Improved tractography using asymmetric fibre orientation distributions
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), whe...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
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Elsevier
2017
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| Online Access: | https://eprints.nottingham.ac.uk/44034/ |
| _version_ | 1848796822131179520 |
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| author | Bastiani, Matteo Cottaar, Michiel Dikranian, Krikor Ghosh, Aurobrata Zhang, Hui Alexander, Daniel C. Behrens, Timothy E. Jbabdi, Saad Sotiropoulos, Stamatios N. |
| author_facet | Bastiani, Matteo Cottaar, Michiel Dikranian, Krikor Ghosh, Aurobrata Zhang, Hui Alexander, Daniel C. Behrens, Timothy E. Jbabdi, Saad Sotiropoulos, Stamatios N. |
| author_sort | Bastiani, Matteo |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T19:54:05Z |
| format | Article |
| id | nottingham-44034 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:54:05Z |
| publishDate | 2017 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-440342020-05-04T19:09:43Z https://eprints.nottingham.ac.uk/44034/ 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. 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. Elsevier 2017-09-30 Article PeerReviewed Bastiani, Matteo, Cottaar, Michiel, Dikranian, Krikor, Ghosh, Aurobrata, Zhang, Hui, Alexander, Daniel C., Behrens, Timothy E., Jbabdi, Saad and Sotiropoulos, Stamatios N. (2017) Improved tractography using asymmetric fibre orientation distributions. NeuroImage, 158 . pp. 205-218. ISSN 1095-9572 Diffusion MRI Tractography Structural connectivity Asymmetry Connectome https://doi.org/10.1016/j.neuroimage.2017.06.050 doi:10.1016/j.neuroimage.2017.06.050 doi:10.1016/j.neuroimage.2017.06.050 |
| spellingShingle | Diffusion MRI Tractography Structural connectivity Asymmetry Connectome Bastiani, Matteo Cottaar, Michiel Dikranian, Krikor Ghosh, Aurobrata Zhang, Hui Alexander, Daniel C. Behrens, Timothy E. Jbabdi, Saad Sotiropoulos, Stamatios N. Improved tractography using asymmetric fibre orientation distributions |
| title | Improved tractography using asymmetric fibre orientation distributions |
| title_full | Improved tractography using asymmetric fibre orientation distributions |
| title_fullStr | Improved tractography using asymmetric fibre orientation distributions |
| title_full_unstemmed | Improved tractography using asymmetric fibre orientation distributions |
| title_short | Improved tractography using asymmetric fibre orientation distributions |
| title_sort | improved tractography using asymmetric fibre orientation distributions |
| topic | Diffusion MRI Tractography Structural connectivity Asymmetry Connectome |
| url | https://eprints.nottingham.ac.uk/44034/ https://eprints.nottingham.ac.uk/44034/ https://eprints.nottingham.ac.uk/44034/ |