Network Damage Predicts Clinical Worsening in Multiple Sclerosis: A 6.4-Year Study

Area of Science:

• Neuroimaging
• Neurology
• Radiology

Background:

• Multiple sclerosis (MS) causes clinical impairment through structural damage and altered brain function.
• Predicting long-term disability progression in MS is crucial for patient management.

Purpose of the Study:

• To assess the added value of integrating structural and functional network magnetic resonance imaging (MRI) measures for predicting long-term (6.4-year) clinical disability deterioration in MS.
• To identify specific MRI network patterns associated with clinical worsening and conversion to secondary progressive MS (SPMS).

Main Methods:

• Baseline 3D T1-weighted and resting-state functional MRI scans were acquired from 233 MS patients and 77 healthy controls.
• Patients underwent neurologic evaluations at baseline and a median 6.4-year follow-up.
• Independent component analysis identified functional connectivity (FC) and gray matter (GM) network patterns; random forest models predicted clinical outcomes.

Main Results:

• 45% of patients worsened clinically; 16% of relapsing-remitting MS (RRMS) patients converted to SPMS.
• Predictors of clinical worsening included normalized GM/brain volumes, decreased default-mode network FC, increased sensorimotor network (SMN) FC, and GM atrophy in the fronto-parietal network.
• Baseline disability, normalized GM volume, and SMN GM atrophy predicted SPMS conversion.

Conclusions:

• Integrating network MRI measures enhances the prediction of disability worsening and SPMS conversion in MS.
• These findings highlight the combined roles of global/local gray matter damage and functional reorganization in MS clinical deterioration.