Characterizing Motor Unit Mechanics and Muscle Contractile Properties In Vivo

点击翻译按钮获取中文摘要

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.