Track-weighted imaging methods: extracting information from a streamlines tractogram

Review Article

Abstract

A whole-brain streamlines data-set (so-called tractogram) generated from diffusion MRI provides a wealth of information regarding structural connectivity in the brain. Besides visualisation strategies, a number of post-processing approaches have been proposed to extract more detailed information from the tractogram. One such approach is based on exploiting the information contained in the tractogram to generate track-weighted (TW) images. In the track-weighted imaging (TWI) approach, a very large number of streamlines are often generated throughout the brain, and an image is then computed based on properties of the streamlines themselves (e.g. based on the number of streamlines in each voxel, or their average length), or based on the values of an associated image (e.g. a diffusion anisotropy map, a T2 map) measured at the coordinates of the streamlines. This review article describes various approaches used to generate TW images and discusses the flexible formalism that TWI provides to generate a range of images with very different contrast, as well as the super-resolution properties of the resulting images. It also explains how this approach provides a powerful means to study structural and functional connectivity simultaneously. Finally, a number of key issues for its practical implementation are discussed.

Keywords

Fibre-tracking Tractogram Super-resolution Connectivity Tractography 

Notes

Acknowledgements

We are grateful to the many colleagues and collaborators involved in the track-weighted imaging work, and in particular to Alan Connelly, Jacques-Donald Tournier, and Robert E. Smith for their extensive contribution to developing these methods. We are also grateful to Chun-Hung Yeh and Donna Parker for help in producing figures for this work. We thank the National Health and Medical Research Council (NHMRC) of Australia, the Australian Research Council (ARC), and the Victorian Government’s Operational Infrastructure Support Grant for their support.

Compliance with ethical standards

Conflict of interest

FC is co-inventor in a patent application on the TDI method.

Funding

This study was funded by the National Health and Medical Research Council (NHMRC) of Australia, the Australian Research Council (ARC), and the Victorian Government’s Operational Infrastructure Support Grant.

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Copyright information

© ESMRMB 2017

Authors and Affiliations

  1. 1.Florey Institute of Neuroscience and Mental HealthMelbourne Brain CentreHeidelbergAustralia
  2. 2.Florey Department of Neuroscience and Mental HealthUniversity of MelbourneMelbourneAustralia
  3. 3.Department of Medicine, Austin Health and Northern HealthUniversity of MelbourneMelbourneAustralia

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