Characterization of atrophic changes in the cerebral cortex using fractal dimensional analysis

Richard D. King, Anuh T. George, Tina Jeon, Linda S. Hynan, Teddy S. Youn, David N. Kennedy, Bradford Dickerson

Research output: Contribution to journalArticlepeer-review

97 Scopus citations

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 (Df) of the cortical ribbons were then computed using a box-counting algorithm. The mean Df 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.

Original languageEnglish
Pages (from-to)154-166
Number of pages13
JournalBrain Imaging and Behavior
Volume3
Issue number2
DOIs
StatePublished - Jun 2009

Bibliographical note

Funding Information:
Acknowledgements This project has been funded by generous support from the UNCF*Merck Science Initiative and the Harold Amos Medical Faculty Development Program (a program of the Robert Wood Johnson Foundation), NIH grant NS34189, and by NIA grant 5P30AG012300. In addition, the authors would like to thank Dr. John Hart for his helpful comments and overall tremendous support of this project. We also thank Paul Bourke, Dr. Mike Kraut, Ms. Sharon O’Meara, and the staff at the Center for BrainHealth at the University of Texas at Dallas for providing support and infrastructure for this work to proceed. Many thanks are also given to Dr. Roger Rosenberg and the faculty and staff of the Alzheimer’s Disease Center at the University of Texas Southwestern Medical Center for providing a forum to discuss ideas developed in this paper. We also thank Dr. Verne Caviness and the members of the Center for Morphometric Analysis at Massachusetts General Hospital for support in learning FreeSurfer and technical assistance with the project in general. Data collection and sharing for this project was funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI; Principal Investigator: Michael Weiner; NIH grant U01 AG024904). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering (NIBIB), and through generous contributions from the following: Pfizer Inc., Wyeth Research, Bristol-Myers Squibb, Eli Lilly and Company, GlaxoSmithKline, Merck & Co. Inc., AstraZeneca AB, Novartis Pharmaceuticals Corporation, Alzheimer’s Association, Eisai Global Clinical Development, Elan Corporation plc, Forest Laboratories, and the Institute for the Study of Aging, with participation from the U.S. Food and Drug Administration. Industry partnerships are coordinated through the Foundation for the National Institutes of Health.

Keywords

  • Alzheimer's disease
  • Cerebral cortex
  • Fractal analysis
  • Fractal dimension
  • Neuroimaging initiative

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Cognitive Neuroscience
  • Clinical Neurology
  • Cellular and Molecular Neuroscience
  • Psychiatry and Mental health
  • Behavioral Neuroscience

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