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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2015
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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. |
format | Online Article Text |
id | pubmed-4879518 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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