Ji Eun Kim, Sung-Woo Kim, Minsuk Choi, Joon-Kyung Seong, Jae-Hong Lee
{"title":"利用基于网络的统计数据识别按β-淀粉样蛋白阳性率分层的失忆性轻度认知障碍患者的大脑连通性","authors":"Ji Eun Kim, Sung-Woo Kim, Minsuk Choi, Joon-Kyung Seong, Jae-Hong Lee","doi":"10.1177/1533317518813556","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The aim of this study was to identify white matter structural networks of amnestic mild cognitive impairment (aMCI) dichotomized by β amyloid (Aβ) status and compare them using network-based statistics (NBS).</p><p><strong>Methods: </strong>Patients underwent whole-brain diffusion-weighted magnetic resonance imaging, detailed neuropsychological test and [<sup>18</sup>F]-Florbetaben amyloid positron emission tomography. We performed the NBS analysis to compare the whole-brain white matter structural networks extracted from diffusion tensor images.</p><p><strong>Results: </strong>One hundred sixteen participants (Aβ- cognitively normal [CN], n = 35; Aβ- aMCI, n = 42; Aβ+ aMCI, n = 39) were included. There was no subnetwork showing significant difference between Aβ+ aMCI and Aβ- aMCI. However, by comparing each aMCI group with control group, we found that supplementary motor areas were common hub regions. Intriguingly, Aβ+ aMCI showed reduced connectivity mainly in the medial frontal regions, while Aβ- aMCI showed somewhat uniform disruption when compared to CN.</p><p><strong>Conclusion: </strong>Structural network analysis using network-based approach in aMCI may shed light on further understanding of white matter disruption in the prodromal stage of Alzheimer's disease.</p>","PeriodicalId":50816,"journal":{"name":"American Journal of Alzheimers Disease and Other Dementias","volume":"34 2","pages":"104-111"},"PeriodicalIF":2.7000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10852511/pdf/","citationCount":"0","resultStr":"{\"title\":\"Identifying Brain Connectivity Using Network-Based Statistics in Amnestic Mild Cognitive Impairment Stratified by β-Amyloid Positivity.\",\"authors\":\"Ji Eun Kim, Sung-Woo Kim, Minsuk Choi, Joon-Kyung Seong, Jae-Hong Lee\",\"doi\":\"10.1177/1533317518813556\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The aim of this study was to identify white matter structural networks of amnestic mild cognitive impairment (aMCI) dichotomized by β amyloid (Aβ) status and compare them using network-based statistics (NBS).</p><p><strong>Methods: </strong>Patients underwent whole-brain diffusion-weighted magnetic resonance imaging, detailed neuropsychological test and [<sup>18</sup>F]-Florbetaben amyloid positron emission tomography. We performed the NBS analysis to compare the whole-brain white matter structural networks extracted from diffusion tensor images.</p><p><strong>Results: </strong>One hundred sixteen participants (Aβ- cognitively normal [CN], n = 35; Aβ- aMCI, n = 42; Aβ+ aMCI, n = 39) were included. There was no subnetwork showing significant difference between Aβ+ aMCI and Aβ- aMCI. However, by comparing each aMCI group with control group, we found that supplementary motor areas were common hub regions. Intriguingly, Aβ+ aMCI showed reduced connectivity mainly in the medial frontal regions, while Aβ- aMCI showed somewhat uniform disruption when compared to CN.</p><p><strong>Conclusion: </strong>Structural network analysis using network-based approach in aMCI may shed light on further understanding of white matter disruption in the prodromal stage of Alzheimer's disease.</p>\",\"PeriodicalId\":50816,\"journal\":{\"name\":\"American Journal of Alzheimers Disease and Other Dementias\",\"volume\":\"34 2\",\"pages\":\"104-111\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2019-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10852511/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Journal of Alzheimers Disease and Other Dementias\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/1533317518813556\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2018/11/29 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Alzheimers Disease and Other Dementias","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/1533317518813556","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2018/11/29 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Identifying Brain Connectivity Using Network-Based Statistics in Amnestic Mild Cognitive Impairment Stratified by β-Amyloid Positivity.
Background: The aim of this study was to identify white matter structural networks of amnestic mild cognitive impairment (aMCI) dichotomized by β amyloid (Aβ) status and compare them using network-based statistics (NBS).
Methods: Patients underwent whole-brain diffusion-weighted magnetic resonance imaging, detailed neuropsychological test and [18F]-Florbetaben amyloid positron emission tomography. We performed the NBS analysis to compare the whole-brain white matter structural networks extracted from diffusion tensor images.
Results: One hundred sixteen participants (Aβ- cognitively normal [CN], n = 35; Aβ- aMCI, n = 42; Aβ+ aMCI, n = 39) were included. There was no subnetwork showing significant difference between Aβ+ aMCI and Aβ- aMCI. However, by comparing each aMCI group with control group, we found that supplementary motor areas were common hub regions. Intriguingly, Aβ+ aMCI showed reduced connectivity mainly in the medial frontal regions, while Aβ- aMCI showed somewhat uniform disruption when compared to CN.
Conclusion: Structural network analysis using network-based approach in aMCI may shed light on further understanding of white matter disruption in the prodromal stage of Alzheimer's disease.
期刊介绍:
American Journal of Alzheimer''s Disease and other Dementias® (AJADD) is for professionals on the frontlines of Alzheimer''s care, dementia, and clinical depression--especially physicians, nurses, psychiatrists, administrators, and other healthcare specialists who manage patients with dementias and their families. This journal is a member of the Committee on Publication Ethics (COPE).