The Publication Database hosted by SPL
|
All Publications
Upload
Advanced Search
Gallery View
Download Statistics
Help
Import
Log in
Group Analysis of DTI Fiber Tract Statistics with Application to Neurodevelopment
|
|
Institution: |
Scientific Computing and Imaging Institute, School of Computing, University of Utah, Salt Lake City, Utah 84112, USA. gcasey@sci.utah.edu |
Publisher: |
Neuroimage |
Publication Date: |
Mar-2009 |
Volume Number: |
45 |
Issue Number: |
1 Suppl |
Pages: |
S133-S142 |
Citation: |
Neuroimage. 2009 Mar;45(1 Suppl):S133-42. |
PubMed ID: |
19059345 |
PMCID: |
PMC2727755 |
Keywords: |
DTIPopulationAnalysis |
Appears in Collections: |
NA-MIC |
Sponsors: |
HD053000 (HD) funded by NICHD NIH HHS MH064065 (MH) funded by NIMH NIH HHS U54 EB005149 (EB) funded by NIBIB NIH HHS |
Generated Citation: |
Goodlett C., Fletcher P.T., Gilmore J.H., Gerig G. Group Analysis of DTI Fiber Tract Statistics with Application to Neurodevelopment. Neuroimage. 2009 Mar;45(1 Suppl):S133-42. PMID: 19059345. PMCID: PMC2727755. |
| Downloaded: | 542 times. [view map] |
| Paper: | Download, View online |
| Export citation: |
Diffusion tensor imaging (DTI) provides a unique source of information about the underlying tissue structure of brain white matter in vivo including both the geometry of major fiber bundles as well as quantitative information about tissue properties represented by derived tensor measures. This paper presents a method for statistical comparison of fiber bundle diffusion properties between populations of diffusion tensor images. Unbiased diffeomorphic atlas building is used to compute a normalized coordinate system for populations of diffusion images. The diffeomorphic transformations between each subject and the atlas provide spatial normalization for the comparison of tract statistics. Diffusion properties, such as fractional anisotropy (FA) and tensor norm, along fiber tracts are modeled as multivariate functions of arc length. Hypothesis testing is performed non-parametrically using permutation testing based on the Hotelling T(2) statistic. The linear discriminant embedded in the T(2) metric provides an intuitive, localized interpretation of detected differences. The proposed methodology was tested on two clinical studies of neurodevelopment. In a study of 1 and 2 year old subjects, a significant increase in FA and a correlated decrease in Frobenius norm was found in several tracts. Significant differences in neonates were found in the splenium tract between controls and subjects with isolated mild ventriculomegaly (MVM) demonstrating the potential of this method for clinical studies.
Additional Material
1 File (46.017kB)
Goodlett-Neuroimage2009-fig5.jpg (46.017kB)