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.