Electrical impedance myography (EIM) provides a powerful method to assess muscle condition, potentially enabling the diagnosis of neuromuscular disorders, tracking of disease progression, and assessment of response to therapy1,2,3. It can be applied analogously to animal disease models and humans, allowing for relatively seamless translation from preclinical to clinical studies. EIM measurements are easily obtained using four linearly-placed electrodes, with the two outer ones applying a painless, weak electrical current across a range of frequencies (generally between 1 kHz and approximately 2 MHz), and the two inner ones recording the resulting voltages1. From these voltages, the impedance characteristics of the tissue can be obtained, including the resistance (R), a measure of how difficult it is for current to pass through the tissue, and the reactance (X) or "chargeability" of the tissue, a measure related to the tissue's ability to store charge (capacitance). From the reactance and resistance, the phase angle (θ) is calculated via the following equation:
, providing a single summative impedance measure. Such measurements can be obtained using any multifrequency bioimpedance device. As myofibers are essentially long cylinders, muscle tissue is also highly anisotropic, with current flowing more easily along fibers than across them4,5. Thus, EIM is often performed in two directions: with the array placed along the fibers such that current runs parallel to them, and across the muscle such that the current flows perpendicular to them. Additionally, in ex vivo measurements, where a known volume of tissue is measured in an impedance measuring cell, the inherent electrical properties of the muscle (i.e. the conductivity and relative permittivity), can be derived6.
The term "neuromuscular disorders" defines a wide range of primary and secondary diseases that lead to structural muscle alteration and dysfunction. This includes amyotrophic lateral sclerosis and various forms of muscular dystrophy, as well as simpler changes related to aging (e.g., sarcopenia), disuse atrophy (e.g., due to prolonged bedrest or microgravity) or even injury7. While the causes are plentiful and can originate from the motor neuron, nerves, neuromuscular junctions, or the muscle itself, EIM can be used to detect early alterations in muscle due to many of these processes and to track progression or response to therapy. For example, in patients with Duchenne muscular dystrophy (DMD), EIM has been shown to detect disease progression and response to corticosteroids8. Recent work has also shown EIM to be sensitive to varying disuse states, including fractional gravity9, as would be experienced on the Moon or Mars, and the effects of aging10,11. Finally, by applying predictive and machine learning algorithms to the data set obtained with each measurement (multifrequency and directionally dependent data), it becomes possible to infer histological aspects of the tissue, including myofiber size12,13, inflammatory changes and edema14, and connective tissue and fat content15,16.
Several other noninvasive or minimally invasive methods are also used to evaluate muscle health in humans and animals, including needle electromyography17 and imaging technologies such as magnetic resonance imaging, computerized tomography, and ultrasound18,19. However, EIM demonstrates distinct benefits compared with these technologies. For example, electromyography records only the active electrical properties of the myofiber membranes and not the passive properties, and thus cannot provide a true assessment of muscle composition or structure. In a certain respect, imaging methods are more closely related to EIM, as they too provide information about the structure and composition of tissue. But in some sense, they provide too much data, requiring detailed image segmentation and expert analysis rather than just providing a quantitative output. Moreover, given their complexities, imaging techniques are also greatly impacted by the specifics of both the hardware and software being used, ideally requiring the use of identical systems so that data sets can be compared. In contrast, the fact that EIM is much simpler means that it is less impacted by these technical issues and does not require any form of image processing or expert analysis.
The following protocol demonstrates how to perform in vivo EIM in rats and mice, using both noninvasive (surface array) and minimally invasive (subdermal needle array) techniques, as well as ex vivo EIM on freshly excised muscle.