| Literature DB >> 32557893 |
Chun-Hung Yeh1,2,3,4, Derek K Jones5,6, Xiaoyun Liang3,4,6, Maxime Descoteaux7, Alan Connelly3,4.
Abstract
Diffusion MRI-based tractography is the most commonly-used technique when inferring the structural brain connectome, i.e., the comprehensive map of the connections in the brain. The utility of graph theory-a powerful mathematical approach for modeling complex network systems-for analyzing tractography-based connectomes brings important opportunities to interrogate connectome data, providing novel insights into the connectivity patterns and topological characteristics of brain structural networks. When applying this framework, however, there are challenges, particularly regarding methodological and biological plausibility. This article describes the challenges surrounding quantitative tractography and potential solutions. In addition, challenges related to the calculation of global network metrics based on graph theory are discussed.Evidence Level: 5Technical Efficacy: Stage 1.Keywords: connectomics; diffusion MRI; graph theoretical analysis; network metrics; structural connectome; tractography
Mesh:
Year: 2020 PMID: 32557893 DOI: 10.1002/jmri.27188
Source DB: PubMed Journal: J Magn Reson Imaging ISSN: 1053-1807 Impact factor: 4.813