的 rsfMRI 连接图的长期一致性。在 2.5 年的时间里，从一名成年认知健康志愿者身上扫描了 13 个加拿大站点的三种扫描仪制造商（通用电气、飞利浦和西门子）的 9-10 分钟功能 BOLD 图像。七个标准网络的 rsfMRI 连接图的一致性（空间 Pearson 相关系数）范围为 0.3 至 0.8，时间影响可以忽略不计，但地点和供应商影响显著。我们注意到不同供应商的数据质量（即头部运动、可用时间帧数量、时间信号噪声比）存在系统性差异，这些差异也可能混淆了其中的一些结果，而且在本样本中无法区分。我们还将长期纵向数据与单个地点、短期（1 个月）数据样本（每个受试者 10 次扫描）进行了汇总，称为 HNU1。我们使用从每个受试者中随机选择的一对扫描，量化了数据驱动的无监督聚类分析匹配同一受试者的两次扫描的能力。在这个“指纹识别”实验中，我们发现来自加拿大受试者 (Csub) 的扫描可以在内部站点以高精度匹配 (>95%的某些网络)，但来自不同站点和供应商的扫描的准确性会大大降低，甚至落在 HNU1 观察到的准确性范围之外。总体而言，我们的结果表明，rsfMRI 测量值在几年内具有良好的多变量稳定性，但扫描地点和供应商的影响较大。这些影响的危害性将取决于应用，但我们的结果表明，协调多站点分析的新方法是未来工作的一个重要领域。
