# Evaluation of brain recovery of stroke patients using a novel magnetic resonance compatible hand induced robotic device combined with magnetic resonance imaging > **NIH NIH R01** · MASSACHUSETTS GENERAL HOSPITAL · 2021 · $671,936 ## Abstract The broad, long-term objective of this study is to improve therapy efficacy for, and thus the quality of life (QoL) of, stroke patients. An increasing number of individuals suffer from stroke. Disabilities resulting from stroke were considered irreversible until very recently. Stroke recovery is an emerging field, still overcoming the longstanding view of functions lost to stroke being non-recoverable. We hypothesize that (a) robotic devices that stimulate brain recovery via motor training can support restoration of movement abilities compromised by stroke-induced pathological changes in the brain; and that (b) post-stroke neural changes can be monitored (and therefore later predicted) by in vivo state-of-the-art magnetic resonance imaging (MRI) via brain recovery biomarkers and behavioral motor performance improvements. To test this hypothesis, we propose to conduct a longitudinal study of our novel hand device in conjunction with 3-T brain MRI to monitor recovery in patients with chronic stroke via three Aims. Aim (1) is to perform state-of-the-art MRI with newly-developed phased-array coils and parallel imaging (to maximize sensitivity and resolution) to document quantifiable brain changes during training in 100 chronic stroke patients with confirmed middle cerebral artery (MCA) territory ischemic stroke and ischemic lesions affecting the motor strip. Patients will be assigned randomly to a training group and non-training control group. Participants will train for 30 min/d, 3 d/wk, to be conducted at home to facilitate participation. Volumetric MRI, functional MRI (fMRI), and diffusion tensor imaging (DTI) will be performed before the start of treatment (baseline) and then monthly over a 3-month training period. MRI measurements will focus on the motor cortex and its surrounding cortical areas and connecting tracts. Aim (2) is to evaluate motor performance in these chronic stroke patients with standard clinical indices and hand device measurements. Aim (3) is to demonstrate that brain mapping based on state-of-the art MRI in conjunction with hand device-assisted therapy can provide novel biomarkers for chronic stroke recovery while improving clinical outcome. We will perform a meta-analysis of structural, fMRI, DTI, and motor performance data using a general linear mixed-model (GLMM) approach, which handles heterogeneous data and facilitates deduction of useful results despite inter-individual variability. Impact: Success will facilitate selection of patients and personalized treatment planning optimized to yield improvements based on MRI metrics. Specifically, this study may identify biomarkers of brain recovery that can be monitored during therapy, inform therapy adjustments, and advance our ability to predict stroke recovery outcome. For chronic stroke patients, we anticipate demonstrating that recovery is possible for a longer period of time than previously thought, including motor skill improvements beyond... ## Key facts - **NIH application ID:** 10161871 - **Project number:** 5R01NS105875-04 - **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL - **Principal Investigator:** A ARIA TZIKA - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $671,936 - **Award type:** 5 - **Project period:** 2018-08-01 → 2023-05-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10161871 ## Citation > US National Institutes of Health, RePORTER application 10161871, Evaluation of brain recovery of stroke patients using a novel magnetic resonance compatible hand induced robotic device combined with magnetic resonance imaging (5R01NS105875-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10161871. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*