A comparison of resting state Alzheimer ?s disease and mild EEG and structural MRI for classifying cognitive impairment

被引:63
作者
Farina, F. R. [1 ]
Emek-Savas, D. D. [2 ,3 ,5 ]
Rueda-Delgado, L. [1 ]
Boyle, R. [1 ]
Kiiski, H. [1 ]
Yener, G. [3 ,4 ]
Whelan, R. [1 ,5 ]
机构
[1] Trinity Coll Dublin, Trinity Coll, Inst Neurosci, Dublin 2, Ireland
[2] Dokuz Eylul Univ, Fac Letters, Dept Psychol, TR-35160 Izmir, Turkey
[3] Dokuz Eylul Univ, Inst Hlth Sci, Dept Neurosci, TR-35340 Izmir, Turkey
[4] Dokuz Eylul Univ, Dept Neurol, Med Sch, TR-35340 Izmir, Turkey
[5] Trinity Coll Dublin, Global Brain Hlth Inst, Dublin 2, Ireland
基金
爱尔兰科学基金会;
关键词
ASSOCIATION WORKGROUPS; DIAGNOSTIC GUIDELINES; NATIONAL INSTITUTE; SPECTRAL POWER; DEMENTIA; CLASSIFICATION; RECOMMENDATIONS; PROGRESSION; THICKNESS; DYNAMICS;
D O I
10.1016/j.neuroimage.2020.116795
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Alzheimer's disease (AD) is the leading cause of dementia, accounting for 70% of cases worldwide. By 2050, dementia prevalence will have tripled, with most new cases occurring in low- and middle-income countries. Mild cognitive impairment (MCI) is a stage between healthy aging and dementia, marked by cognitive deficits that do not impair daily living. People with MCI are at increased risk of dementia, with an average progression rate of 39% within 5 years. There is urgent need for low-cost, accessible and objective methods to facilitate early dementia detection. Electroencephalography (EEG) has potential to address this need due to its low cost and portability. Here, we collected resting state EEG, structural MRI (sMRI) and rich neuropsychological data from older adults (55+ years) with AD, amnestic MCI (aMCI) and healthy controls (~60 per group). We evaluated a range of candidate EEG markers (i.e., frequency band power and functional connectivity) for AD and aMCI classification and compared their performance with sMRI. We also tested a combined EEG and cognitive classification model (using Mini-Mental State Examination; MMSE). sMRI outperformed resting state EEG at classifying AD (AUCs ​= ​1.00 vs 0.76, respectively). However, both EEG and sMRI were only moderately good at distinguishing aMCI from healthy aging (AUCs ​= ​0.67–0.73), and neither method achieved sensitivity above 70%. The addition of EEG to MMSE scores had no added benefit relative to MMSE scores alone. This is the first direct comparison of EEG and sMRI for classification of AD and aMCI. © 2020 The Author(s)
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页数:14
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