Abstract
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= -0.513, p= 0.002). The cortical ribbon dimensionality showed a larger effect size (d= 1.12) 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.
Original language | English (US) |
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Pages (from-to) | 471-479 |
Number of pages | 9 |
Journal | NeuroImage |
Volume | 53 |
Issue number | 2 |
DOIs | |
State | Published - Nov 2010 |
Keywords
- Alzheimer's disease
- Complexity
- Cortex
- Cortical Thickness
- Fractal Dimension
- Gyrification Index
ASJC Scopus subject areas
- Neurology
- Cognitive Neuroscience