Alpha Rhythm Wavelength of Electroencephalography Signals as a Diagnostic Biomarker for Alzheimer's Disease.

IF 1.8 4区医学 Q3 CLINICAL NEUROLOGY Current Alzheimer research Pub Date : 2023-01-01 DOI:10.2174/1567205020666230503094441

Lingfeng Liu, Lijun Hao, Qian Yang, Qing Cao, Nan Jiang, Meiyun Zhang

{"title":"Alpha Rhythm Wavelength of Electroencephalography Signals as a Diagnostic Biomarker for Alzheimer's Disease.","authors":"Lingfeng Liu, Lijun Hao, Qian Yang, Qing Cao, Nan Jiang, Meiyun Zhang","doi":"10.2174/1567205020666230503094441","DOIUrl":null,"url":null,"abstract":"Objective: To explore changes in the alpha rhythm wavelength of background electroencephalography in Alzheimer's disease patients with different degrees of dementia in a resting state; examine their correlation with the degree of cognitive impairment; determine whether the alpha rhythm wavelength can distinguish mild Alzheimer's disease patients, moderately severe Alzheimer's disease patients, and healthy controls at the individual level; and identify a cut-off value to differentiate Alzheimer's disease patients from healthy controls.Methods: Quantitative electroencephalography signals of 42 patients with mild Alzheimer's disease, 42 patients with moderately severe Alzheimer's disease, and 40 healthy controls during rest state with eyes closed were analyzed using wavelet transform. Electroencephalography signals were decomposed into different scales, and their segments were superimposed according to the same length (wavelength and amplitude) and phase alignment. Phase averaging was performed to obtain average phase waveforms of the desired scales of each lead. The alpha-band wavelengths corresponding to the ninth scale of the background rhythm of different leads were compared between groups.Results: The average wavelength of the alpha rhythm phase of the whole-brain electroencephalography signals in Alzheimer's disease patients was prolonged and positively correlated with the severity of cognitive dysfunction (P < 0.01). The ninth-scale phase average wavelength of each lead had high diagnostic efficacy for Alzheimer's disease, and the diagnostic efficacy of lead P3 (area under the receiver operating characteristic curve = 0.873) was the highest.Conclusion: The average wavelength of the electroencephalography alpha rhythm phase may be used as a quantitative feature for the diagnosis of Alzheimer's disease, and the slowing of the alpha rhythm may be an important neuro-electrophysiological index for disease evaluation.","PeriodicalId":10810,"journal":{"name":"Current Alzheimer research","volume":"20 1","pages":"11-28"},"PeriodicalIF":1.8000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Alzheimer research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/1567205020666230503094441","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Objective: To explore changes in the alpha rhythm wavelength of background electroencephalography in Alzheimer's disease patients with different degrees of dementia in a resting state; examine their correlation with the degree of cognitive impairment; determine whether the alpha rhythm wavelength can distinguish mild Alzheimer's disease patients, moderately severe Alzheimer's disease patients, and healthy controls at the individual level; and identify a cut-off value to differentiate Alzheimer's disease patients from healthy controls.

Methods: Quantitative electroencephalography signals of 42 patients with mild Alzheimer's disease, 42 patients with moderately severe Alzheimer's disease, and 40 healthy controls during rest state with eyes closed were analyzed using wavelet transform. Electroencephalography signals were decomposed into different scales, and their segments were superimposed according to the same length (wavelength and amplitude) and phase alignment. Phase averaging was performed to obtain average phase waveforms of the desired scales of each lead. The alpha-band wavelengths corresponding to the ninth scale of the background rhythm of different leads were compared between groups.

Results: The average wavelength of the alpha rhythm phase of the whole-brain electroencephalography signals in Alzheimer's disease patients was prolonged and positively correlated with the severity of cognitive dysfunction (P < 0.01). The ninth-scale phase average wavelength of each lead had high diagnostic efficacy for Alzheimer's disease, and the diagnostic efficacy of lead P3 (area under the receiver operating characteristic curve = 0.873) was the highest.

Conclusion: The average wavelength of the electroencephalography alpha rhythm phase may be used as a quantitative feature for the diagnosis of Alzheimer's disease, and the slowing of the alpha rhythm may be an important neuro-electrophysiological index for disease evaluation.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

脑电图信号的α节律波长作为阿尔茨海默病的诊断生物标志物。

目的:探讨不同程度痴呆的阿尔茨海默病患者静息状态下背景脑电图α节律波长的变化;检查它们与认知障碍程度的相关性;确定α节律波长是否能在个体水平上区分轻度阿尔茨海默病患者、中重度阿尔茨海默病患者和健康对照组;并确定一个临界值来区分阿尔茨海默病患者和健康对照者。方法:应用小波变换对42例轻度阿尔茨海默病患者、42例中重度阿尔茨海默病患者和40例健康对照者闭眼静息状态的定量脑电图信号进行分析。将脑电图信号分解成不同的尺度，并按照相同的长度(波长和幅度)和相位排列叠加。进行相位平均，得到各引线所需尺度的平均相位波形。比较两组不同导音背景节奏第九音阶对应的α波段波长。结果:阿尔茨海默病患者全脑脑电图信号α节律相平均波长延长，且与认知功能障碍严重程度呈正相关(P < 0.01)。各导联第九尺度相平均波长对阿尔茨海默病的诊断效能较高，其中P3导联(受者工作特征曲线下面积= 0.873)的诊断效能最高。结论:脑电图α节律相平均波长可作为阿尔茨海默病诊断的定量特征，α节律减慢可作为疾病评价的重要神经电生理指标。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Current Alzheimer research 医学-神经科学

CiteScore

4.00

自引率

4.80%

发文量

审稿时长

4-8 weeks

期刊介绍： Current Alzheimer Research publishes peer-reviewed frontier review, research, drug clinical trial studies and letter articles on all areas of Alzheimer’s disease. This multidisciplinary journal will help in understanding the neurobiology, genetics, pathogenesis, and treatment strategies of Alzheimer’s disease. The journal publishes objective reviews written by experts and leaders actively engaged in research using cellular, molecular, and animal models. The journal also covers original articles on recent research in fast emerging areas of molecular diagnostics, brain imaging, drug development and discovery, and clinical aspects of Alzheimer’s disease. Manuscripts are encouraged that relate to the synergistic mechanism of Alzheimer''s disease with other dementia and neurodegenerative disorders. Book reviews, meeting reports and letters-to-the-editor are also published. The journal is essential reading for researchers, educators and physicians with interest in age-related dementia and Alzheimer’s disease. Current Alzheimer Research provides a comprehensive ''bird''s-eye view'' of the current state of Alzheimer''s research for neuroscientists, clinicians, health science planners, granting, caregivers and families of this devastating disease.