https://www.selleckchem.com/products/guanosine-5-triphosphate-trisodium-salt.html Graph theory has been applied to study the pathophysiology of multiple sclerosis (MS) since it provides global and focal measures of brain networks properties that are affected by MS. Typically, the connections strength and, consequently, the network(s) properties are computed by counting the number of streamlines (NOS) connecting couples of grey matter regions. However, recent studies have shown that this method is not quantitative. We evaluated diffusion-based microstructural measures extracted from three different models to assess the network properties in a group of sixty-six MS patients and sixty-four healthy subjects. Besides, we assessed their correlation with patients' disability and with a biological measure of neuroaxonal damage. Graph metrics extracted from connectomes weighted by intra-axonal microstructural components were the most sensitive to MS pathology and the most related to clinical disability. On the other hand, measures of network segregation extracted from the connectomes weighted by maps describing extracellular diffusivity were the most related to serum concentration of neurofilament light chain. Network properties assessed with NOS were neither sensitive to MS pathology nor correlated with clinical and pathological measures of disease impact in MS patients. Using tractometry-derived graph measures in MS patients, we identified a set of metrics based on microstructural components that are highly sensitive to the disease and that provide sensitive correlates of clinical and biological deterioration in MS patients. Using tractometry-derived graph measures in MS patients, we identified a set of metrics based on microstructural components that are highly sensitive to the disease and that provide sensitive correlates of clinical and biological deterioration in MS patients.Introduction Diffusion magnetic resonance imaging (MRI) allows noninvasive assessment of white