Tract Profiles of White Matter Properties: Automating Fiber-Tract Quantification

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Abstract

Tractography based on diffusion weighted imaging (DWI) data is a method for identifying the major white matter fascicles (tracts) in the living human brain. The health of these tracts is an important factor underlying many cognitive and neurological disorders. In vivo, tissue properties may vary systematically along each tract for several reasons: different populations of axons enter and exit the tract, and disease can strike at local positions within the tract. Hence quantifying and understanding diffusion measures along each fiber tract (Tract Profile) may reveal new insights into white matter development, function, and disease that are not obvious from mean measures of that tract. We demonstrate several novel findings related to Tract Profiles in the brains of typically developing children and children at risk for white matter injury secondary to preterm birth. First, fractional anisotropy (FA) values vary substantially within a tract but the Tract FA Profile is consistent across subjects. Thus, Tract Profiles contain far more information than mean diffusion measures. Second, developmental changes in FA occur at specific positions within the Tract Profile, rather than along the entire tract. Third, Tract Profiles can be used to compare white matter properties of individual patients to standardized Tract Profiles of a healthy population to elucidate unique features of that patient's clinical condition. Fourth, Tract Profiles can be used to evaluate the association between white matter properties and behavioral outcomes. Specifically, in the preterm group reading ability is positively correlated with FA measured at specific locations on the left arcuate and left superior longitudinal fasciculus and the magnitude of the correlation varies significantly along the Tract Profiles. We introduce open source software for automated fiber-tract quantification (AFQ) that measures Tract Profiles of MRI parameters for 18 white matter tracts. With further validation, AFQ Tract Profiles have potential for informing clinical management and decision-making.

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Microstructural maturation of the human brain from childhood to adulthood.

C. Lebel, L. Walker, A Leemans … (2008)

Brain maturation is a complex process that continues well beyond infancy, and adolescence is thought to be a key period of brain rewiring. To assess structural brain maturation from childhood to adulthood, we charted brain development in subjects aged 5 to 30 years using diffusion tensor magnetic resonance imaging, a novel brain imaging technique that is sensitive to axonal packing and myelination and is particularly adept at virtually extracting white matter connections. Age-related changes were seen in major white matter tracts, deep gray matter, and subcortical white matter, in our large (n=202), age-distributed sample. These diffusion changes followed an exponential pattern of maturation with considerable regional variation. Differences observed in developmental timing suggest a pattern of maturation in which areas with fronto-temporal connections develop more slowly than other regions. These in vivo results expand upon previous postmortem and imaging studies and provide quantitative measures indicative of the progression and magnitude of regional human brain maturation.

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Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers.

V J Wedeen, R. -P. Wang, J Schmahmann … (2008)

MRI tractography is the mapping of neural fiber pathways based on diffusion MRI of tissue diffusion anisotropy. Tractography based on diffusion tensor imaging (DTI) cannot directly image multiple fiber orientations within a single voxel. To address this limitation, diffusion spectrum MRI (DSI) and related methods were developed to image complex distributions of intravoxel fiber orientation. Here we demonstrate that tractography based on DSI has the capacity to image crossing fibers in neural tissue. DSI was performed in formalin-fixed brains of adult macaque and in the brains of healthy human subjects. Fiber tract solutions were constructed by a streamline procedure, following directions of maximum diffusion at every point, and analyzed in an interactive visualization environment (TrackVis). We report that DSI tractography accurately shows the known anatomic fiber crossings in optic chiasm, centrum semiovale, and brainstem; fiber intersections in gray matter, including cerebellar folia and the caudate nucleus; and radial fiber architecture in cerebral cortex. In contrast, none of these examples of fiber crossing and complex structure was identified by DTI analysis of the same data sets. These findings indicate that DSI tractography is able to image crossing fibers in neural tissue, an essential step toward non-invasive imaging of connectional neuroanatomy.

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Resolving crossing fibres using constrained spherical deconvolution: validation using diffusion-weighted imaging phantom data.

J-Donald Tournier, Chun-Hung Yeh, Fernando Calamante … (2008)

Diffusion-weighted imaging can potentially be used to infer the connectivity of the human brain in vivo using fibre-tracking techniques, and is therefore of great interest to neuroscientists and clinicians. A key requirement for fibre tracking is the accurate estimation of white matter fibre orientations within each imaging voxel. The diffusion tensor model, which is widely used for this purpose, has been shown to be inadequate in crossing fibre regions. A number of approaches have recently been proposed to address this issue, based on high angular resolution diffusion-weighted imaging (HARDI) data. In this study, an experimental model of crossing fibres, consisting of water-filled plastic capillaries, is used to thoroughly assess three such techniques: constrained spherical deconvolution (CSD), super-resolved CSD (super-CSD) and Q-ball imaging (QBI). HARDI data were acquired over a range of crossing angles and b-values, from which fibre orientations were computed using each technique. All techniques were capable of resolving the two fibre populations down to a crossing angle of 45 degrees , and down to 30 degrees for super-CSD. A bias was observed in the fibre orientations estimated by QBI for crossing angles other than 90 degrees, consistent with previous simulation results. Finally, for a 45 degrees crossing, the minimum b-value required to resolve the fibre orientations was 4000 s/mm(2) for QBI, 2000 s/mm(2) for CSD, and 1000 s/mm(2) for super-CSD. The quality of estimation of fibre orientations may profoundly affect fibre tracking attempts, and the results presented provide important additional information regarding performance characteristics of well-known methods.

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Author and article information

Contributors

Christian Beaulieu: Role: Editor

Journal

Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS ONE

Journal ID (publisher-id): plos

Journal ID (pmc): plosone

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, USA )

ISSN (Electronic): 1932-6203

Publication date Collection: 2012

Publication date (Electronic): 14 November 2012

Volume: 7

Issue: 11

Electronic Location Identifier: e49790

Affiliations

[1 ]Department of Psychology, Stanford University, Stanford, California, United States of America

[2 ]Stanford Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, California, United States of America

[3 ]Stanford University School of Medicine, Stanford, California, United States of America

[4 ]Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America

University of Alberta, Canada

Author notes

* E-mail: jyeatman@ 123456stanford.edu

Competing Interests: The authors have declared that no competing interests exist.

Conceived and designed the experiments: JDY RFD HMF BAW. Performed the experiments: JDY NJM. Analyzed the data: JDY RFD NJM HMF BAW. Contributed reagents/materials/analysis tools: JDY RFD BAW. Wrote the paper: JDY BAW HMF.

Article

Publisher ID: PONE-D-12-15285

DOI: 10.1371/journal.pone.0049790

PMC ID: 3498174

PubMed ID: 23166771

SO-VID: a05293cd-7126-4d27-b228-3193b3b5eb7e

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 29 May 2012

Date accepted : 17 October 2012

Page count

Pages: 15

Funding

This study was supported by grant RO1-HD46500 from the National Institutes of Health to Heidi M. Feldman, RO1-EY15000 to Brian A. Wandell, National Science Foundation Graduate Research Fellowship to Jason D. Yeatman, Stanford Medical Scholars Research Program Fellowship to Nathaniel J. Myall, and in part by the Clinical and Translational Science Award 1UL1 RR025744 for the Stanford Center for Clinical and Translational Education and Research (Spectrum) from the National Center for Research Resources, National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Tract Profiles of White Matter Properties: Automating Fiber-Tract Quantification

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Abstract

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Most cited references 33

Microstructural maturation of the human brain from childhood to adulthood.

Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers.

Resolving crossing fibres using constrained spherical deconvolution: validation using diffusion-weighted imaging phantom data.

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