Predicting muscle function and mass with electrical impedance myography: A study in rat analogs of micro- and partial gravity

• Published in: Acta astronautica Vol. 223; pp. 384 - 388
• Main Authors: Rosa-Caldwell, Megan E., Pandeya, Sarbesh, Mortreux, Marie, Rutkove, Seward B.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2024
• Subjects: Electrical impedance myography; Fractional gravity; Machine learning; Rats; Unloading; Rats; Unloading; Fractional gravity; Electrical impedance myography; Machine learning
• ISSN: 0094-5765
• DOI: 10.1016/j.actaastro.2024.07.017

Spaceflight results in marked muscle atrophy and a corresponding loss in muscle strength. Methods to evaluate spaceflight-induced changes to muscle size and strength are difficult to achieve within the tight confines of spacecrafts. Therefore, convenient methods to non-invasively monitor muscle that are predictive of actual muscle function are critical for future missions to ensure the health and safety of crew members. Evaluate the ability of non-invasive in vivo electrical impedance myography (EIM) combined with statistical models to predict muscle size and strength in rodent models of micro- and partial gravity. Male and female Fisher rats (N = 120), half gonadectomized, were divided into three different weightbearing (WB) conditions of 40 animals each, including 0%WB (0 % of weight-bearing, simulated microgravity), 40%WB (40 % of weight-bearing, simulated Martian gravity), and 100%WB (100 % of weight-bearing, full weight-bearing controls). Rats remained in designated interventions for 28 days. Afterward, rats underwent a series of musculoskeletal strength assessments and measurement of EIM. Rats were then euthanized and gastrocnemius tissues collected. Machine-learning (ML) algorithms were applied to full spectrum EIM data to predict various muscle parameters. 40%WB and 0%WB rats had lower grip strength and plantar flexion compared to 100%WB. Correspondingly, 40%WB and 0%WB also had reduced gastrocnemius mass compared to 100%WB. EIM resistance values demonstrated a dose-dependency response, with greater resistance values associated with reduced gravitational load. ML-enhanced EIM yielded strong predictions of muscle plantar flexion force and muscle mass, with root mean squared errors of 18.4 % of 22.0 %, and R2 values of 0.87 an 0.88, respectively. ML-enhanced EIM may be a helpful tool to non-invasively monitor muscle changes predictive of muscle force production and mass during exposure to reduced gravity. •Electrical impedance myography (EIM) data can be used to predict muscle mass in rats exposed to reduced loading.•EIM data can be used to predict muscle force in rats exposed to reduced loading.•These data support that EIM may find use as a predictor of muscle function in human spaceflight.