Cortical atrophy pattern-based subtyping predicts prognosis of amnestic MCI: an individual-level analysis
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Hee Jin | - |
dc.contributor.author | Park, Jong-Yun | - |
dc.contributor.author | Seo, Sang Won | - |
dc.contributor.author | Jung, Young Hee | - |
dc.contributor.author | Kim, Yeshin | - |
dc.contributor.author | Jang, Hyemin | - |
dc.contributor.author | Kim, Sung Tae | - |
dc.contributor.author | Seong, Joon-Kyung | - |
dc.contributor.author | Na, Duk L. | - |
dc.date.accessioned | 2021-09-01T20:10:03Z | - |
dc.date.available | 2021-09-01T20:10:03Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2019-02 | - |
dc.identifier.issn | 0197-4580 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/67837 | - |
dc.description.abstract | We categorized patients with amnestic mild cognitive impairment (aMCI) based on cortical atrophy patterns and evaluated whether the prognosis differed across the subtypes. Furthermore, we developed a classifier that learns the cortical atrophy pattern and predicts subtypes at an individual level. A total of 662 patients with aMCI were clustered into 3 subtypes based on cortical atrophy patterns. Of these, 467 patients were followed up for more than 12 months, and the median follow-up duration was 43 months. To predict individual-level subtype, we used a machine learning-based classifier with a 10-fold cross-validation scheme. Patients with aMCI were clustered into 3 subtypes: medial temporal atrophy, minimal atrophy (Min), and parietotemporal atrophy (PT) subtypes. The PT subtype had higher prevalence of APOE epsilon 4 carriers, amyloid PET positivity, and greater risk of dementia conversion than the Min subtype. The accuracy for binary classification was 89.3% (MT vs. Rest), 92.6% (PT vs. Rest), and 86.6% (Min vs. Rest). When we used ensemble model of 3 binary classifiers, the accuracy for predicting the aMCI subtype at an individual level was 89.6%. Patients with aMCI with the PT subtype were more likely to have underlying Alzheimer's disease pathology and showed the worst prognosis. Our classifier may be useful for predicting the prognosis of individual aMCI patients. (C) 2018 Elsevier Inc. All rights reserved. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCIENCE INC | - |
dc.subject | MILD COGNITIVE IMPAIRMENT | - |
dc.subject | ALZHEIMERS-DISEASE | - |
dc.subject | IDENTIFICATION | - |
dc.subject | HETEROGENEITY | - |
dc.subject | PREVALENCE | - |
dc.title | Cortical atrophy pattern-based subtyping predicts prognosis of amnestic MCI: an individual-level analysis | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Seong, Joon-Kyung | - |
dc.identifier.doi | 10.1016/j.neurobiolaging.2018.10.010 | - |
dc.identifier.scopusid | 2-s2.0-85056167379 | - |
dc.identifier.wosid | 000455193900004 | - |
dc.identifier.bibliographicCitation | NEUROBIOLOGY OF AGING, v.74, pp.38 - 45 | - |
dc.relation.isPartOf | NEUROBIOLOGY OF AGING | - |
dc.citation.title | NEUROBIOLOGY OF AGING | - |
dc.citation.volume | 74 | - |
dc.citation.startPage | 38 | - |
dc.citation.endPage | 45 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Geriatrics & Gerontology | - |
dc.relation.journalResearchArea | Neurosciences & Neurology | - |
dc.relation.journalWebOfScienceCategory | Geriatrics & Gerontology | - |
dc.relation.journalWebOfScienceCategory | Neurosciences | - |
dc.subject.keywordPlus | MILD COGNITIVE IMPAIRMENT | - |
dc.subject.keywordPlus | ALZHEIMERS-DISEASE | - |
dc.subject.keywordPlus | IDENTIFICATION | - |
dc.subject.keywordPlus | HETEROGENEITY | - |
dc.subject.keywordPlus | PREVALENCE | - |
dc.subject.keywordAuthor | Mild cognitive impairment | - |
dc.subject.keywordAuthor | Alzheimer&apos | - |
dc.subject.keywordAuthor | s disease | - |
dc.subject.keywordAuthor | Cortical atrophy pattern | - |
dc.subject.keywordAuthor | Classifier | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.