Structural connectivity in multiple sclerosis and modeling of disconnection.

Area of Science:

• Neuroscience
• Medical Imaging
• Network Science

Background:

• Multiple sclerosis (MS) is characterized by white matter damage.
• Brain lesions in MS can be modeled as network disconnection events.

Purpose of the Study:

• To evaluate if modeling lesion-induced disconnection explains motor and cognitive impairments in MS patients.
• To assess the impact of simulated disconnections on brain network metrics in different MS phenotypes.

Main Methods:

• Structural connectivity was derived using MRI tractography in 227 MS patients and 50 healthy controls (HCs).
• Disconnection was modeled by assessing the likelihood of pathways traversing lesions.
• Network metrics were compared across MS phenotypes (RRMS, SPMS, benign MS) and correlated with clinical scores.

Main Results:

• Global network metrics differentiated RRMS from SPMS and benign MS, but not SPMS from benign MS.
• Simulated disconnection minimally altered network differences between benign MS and RRMS.
• Specific network nodes correlated with motor and cognitive deficits, with slightly stronger correlations post-disconnection.

Conclusions:

• The brain network demonstrates robustness against damage from MS lesions.
• Modeled disconnection provides insights into the neural correlates of motor and cognitive dysfunction in MS.