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

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...

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Autores principales: Hwang, Jihye, Kim, Chan Mi, Jeon, Seun, Lee, Jong Min, Hong, Yun Jeong, Roh, Jee Hoon, Lee, Jae-Hong, Koh, Jae-Young, Na, Duk L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4879518/
https://www.ncbi.nlm.nih.gov/pubmed/27239533
http://dx.doi.org/10.1016/j.dadm.2015.11.008
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author Hwang, Jihye
Kim, Chan Mi
Jeon, Seun
Lee, Jong Min
Hong, Yun Jeong
Roh, Jee Hoon
Lee, Jae-Hong
Koh, Jae-Young
Na, Duk L.
author_facet Hwang, Jihye
Kim, Chan Mi
Jeon, Seun
Lee, Jong Min
Hong, Yun Jeong
Roh, Jee Hoon
Lee, Jae-Hong
Koh, Jae-Young
Na, Duk L.
author_sort Hwang, Jihye
collection PubMed
description 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.
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spelling pubmed-48795182016-05-27 Prediction of Alzheimer's disease pathophysiology based on cortical thickness patterns Hwang, Jihye Kim, Chan Mi Jeon, Seun Lee, Jong Min Hong, Yun Jeong Roh, Jee Hoon Lee, Jae-Hong Koh, Jae-Young Na, Duk L. Alzheimers Dement (Amst) Neuroimaging 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. Elsevier 2015-12-28 /pmc/articles/PMC4879518/ /pubmed/27239533 http://dx.doi.org/10.1016/j.dadm.2015.11.008 Text en © 2016 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Neuroimaging
Hwang, Jihye
Kim, Chan Mi
Jeon, Seun
Lee, Jong Min
Hong, Yun Jeong
Roh, Jee Hoon
Lee, Jae-Hong
Koh, Jae-Young
Na, Duk L.
Prediction of Alzheimer's disease pathophysiology based on cortical thickness patterns
title Prediction of Alzheimer's disease pathophysiology based on cortical thickness patterns
title_full Prediction of Alzheimer's disease pathophysiology based on cortical thickness patterns
title_fullStr Prediction of Alzheimer's disease pathophysiology based on cortical thickness patterns
title_full_unstemmed Prediction of Alzheimer's disease pathophysiology based on cortical thickness patterns
title_short Prediction of Alzheimer's disease pathophysiology based on cortical thickness patterns
title_sort prediction of alzheimer's disease pathophysiology based on cortical thickness patterns
topic Neuroimaging
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4879518/
https://www.ncbi.nlm.nih.gov/pubmed/27239533
http://dx.doi.org/10.1016/j.dadm.2015.11.008
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