Tract-based morphometry for white matter group analysis
Open accessAbstract
We introduce an automatic method that we call tract-based morphometry, or TBM, for measurement and analysis of diffusion MRI data along white matter fiber tracts. Using subject-specific tractography bundle segmentations, we generate an arc length parameterization of the bundle with point correspondences across all fibers and all subjects, allowing tract-based measurement and analysis. In this paper we present a quantitative comparison of fiber coordinate systems from the literature and we introduce an improved optimal match method that reduces spatial distortion and improves intra- and inter-subject variability of FA measurements. We propose a method for generating arc length correspondences across hemispheres, enabling a TBM study of interhemispheric diffusion asymmetries in the arcuate fasciculus (AF) and cingulum bundle (CB). The results of this study demonstrate that TBM can detect differences that may not be found by measuring means of scalar invariants in entire tracts, such as the mean diffusivity (MD) differences found in AF. We report TBM results of higher fractional anisotropy (FA) in the left hemisphere in AF (caused primarily by lower lambda(3), the smallest eigenvalue of the diffusion tensor, in the left AF), and higher left hemisphere FA in CB (related to higher lambda(1), the largest eigenvalue of the diffusion tensor, in the left CB). By mapping the significance levels onto the tractography trajectories for each structure, we demonstrate the anatomical locations of the interhemispheric differences. The TBM approach brings analysis of DTI data into the clinically and neuroanatomically relevant framework of the tract anatomy.
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Many methods perform along-tract analysis to investigate the distribution of microstructural measures along the fiber pathway.
“Instead of using a single scalar value to summarize the entire pathway, many methods perform along-tract analysis to investigate the distribution of the microstructural measures along the fiber pathway (variously called “tractometry,” “profilometry,” and “tract-based morphometry”) (Bells et al., 2011b; O’Donnell et al., 2009; Yeatman et al., 2012).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as O’Donnell et al., 2009
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References 39 · Cited by 186
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- Authors
- O'Donnell, L. J., Westin, C.-F., & Golby, A. J.
- Affiliations
- Brigham and Women's Hospital (US)
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2009-04
- Volume
- 45
- Issue
- 3
- Pages
- 832-844
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2768362
- OpenAlex
- W2037050487
- Cited by
- 186
- References
- 39
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 6 · 2023: 2 · 2022: 11 · 2021: 5 · 2020: 10 · 2019: 12 · 2018: 13 · 2017: 14 · 2016: 14 · 2015: 14 · 2014: 12 · 2013: 13 · 2012: 14
- FWCI
- 10.27
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (R01AG020012, R01-AG20012)
- National Institute of Mental Health (R01MH074794)
- National Cancer Institute (R25CA089017)
- National Institute of Neurological Disorders and Stroke (K08NS048063)
- National Institute of Biomedical Imaging and Bioengineering (U54EB005149)
- National Center for Research Resources (P41RR15241, P41RR015241, U41RR019703, P41RR013218, P41 RR13218)
- 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
- white matter tracts, diffusion MRI, arc length parameterization, optimal matching, fractional anisotropy, hemispheric lateralization, arcuate fasciculus, cingulum, group analysis
- MeSH terms
- Brain, Brain Mapping, Humans, Image Processing, Computer-Assisted, Diffusion Magnetic Resonance Imaging
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