https://doi.org/10.1155/2018/9867196

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Document Type

Article

Abstract

Biomarkers that capture treatment effects could improve the precision of clinical decision making for restorative therapies. We examined the performance of candidate structural, functional, and angiogenesis-related MRI biomarkers before and after a 3-week course of standardized robotic therapy in 18 patients with chronic stroke and hypothesized that results vary significantly according to stroke severity. Patients were 4.1 ± 1 months poststroke, with baseline arm Fugl-Meyer scores of 20–60. When all patients were examined together, no imaging measure changed over time in a manner that correlated with treatment-induced motor gains. However, when also considering the interaction with baseline motor status, treatment-induced motor gains were significantly related to change in three functional connectivity measures: ipsilesional motor cortex connectivity with (1) contralesional motor cortex (p= 0.003), (2) contralesional dorsal premotor cortex (p= 0.005), and (3) ipsilesional dorsal premotor cortex (p= 0.004). In more impaired patients, larger treatment gains were associated with greater increases in functional connectivity, whereas in less impaired patients larger treatment gains were associated with greater decreases in functional connectivity. Functional connectivity measures performed best as biomarkers of treatment effects after stroke. The relationship between changes in functional connectivity and treatment gains varied according to baseline stroke severity. Biomarkers of restorative therapy effects are not one-size-fits-all after stroke.

Digital Object Identifier (DOI)

https://doi.org/10.1155/2018/9867196

APA Citation

Quinlan, E. B., Dodakian, L., See, J., McKenzie, A., Stewart, J. C., & Cramer, S. C. (2018). Biomarkers of rehabilitation therapy vary according to stroke severity. Neural Plasticity, 2018, 1–8. https://doi.org/10.1155/2018/9867196

Rights

© 2018 Erin Burke Quinlan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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