Functional MRI of Rehabilitation in Chronic Stroke Patients Using Novel MR-Compatible Hand Robots

We monitored brain activation after chronic stroke by combining functional magnetic resonance imaging (fMRI) with a novel MR-compatible, hand-induced, robotic device (MR_CHIROD). We evaluated 60 fMRI datasets on a 3 T MR system from five right-handed patients with left-sided stroke ≥6 months prior and mild to moderate hemiparesis. Patients trained the paretic right hand at approximately 75% of maximum strength with an exercise ball for 1 hour/day, 3 days/week for 4 weeks. Multi-level fMRI data were acquired before, during training, upon completion of training, and after a non-training period using parallel imaging employing GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) while the participant used the MR_CHIROD. Training increased the number of activated sensorimotor cortical voxels, indicating functional cortical plasticity in chronic stroke patients. The effect persisted four weeks after training completion, indicating the potential of rehabilitation in inducing cortical plasticity in chronic stroke patients.

[1]  E. Dietrichs.  [Brain plasticity after stroke--implications for post-stroke rehabilitation]. , 2007, Tidsskrift for den Norske laegeforening : tidsskrift for praktisk medicin, ny raekke.

[2]  Robin M Heidemann,et al.  Generalized autocalibrating partially parallel acquisitions (GRAPPA) , 2002, Magnetic resonance in medicine.

[3]  Seong-Gi Kim,et al.  Effects of movement predictability on cortical motor activation , 1998, Neuroscience Research.

[4]  Jens Frahm,et al.  The cost of parallel imaging in functional MRI of the human brain. , 2006, Magnetic resonance imaging.

[5]  Constantinos Mavroidis,et al.  MR Compatible ERF-based Robotic Device for Hand Rehabilitation after Stroke , 2005 .

[6]  J C Gore,et al.  Cerebral vascular malformations adjacent to sensorimotor and visual cortex. Functional magnetic resonance imaging studies before and after therapeutic intervention. , 1997, Stroke.

[7]  B. Rosen,et al.  A Functional MRI Study of Three Motor Tasks in the Evaluation of Stroke Recovery , 2001, Neurorehabilitation and neural repair.

[8]  S J Riederer,et al.  Mapping of the central sulcus with functional MR: active versus passive activation tasks. , 1998, AJNR. American journal of neuroradiology.

[9]  N. Hogan,et al.  Robot training enhanced motor outcome in patients with stroke maintained over 3 years , 1999, Neurology.

[10]  Jonathan D. Cohen,et al.  Reproducibility of fMRI Results across Four Institutions Using a Spatial Working Memory Task , 1998, NeuroImage.

[11]  Subashan Perera,et al.  Persisting Consequences of Stroke Measured by the Stroke Impact Scale , 2002, Stroke.

[12]  P. Verschure,et al.  New Technologies and Concepts for Rehabilitation in the Acute Phase of Stroke: A Collaborative Matrix , 2007, Neurodegenerative Diseases.

[13]  Cornelius Weiller,et al.  Imaging recovery from stroke , 1998, Experimental Brain Research.

[14]  L. L. Wald,et al.  A Phased Array Echoplanar Imaging System for fMRI , 1998, NeuroImage.

[15]  G. Samsa,et al.  How strong is the relationship between functional status and quality of life among persons with stroke? , 2004, Journal of rehabilitation research and development.

[16]  Alan J Thompson,et al.  The relationship between brain activity and peak grip force is modulated by corticospinal system integrity after subcortical stroke , 2007, The European journal of neuroscience.

[17]  R.N.Dej.,et al.  The Cerebral Cortex of Man , 1951, Neurology.

[18]  Stephen M Smith,et al.  Variability in fMRI: A re‐examination of inter‐session differences , 2005, Human brain mapping.

[19]  Steen Moeller,et al.  Application of parallel imaging to fMRI at 7 Tesla utilizing a high 1D reduction factor , 2006, Magnetic resonance in medicine.

[20]  Lawrence L. Wald,et al.  Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters , 2005, NeuroImage.

[21]  N. Ward,et al.  Future perspectives in functional neuroimaging in stroke recovery. , 2007, Europa medicophysica.

[22]  B. Rosen,et al.  Motor cortex activation is related to force of squeezing , 2002, Human brain mapping.

[23]  S. Strother,et al.  Reproducibility of BOLD‐based functional MRI obtained at 4 T , 1999, Human brain mapping.

[24]  R. Poldrack.  Imaging Brain Plasticity: Conceptual and Methodological Issues— A Theoretical Review , 2000, NeuroImage.

[25]  C. Mavroidis,et al.  MR_CHIROD v.2: Magnetic Resonance Compatible Smart Hand Rehabilitation Device for Brain Imaging , 2008, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[26]  J L Lancaster,et al.  Automated Talairach Atlas labels for functional brain mapping , 2000, Human brain mapping.

[27]  Chris Rorden,et al.  Spatial Normalization of Brain Images with Focal Lesions Using Cost Function Masking , 2001, NeuroImage.

[28]  Constantinos Mavroidis,et al.  Magnetic resonance-compatible robotic and mechatronics systems for image-guided interventions and rehabilitation: a review study. , 2007, Annual review of biomedical engineering.

[29]  Christina Triantafyllou,et al.  fMRI-compatible rehabilitation hand device , 2006, Journal of NeuroEngineering and Rehabilitation.

[30]  Stephen M. Smith,et al.  Correlation between motor improvements and altered fMRI activity after rehabilitative therapy. , 2002, Brain : a journal of neurology.

[31]  Klaas P Pruessmann,et al.  Parallel Imaging at High Field Strength: Synergies and Joint Potential , 2004, Topics in magnetic resonance imaging : TMRI.

[32]  L. G. Astrakas,et al.  Proton magnetic spectroscopic imaging of the child's brain: the response of tumors to treatment , 2001, Neuroradiology.

[33]  G. Nelles,et al.  Cortical reorganization--effects of intensive therapy. , 2004, Restorative neurology and neuroscience.

[34]  Lawrence L. Wald,et al.  Effect of spatial smoothing on physiological noise in high-resolution fMRI , 2006, NeuroImage.

[35]  Rick M Dijkhuizen,et al.  Structural and functional plasticity in the somatosensory cortex of chronic stroke patients. , 2006, Brain : a journal of neurology.

[36]  Hidenao Fukuyama,et al.  Movement-related cortical potentials and regional cerebral blood flow change in patients with stroke after motor recovery , 1997, Journal of the Neurological Sciences.

[37]  Karl J. Friston,et al.  Variability in fMRI: An Examination of Intersession Differences , 2000, NeuroImage.

[38]  N. Ward.  Functional reorganization of the cerebral motor system after stroke , 2004, Current opinion in neurology.

[39]  D B Vigneron,et al.  Registration of images from sequential MR studies of the brain , 1994, Journal of magnetic resonance imaging : JMRI.

[40]  J. Donoghue,et al.  Plasticity and primary motor cortex. , 2000, Annual review of neuroscience.

[41]  L L Wald,et al.  Phased array detectors and an automated intensity‐correction algorithm for high‐resolution MR imaging of the human brain , 1995, Magnetic resonance in medicine.

[42]  P. Parizel,et al.  A brief review of parallel magnetic resonance imaging , 2003, European Radiology.

[43]  N. Hogan,et al.  Robotic therapy for chronic motor impairments after stroke: Follow-up results. , 2004, Archives of physical medicine and rehabilitation.

[44]  Robin M Heidemann,et al.  Perspectives and limitations of parallel MR imaging at high field strengths. , 2006, Neuroimaging clinics of North America.

[45]  P. Boesiger,et al.  SENSE: Sensitivity encoding for fast MRI , 1999, Magnetic resonance in medicine.

[46]  Karl J. Friston,et al.  Detecting Activations in PET and fMRI: Levels of Inference and Power , 1996, NeuroImage.

[47]  J. Ware,et al.  Random-effects models for longitudinal data. , 1982, Biometrics.

[48]  Paul J. Laurienti,et al.  An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets , 2003, NeuroImage.