Alzheimer's research & therapy · 2026
Estimation of positron emission tomography amyloid load and related biomarkers in Alzheimer's disease using evoked potential tomography EEG: development and internal validation in a cross-sectional cohort.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Rauchmann Boris-Stephan, Hamet James, Lai Jesyin, Kafi Homeira, Rexwinkle Joe, Brendel Matthias, Franzmeier Nicolai, Kurz Carolin, Pogarell Oliver, Levin Johannes, Höglinger Günter, Perneczky Robert
Аннотация
BACKGROUND: Dementia affects over 50 million individuals globally, predominantly due to Alzheimer's disease (AD). Effective early detection and intervention remain clinical challenges, as there is a lack of unified, portable solutions to assess multiple biomarkers.
METHODS: We evaluated Evoked Potential Tomography (EPT), an EEG-based method using a novel visual evoked potential protocol. An automated pipeline for EEG preprocessing, ERP extraction, feature selection, optimization, and regression modeling was developed to estimate key AD biomarkers: PET-amyloid standardized uptake value ratio (SUVR), CSF phosphorylated tau (p-tau181), Free and Cued Selective Reminding Test (FCSRT), and Mini-Mental State Examination (MMSE) scores.
RESULTS: Regression models using ERP features from dementia participants demonstrated strong correlations (r = 0.8-0.94, p < 0.01) between predicted and true PET-amyloid SUVR, p-tau181, FCSRT, and MMSE values. In an independent external cohort, PET-amyloid SUVR predictions remained significantly associated with true values (r = 0.60, p < 0.01).
DISCUSSION: Despite limitations, these preliminary results support EPT's potential as a sensitive and non-invasive method for estimating AD-related biomarkers in a clinically enriched AD cohort. Further validation studies are ongoing.
METHODS: We evaluated Evoked Potential Tomography (EPT), an EEG-based method using a novel visual evoked potential protocol. An automated pipeline for EEG preprocessing, ERP extraction, feature selection, optimization, and regression modeling was developed to estimate key AD biomarkers: PET-amyloid standardized uptake value ratio (SUVR), CSF phosphorylated tau (p-tau181), Free and Cued Selective Reminding Test (FCSRT), and Mini-Mental State Examination (MMSE) scores.
RESULTS: Regression models using ERP features from dementia participants demonstrated strong correlations (r = 0.8-0.94, p < 0.01) between predicted and true PET-amyloid SUVR, p-tau181, FCSRT, and MMSE values. In an independent external cohort, PET-amyloid SUVR predictions remained significantly associated with true values (r = 0.60, p < 0.01).
DISCUSSION: Despite limitations, these preliminary results support EPT's potential as a sensitive and non-invasive method for estimating AD-related biomarkers in a clinically enriched AD cohort. Further validation studies are ongoing.