Power Spectral Density Analysis of Long-Term Motor Recovery in Patients With Subacute Stroke

Abstract

Background: Prognostic measures of long-term motor recovery are important in patients with stroke presenting with severe hemiplegia.

Objective: We aimed to investigate whether initial power spectral density (PSD) analysis of resting-state functional magnetic resonance (fMRI) data can provide a sensitive prognostic predictor in patients with subacute stroke with severe hand disability.

Methods: Twelve patients with good recovery, 14 patients with poor recovery, and 12 healthy subjects were included. PSD analysis was performed using resting-state fMRI data. Contralesional and ipsilesional PSD in the motor cortex were measured. Pearson correlation analysis was performed to assess a possible association between the difference in ipsilesional versus contralesional PSD and motor outcomes. A receiver operating characteristic (ROC) curve was constructed to estimate the discriminative value of the difference between the ipsilesional PSD and the contralesional PSD for good versus poor recovery.

Results: There were no differences in PSD between the contralesional and ipsilesional hemispheres in the good recovery group ( P = .77). In contrast, there were significant differences in PSD between the 2 hemispheres in the poor recovery group ( P = .07). The difference in PSD between the 2 hemispheres had a positive correlation with post Brunnstrom stage scores. ROC analysis showed that the difference in PSD between the 2 hemispheres was sensitive in discriminating good versus poor recovery.

Conclusion: The present study suggests that PSD in the motor cortex may be a sensitive predictor of late-onset motor recovery following stroke.

Keywords: Motor cortex; long-term motor recovery; power spectral density (PSD); resting-state functional magnetic resonance imaging (fMRI); stroke.