Quantitative EEG as a biomarker in mild cognitive impairment with Lewy bodies

Abstract

Objectives: To investigate using quantitative EEG (1) differences between patients with mild cognitive impairment with Lewy bodies (MCI-LB) and MCI with Alzheimer’s disease (MCI-AD) and (2) its utility as a potential biomarker for early differential diagnosis. Methods: We analyzed eyes-closed, resting state, high-density EEG data from highly phenotyped participants (39 MCI-LB, 36 MCI-AD, and 31 healthy controls). EEG measures included spectral power in different frequency bands (delta, theta, pre-alpha, alpha, and beta), theta/alpha ratio, dominant frequency, and dominant frequency variability. Receiver operating characteristics (ROC) analyses were performed to assess diagnostic accuracy. Results: There was a shift in power from beta and alpha frequency bands towards slower frequencies in the pre-alpha and theta range in MCI-LB compared to healthy controls. Additionally, dominant frequency was slower in MCI-LB compared to controls. We found significantly increased pre-alpha power, decreased beta power, and slower dominant frequency in MCI-LB compared to MCI-AD. EEG abnormalities were more apparent in MCI-LB cases with more diagnostic features. There were no significant differences between MCI-AD and controls. In the ROC analysis to distinguish MCI-LB from MCI-AD, beta power and dominant frequency showed the highest area under the curve values of 0.71 and 0.70, respectively. While specificity was high for some measures (up to 0.97 for alpha power and 0.94 for theta/alpha ratio), sensitivity was generally much lower. Conclusions: Early EEG slowing is a specific feature of MCI-LB compared to MCI-AD. However, there is overlap between the two MCI groups which makes it difficult to distinguish between them based on EEG alone.

The Role of EEG in the Diagnosis, Prognosis and Clinical Correlations of Dementia with Lewy Bodies—A Systematic Review

“…Quantitative EEG findings of MCI-LB have been reported to be similar to those reported in DLB vs. AD, where MCI-LB have lower dominant frequency compared to MCI-AD [ 65 , 66 , 67 ]. This also translates into higher pre-alpha power and lower alpha and beta power and a higher theta/alpha ratio [ 65 , 66 , 67 ].…”

“…AD, where MCI-LB have lower dominant frequency compared to MCI-AD [ 65 , 66 , 67 ]. This also translates into higher pre-alpha power and lower alpha and beta power and a higher theta/alpha ratio [ 65 , 66 , 67 ]. Schumacher 2020b reported that spectral power analyses had sensitivities of 23–51%, specificity of 81–97% and area under receiver operating characteristics curve (AUROC) of 0.54–0.71 in diagnosing MCI-LB ( Table 4 ) [ 67 ].…”

“…This also translates into higher pre-alpha power and lower alpha and beta power and a higher theta/alpha ratio [ 65 , 66 , 67 ]. Schumacher 2020b reported that spectral power analyses had sensitivities of 23–51%, specificity of 81–97% and area under receiver operating characteristics curve (AUROC) of 0.54–0.71 in diagnosing MCI-LB ( Table 4 ) [ 67 ]. On the other hand, van der Zande 2020 reported AUROC of 0.76–0.97 but sensitivities and specificities were not reported [ 66 ].…”

“…The slowing of dominant frequency with its associated spectral power features had moderate (AUROC 0.54–0.71, sensitivities 23–51%, specificities 81–97%) to good (AUROC 0.76–0.97) performance in diagnosing MCI-LB [ 66 , 67 ]. Thus, potentially at the prodromal stage, EEG may be comparable to dopaminergic imaging which had a sensitivity of 61% and specificity of 89% in diagnosing MCI-LB [ 75 ].…”