Litcius/Paper detail

Mapping Structural Connectivity Using Diffusion <scp>MRI</scp>: Challenges and Opportunities

Chun‐Hung Yeh, Derek K. Jones, Xiaoyun Liang, Maxime Descoteaux, Alan Connelly

2020Journal of Magnetic Resonance Imaging199 citationsDOIOpen Access PDF

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.

Topics & Concepts

ConnectomeTractographyDiffusion MRIComputer scienceConnectomicsHuman Connectome ProjectGraph theoryGraphArtificial intelligenceData scienceComplex networkMachine learningNeuroscienceFunctional connectivityTheoretical computer sciencePsychologyMagnetic resonance imagingMathematicsMedicineWorld Wide WebRadiologyCombinatoricsAdvanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity StudiesAdvanced MRI Techniques and Applications