Matteo Bastiani
Improved tractography using asymmetric fibre orientation distributions
Bastiani, Matteo; Cottaar, Michiel; Dikranian, Krikor; Ghosh, Aurobrata; Zhang, Hui; Alexander, Daniel C.; Behrens, Timothy E.; Jbabdi, Saad; Sotiropoulos, Stamatios N.
Authors
Michiel Cottaar
Krikor Dikranian
Aurobrata Ghosh
Hui Zhang
Daniel C. Alexander
Timothy E. Behrens
Saad Jbabdi
Professor STAMATIOS SOTIROPOULOS STAMATIOS.SOTIROPOULOS@NOTTINGHAM.AC.UK
PROFESSOR OF COMPUTATIONAL NEUROIMAGING
Abstract
Diffusion MRI allows us to make inferences on the structural organisation of the brain by mapping water diffusion to white matter microstructure. However, such a mapping is generally ill-defined; for instance, diffusion measurements are antipodally symmetric (diffusion along x and –x are equal), whereas the distribution of fibre orientations within a voxel is generally not symmetric. Therefore, different sub-voxel patterns such as crossing, fanning, or sharp bending, cannot be distinguished by fitting a voxel-wise model to the signal. However, asymmetric fibre patterns can potentially be distinguished once spatial information from neighbouring voxels is taken into account. We propose a neighbourhood-constrained spherical deconvolution approach that is capable of inferring asymmetric fibre orientation distributions (A-fods). Importantly, we further design and implement a tractography algorithm that utilises the estimated A-fods, since the commonly used streamline tractography paradigm cannot directly take advantage of the new information. We assess performance using ultra-high resolution histology data where we can compare true orientation distributions against sub-voxel fibre patterns estimated from down-sampled data. Finally, we explore the benefits of A-fods-based tractography using in vivo data by evaluating agreement of tractography predictions with connectivity estimates made using different in-vivo modalities. The proposed approach can reliably estimate complex fibre patterns such as sharp bending and fanning, which voxel-wise approaches cannot estimate. Moreover, histology-based and in-vivo results show that the new framework allows more accurate tractography and reconstruction of maps quantifying (symmetric and asymmetric) fibre complexity.
Citation
Bastiani, M., Cottaar, M., Dikranian, K., Ghosh, A., Zhang, H., Alexander, D. C., Behrens, T. E., Jbabdi, S., & Sotiropoulos, S. N. (2017). Improved tractography using asymmetric fibre orientation distributions. NeuroImage, 158, https://doi.org/10.1016/j.neuroimage.2017.06.050
Journal Article Type | Article |
---|---|
Acceptance Date | Jun 21, 2017 |
Online Publication Date | Jun 29, 2017 |
Publication Date | Sep 30, 2017 |
Deposit Date | Jul 6, 2017 |
Publicly Available Date | Jul 6, 2017 |
Journal | NeuroImage |
Print ISSN | 1053-8119 |
Electronic ISSN | 1095-9572 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 158 |
DOI | https://doi.org/10.1016/j.neuroimage.2017.06.050 |
Keywords | Diffusion MRI, Tractography, Structural connectivity, Asymmetry, Connectome |
Public URL | https://nottingham-repository.worktribe.com/output/885520 |
Publisher URL | https://doi.org/10.1016/j.neuroimage.2017.06.050 |
Contract Date | Jul 6, 2017 |
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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0
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