Ensemble average propagator-based detection of microstructural alterations after stroke.

Area of Science:

• Neuroimaging
• Biomarkers
• Diffusion Spectrum Imaging (DSI)

Background:

• Diffusion weighted signal reconstruction techniques are evolving.
• Previous studies highlighted the utility of 3D-SHORE derived indices for neural plasticity assessment post-stroke.

Purpose of the Study:

• To extend the analysis of 3D-SHORE indices to include return to the plane/origin (RTPP/RTOP) probabilities.
• To evaluate these indices across various motor networks and time scales.
• To assess their potential as numerical biomarkers for neural plasticity after stroke.

Main Methods:

• Diffusion Spectrum Imaging (DSI) scans were acquired from 10 stroke patients at 1 week, 1 month, and 6 months post-stroke, and from 10 controls.
• 3D-SHORE was employed for signal reconstruction, followed by derivation of microstructural indices.
• Tract-based analysis was conducted on motor cortical, subcortical, and transcallosal networks in the contralesional area.

Main Results:

• Propagator anisotropy and generalized fractional anisotropy showed high stability (ICC > 0.94) in the subcortical loop.
• New indices demonstrated high stability in the transcallosal network and performed well in other networks, with some exceptions.
• The indices successfully differentiated stroke patients from controls across most time scales.
• A regression model using subcortical loop indices at 1 week post-stroke best predicted clinical outcome.

Conclusions:

• The microstructural indices derived from 3D-SHORE offer precise measurements.
• These novel indices can distinguish patients from controls in most analyzed networks.
• 3D-SHORE indices in subcortical connections show promise as predictive biomarkers for clinical outcomes and neuronal plasticity post-stroke.