Article

Brain Imaging and Behavior

, Volume 3, Issue 2, pp 154-166

Characterization of Atrophic Changes in the Cerebral Cortex Using Fractal Dimensional Analysis

  • Richard D. KingAffiliated withDepartment of Neurology, University of Texas Southwestern Medical CenterCenter for BrainHealth, University of Texas at Dallas Email author 
  • , Anuh T. GeorgeAffiliated withDepartment of Neurology, University of Texas Southwestern Medical CenterCenter for BrainHealth, University of Texas at Dallas
  • , Tina JeonAffiliated withDepartment of Neurology, University of Texas Southwestern Medical CenterCenter for BrainHealth, University of Texas at Dallas
  • , Linda S. HynanAffiliated withDepartment of Clinical Sciences, Division of Biostatistics, University of Texas Southwestern Medical CenterDepartment of Psychiatry, University of Texas Southwestern Medical Center
  • , Teddy S. YounAffiliated withDepartment of Neurology, University of Texas Southwestern Medical Center
  • , David N. KennedyAffiliated withCenter for Morphometric Analysis, Massachusetts General Hospital, Harvard Medical School
  • , Bradford DickersonAffiliated withDepartment of Neurology, Massachusetts General Hospital, Harvard Medical School
  • , and the Alzheimer’s Disease Neuroimaging Initiative

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Abstract

The purpose of this project is to apply a modified fractal analysis technique to high-resolution T1 weighted magnetic resonance images in order to quantify the alterations in the shape of the cerebral cortex that occur in patients with Alzheimer’s disease. Images were selected from the Alzheimer’s Disease Neuroimaging Initiative database (Control N = 15, Mild-Moderate AD N = 15). The images were segmented using a semi-automated analysis program. Four coronal and three axial profiles of the cerebral cortical ribbon were created. The fractal dimensions (D f) of the cortical ribbons were then computed using a box-counting algorithm. The mean D f of the cortical ribbons from AD patients were lower than age-matched controls on six of seven profiles. The fractal measure has regional variability which reflects local differences in brain structure. Fractal dimension is complementary to volumetric measures and may assist in identifying disease state or disease progression.

Keywords

Fractal dimension Alzheimer’s disease Neuroimaging initiative Cerebral cortex Fractal analysis