Patterns of structural complexity in Alzheimer's disease and frontotemporal dementia

Hum Brain Mapp. 2009 May;30(5):1667-77. doi: 10.1002/hbm.20632.

Abstract

The goal of this project was to utilize an information theoretic formalism for medical image analysis initially proposed in [Young et al. (2005): Phys Rev Lett 94:098701-1] to detect and quantify subtle global and regional differences in spatial patterns in patients suffering from Alzheimer's disease (AD) and frontotemporal dementia (FTD) by estimating the structural complexity of anatomical brain MRI. The sensitivity and specificity of the results are compared with those of a recent analysis, currently considered state of the art for MR studies of neurodegeneration. The previous study used regional estimates of cortical thinning and/or volume loss to differentiate between normal aging, AD, and FTD. The analysis illustrates that the structural complexity estimation method, a general multivariate approach to the study of variation in brain structure which does not depend on highly specialized volumetric and thickness estimates, is capable of providing sensitive and interpretable diagnostic information.

The goal of this project was to utilize an information theoretic formalism for medical image analysis initially proposed in [Young et al. (2005): Phys Rev Lett 94:098701‐1] to detect and quantify subtle global and regional differences in spatial patterns in patients suffering from Alzheimer's disease (AD) and frontotemporal dementia (FTD) by estimating the structural complexity of anatomical brain MRI. The sensitivity and specificity of the results are compared with those of a recent analysis, currently considered state of the art for MR studies of neurodegeneration. The previous study used regional estimates of cortical thinning and/or volume loss to differentiate between normal aging, AD, and FTD. The analysis illustrates that the structural complexity estimation method, a general multivariate approach to the study of variation in brain structure which does not depend on highly specialized volumetric and thickness estimates, is capable of providing sensitive and interpretable diagnostic information. Human Brain Mapp 2009. © 2008 Wiley‐Liss, Inc.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Alzheimer Disease / pathology*
  • Brain / pathology*
  • Brain Mapping
  • Dementia / pathology*
  • Discriminant Analysis
  • Female
  • Humans
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging / methods
  • Male
  • Middle Aged