Objective: To investigate the relationship between the electroencephalographic (EEG) power spectra features obtained by quantitative EEG (qEEG) and the hemodynamic parameters detected by dynamic susceptibility contrast-enhanced MR imaging (DSC MRI) in patients with Alzheimer's disease (AD).
Methods: Fourteen patients with probable AD and 15 elderly healthy controls were included in the study. All subjects underwent both EEG recording in a rest condition and perfusion MRI. Three EEG scalp areas were defined (anterior, central and posterior) and power spectra values were obtained from each scalp area. Relative values of temporoparietal and sensorimotor regional cerebral blood volume (rCBV) were measured bilaterally and successively averaged to obtain a total perfusion index. The brain atrophy index was calculated and used as a covariate to rCBV. Correlation analysis was performed between EEG variables and hemodynamic-morphological parameters.
Results: qEEG power spectra of AD patients were characterized by an increase in mean relative power of theta (4-7.75 Hz) associated with a decrease in alpha (8-12.75 Hz) frequency bands with a topographic distribution over the central and posterior EEG scalp regions, when compared with controls; beta (13-31 Hz) frequency band also displayed a significant decrease over the anterior and posterior EEG scalp regions of AD patients with respect to controls. The DSC MRI revealed a bilateral reduction in the temporoparietal and sensorimotor rCBV with respect to controls. Correlation analysis showed that the total level of hypoperfusion selectively correlates with the EEG power spectra in theta and alpha frequency bands distributed over anterior/central and central region, respectively. Within AD patients, the lower the level of hypoperfusion, the higher the content of EEG power spectra in theta frequency band, and the lower the level of hypoperfusion, the lower the content of EEG power spectra in alpha band.
Conclusions: The combined qEEG and DSC MRI technology unveiled a selective correlation between neurophysiological and hemodynamical patterns in AD patients. Further investigations will ascertain the relevance of this multi-modal approach in the heterogeneous clinical context of AD.