EEG features associated with Alzheimer’s disease and Frontotemporal dementia are not reflected by processed indices used in anesthesia monitoring

Patients with dementia face increased risks after general anesthesia. Improved perioperative electroencephalogram (EEG) monitoring techniques could aid in identifying vulnerable patients. However, current technology relies on processed indices to measure "depth-of-anesthesia". Analyzing OpenNeuro Dataset ds004504, we compared resting-state, eyes-closed EEG recordings of healthy controls (n = 27) with patients diagnosed with Alzheimer's disease (AD, n = 35) and Frontotemporal dementia (FTD, n = 23). We focused on prefrontal recordings. Analysis included spectral analysis, the "fitting-oscillations&-one-over-f"-algorithm for aperiodic and periodic signal features, as well as calculations of openibis, permutation entropy (PeEn), spectral entropy (SpEn), and spectral edge frequency (SEF). Spectral differences were pronounced, including a higher alpha/theta-ratio of controls (2.62 [95%CI: 1.54-3.62]) compared to both AD (0.55 [95%CI: 0.26-1.92], P < 0.001, AUC: 0.765 [0.642-0.888]) and FTD (0.83 [95%CI: 0.33-1.65], P = 0.007, AUC: 0.779 [0.652-0.907]). Oscillatory peak detection within the alpha frequency band was more robust in control (versus AD: P = 0.003, Cramér's V = 0.374; versus FTD: P = 0.003, Cramér's V = 0.414). Processed index parameters did not show a clear trend. FTD was associated with a higher prefrontal openibis (95.53 [95%CI: 93.43-97.39]) than control (91.98 [95%CI: 89.46-96.27], P = 0.033, AUC: 0.717 [0.572-0.862]) and an elevated SEF (23.68 [95%CI: 14.10-25.57] Hz) compared to AD (16.60 [95%CI: 14.22-22.22] Hz, P = 0.041, AUC: 0.676 [0.532-0.821]). AD and FTD are associated with EEG baseline abnormalities, and a standard prefrontal montage, as used intraoperatively, could present a promising technical screening approach for cognitive vulnerability. However, these EEG features are obscured by processed index parameters currently used in neuroanesthesia monitoring. OpenNeuro Dataset ds004504 "A dataset of EEG recordings from: Alzheimer's disease, Frontotemporal dementia and Healthy subjects" (doi: https://doi.org/10.18112/openneuro.ds004504.v1.0.7 ).

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Publication Details

Journal
Journal of Clinical Monitoring and Computing
Published
2025-04-21
DOI
https://doi.org/10.1007/s10877-025-01294-y
Citations
6
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
8.59

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article

EEG features associated with Alzheimer’s disease and Frontotemporal dementia are not reflected by processed indices used in anesthesia monitoring

Matthias Kreuzer, Julian Ostertag, Srdjan Dragovic, Gerhard Schneider et al.
6 citations
Journal of Clinical Monitoring and Computing
EEG and Brain-Computer Interfaces
8.59
article

EEG features associated with Alzheimer’s disease and Frontotemporal dementia are not reflected by processed indices used in anesthesia monitoring

Matthias Kreuzer, Julian Ostertag, Srdjan Dragovic, Gerhard Schneider, Duy-Minh Nguyen, Stefan Schwerin
article en
6 citations

Abstract

Patients with dementia face increased risks after general anesthesia. Improved perioperative electroencephalogram (EEG) monitoring techniques could aid in identifying vulnerable patients. However, current technology relies on processed indices to measure "depth-of-anesthesia". Analyzing OpenNeuro Dataset ds004504, we compared resting-state, eyes-closed EEG recordings of healthy controls (n = 27) with patients diagnosed with Alzheimer's disease (AD, n = 35) and Frontotemporal dementia (FTD, n = 23). We focused on prefrontal recordings. Analysis included spectral analysis, the "fitting-oscillations&-one-over-f"-algorithm for aperiodic and periodic signal features, as well as calculations of openibis, permutation entropy (PeEn), spectral entropy (SpEn), and spectral edge frequency (SEF). Spectral differences were pronounced, including a higher alpha/theta-ratio of controls (2.62 [95%CI: 1.54-3.62]) compared to both AD (0.55 [95%CI: 0.26-1.92], P < 0.001, AUC: 0.765 [0.642-0.888]) and FTD (0.83 [95%CI: 0.33-1.65], P = 0.007, AUC: 0.779 [0.652-0.907]). Oscillatory peak detection within the alpha frequency band was more robust in control (versus AD: P = 0.003, Cramér's V = 0.374; versus FTD: P = 0.003, Cramér's V = 0.414). Processed index parameters did not show a clear trend. FTD was associated with a higher prefrontal openibis (95.53 [95%CI: 93.43-97.39]) than control (91.98 [95%CI: 89.46-96.27], P = 0.033, AUC: 0.717 [0.572-0.862]) and an elevated SEF (23.68 [95%CI: 14.10-25.57] Hz) compared to AD (16.60 [95%CI: 14.22-22.22] Hz, P = 0.041, AUC: 0.676 [0.532-0.821]). AD and FTD are associated with EEG baseline abnormalities, and a standard prefrontal montage, as used intraoperatively, could present a promising technical screening approach for cognitive vulnerability. However, these EEG features are obscured by processed index parameters currently used in neuroanesthesia monitoring. OpenNeuro Dataset ds004504 "A dataset of EEG recordings from: Alzheimer's disease, Frontotemporal dementia and Healthy subjects" (doi: https://doi.org/10.18112/openneuro.ds004504.v1.0.7 ).

Journal of Clinical Monitoring and ComputingVol. 39(4)
Universität Ulm (DE), TUM Klinikum (DE), Technical University of Munich (DE)
Technische Universität München
Openalex Percentile: Top 2%
EEG and Brain-Computer Interfaces
8.59
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