Corticospinal Tract Microstructure Predicts Distal Arm Motor Improvements in Chronic Stroke

Bokkyu Kim; Nicolas Schweighofer; Justin P Haldar; Richard M Leahy; Carolee J Winstein

doi:10.1097/NPT.0000000000000363

Corticospinal Tract Microstructure Predicts Distal Arm Motor Improvements in Chronic Stroke

J Neurol Phys Ther. 2021 Oct 1;45(4):273-281. doi: 10.1097/NPT.0000000000000363.

Authors

Bokkyu Kim¹, Nicolas Schweighofer, Justin P Haldar, Richard M Leahy, Carolee J Winstein

Affiliation

¹ Department of Physical Therapy Education, SUNY Upstate Medical University, Syracuse, New York (B.K.); Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles (B.K., N.S., C.J.W.); Neuroscience Graduate Program, University of Southern California, Los Angeles (N.S.); Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles (J.P.H., R.M.L.); Brain and Creativity Institute, University of Southern California, Los Angeles (J.P.H., R.M.L.); and Department of Neurology, University of Southern California, Los Angeles (C.J.W.).

Abstract

Background and purpose: The corticospinal tract (CST) is a crucial brain pathway for distal arm and hand motor control. We aimed to determine whether a diffusion tensor imaging (DTI)-derived CST metric predicts distal upper extremity (UE) motor improvements in chronic stroke survivors.

Methods: We analyzed clinical and neuroimaging data from a randomized controlled rehabilitation trial. Participants completed clinical assessments and neuroimaging at baseline and clinical assessments 4 months later, postintervention. Using univariate linear regression analysis, we determined the linear relationship between the DTI-derived CST fractional anisotropy asymmetry (FAasym) and the percentage of baseline change in log-transformed average Wolf Motor Function Test time for distal items (ΔlnWMFT-distal_%). The least absolute shrinkage and selection operator (LASSO) linear regressions with cross-validation and bootstrapping were used to determine the relative weighting of CST FAasym, other brain metrics, clinical outcomes, and demographics on distal motor improvement. Logistic regression analyses were performed to test whether the CST FAasym can predict clinically significant UE motor improvement.

Results: lnWMFT-distal significantly improved at the group level. Baseline CST FAasym explained 26% of the variance in ΔlnWMFT-distal_%. A multivariate LASSO model including baseline CST FAasym, age, and UE Fugl-Meyer explained 39% of the variance in ΔlnWMFT-distal_%. Further, CST FAasym explained more variance in ΔlnWMFT-distal_% than the other significant predictors in the LASSO model.

Discussion and conclusions: CST microstructure is a significant predictor of improvement in distal UE motor function in the context of an UE rehabilitation trial in chronic stroke survivors with mild-to-moderate motor impairment.Video Abstract available for more insight from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A350).

Trial registration: ClinicalTrials.gov NCT00174935.

Publication types

Randomized Controlled Trial
Research Support, N.I.H., Extramural
Video-Audio Media

MeSH terms

Arm
Diffusion Tensor Imaging
Humans
Pyramidal Tracts / diagnostic imaging
Stroke Rehabilitation*
Stroke* / diagnostic imaging
Upper Extremity

Associated data

ClinicalTrials.gov/NCT00174935

Abstract

Publication types

MeSH terms

Associated data

Grants and funding