Literature DB >> 31082471

Connectomes from streamlines tractography: Assigning streamlines to brain parcellations is not trivial but highly consequential.

Chun-Hung Yeh1, Robert E Smith2, Thijs Dhollander2, Fernando Calamante3, Alan Connelly3.   

Abstract

When using diffusion MRI streamlines tractograms to construct structural connectomes, ideally, each streamline should connect exactly 2 regions-of-interest (i.e. network nodes) as defined by a given brain parcellation scheme. However, the ill-posed nature of termination criteria in many tractography algorithms can cause streamlines apparently being associated with zero, one, or more than two grey matter (GM) nodes; streamlines that terminate in white matter or cerebrospinal fluid may even end up being assigned to nodes if the definitions of these nodes are not strictly constrained to genuine GM areas, resulting in a misleading connectome in non-trivial ways. Based on both in-house MRI data and state-of-the-art data provided by the Human Connectome Project, this study investigates the actual influence of streamline-to-node assignment methods, and their interactions with fibre-tracking terminations and brain parcellations, on the construction of pairwise regional connectivity and subsequent connectomic measures. Our results show that the frequency of generating successful pairwise connectivity is heavily affected by the convoluted interactions between the applied strategies for connectome construction, and that minor changes in the mechanism can cause significant variations in the within- and between-module connectivity strengths as well as in the commonly-used graph theory metrics. Our data suggest that these fundamental processes should not be overlooked in structural connectomics research, and that improved data quality is not in itself sufficient to solve the underlying problems associated with assigning streamlines to brain nodes. We demonstrate that the application of advanced fibre-tracking techniques that are designed to correct for inaccuracies of track terminations with respect to anatomical information at the fibre-tracking stage is advantageous to the subsequent connectome construction process, in which pairs of parcellation nodes can be more robustly identified from streamline terminations via a suitable assignment mechanism.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Brain parcellation; Connectomics; Diffusion MRI; Network metrics; Structural connectome; Tractography

Mesh:

Year:  2019        PMID: 31082471     DOI: 10.1016/j.neuroimage.2019.05.005

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  8 in total

1.  Deep white matter analysis (DeepWMA): Fast and consistent tractography segmentation.

Authors:  Fan Zhang; Suheyla Cetin Karayumak; Nico Hoffmann; Yogesh Rathi; Alexandra J Golby; Lauren J O'Donnell
Journal:  Med Image Anal       Date:  2020-06-24       Impact factor: 8.545

2.  Inner Hemispheric and Interhemispheric Connectivity Balance in the Human Brain.

Authors:  Ronnie Krupnik; Yossi Yovel; Yaniv Assaf
Journal:  J Neurosci       Date:  2021-08-31       Impact factor: 6.167

Review 3.  Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review.

Authors:  Fan Zhang; Alessandro Daducci; Yong He; Simona Schiavi; Caio Seguin; Robert E Smith; Chun-Hung Yeh; Tengda Zhao; Lauren J O'Donnell
Journal:  Neuroimage       Date:  2022-01-01       Impact factor: 7.400

4.  Simulated Attack Reveals How Lesions Affect Network Properties in Poststroke Aphasia.

Authors:  John D Medaglia; Brian A Erickson; Dorian Pustina; Apoorva S Kelkar; Andrew T DeMarco; J Vivian Dickens; Peter E Turkeltaub
Journal:  J Neurosci       Date:  2022-05-11       Impact factor: 6.709

5.  Hierarchical Complexity of the Macro-Scale Neonatal Brain.

Authors:  Manuel Blesa; Paola Galdi; Simon R Cox; Gemma Sullivan; David Q Stoye; Gillian J Lamb; Alan J Quigley; Michael J Thrippleton; Javier Escudero; Mark E Bastin; Keith M Smith; James P Boardman
Journal:  Cereb Cortex       Date:  2021-03-05       Impact factor: 5.357

6.  Structural Connectivity of Human Inferior Colliculus Subdivisions Using in vivo and post mortem Diffusion MRI Tractography.

Authors:  Kevin R Sitek; Evan Calabrese; G Allan Johnson; Satrajit S Ghosh; Bharath Chandrasekaran
Journal:  Front Neurosci       Date:  2022-03-22       Impact factor: 4.677

7.  Diffusion MRI tractography filtering techniques change the topology of structural connectomes.

Authors:  Matteo Frigo; Samuel Deslauriers-Gauthier; Drew Parker; Abdol Aziz Ould Ismail; Junghoon John Kim; Ragini Verma; Rachid Deriche
Journal:  J Neural Eng       Date:  2020-11-11       Impact factor: 5.379

Review 8.  The Seven Deadly Sins of Measuring Brain Structural Connectivity Using Diffusion MRI Streamlines Fibre-Tracking.

Authors:  Fernando Calamante
Journal:  Diagnostics (Basel)       Date:  2019-09-06
  8 in total

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