The biophysics of crossing fibers
Abstract
Crossing fibers are increasingly acknowledged to be a significant problem, affecting both tractography and tensor-derived measures of anisotropy. Moreover, typical human scans have been shown to contain a significant proportion of voxels with crossing fibers. Thankfully, there is information in the diffusion-weighted signal that can be used to resolve these crossing fibers. This chapter examines the general biophysical considerations relevant to the crossing fiber problem and describes a number of algorithms that have recently been proposed to estimate fiber orientations. It introduces a classification of these algorithms based on their conceptual framework, along with a brief description of their distinctive features where relevant. DWI acquisition requirements are different for resolving crossing fibers than for diffusion tensor imaging, generally requiring higher b-values and a larger number of directions, depending on the algorithm used. Crossing fibers have a profound impact on scalar measures of white matter “integrity” (e.g.m anisotropy), and make it extremely difficult, if not impossible, to obtain scalar markers of white matter status that are truly independent of crossing fibers.
Integrity signals
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Tract-crossing fibers can affect clustering measures, thus discouraging the use of TFCE corrections.
“Moreover, tract-crossing fibers (Tournier, 2010) can affect clustering measures, thus discouraging the use of TFCE corrections.”
From Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference (2023) · cites this paper as Tournier, 2010
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MRtrix: Diffusion tractography in crossing fiber regions
Tournier, J., Calamante, F., & Connelly, A. (2012) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22005 · Cited by 1,370 · see citing works
Self-citationLimits to anatomical accuracy of diffusion tractography using modern approaches
Schilling, K. G., Nath, V., Hansen, C., Parvathaneni, P., Blaber, J., Gao, Y., Neher, P., Aydogan, D. B., Shi, Y., Ocampo-Pineda, M., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.10.029 · Cited by 260 · see citing works
Can increased spatial resolution solve the crossing fiber problem for diffusion MRI?
Schilling, K., Gao, Y., Janve, V., Stepniewska, I., Landman, B. A., & Anderson, A. W. (2017) · NMR in Biomedicine · doi:10.1002/nbm.3787 · Cited by 102 · see citing works
Working Memory Training Effects on White Matter Integrity in Young and Older Adults
Dziemian, S., Appenzeller, S., von Bastian, C. C., Jäncke, L., & Langer, N. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.605213 · Cited by 26 · see citing works
Gonzalez-Gomez, R., Ibañez, A., & Moguilner, S. (2023) · Network Neuroscience · doi:10.1162/netn_a_00285 · Cited by 10 · see citing works
- Authors
- Tournier, J.-D.
- Corresponding author
- Tournier, Jacques-Donald
- Venue
- Diffusion MRI
- Publisher
- Oxford University Press
- Published
- 2010-11
- Pages
- 465-482
- OpenAlex
- W4255309917
- Cited by
- 16
- References
- 0
- Citations by year
- 2026: 2 · 2025: 1 · 2023: 2 · 2022: 2 · 2021: 3 · 2020: 1 · 2018: 1 · 2017: 1 · 2016: 1 · 2015: 1 · 2012: 1
- FWCI
- 1.47
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Oxford University Press eBooks (publishedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- crossing fibers, fiber orientation estimation, diffusion-weighted imaging, tractography, anisotropy parameter, white matter integrity, b-value, diffusion tensor imaging
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