EEG Markers of Dementia with Lewy Bodies: A Multicenter Cohort Study

E-DLB study group

Research output: Contribution to journalArticlepeer-review

Abstract

Quantitative EEG (QEEG) has demonstrated good discriminative capacity for dementia with Lewy bodies (DLB) diagnosis as compared to Alzheimer's disease (AD) with a predictive value of 100 in a single cohort study. EEG in DLB was characterized by a dominant frequency (DF) in pre-alpha (5.5-7.5Hz), theta, or delta bands and DF variability (DFV) >1.2Hz, frequency prevalence (FP) pre-alpha in >40 and FP alpha in <32 of the epochs. To validate the aforementioned QEEG findings in independent cohorts of clinically diagnosed DLB versus AD patients, we analyzed EEG traces of 79 DLB and 133 AD patients (MMSE >20) collected from four European Centers. EEG traces from 19 scalp derivations were acquired as at least 10min continuous signals and epoched in off-setting as series of 2-second-long epochs, subsequently processed by Fast Fourier Transform (frequency resolution 0.5Hz). DLB patients showed EEG specific abnormalities in posterior derivations characterized by DF <8Hz FP pre-alpha >50, FP alpha <25. DFV was >0.5Hz. AD patients displayed stable alpha DF, DFV <0.5Hz, FP pre-alpha <30, and FP alpha >55. DLB and AD differed for DF (p<10-6), DFV (p<0.05), FP pre-alpha (p<10-12) and FP alpha (p<10-12). Discriminant analysis detected specific cut-offs for every EEG mathematical descriptor; DF=8, DFV=2.2Hz, FP pre-alpha=33, FP alpha=41 for posterior derivations. If at least one of the cut-off values was met, the percentage of DLB and AD patients correctly classified was 90 and 64, respectively. The findings in this multicenter study support the validity of QEEG analysis as a tool for diagnosis in DLB patients.

Original languageEnglish
Pages (from-to)1649-1657
Number of pages9
JournalJournal of Alzheimer's Disease
Volume54
Issue number4
DOIs
Publication statusPublished - Oct 18 2016

Keywords

  • Dementia with Lewy bodies
  • quantitative EEG

ASJC Scopus subject areas

  • Neuroscience(all)
  • Clinical Psychology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health

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