ORIGINAL RESEARCH article

Front. Hum. Neurosci.

Sec. Brain Imaging and Stimulation

Volume 19 - 2025 | doi: 10.3389/fnhum.2025.1598598

Early Corticospinal tract Sub-Pathway Lesion Load and Integrity Predict Post-Stroke Motor Outcomes

Provisionally accepted
Xin  WenXin Wen1Wentao  ZengWentao Zeng1Chiyin  LiChiyin Li2Yue  QinYue Qin3Yanqiang  QiaoYanqiang Qiao3Tao  LuTao Lu4Wanghuan  DunWanghuan Dun5Ming  ZhangMing Zhang4*Junya  MuJunya Mu1*
  • 1The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
  • 2Xi'an Academy of Fine Arts, Xi'an, Shaanxi Province, China
  • 3Department of Radiology, Xi'an Daxing Hospital, Xi'an, Shanxi Province, China
  • 4Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
  • 5Department of Rehabilitation Medicine, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China

The final, formatted version of the article will be published soon.

Introduction. Growing evidence suggests that corticospinal tract (CST) damage and microstructural integrity are key predictors of post-stroke motor impairment. However, their combined clinical utility-particularly in CST sub-pathways originating from non-primary motor cortical areasremains underexplored. This study aimed to determine whether microstructural integrity and lesion load (LL) of each CST sub-pathway at 2 weeks predict motor outcomes at 2, 6, and 12 weeks poststroke.Methods. 57 participants completed motor and neuroimaging evaluations at 2 weeks post-stroke and underwent follow-up motor assessments at 6 (n = 37) and 12 weeks (n = 34). The integrity of the CSTs was quantified using diffusion spectrum imaging (DSI), while CST-LL was measured using structural magnetic resonance imaging, both based on the sensorimotor area tract template atlas. Multivariable regression models were used to assess the predictive value of CST microstructural integrity and CST-LL in each sub-pathway at 2 weeks for motor function at 2, 6, and 12 weeks poststroke.Results. Stepwise multiple linear regression analyses showed CST integrity and CST-LL were both the main determinants of motor deficit at 2 weeks post-stroke. Specifically, the integrity of CSTs from the primary motor cortex (M1), reflected by fractional anisotropy, emerged as a significant predictor of post-stroke motor deficits at 2 weeks, whereas CST integrity from the dorsal premotor cortex (PMd), reflected by generalized fractional anisotropy, quantitative anisotropy, and radial diffusivity. CST-LL originating from non-M1 motor areas, such as primary sensory cortex (S1), were also the main determinants for motor impairment at 2 weeks post-stroke. However, compared to CST integrity, CST-LL from non-M1 motor areascortical origins, including both the PMd and S1, were more dominant predictors, explaining 68.3% (R 2 adjusted = 0.683, p < 0.001) and 79.5% (R 2 adjusted = 0.795, p < 0.001) of the variance in motor outcomes at 6 and 12 weeks.Conclusions. The microstructural integrity of the PMd tracts and CST-LL from the non-M1 motor areas may be promising biomarker for post-stroke motor impairment. These findings highlight the pivotal role of non-M1 tracts in post-stroke motor function, particularly the PMd tracts, as a potential intervention target to enhance motor recovery.

Keywords: Stroke, motor recovery, corticospinal tract, Diffusion spectrum imaging, Lesion Load

Received: 23 Mar 2025; Accepted: 28 May 2025.

Copyright: © 2025 Wen, Zeng, Li, Qin, Qiao, Lu, Dun, Zhang and Mu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Ming Zhang, Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
Junya Mu, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China

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