Multiple Sclerosis (MS) is a chronic neurologic disease that represents a leading cause of disability in young adults. It affects the brain in both the myelin content and axonal integrity, causing structural and functional disconnection between various brain areas. Damage accumulation leads to cognitive and motor impairment.
How the structural disconnection and plasticity to reorganise the integration pathways are related is still matter of debate. Graph theory analysis is a straightforward tool to investigate how linkages are generated and integrated in a network, and the brain can be described as a complicated network of interconnected and interacting elements. Nodes denote neural elements (neurons or brain regions) that are linked by edges representing physical connections (synapses or axonal projections). Graph theory analysis applied to advanced magnetic resonance imaging (MRI), i.e. diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI), provides information on the anatomical configuration of the brain network and describes how brain regions are functionally related.
We aim to exploit network analysis to study how the structural disruption is combined with the functional reorganization in MS, since the two phenomena are intrinsically connected. We will analyse MR data of a large sample of patients with MS (n=100), who have recently underwent clinical evaluation and 3T MRI with advanced sequences, i.e. T1-3D (cortical thickness), DTI (structural connectivity) and rs-fMRI (functional connectivity). Data will be analysed on large-scale according to the graph theory.
We will analyse the relationships between structural and functional connectivity changes and the correlation between MRI and clinical data.
By determining the structural and functional substrates underlying motor and cognitive impairment in MS, the results of this research may help to guide the therapeutic approach, and in particular rehabilitative intervention strategies.
