Open AccessNeuroimaging markers of global cognition in early Alzheimer's disease: A magnetic resonance imaging–electroencephalography study
Author(s) -
Waser Markus,
Benke Thomas,
DalBianco Peter,
Garn Heinrich,
Mosbacher Jochen A.,
Ransmayr Gerhard,
Schmidt Reinhold,
Seiler Stephan,
Sorensen Helge B. D.,
Jennum Poul J.
Publication year - 2019
Publication title -
brain and behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.915
H-Index - 41
ISSN - 2162-3279
DOI - 10.1002/brb3.1197
Subject(s) - neuroimaging , electroencephalography , magnetic resonance imaging , neuroscience , cognition , disease , functional magnetic resonance imaging , medicine , dementia , psychology , alzheimer's disease , pathology , radiology
Magnetic resonance imaging ( MRI ) and electroencephalography ( EEG ) are a promising means to an objectified assessment of cognitive impairment in Alzheimer's disease ( AD ). Individually, however, these modalities tend to lack precision in both AD diagnosis and AD staging. A joint MRI – EEG approach that combines structural with functional information has the potential to overcome these limitations. Materials and Methods This cross‐sectional study systematically investigated the link between MRI and EEG markers and the global cognitive status in early AD . We hypothesized that the joint modalities would identify cognitive deficits with higher accuracy than the individual modalities. In a cohort of 111 AD patients, we combined MRI measures of cortical thickness and regional brain volume with EEG measures of rhythmic activity, information processing and functional coupling in a generalized multiple regression model. Machine learning classification was used to evaluate the markers’ utility in accurately separating the subjects according to their cognitive score. Results We found that joint measures of temporal volume, cortical thickness, and EEG slowing were well associated with the cognitive status and explained 38.2% of ifs variation. The inclusion of the covariates age, sex, and education considerably improved the model. The joint markers separated the subjects with an accuracy of 84.7%, which was considerably higher than by using individual modalities. Conclusions These results suggest that including joint MRI – EEG markers may be beneficial in the diagnostic workup, thus allowing for adequate treatment. Further studies in larger populations, with a longitudinal design and validated against functional‐metabolic imaging are warranted to confirm the results.