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dc.contributor.author김건하-
dc.date.accessioned2016-08-27T04:08:04Z-
dc.date.available2016-08-27T04:08:04Z-
dc.date.issued2014-
dc.identifier.issn0028-3878-
dc.identifier.issn1526-632X-
dc.identifier.otherOAK-12162-
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/216954-
dc.description.abstractObjective: Because the signs associated with dementia due to Alzheimer disease (AD) can be heterogeneous, the goal of this study was to use 3-dimensional MRI to examine the various patterns of cortical atrophy that can be associated with dementia of AD type, and to investigate whether AD dementia can be categorized into anatomical subtypes. Methods: High-resolution T1-weighted volumetric MRIs were taken of 152 patients in their earlier stages of AD dementia. The images were processed to measure cortical thickness, and hierarchical agglomerative cluster analysis was performed using Ward's clustering linkage. The identified clusters of patients were compared with an age-and sex-matched control group using a general linear model. Results: There were several distinct patterns of cortical atrophy and the number of patterns varied according to the level of cluster analyses. At the 3-cluster level, patients were divided into (1) bilateral medial temporal-dominant atrophy subtype (n = 52, similar to 34.2%), (2) parietal-dominant subtype (n = 28, similar to 18.4%) in which the bilateral parietal lobes, the precuneus, along with bilateral dorsolateral frontal lobes, were atrophic, and (3) diffuse atrophy subtype (n = 72, similar to 47.4%) in which nearly all association cortices revealed atrophy. These 3 subtypes also differed in their demographic and clinical features. Conclusions: This cluster analysis of cortical thickness of the entire brain showed that AD dementia in the earlier stages can be categorized into various anatomical subtypes, with distinct clinical features.-
dc.languageEnglish-
dc.publisherLIPPINCOTT WILLIAMS &amp-
dc.publisherWILKINS-
dc.titleAnatomical heterogeneity of Alzheimer disease Based on cortical thickness on MRIs-
dc.typeArticle-
dc.relation.issue21-
dc.relation.volume83-
dc.relation.indexSCI-
dc.relation.indexSCIE-
dc.relation.indexSCOPUS-
dc.relation.startpage1936-
dc.relation.lastpage1944-
dc.relation.journaltitleNEUROLOGY-
dc.identifier.wosidWOS:000345301000011-
dc.author.googleNoh, Young-
dc.author.googleJeon, Seun-
dc.author.googleLee, Jong Min-
dc.author.googleSeo, Sang Won-
dc.author.googleKim, Geon Ha-
dc.author.googleCho, Hanna-
dc.author.googleYe, Byoung Seok-
dc.author.googleYoon, Cindy W.-
dc.author.googleKim, Hee Jin-
dc.author.googleChin, Juhee-
dc.author.googlePark, Kee Hyung-
dc.author.googleHeilman, Kenneth M.-
dc.author.googleNa, Duk L.-
dc.contributor.scopusid김건하(36554502600)-
dc.date.modifydate20230125114714-
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