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Corticospinal tract lesion load: An imaging biomarker for stroke motor outcomes
Open accessAbstract
Objective: The aim of this work was to investigate whether an imaging measure of corticospinal tract (CST) injury in the acute phase can predict motor outcome at 3 months in comparison to clinical assessment of initial motor impairment. Methods: A two‐site prospective cohort study followed up a group of first‐ever ischemic stroke patients using the Upper‐Extremity Fugl‐Meyer (UE‐FM) Scale to measure motor impairment in the acute phase and at 3 months. A weighted CST lesion load (wCST‐LL) was calculated by overlaying the patient's lesion map on magnetic resonance imaging with a probabilistic CST constructed from healthy control subjects. Regression models were fit to assess the predictive value of wCST‐LL and compared with initial motor impairment. Results: Seventy‐six patients (37 from cohort 1 and 39 from cohort 2) completed the study. wCST‐LL as well as assessment of motor impairment (UE‐FM) in the acute phase correlated with motor impairment (UE‐FM) at 3 months in both cohort 1 (R 2 = 0.69 vs. R 2 = 0.67; p = 0.43) and cohort 2 (R 2 = 0.69 vs. R 2 = 0.62; p = 0.25). In the severely impaired subgroup (defined as UE‐FM ≤ 10 at baseline), wCST‐LL correlated with outcomes significantly better than clinical assessment (R 2 = 0.47 vs. R 2 = 0.11; p = 0.03). In the nonseverely impaired subgroup, stroke patients recovered approximately 70% of their maximal recovery potential. All stroke patients in both cohorts had poor motor outcomes at 3 months (defined as UE‐FM ≤ 25) when wCST‐LL was ≥ 7.0 cc (positive predictive value was 100%). Interpretation: wCST‐LL, an imaging biomarker determined in the acute phase, can predict poststroke motor outcomes at 3 months, especially in patients with severe impairment at baseline. Ann Neurol 2015;78:860–870
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Kleim, J. A., Chan, S., Pringle, E., Schallert, K., Procaccio, V., Jimenez, R., & Cramer, S. C. (2006) · Nature Neuroscience · doi:10.1038/nn1699 · Cited by 529
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Spontaneous and Therapeutic-Induced Mechanisms of Functional Recovery After Stroke
Cassidy, J. M., & Cramer, S. C. (2017) · Translational Stroke Research · doi:10.1007/s12975-016-0467-5 · Cited by 292
Adans-Dester, C., Hankov, N., O’Brien, A., Vergara-Diaz, G., Black-Schaffer, R., Zafonte, R., Dy, J., Lee, S. I., & Bonato, P. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-00328-w · Cited by 130
Predicting motor outcomes in stroke patients using diffusion Spectrum mri microstructural measures
Hodgson, K., Adluru, G., Richards, L. G., Majersik, J. J., Stoddard, G., Adluru, N., & DiBella, E. (2019) · Frontiers in Neurology · doi:10.3389/fneur.2019.00072 · Cited by 36
Montane, E., Brihmat, N., Cormier, C., Thalamas, C., Rousseau, V., Tap, G., De Boissezon, X., Castel-Lacanal, E., Baclotox Group, & Marque, P. (2025) · JMIR Research Protocols · doi:10.2196/62951 · Cited by 4
Metadata
- Authors
- Feng, W., Wang, J., Chhatbar, P. Y., Doughty, C., Landsittel, D., Lioutas, V., Kautz, S. A., & Schlaug, G.
- Venue
- Annals of Neurology
- Publisher
- Wiley
- Published
- 2015-10-31
- Volume
- 78
- Issue
- 6
- Pages
- 860-870
- ISSN
- 0364-5134 (ISSN-L)
- 1531-8249
- OpenAlex
- W2131456668
- Cited by
- 333
- References
- 1
- FWCI
- 26.93
- Type
- journal article
- Language
- en
- Open access
- green
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