权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

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

基本信息

批准号：
10704186
负责人：
Jongsang Son
金额：
$ 20.03万
依托单位：
NEW JERSEY INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
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/10704186
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 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 density disability early onset image processing in vivo in vivo imaging independent component analysis individual response muscular structure nervous system disorder neural neuron loss neurophysiology novel personalized medicine reconstruction response spatiotemporal tool treatment planning ultrasound

项目摘要

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.

表征运动单元力学和肌肉在体内的收缩特性