Structural brain network metrics as novel predictors of treatment response in restless legs syndrome

Abstract

Objective

This study aimed to investigate morphometric similarity networks in patients with newly diagnosed restless legs syndrome (RLS) compared with healthy controls and to examine their relationship with treatment response.

Methods

A total of 49 patients with newly diagnosed RLS and 58 healthy controls were prospectively enrolled. Brain magnetic resonance imaging was performed using a 3-T scanner, and morphometric similarity network analysis was conducted on T1-weighted images. The severity of RLS was assessed using the International RLS Scale at baseline and at three months post-treatment initiation. Patients were classified as good or poor responders based on a decrease of ≥5 points in RLS severity scores following treatment with either pramipexole or pregabalin.

Results

Although no significant differences were observed in morphometric similarity networks between patients with RLS and controls, both modularity and small-worldness indices were lower in the RLS group (0.218 vs. 0.258, p = 0.023; 0.841 vs. 0.861, p = 0.042). Among the 40 patients who completed follow-up evaluation, 27 were good responders and 13 were poor responders. Network diameter was significantly higher in good responders than in poor responders (7.061 vs. 6.552, p = 0.002). Similarly, eccentricity was elevated in good responders (5.875 vs. 5.385, p = 0.008). Receiver operating characteristic curve analysis revealed high predictive values for both diameter and eccentricity (AUC = 0.838, p < 0.001; AUC = 0.751, p = 0.002, respectively).

Conclusion

Network metrics, particularly diameter and eccentricity, demonstrate potential utility as biomarkers for predicting treatment response in patients with RLS.