Dept. of Neurology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Breisacher Strasse 64, 79106 Freiburg, Germany; Medical Psychology and Medical Sociology, Faculty of Medicine, University of Freiburg, Rheinstrasse 12, 79104 Freiburg, Germany; Dept. of Neuroradiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Breisacher Strasse 64, 79106 Freiburg, Germany; Freiburg Brain Imaging Center, University of Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany.
Freiburg Brain Imaging Center, University of Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Medical Physics, Dept. of Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Breisacher Strasse 60a, 79106 Freiburg, Germany.
Neuroimage. 2018 Jul 15;175:215-229. doi: 10.1016/j.neuroimage.2018.01.086. Epub 2018 Feb 10.
As quantitative measures derived from fiber tractography are increasingly being used to characterize the structural connectivity of the brain, it is important to establish their reproducibility. However, no such information is as yet available for global tractography. Here we provide the first comprehensive analysis of the reproducibility of streamline counts derived from global tractography as quantitative estimates of structural connectivity. In a sample of healthy young adults scanned twice within one week, within-session and between-session test-retest reproducibility was estimated for streamline counts of connections based on regions of the AAL atlas using the intraclass correlation coefficient (ICC) for absolute agreement. We further evaluated the influence of the type of head-coil (12 versus 32 channels) and the number of reconstruction repetitions (reconstructing streamlines once or aggregated over ten repetitions). Factorial analyses demonstrated that reproducibility was significantly greater for within- than between-session reproducibility and significantly increased by aggregating streamline counts over ten reconstruction repetitions. Using a high-resolution head-coil incurred only small beneficial effects. Overall, ICC values were positively correlated with the streamline count of a connection. Additional analyses assessed the influence of different selection variants (defining fuzzy versus no fuzzy borders of the seed mask; selecting streamlines that end in versus pass through a seed) showing that an endpoint-based variant using fuzzy selection provides the best compromise between reproducibility and anatomical specificity. In sum, aggregating quantitative indices over repeated estimations and higher numbers of streamlines are important determinants of test-retest reproducibility. If these factors are taken into account, streamline counts derived from global tractography provide an adequately reproducible quantitative measure that can be used to gauge the structural connectivity of the brain in health and disease.
随着基于纤维束追踪技术的定量指标越来越多地被用于描述大脑的结构连接，确定其可重复性变得尤为重要。然而，目前还没有关于全局纤维追踪技术的可重复性的相关信息。在这里，我们首次对基于 AAL 图谱的区域的全局纤维追踪技术的流线计数的可重复性进行了全面分析，这些流线计数是作为结构连接的定量估计值。在一周内扫描两次的健康年轻成年人样本中，我们使用绝对一致性的组内相关系数（ICC）来估计基于 AAL 图谱的区域的连接的流线计数的会话内和会话间测试-重测可重复性。我们进一步评估了头线圈类型（12 通道与 32 通道）和重建重复次数（一次或聚合十次重复进行重建）的影响。析因分析表明，会话内的可重复性显著大于会话间的可重复性，并且通过聚合十次重建重复的流线计数，可重复性显著提高。使用高分辨率的头线圈仅会带来很小的有益效果。总体而言，ICC 值与连接的流线计数呈正相关。进一步的分析评估了不同选择变体（定义种子掩模的模糊与非模糊边界；选择终止于种子的流线与穿过种子的流线）的影响，结果表明使用模糊选择的基于终点的变体在可重复性和解剖学特异性之间提供了最佳的折衷。总之，通过重复估计和增加更多的流线来聚合定量指标是测试-重测可重复性的重要决定因素。如果考虑到这些因素，基于全局纤维追踪技术的流线计数提供了一种可重复性足够好的定量指标，可以用于评估健康和疾病状态下大脑的结构连接。
