Improved tractography using asymmetric fibre orientation distributions

Bastiani, Matteo and Cottaar, Michiel and Dikranian, Krikor and Ghosh, Aurobrata and Zhang, Hui and Alexander, Daniel C. and Behrens, Timothy E. and Jbabdi, Saad and Sotiropoulos, Stamatios N. (2017) Improved tractography using asymmetric fibre orientation distributions. NeuroImage, 158 . pp. 205-218. ISSN 1095-9572

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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.

Item Type: Article
Keywords: Diffusion MRI, Tractography, Structural connectivity, Asymmetry, Connectome
Schools/Departments: University of Nottingham, UK > Faculty of Medicine and Health Sciences > School of Medicine > Division of Clinical Neuroscience
Identification Number: 10.1016/j.neuroimage.2017.06.050
Depositing User: Eprints, Support
Date Deposited: 06 Jul 2017 13:15
Last Modified: 12 Oct 2017 23:49
URI: http://eprints.nottingham.ac.uk/id/eprint/44034

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