Evaluation of brain recovery of stroke patients using a novel magnetic resonance compatible hand induced robotic device combined with magnetic resonance imaging

使用新型磁共振兼容手诱导机器人装置结合磁共振成像评估中风患者的脑恢复

• 批准号: 10161871
• 负责人: A ARIA TZIKA
• 金额: $ 67.19万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10161871
• 关键词: Address; Affect; American; Animal Experiments; Area; Attention; Behavioral; Biological Markers; Brain; Brain Mapping; Brain imaging; Caring; Cause of Death; Clinical; Clinical assessments; Computers; Control Groups; Data; Deductibles; Devices; Diffusion Magnetic Resonance Imaging; Elderly; Evaluation; Feedback; Fiber; Functional Magnetic Resonance Imaging; Hand; Healthcare; Home; Image; Individual; Insurance; Ischemic Stroke; Knowledge; Life; Longitudinal Studies; Magnetic Resonance; Magnetic Resonance Imaging; Measurement; Measures; Medicare; Meta-Analysis; Modeling; Modernization; Monitor; Morbidity - disease rate; Motor; Motor Cortex; Motor Skills; Movement; Outcome; Participant; Pathologic; Patient Selection; Patients; Perception; Performance; Phase; Physical therapy; Prognosis; Protocols documentation; Quality of life; Randomized; Recovery; Reporting; Research; Resolution; Robotics; Role; Self-Help Devices; Societies; Stroke; Structure; Supervision; Testing; Thick; Time; Training; Treatment Efficacy; Variant; Visualization; Work; arm; base; chronic stroke; cost; density; design; disability; effective intervention; expectation; experience; experimental group; heterogenous data; human old age (65+); improved; in vivo; indexing; individualized medicine; inter-individual variation; ischemic lesion; light weight; magnetic resonance imaging biomarker; middle cerebral artery; motor deficit; motor recovery; neuroimaging; novel; novel marker; patient population; personalized medicine; physical therapist; portability; post stroke; predict clinical outcome; relating to nervous system; restoration; robot therapy; robotic device; stroke event; stroke outcome; stroke patient; stroke recovery; stroke survivor; stroke victims; success; tractography; treatment planning; white matter

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 6 mos. after a stroke event, owing to the capacity for brain plasticity and functionally adaptive reorganization. If this research indicates continued improvement with physical therapy, then the limitations of Medicare and other insurances should be extended to assist in longer-term recovery of stroke victims, thus improving their QoL, especially in the geriatric patient population, where stroke is most prevalent.

这项研究的广泛长期目标是提高治疗疗效，因此 中风患者的生活质量（QOL）。越来越多的人遭受 中风。直到最近，中风引起的残疾被认为是不可逆的。 中风恢复是一个新兴领域，仍然克服了对失去的功能的长期观点 中风是不可恢复的。 我们假设（a）通过电机刺激大脑恢复的机器人设备 训练可以支持恢复中风引起的运动能力 大脑的病理变化； （b）中风后神经变化可能是 通过体内最先进的磁共振监测（因此后来预测） 成像（MRI）通过大脑恢复生物标志物和行为运动性能改善。 为了检验这一假设，我们建议对我们的新手装置进行纵向研究 与3-T脑MRI结合以通过三个目标监测慢性中风患者的恢复。 AIM（1）是用新开发的分阶段线圈和并行执行最先进的MRI 成像（以最大化灵敏度和分辨率），以记录可量化的大脑变化 对100例慢性中风患者进行培训，确认脑动脉（MCA） 区域缺血性中风和缺血性病变影响运动带。将分配患者 随机到训练组和非训练对照组。参与者将训练30分钟/d， 3 d/wk，将在家中进行以促进参与。体积MRI，功能性MRI （fMRI）和扩散张量成像（DTI）将在开始之前进行 治疗（基线），然后在3个月的培训期间每月一次。 MRI测量 将专注于运动皮层及其周围的皮质区域和连接区。目标（2） 是评估具有标准临床的慢性中风患者的运动性能 索引和手动设备测量。目的（3）是证明大脑映射 基于最先进的MRI与手动辅助治疗结合使用 为慢性中风恢复提供新颖的生物标志物，同时改善临床结果。我们将 使用A进行结构，fMRI，DTI和运动性能数据的荟萃分析 一般线性混合模型（GLMM）方法，该方法处理异质数据和 尽管个体间的可变性，但仍促进有用的结果。 影响：成功将有助于选择患者和个性化治疗计划 优化以根据MRI指标产生改进。具体而言，这项研究可能 确定可以在治疗过程中监测的大脑恢复的生物标志物，告知治疗 调整，并提高我们预测中风恢复结果的能力。对于慢性中风 患者，我们预计会证明比恢复时间比 以前认为，包括6个MOS以上的运动技能改进。中风后 事件，由于大脑可塑性的能力和功能自适应的能力 重组。如果这项研究表明通过物理疗法继续改善 那么，应扩大医疗保险和其他保险的局限性 中风受害者的恢复，从而改善了他们的QOL，尤其是在老年患者中 人口，中风最普遍。