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Prediction of Alzheimer's disease pathophysiology based on cortical thickness patterns.


ABSTRACT:

Introduction

Recent studies have shown that pathologically defined subtypes of Alzheimer's disease (AD) represent distinctive atrophy patterns and clinical characteristics. We investigated whether a cortical thickness-based clustering method can reflect such findings.

Methods

A total of 77 AD subjects from the Alzheimer's Disease Neuroimaging Initiative 2 data set who underwent 3-T magnetic resonance imaging, [(18)F]-fluorodeoxyglucose-positron emission tomography (PET), [(18)F]-Florbetapir PET, and cerebrospinal fluid (CSF) tests were enrolled. After clustering based on cortical thickness, diverse imaging and biofluid biomarkers were compared between these groups.

Results

Three cortical thinning patterns were noted: medial temporal (MT; 19.5%), diffuse (55.8%), and parietal dominant (P; 24.7%) atrophy subtypes. The P subtype was the youngest and represented more glucose hypometabolism in the parietal and occipital cortices and marked amyloid-beta accumulation in most brain regions. The MT subtype revealed more glucose hypometabolism in the left hippocampus and bilateral frontal cortices and less performance in memory tests. CSF test results did not differ between the groups.

Discussion

Cortical thickness patterns can reflect pathophysiological and clinical changes in AD.

SUBMITTER: Hwang J 

PROVIDER: S-EPMC4879518 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Prediction of Alzheimer's disease pathophysiology based on cortical thickness patterns.

Hwang Jihye J   Kim Chan Mi CM   Jeon Seun S   Lee Jong Min JM   Hong Yun Jeong YJ   Roh Jee Hoon JH   Lee Jae-Hong JH   Koh Jae-Young JY   Na Duk L DL  

Alzheimer's & dementia (Amsterdam, Netherlands) 20151228


<h4>Introduction</h4>Recent studies have shown that pathologically defined subtypes of Alzheimer's disease (AD) represent distinctive atrophy patterns and clinical characteristics. We investigated whether a cortical thickness-based clustering method can reflect such findings.<h4>Methods</h4>A total of 77 AD subjects from the Alzheimer's Disease Neuroimaging Initiative 2 data set who underwent 3-T magnetic resonance imaging, [(18)F]-fluorodeoxyglucose-positron emission tomography (PET), [(18)F]-F  ...[more]

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