
Proceedings Paper
Mapping longitudinal cerebral cortex development using diffusion tensor imagingFormat | Member Price | Non-Member Price |
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Paper Abstract
Diffusion tensor imaging (DTI) could provide convenient and crucial insights into the underlying age-related biological
maturation of human brains, including myelination, axonal density changes, fiber tract reorganization, and synaptic
pruning processes. Fractional anisotropy (FA) derived from DTI has been commonly used to characterize cellular
morphological changes associated with the development of human brain, due to its sensitivity to microstructural
changes. In this paper, we aim to discern the longitudinal neurodevelopmental patterns in typically maturing human
brains using 200 healthy subjects from 5 to 22 years of age, based on the FA in cortical gray matter (GM). Specifically,
FA image is first aligned with the corresponding T1 image, which has been parcellated into different cortical ROIs, and
then the average FA in each ROI is computed. Linear mixed model is used to analyze the FA developmental pattern in
each cortical ROI. The developmental trajectory of FA in each ROI across ages is delineated, and the best-fitting models
of age-related changes in FA were linear for all ROIs. FA generally increases with the age from 5 to 22 years of age. In
addition, males and females follow the similar pattern, with the FA of females being generally lower than that of males
in most ROIs. This provides us some insights into the microstructural changes in the longitudinal cerebral cortex development.
Paper Details
Date Published: 13 March 2013
PDF: 7 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86692E (13 March 2013); doi: 10.1117/12.2007164
Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)
PDF: 7 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86692E (13 March 2013); doi: 10.1117/12.2007164
Show Author Affiliations
Yaping Wang, Northwestern Polytechnical Univ. (China)
Univ. of North Carolina at Chapel Hill (United States)
Gang Li, Univ. of North Carolina at Chapel Hill (United States)
Mihye Ahn, Univ. of North Carolina at Chapel Hill (United States)
Univ. of North Carolina at Chapel Hill (United States)
Gang Li, Univ. of North Carolina at Chapel Hill (United States)
Mihye Ahn, Univ. of North Carolina at Chapel Hill (United States)
Jingxin Nie, Univ. of North Carolina at Chapel Hill (United States)
Hongtu Zhu, Univ. of North Carolina at Chapel Hill (United States)
Lei Guo, Northwestern Polytechnical Univ. (China)
Hongtu Zhu, Univ. of North Carolina at Chapel Hill (United States)
Lei Guo, Northwestern Polytechnical Univ. (China)
Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)
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