Literature DB >> 15537673

Focal decline of cortical thickness in Alzheimer's disease identified by computational neuroanatomy.

Jason P Lerch1, Jens C Pruessner, Alex Zijdenbos, Harald Hampel, Stefan J Teipel, Alan C Evans.   

Abstract

Alzheimer's disease (AD) is characterized by a heterogeneous distribution of pathological changes throughout the brain. Magnetic resonance imaging can be used to investigate the regional distribution of cortical atrophy in AD in vivo. One marker for the disease-specific atrophy is the thickness of the cortical mantle across the brain, obtained with automated 3-D image processing. Here, we present data from 36 subjects (17 controls and, 19 patients diagnosed as probable AD) investigated for cortical thickness across the entire brain. We show significant cortical thickness decline in AD in temporal, orbitofrontal and parietal regions, with the most pronounced changes occurring in the allocortical region of the medial temporal lobes, outlining the parahippocampal gyrus, and representing a loss of >1.25 millimeters of cortical thickness. Moreover, focal cortical areas decline with progression of the disease as measured by time from baseline scan as well as the Mini-Mental State Exam. The results demonstrate the ability of this method to detect changes in cortical thickness in AD, across the entire brain, without need of prior anatomical definitions. The regional distribution of changes reported here is consistent with independent findings on the distribution of neuropathological alterations in AD. Using cortical thickness, moreover, we provide a direct quantitative index of atrophy in the disease.

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Year:  2004        PMID: 15537673     DOI: 10.1093/cercor/bhh200

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


  139 in total

1.  Discriminant analysis of longitudinal cortical thickness changes in Alzheimer's disease using dynamic and network features.

Authors:  Yang Li; Yaping Wang; Guorong Wu; Feng Shi; Luping Zhou; Weili Lin; Dinggang Shen
Journal:  Neurobiol Aging       Date:  2011-01-26       Impact factor: 4.673

2.  Dynamic brain structural changes after left hemisphere subcortical stroke.

Authors:  Fengmei Fan; Chaozhe Zhu; Hai Chen; Wen Qin; Xunming Ji; Liang Wang; Yujin Zhang; Litao Zhu; Chunshui Yu
Journal:  Hum Brain Mapp       Date:  2012-03-19       Impact factor: 5.038

3.  Topological correction of brain surface meshes using spherical harmonics.

Authors:  Rachel Aine Yotter; Robert Dahnke; Paul M Thompson; Christian Gaser
Journal:  Hum Brain Mapp       Date:  2010-07-27       Impact factor: 5.038

4.  Spatial patterns of intrinsic brain activity in mild cognitive impairment and Alzheimer's disease: a resting-state functional MRI study.

Authors:  Zhiqun Wang; Chaogan Yan; Cheng Zhao; Zhigang Qi; Weidong Zhou; Jie Lu; Yong He; Kuncheng Li
Journal:  Hum Brain Mapp       Date:  2010-11-12       Impact factor: 5.038

5.  Individual subject classification for Alzheimer's disease based on incremental learning using a spatial frequency representation of cortical thickness data.

Authors:  Youngsang Cho; Joon-Kyung Seong; Yong Jeong; Sung Yong Shin
Journal:  Neuroimage       Date:  2011-10-08       Impact factor: 6.556

6.  Relevant feature set estimation with a knock-out strategy and random forests.

Authors:  Melanie Ganz; Douglas N Greve; Bruce Fischl; Ender Konukoglu
Journal:  Neuroimage       Date:  2015-08-10       Impact factor: 6.556

Review 7.  Towards multimodal atlases of the human brain.

Authors:  Arthur W Toga; Paul M Thompson; Susumu Mori; Katrin Amunts; Karl Zilles
Journal:  Nat Rev Neurosci       Date:  2006-12       Impact factor: 34.870

8.  Associations between brain morphology and motor performance in chronic neck pain: A whole-brain surface-based morphometry approach.

Authors:  Robby De Pauw; Iris Coppieters; Karen Caeyenberghs; Jeroen Kregel; Hannelore Aerts; Dorine Lenoir; Barbara Cagnie
Journal:  Hum Brain Mapp       Date:  2019-06-20       Impact factor: 5.038

9.  Consistent 4D cortical thickness measurement for longitudinal neuroimaging study.

Authors:  Yang Li; Yaping Wang; Zhong Xue; Feng Shi; Weili Lin; Dinggang Shen
Journal:  Med Image Comput Comput Assist Interv       Date:  2010

Review 10.  Brain mapping as a tool to study neurodegeneration.

Authors:  Liana G Apostolova; Paul M Thompson
Journal:  Neurotherapeutics       Date:  2007-07       Impact factor: 7.620

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