Elisa Canu1, Federica Agosta1, Silvia Basaia1, Alessandro Meani1, Sebastiano Galantucci1, Francesca Caso1, Giuseppe Magnani2, Roberto Santangelo2, Monica Falautano2, Giancarlo Comi2, Andrea Falini3, and Massimo Filippi1,2
1Neuroimaging Research Unit, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy, 2Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy, 3Department of Neuroradiology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
This
is a graph analysis study applying a new parcellation approach, which combines
the need for equal sized nodes with respecting brain anatomy, on resting state
fMRI data from a population of 247 patients with neurodegenerative cognitive
impairment (early [EO] and late onset [LO] Alzheimer’s disease (AD),
behavioural frontotemporal dementia [bvFTD], mild cognitive impairment [MCI])
and 86 controls. Compared to other groups, AD patients showed disrupted global
network connectivity, while MCI had specific regional changes,
suggesting that graph-analysis is promising to detect early features of
neurodegeneration. Global and regional graph network properties were able to
distinguish EOAD and bvFTD.