期刊
NEUROIMAGE
卷 45, 期 1, 页码 S133-S142出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2008.10.060
关键词
Diffusion tensor imaging; Registration; Tract modeling; Neurodevelopment; Statistical modeling
资金
- NIBIB NIH HHS [U54 EB005149-010004, U54 EB005149] Funding Source: Medline
- NICHD NIH HHS [R01 HD053000, R01 HD053000-01A1, HD053000] Funding Source: Medline
- NIMH NIH HHS [P50 MH064065, MH064065] Funding Source: Medline
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. (C) 2008 Elsevier Inc. All rights reserved.
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