期刊
NEUROIMAGE
卷 53, 期 2, 页码 471-479出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2010.06.050
关键词
Fractal Dimension; Cortex; Complexity; Alzheimer's disease; Cortical Thickness; Gyrification Index
资金
- Center for Alzheimer's Care Imaging and Research at the University of Utah
- Robert Wood Johnson Foundation
- National Institute of Aging [5-R37-AG006265-27, 5-P30-AG012300-15]
- Alzheimer's Association
- Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health) [U01 AG024904]
- National Institute on Aging
- National Institute of Biomedical Imaging and Bioengineering
- NIH [P30 AG010129, K01 AG030514]
- Dana Foundation
Fractal analysis methods are used to quantify the complexity of the human cerebral cortex Many recent studies have focused on high resolution three-dimensional reconstructions of either the outer (pial) surface of the brain or the junction between the gray and white matter, but ignore the structure between these surfaces. This study uses a new method to incorporate the entire cortical thickness. Data were obtained from the Alzheimer's Disease (AD) Neuroimaging Initiative database (Control N=35, Mild AD N=35) Image segmentation was performed using a semi-automated analysis program The fractal dimension of three cortical models (the pial surface, gray/white surface and entire cortical ribbon) were calculated using a custom cube-counting triangle-intersection algorithm The fractal dimension of the cortical ribbon showed highly significant differences between control and AD subjects (p<0 001) The inner surface analysis also found smaller but significant differences (p<0 05) The pial surface dimensionality was not significantly different between the two groups All three models had a significant positive correlation with the cortical gyrification index (r>0.55. p<0 001) Only the cortical ribbon had a significant correlation with cortical thickness (r=0 832, p<0.001) and the Alzheimer's Disease Assessment Scale cognitive battery (r = -0513, p = 0.002). The cortical ribbon dimensionality showed a larger effect size (d = I 12) in separating control and mild AD subjects than cortical thickness (d = 1 01) or gyrification index (d = 0 84) The methodological change shown in this paper may allow for further clinical application of cortical fractal dimension as a biomarker for structural changes that accrue with neurodegenerative diseases (C) 2010 Elsevier Inc All rights reserved
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