The optimal trackability threshold of fractional anisotropy for diffusion tensor tractography of the corticospinal tract
Open accessAbstract
PURPOSE: In order to ensure that three-dimensional diffusion tensor tractography (3D-DTT) of the corticospinal tract (CST), is performed accurately and efficiently, we set out to find the optimal lower threshold of fractional anisotropy (FA) below which tract elongation is terminated (trackability threshold). METHODS: Thirteen patients with acute or early subacute ischemic stroke causing motor deficits were enrolled in this study. We performed 3D-DTT of the CST with diffusion tensor MR (magnetic resonance) imaging. We segmented the CST and established a cross-section of the CST in a transaxial plane as a region of interest. Thus, we selectively measured the FA values of the right and left corticospinal tracts at the level of the cerebral peduncle, the posterior limb of the internal capsule, and the centrum semiovale. The FA values of the CST were also measured on the affected side at the level where the clinically relevant infarction was present in isotropic diffusion-weighted imaging. RESULTS: 3D-DTT allowed us to selectively measure the FA values of the CST. Among the 267 regions of interest we measured, the minimum FA value was 0.22. The FA values of the CST were smaller and more variable in the centrum semiovale than in the other regions. The mean minus twice the standard deviation of the FA values of the CST in the centrum semiovale was calculated at 0.22 on the normal unaffected side and 0.16 on the affected side. CONCLUSION: An FA value of about 0.20 was found to be the optimal trackability threshold.
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Sampling of microstructural measures along fiber pathways can be done by generating a binary mask of voxels through which streamlines pass and sampling within this mask, or by sampling at each point of the streamlines from a pre-calculated microstructure image.
“This sampling may be done by first generating a binary mask that defines the voxels through which streamlines pass and then sampling from an underlying microstructure image within this mask (Ciccarelli et al., 2003; Heiervang et al., 2006; Kunimatsu et al., 2004; Voineskos et al., 2010). The sampling may alternatively be done by sampling microstructural measures at each point of the streamlines”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Kunimatsu et al., 2004
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- Conturo TE, Lori NF, Cull TS, et al. Tracking neuronal ˆber pathways in the living human brain. Proc Natl Acad Sci USA 1999; 96:10422-10427.
- Kunimatsu A, Aoki S, Masutani Y, Abe O, Mori H, Ohtomo K. Three-dimensional white matter tractography by diŠusion tensor imaging in ische- mic stroke involving the corticospinal tract. Neu- roradiology 2003; 45:532-535.
- Yamada K, Kizu O, Mori S, et al. Brain ˆber tracking with clinically feasible diŠusion-tensor MR imaging: initial experience. Radiology 2003; 227:295-301.
- Yamada K, Mori S, Nakamura H, et al. Fiber- tracking method reveals sensorimotor pathway involvement in stroke patients. Stroke 2003; 34:E159-162.
- Mori S, Frederiksen K, van Zijl PC, et al. Brain white matter anatomy of tumor patients evaluated with diŠusion tensor imaging. Ann Neurol 2002; 51:377-380.
- Basser PJ, Pierpaoli C. Microstructural and physiological features of tissues elucidated by quantitative-diŠusion-tensor MRI. J Magn Reson B 1996; 111:209-219.
- Jezzard P, Barnett AS, Pierpaoli C. Charac- terizaion of and correction for eddy current arti- facts in echo planar diŠusion imaging. Magn Reson Med 1998; 39:801-812.
- Masutani Y, Aoki S, Abe O, Hayashi N, Otomo K. MR diŠusion tensor imaging: recent advance and new techniques for diŠusion tensor visualization. Eur J Radiol 2003; 46:53-66.
- VOLUME-ONE developers group. VOLUME- ONE. Available at: http://www.volume-one.org W 10. Iwasaki S, Nakagawa H, Fukusumi A, et al. Identiˆcation of pre-and postcentral gyri on CT and MR images on the basis of the medullary pattern of cerebral white matter. Radiology 1991; 179:207-213.
- Wiegell MR, Larsson HB, Wedeen VJ. Fiber crossing in human brain depicted with diŠusion tensor MR imaging. Radiology 2000; 217:897-903.
- Armitage P, Berry G, Matthews JNS. The normal (or Gaussian) distribution, In: Statistical methods in medical research. 4th edition. Williston: Black- well Sciences, 2002; 76-83.
- Abe O, Aoki S, Hayashi N, et al. Normal aging in the central nervous system: quantitative MR diŠusion-tensor analysis. Neurobiol Aging 2002; 23:433-441.
- Sorensen AG, Wu O, Copen WA, et al. Human acute cerebral ischemia: detection of changes in water diŠusion anisotropy by using MR imaging. Radiology 1999; 212:785-792.
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- Authors
- KUNIMATSU, A., AOKI, S., MASUTANI, Y., ABE, O., HAYASHI, N., MORI, H., MASUMOTO, T., & OHTOMO, K.
- Affiliations
- The University of Tokyo (JP)
- ORCID
- Venue
- Magnetic Resonance in Medical Sciences
- Published
- 2004
- Volume
- 3
- Issue
- 1
- Pages
- 11-17
- ISSN
- 1347-3182 (ISSN-L)
- 1880-2206
- OpenAlex
- W2022781987
- Cited by
- 245
- References
- 0
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 5 · 2023: 5 · 2022: 17 · 2021: 12 · 2020: 8 · 2019: 10 · 2018: 10 · 2017: 15 · 2016: 19 · 2015: 13 · 2014: 22 · 2013: 17 · 2012: 12
- FWCI
- 5.37
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Magnetic Resonance in Medical Sciences (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- corticospinal tract, fractional anisotropy, diffusion tensor tractography, ischemic stroke, motor impairment, cerebral peduncle, centrum semiovale, internal capsule, diffusion-weighted imaging
- MeSH terms
- Aged, Female, Humans, Male, Middle Aged, Pyramidal Tracts, Anisotropy, Stroke, Imaging, Three-Dimensional, Diffusion Magnetic Resonance Imaging
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