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Background and Purpose: Precise and timely diagnosis is crucial for the optimal use of emerging disease‐modifying treatments for Alzheimer disease (AD). Electroencephalography (EEG), which is noninvasive and cost‐effective, can capture neural abnormalities linked to various dementias. This study explores the use of individual alpha frequency (IAF) derived from EEG as a diagnostic and prognostic tool in cognitively impaired patients. Methods: This retrospective study included 375 patients from the tertiary Memory Clinic of IRCCS San Raffaele Hospital, Milan, Italy. Participants underwent clinical and neuropsychological assessments, brain imaging, cerebrospinal fluid biomarker analysis, and resting‐state EEG. Patients were categorized by amyloid status, the AT(N) classification system, clinical diagnosis, and mild cognitive impairment (MCI) progression to AD dementia. IAF was calculated and compared among study groups. Receiver operating characteristic (ROC) analysis was used to calculate its discriminative performance. Results: IAF was higher in amyloid‐negative subjects and varied significantly across AT(N) groups. ROC analysis confirmed IAF's ability to distinguish A–T–N– from the A+T+N+ and A+T–N+ groups. IAF was lower in AD and Lewy body dementia patients compared to MCI and other dementia types, with moderate discriminatory capability. Among A+ MCI patients, IAF was significantly lower in those who converted to AD within 2 years compared to stable MCI patients and predicted time to conversion (p < 0.001, R = 0.38). Conclusions: IAF is a valuable tool for dementia diagnosis and prognosis, correlating with amyloid status and neurodegeneration. It effectively predicts MCI progression to AD, supporting its use in early, targeted interventions in the context of disease‐modifying treatments. [ABSTRACT FROM AUTHOR]

Background: The amnestic presentation of mild cognitive impairment (aMCI) represents the most common prodromal stage of Alzheimer's disease (AD) dementia. There is, however, some evidence of aMCI with typical amnestic syndrome but showing long‐term clinical stability. The ability to predict stability or progression to dementia in the aMCI condition is important, particularly for the selection of candidates in clinical trials. We aimed to establish the role of in vivo biomarkers, as assessed by cerebrospinal fluid (CSF) measures and [18F]fluorodeoxyglucose (FDG)‐positron emission tomography (PET) imaging, in predicting prognosis in a large aMCI cohort. Methods: We conducted a retrospective study, including 142 aMCI subjects who had a long follow‐up (4–19 years), baseline CSF data and [18F]FDG‐PET scans individually assessed by validated voxel‐based procedures, classifying subjects into either limbic‐predominant or AD‐like hypometabolism patterns. Results: The two aMCI cohorts were clinically comparable at baseline. At follow‐up, the aMCI group with a limbic‐predominant [18F]FDG‐PET pattern showed clinical stability over a very long follow‐up (8.20 ± 3.30 years), no decline in Mini‐Mental State Examination score, and only 7% conversion to dementia. Conversely, the aMCI group with an AD‐like [18F]FDG‐PET pattern had a high rate of dementia progression (86%) over a shorter follow‐up (6.47 ± 2.07 years). Individual [18F]FDG‐PET hypometabolism patterns predicted stability or conversion with high accuracy (area under the curve = 0.89), sensitivity (0.90) and specificity (0.89). In the limbic‐predominant aMCI cohort, CSF biomarkers showed large variability and no prognostic value. Conclusions: In a large series of clinically comparable subjects with aMCI at baseline, the specific [18F]FDG‐PET limbic‐predominant hypometabolism pattern was associated with clinical stability, making progression to AD very unlikely. The identification of a biomarker‐based benign course in aMCI subjects has important implications for prognosis and in planning clinical trials. [ABSTRACT FROM AUTHOR]