Characterizing Motor Unit Mechanics and Muscle Contractile Properties In Vivo

表征体内运动单位力学和肌肉收缩特性

• 批准号: 10527926
• 负责人: Jongsang Son
• 金额: $ 16.41万
• 依托单位: NEW JERSEY INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10527926
• 关键词: Agreement; Algorithms; Amyotrophic Lateral Sclerosis; Anatomy; Animals; Architecture; Atrophic; Biological Markers; Biopsy; Clinical; Coupling; Data; Diagnosis; Diagnostic Procedure; Dimensions; Disease; Disease Progression; Early Diagnosis; Electric Stimulation; Elements; Evaluation; Fascicle; Fiber; Frequencies; Functional disorder; Goals; Gold; Hereditary Disease; Heterogeneity; Human; Imaging Device; Imaging Techniques; Impairment; In Vitro; Inflammatory; Intramuscular; Isometric Contraction; Link; Lower Extremity; Maps; Measurable; Measures; Mechanics; Methods; Modeling; Motion; Motor; Motor Neurons; Muscle; Muscle Contraction; Muscle Fibers; Muscle Weakness; Muscle function; Musculoskeletal Diseases; Myopathy; Nerve; Neuromuscular Diseases; Neuropathy; Onset of illness; Optics; Outcome; Pattern; Physiological; Procedures; Property; Relaxation; Research; Research Personnel; Sampling; Series; Severities; Skeletal Muscle; Spatial Distribution; Speed; Spinal Muscular Atrophy; Surface; System; Techniques; Testing; Time; Time Series Analysis; Tissues; Training; Ultrasonography; Upper Extremity; base; density; disability; early onset; image processing; in vivo; in vivo imaging; independent component analysis; individual response; muscular structure; nervous system disorder; neuron loss; neurophysiology; novel; personalized medicine; reconstruction; relating to nervous system; response; spatiotemporal; tool; treatment planning; ultrasound

Characterizing motor unit mechanics and muscle contractile properties in vivo Muscle contractility has the potential as a promising biomarker for detecting disease onset earlier and tracking the progress of neuromuscular diseases (NMDs). However, quantifying muscle contractile properties is not currently within reach of standard diagnostic techniques, mainly because of a lack of in vivo techniques that can readily be applied in a real clinical setting. The gold standard to quantify muscle contractile properties is based on muscle biopsy and on in vitro studies, which is not only very invasive but also uncertain whether muscle contractile properties induced by electrical stimulation reflect natural motor unit mechanics. More importantly, slow-twitch fibers, not as accessible by electrical stimulation, are the most relevant to clinical observations in neuromuscular diseases, emphasizing the need for new in vivo technique to understand the contractile properties during voluntary contractions. Surface or intramuscular EMG is a potential alternative to describe motor unit discharge properties, but EMG does not provide quantitative data about muscle contractile properties. As both neural and muscular mechanisms are not only linked anatomically but also closely interacted functionally, just one part of the information is not sufficient to comprehensively understand muscle mechanical function. There is therefore a profound need to develop new in vivo techniques to characterize muscle contractile properties as well as motor unit mechanics. Accordingly, the main goal of this R21 project is to develop a new in vivo ultrasound imaging-based framework to precisely capture fascicle motion during voluntary muscle contractions so that we can characterize muscle contractile properties and motor unit mechanics. In Aim 1, we will develop an ultrafast ultrasound imaging sequence, using a research ultrasound system, to capture dynamic fascicle motion during voluntary isometric contractions. We will also develop an image processing method to quantify the tissue velocity field and in turn to identify mechanical responses of individual active motor units (i.e., twitch trains). The twitch trains allow us to estimate motor unit discharge patterns and muscle contractile properties. In Aim 2, we will evaluate the outcomes from the proposed technique compared to the advanced surface EMG decomposition technique. We will quantify the similarity of motor unit discharge patterns independently estimated from both ultrafast ultrasound recordings and decomposition EMG recordings from human skeletal muscles during voluntary isometric contractions. A time- series deconvolution method will be used to characterize muscle contractile properties. This aim will demonstrate the feasibility that the proposed technique can characterize motor unit mechanics and muscle contractile properties of human skeletal muscle in vivo. This project will provide a powerful tool to help researchers/clinicians study understand the origins of muscle weakness in musculoskeletal or neurological disorders, diagnose early muscle changes in inherited diseases, in inflammatory diseases, or detect abnormal muscle activities in progressive nervous system disease.

活体运动单位力学和肌肉收缩特性的表征 肌肉收缩能力有可能成为一种有希望的生物标志物，用于检测疾病的早期和 跟踪神经肌肉疾病(NMD)的进展。然而，量化肌肉收缩特性 目前不在标准诊断技术的范围内，主要是因为缺乏活体技术 可以很容易地应用到真正的临床环境中。量化肌肉收缩特性的黄金标准 是基于肌肉活检和体外研究，这不仅是非常有侵入性的，而且也不确定 电刺激引起的肌肉收缩特性反映了自然的运动单位力学。更多 重要的是，慢收缩纤维不像电刺激那样容易接近，是与临床最相关的。 神经肌肉疾病的观察，强调需要新的活体技术来了解 自主收缩时的收缩特性。表面肌电信号或肌内肌电是一种潜在的替代 描述运动单位放电特性，但肌电图不能提供有关肌肉收缩的定量数据 属性。因为神经和肌肉的机制不仅在解剖学上是联系在一起的，而且 在功能上相互作用，仅有一部分信息不足以全面了解肌肉 机械功能。因此，迫切需要开发新的体内技术来表征 肌肉收缩特性以及运动单位力学。因此，这个R21项目的主要目标是 开发一种新的基于体内超声成像的框架，以精确地捕捉在 随意肌肉收缩，以便我们可以表征肌肉收缩特性和运动单位 机械师。在目标1中，我们将开发一种超快超声成像序列，使用研究型超声波 系统，捕捉自主等长收缩过程中的动态肌束运动。我们还将开发一种 一种图像处理方法，用于量化组织速度场并进而识别 单独的主动运动单元(即抽搐列车)。抽搐列车使我们可以估计运动单位的放电 模式和肌肉收缩特性。在目标2中，我们将评估拟议的 技术与先进的表面肌电信号分解技术进行比较。我们将量化它们之间的相似性 根据超快超声记录独立估计的运动单位放电模式 人体骨骼肌在自主等长收缩过程中的分解肌电记录。一段时间- 序列去卷积方法将被用来表征肌肉的收缩特性。这一目标将 论证了所提出的技术能够表征运动单位力学和肌肉的可行性 活体人体骨骼肌的收缩特性。这个项目将提供一个强大的工具来帮助 研究人员/临床医生研究了解肌肉骨骼或神经系统肌肉无力的起源 在遗传性疾病、炎症性疾病中诊断早期肌肉变化，或检测异常 进行性神经系统疾病中的肌肉活动。