Display Settings:

Format

Send to:

Choose Destination
See comment in PubMed Commons below
Neuroimage. 2010 Nov 1;53(2):471-9. doi: 10.1016/j.neuroimage.2010.06.050. Epub 2010 Jun 25.

Fractal dimension analysis of the cortical ribbon in mild Alzheimer's disease.

Author information

  • 1Department of Neurology, University of Utah, USA. richard.king@hsc.utah.edu

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.

Copyright 2010 Elsevier Inc. All rights reserved.

PMID:
20600974
[PubMed - indexed for MEDLINE]
PMCID:
PMC2942777
Free PMC Article

Images from this publication.See all images (8)Free text

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Icon for Elsevier Science Icon for PubMed Central
    Loading ...
    Write to the Help Desk