Diffusion MRI tractography filtering techniques change the topology of structural connectomes.
Diffusion MRI tractography filtering techniques change the topology of structural connectomes.
复制标题
扩散 MRI 纤维束成像过滤技术改变了结构连接体的拓扑结构。
DOI：
10.1088/1741-2552/abc29b
复制
发表时间：
2020-11-11
影响因子：
4
通讯作者：
Deriche R
中科院分区：
文献类型：
--
作者：
Frigo M;Deslauriers-Gauthier S;Parker D;Aziz Ould Ismail A;John Kim J;Verma R;Deriche R
使用非侵入性技术来估计结构性大脑网络（即连接体）为大规模研究大脑的功能和结构打开了大门，揭示了神经系统疾病和大脑网络拓扑变化之间的联系。本研究旨在评估使用扩散 MRI 无创估计的结构连接体的拓扑结构是否以及如何受到在结构连接体管道中使用纤维束成像过滤技术的影响。此外，这项工作还研究了过滤连接组的拓扑描述符对基于密度的阈值处理的常见做法的鲁棒性。我们研究了通过对纤维束图进行球形反卷积通知过滤并使用微结构通知纤维束成像的凸优化模型获得的过滤连接组的全局效率、特征路径长度、模块化和聚类系数的变化。该分析对健康受试者和受创伤性脑损伤影响的患者进行，并评估计算的图论测量相对于基于密度的连接组阈值的鲁棒性。我们的结果表明，纤维束成像过滤技术改变了大脑网络的拓扑结构，从而改变了病理和健康病例中的网络指标。此外，这些措施被证明对基于密度的阈值处理具有鲁棒性。目前的工作强调了如何将纤维束成像过滤技术纳入连接组管道中需要格外小心，因为它们系统地改变了健康受试者和受创伤性脑损伤影响的患者的网络拓扑。最后，证实基于低到中等密度的连接体阈值的实践对拓扑分析的影响可以忽略不计。
The use of non-invasive techniques for the estimation of structural brain networks (i.e. connectomes) opened the door to large-scale investigations on the functioning and the architecture of the brain, unveiling the link between neurological disorders and topological changes of the brain network. This study aims at assessing if and how the topology of structural connectomes estimated non-invasively with diffusion MRI is affected by the employment of tractography filtering techniques in structural connectomic pipelines. Additionally, this work investigates the robustness of topological descriptors of filtered connectomes to the common practice of density-based thresholding. We investigate the changes in global efficiency, characteristic path length, modularity and clustering coefficient on filtered connectomes obtained with the spherical deconvolution informed filtering of tractograms and using the convex optimization modelling for microstructure informed tractography. The analysis is performed on both healthy subjects and patients affected by traumatic brain injury and with an assessment of the robustness of the computed graph-theoretical measures with respect to density-based thresholding of the connectome. Our results demonstrate that tractography filtering techniques change the topology of brain networks, and thus alter network metrics both in the pathological and the healthy cases. Moreover, the measures are shown to be robust to density-based thresholding. The present work highlights how the inclusion of tractography filtering techniques in connectomic pipelines requires extra caution as they systematically change the network topology both in healthy subjects and patients affected by traumatic brain injury. Finally, the practice of low-tomoderate density-based thresholding of the connectomes is confirmed to have negligible effects on the topological analysis.