Abstract #4033

Functional connectome architecture of Alzheimer’s disease, mild cognitive impairment and behavioral variant of frontotemporal dementia: a graph analysis study.

Elisa Canu¹, Federica Agosta¹, Silvia Basaia¹, Alessandro Meani¹, Sebastiano Galantucci¹, Francesca Caso¹, Giuseppe Magnani², Roberto Santangelo², Monica Falautano², Giancarlo Comi², Andrea Falini³, and Massimo Filippi^1,2

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.

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