Combining diffusion tensor imaging and gray matter volumetry to investigate motor functioning in chronic stroke

Area of Science:

• Neuroscience
• Radiology
• Rehabilitation Medicine

Background:

• Motor impairment after stroke is often linked to the corticospinal tract (CST), but significant variability in recovery remains unexplained.
• Accurate prediction of long-term motor function is crucial for effective neurorehabilitative strategies following ischemic stroke.

Purpose of the Study:

• To investigate if combining diffusion tensor imaging (DTI) and gray matter (GM) volumetry enhances the characterization of long-term motor deficits in chronic stroke patients compared to using either method alone.

Main Methods:

• Recruited 31 chronic stroke patients with initial upper extremity weakness (MRC grade ≤ 3/5).
• Assessed motor impairment using the Upper Extremity Fugl-Meyer (UE-FM) assessment.
• Calculated fractional anisotropy ratio (CSTratio) from DTI and volume of interest ratio (VOIratio) for GM in motor-related regions and the temporal lobe.

Main Results:

• Both CSTratio and VOIratio (motor regions, temporal lobe) correlated with UE-FM scores.
• A multiple regression model incorporating CSTratio and VOIratio of the caudate nucleus explained 40.7% of UE-FM variability.
• Individual predictors showed lower explanatory power: CSTratio (29.4% adjusted R²) and caudate nucleus VOIratio (23.1% adjusted R²).

Conclusions:

• Combining DTI and GM volumetry provides a more comprehensive explanation of long-term motor deficits in stroke survivors than individual imaging techniques.
• This integrated neuroimaging approach may guide the selection of optimal neurorehabilitative interventions for stroke patients.