Bilateral corticospinal tract asymmetry predicts motor recovery after transcranial direct current stimulation in subacute stroke patients

Motivation: A reliable neuroimaging biomarker to predict motor improvement after neuromodulation is lacking. Goal(s): We compared the integrity of bilateral corticospinal tracts and evaluated the asymmetry before tDCS. The association between the motor improvement and pretreatment integrity of the CST was identified to predict motor recovery in subacute stroke patients. Approach: We calculated the asymmetry and fractional anisotropy between bilateral CST. The linear regression analysis was conducted to predict the motor recovery. Results: The patients with more severe motor impairment have higher asymmetry in CST. The tDCS regression models achieved an R2=0.796 and 0.624 for predicting FMA at three months after stroke onset. Impact: The ischemic stroke patients with higher degree of right white matter integrity have better response to neural modulation effects of tDCS treatment. The identified DTI predictors could be the basis for optimizing the treatment protocols of tDCS in stroke patient.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/0078
Primary Topic
Transcranial Magnetic Stimulation Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bilateral corticospinal tract asymmetry predicts motor recovery after transcranial direct current stimulation in subacute stroke patients

Bing‐Fong Lin, Shih‐Pin Hsu, I‐Hui Lee, Chia‐Feng Lu et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Transcranial Magnetic Stimulation Studies
article

Bilateral corticospinal tract asymmetry predicts motor recovery after transcranial direct current stimulation in subacute stroke patients

Bing‐Fong Lin, Shih‐Pin Hsu, I‐Hui Lee, Chia‐Feng Lu, Wei Yang
article en

Abstract

Motivation: A reliable neuroimaging biomarker to predict motor improvement after neuromodulation is lacking. Goal(s): We compared the integrity of bilateral corticospinal tracts and evaluated the asymmetry before tDCS. The association between the motor improvement and pretreatment integrity of the CST was identified to predict motor recovery in subacute stroke patients. Approach: We calculated the asymmetry and fractional anisotropy between bilateral CST. The linear regression analysis was conducted to predict the motor recovery. Results: The patients with more severe motor impairment have higher asymmetry in CST. The tDCS regression models achieved an R2=0.796 and 0.624 for predicting FMA at three months after stroke onset. Impact: The ischemic stroke patients with higher degree of right white matter integrity have better response to neural modulation effects of tDCS treatment. The identified DTI predictors could be the basis for optimizing the treatment protocols of tDCS in stroke patient.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Good health and well-being
Openalex Percentile: Top 76%
Transcranial Magnetic Stimulation Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.