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Integrated neuroimaging and robotic rehabilitation in chronic stroke: Neural correlates and predictors of motor recovery

  • Authors:
    • Maria Magouni
    • Loukas G. Astrakas
    • Sabrina Elbach
    • A. Aria Tzika
  • View Affiliations / Copyright

    Affiliations: Medical Physics Laboratory, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece, Department of Surgery, Nuclear Magnetic Resonance Surgical Laboratory, Massachusetts General Hospital, Boston, MA 02114, United States
    Copyright: © Magouni et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 182
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    Published online on: July 28, 2025
       https://doi.org/10.3892/etm.2025.12932
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Abstract

Chronic stroke survivors are frequently afflicted with persistent motor impairments. Neural mechanisms underlying recovery and predictors of rehabilitation response remain poorly understood. Advances in MRI‑compatible robotic devices have enabled the integration of neuroimaging with targeted therapy, allowing for the real‑time assessment of brain plasticity. The present study aimed to identify neuroimaging biomarkers of motor performance and recovery in patients with chronic stroke using functional MRI (fMRI), diffusion tensor imaging and robotic‑assisted therapy. In total, 14 patients with chronic stroke (8 women, 6 men; mean age, 55.2±12.2 years) with left middle cerebral artery infarcts from Massachusetts General Hospital (Boston, USA) underwent a 10‑week home‑based rehabilitation program using an MRI‑compatible robotic hand device. Motor outcomes were assessed using the Fugl‑Meyer assessment for upper extremity (FMA‑UE), Box and Block Test (BBT) and grip strength. Imaging data from 210 sessions were then analyzed to evaluate the degree of task‑related brain activation and white matter integrity. Generalized linear mixed models revealed that focused activation in the ipsilesional primary motor cortex (M1) was positively associated with BBT (B=7.57; P<0.001) and grip strength (B=8.65; P<0.001). By contrast, activation in the contralesional ventral premotor cortex was found to be negatively associated with motor outcomes (B=‑2.89; P<0.001). Higher fractional anisotropy (FA) in the corticospinal tract and posterior limb of the internal capsule was positively associated with motor performance (FMA‑UE, B=133.10; P<0.001), whilst higher FA in the posterior corona radiata was negatively associated with motor performance (BBT: B=‑1,409.10; P<0.001). Rehabilitation‑induced improvements were also associated with increased ipsilesional M1 activation (B=0.67; P=0.002) and recruitment of the contralesional dorsal premotor cortex (B=3.43; P<0.001). In conclusion, these data suggest that recovery from chronic stroke is supported by lateralized motor network engagement and preserved white matter integrity. Therefore, neuroimaging biomarkers may be exploited for guiding personalized rehabilitation strategies and predicting the patients' response to rehabilitation.
View Figures

Figure 1

Evolution of FMA-UE, BBT and grip
strength (Force) in lbf across imaging sessions for all patients
(ID). Session 1 was conducted before the start of rehabilitation
(baseline), sessions 2, 3, and 4 occurred during rehabilitation (1
month apart), and session 5 was 1-month post-rehabilitation. Note
that in some cases, ID lines overlap completely and are obscured.
FMA-UE, Fugl-Meyer assessment upper extremity; BBT, Box and Blocks
Test. Lbf, pound-force.

Figure 2

Representative baseline imaging
findings in (A) patient no. 14 of Table I without post-rehabilitation motor
improvement and (B) patient no 13 with post-rehabilitation motor
improvement. FLAIR images reveal the site and extent of the stroke
lesions (white arrow). Axial T1-weighted imaging have superimposed
fMRI statistical parametric SPM(T) color maps depicting brain
activation. Note the difference between the focal bilateral hyper
activation posterior to the M1 (A) and the dispersed mild
activation pattern including normal activation of the SMA and M1 in
(B). In both cases, FA mapping reveals preserved corticospinal
tract integrity at the left lesioned hemisphere, though the
measured mean FA value of 0.44 in (A) lies at the lower end of the
normal reference range (0.44-0.64) compared to the FA of 0.53 in
(B). fMRI, functional MRI; FA, Fractional Anisotropy; FLAIR, fluid
attenuation inversion recovery; SMA, supplementary motor area; M1,
primary motor cortex.

Figure 3

Circular scatter plots comparing
observed values with generalized linear mixed model-predicted
FMA-UE and Δ(FMA-UE) values. Circle color (counts) reflect the
number of overlapping data points at that location (i.e., the
frequency of identical value pairs). FMA-UE, Fugl-Meyer assessment
upper extremity.
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Copy and paste a formatted citation
Spandidos Publications style
Magouni M, Astrakas LG, Elbach S and Tzika A: Integrated neuroimaging and robotic rehabilitation in chronic stroke: Neural correlates and predictors of motor recovery. Exp Ther Med 30: 182, 2025.
APA
Magouni, M., Astrakas, L.G., Elbach, S., & Tzika, A. (2025). Integrated neuroimaging and robotic rehabilitation in chronic stroke: Neural correlates and predictors of motor recovery. Experimental and Therapeutic Medicine, 30, 182. https://doi.org/10.3892/etm.2025.12932
MLA
Magouni, M., Astrakas, L. G., Elbach, S., Tzika, A."Integrated neuroimaging and robotic rehabilitation in chronic stroke: Neural correlates and predictors of motor recovery". Experimental and Therapeutic Medicine 30.4 (2025): 182.
Chicago
Magouni, M., Astrakas, L. G., Elbach, S., Tzika, A."Integrated neuroimaging and robotic rehabilitation in chronic stroke: Neural correlates and predictors of motor recovery". Experimental and Therapeutic Medicine 30, no. 4 (2025): 182. https://doi.org/10.3892/etm.2025.12932
Copy and paste a formatted citation
x
Spandidos Publications style
Magouni M, Astrakas LG, Elbach S and Tzika A: Integrated neuroimaging and robotic rehabilitation in chronic stroke: Neural correlates and predictors of motor recovery. Exp Ther Med 30: 182, 2025.
APA
Magouni, M., Astrakas, L.G., Elbach, S., & Tzika, A. (2025). Integrated neuroimaging and robotic rehabilitation in chronic stroke: Neural correlates and predictors of motor recovery. Experimental and Therapeutic Medicine, 30, 182. https://doi.org/10.3892/etm.2025.12932
MLA
Magouni, M., Astrakas, L. G., Elbach, S., Tzika, A."Integrated neuroimaging and robotic rehabilitation in chronic stroke: Neural correlates and predictors of motor recovery". Experimental and Therapeutic Medicine 30.4 (2025): 182.
Chicago
Magouni, M., Astrakas, L. G., Elbach, S., Tzika, A."Integrated neuroimaging and robotic rehabilitation in chronic stroke: Neural correlates and predictors of motor recovery". Experimental and Therapeutic Medicine 30, no. 4 (2025): 182. https://doi.org/10.3892/etm.2025.12932
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