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

• Published in: NeuroImage (Orlando, Fla.) Vol. 53; no. 2; pp. 471 - 479
• Main Authors: King, Richard D., Brown, Brandon, Hwang, Michael, Jeon, Tina, George, Anuh T.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.11.2010; Elsevier Limited
• Subjects: Aged; Aged, 80 and over; Alzheimer Disease - pathology; Alzheimer Disease - psychology; Alzheimer's disease; Cerebral Cortex - pathology; Complexity; Cortex; Cortical Thickness; Databases, Factual; Female; Fractal Dimension; Fractals; Gender; Gyrification Index; Gyrus Cinguli - pathology; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Male; Medical imaging; Methods; Middle Aged; Models, Statistical; Neuropsychological Tests; Reproducibility of Results; ROC Curve; Sex Characteristics; Studies; Cortical Thickness; Fractal Dimension; Gyrification Index; Alzheimer's disease; Cortex; Complexity
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2010.06.050

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. [Display omitted] ▶ The fractal dimension of the cortical ribbon is lower for AD subjects vs controls. ▶ The entire ribbon is a better cortical model than the pial or grey/white surfaces. ▶ The cortical ribbon separates mild AD vs control better than cortical thickness. ▶ The cortical ribbon separates mild AD vs control better than gyrification index.