Along-tract statistics allow for enhanced tractography analysis

Diffusion imaging tractography is a valuable tool for neuroscience researchers because it allows the generation of individualized virtual dissections of major white matter tracts in the human brain. It facilitates between-subject statistical analyses tailored to the specific anatomy of each particip...

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Vydáno v:NeuroImage (Orlando, Fla.) Ročník 59; číslo 4; s. 3227 - 3242
Hlavní autoři: Colby, John B., Soderberg, Lindsay, Lebel, Catherine, Dinov, Ivo D., Thompson, Paul M., Sowell, Elizabeth R.
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Elsevier Inc 15.02.2012
Elsevier Limited
Témata:
Adolescent
Alcohol
Along-tract
Anisotropy
Attention deficit hyperactivity disorder
B-spline
Brain Mapping - methods
Diffusion imaging
Dissection
FASD
Female
Fetal Alcohol Spectrum Disorders - diagnosis
Functional Neuroimaging - methods
Humans
Image Enhancement - methods
Male
NMR
Nuclear magnetic resonance
Statistics
Studies
Tractography
White matter
Diffusion imaging
Along-tract
FASD
B-spline
White matter
Tractography
ISSN:1053-8119, 1095-9572, 1095-9572
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Shrnutí:Diffusion imaging tractography is a valuable tool for neuroscience researchers because it allows the generation of individualized virtual dissections of major white matter tracts in the human brain. It facilitates between-subject statistical analyses tailored to the specific anatomy of each participant. There is prominent variation in diffusion imaging metrics (e.g., fractional anisotropy, FA) within tracts, but most tractography studies use a “tract-averaged” approach to analysis by averaging the scalar values from the many streamline vertices in a tract dissection into a single point-spread estimate for each tract. Here we describe a complete workflow needed to conduct an along-tract analysis of white matter streamline tract groups. This consists of 1) A flexible MATLAB toolkit for generating along-tract data based on B-spline resampling and compilation of scalar data at different collections of vertices along the curving tract spines, and 2) Statistical analysis and rich data visualization by leveraging tools available through the R platform for statistical computing. We demonstrate the effectiveness of such an along-tract approach over the tract-averaged approach in an example analysis of 10 major white matter tracts in a single subject. We also show that these techniques easily extend to between-group analyses typically used in neuroscience applications, by conducting an along-tract analysis of differences in FA between 9 individuals with fetal alcohol spectrum disorders (FASDs) and 11 typically-developing controls. This analysis reveals localized differences between FASD and control groups that were not apparent using a tract-averaged method. Finally, to validate our approach and highlight the strength of this extensible software framework, we implement 2 other methods from the literature and leverage the existing workflow tools to conduct a comparison study. [Display omitted]
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ISSN:1053-8119
1095-9572
1095-9572
DOI:10.1016/j.neuroimage.2011.11.004