Diffusion tensor imaging for predicting hand motor outcome in chronic stroke patients.

Area of Science:

• Neuroimaging
• Neurology
• Rehabilitation Medicine

Background:

• Diffusion tensor imaging (DTI) parameters have shown associations with clinical outcomes in stroke survivors.
• Predicting hand function recovery is crucial for rehabilitation planning in chronic stroke patients.

Purpose of the Study:

• To investigate the predictive value of DTI parameters for hand function outcomes in chronic stroke patients.
• To explore correlations between specific DTI metrics and clinical assessments of hand function.

Main Methods:

• DTI parameters including rλ1, rλ23, fractional anisotropy (rFA), and mean diffusivity (rMD) were analyzed.
• Two analysis methods were employed: segment of the corticospinal tract (sCST) and pure region of interest (ROI).
• Spearman's correlation coefficient assessed the relationship between DTI parameters and Fugl-Meyer Assessment (FMA) and National Institutes of Health Stroke Scale (NIHSS).

Main Results:

• Significant differences in rFA and rλ23 (sCST analysis) and rMD and rλ23 (ROI analysis) were observed between patients with completely vs. partially paralyzed hands.
• rλ23 (sCST analysis) showed a significant correlation with NIHSS scores.
• rMD (sCST analysis) demonstrated a significant correlation with hand function as measured by the FMA.

Conclusions:

• DTI parameters, specifically rFA, rλ23, and rMD, show potential as predictors of hand function recovery in chronic stroke.
• These DTI metrics may aid in evaluating prognosis and guiding therapeutic strategies for hand motor deficits post-stroke.