Comparison of strain measurement in the mouse forearm using subject-specific finite element models, strain gaging, and digital image correlation

• Published in: Biomechanics and modeling in mechanobiology Vol. 16; no. 4; pp. 1243 - 1253
• Main Authors: Begonia, Mark, Dallas, Mark, Johnson, Mark L., Thiagarajan, Ganesh
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2017; Springer Nature B.V
• Subjects: Animal models; Animals; Biocompatibility; Biological and Medical Physics; Biomechanics; Biomedical Engineering and Bioengineering; Biomedical materials; Biophysics; Bones; Computed tomography; Computer applications; Correlation; Digital imaging; Engineering; Finite Element Analysis; Finite element method; Forearm; Forelimb - diagnostic imaging; Forelimb - physiology; Gaging; Inertia; Load; Mathematical analysis; Mathematical models; Mechanical loading; Mechanical properties; Mechanical stimuli; Mice; Models, Biological; Modulus of elasticity; Moments of inertia; Mouse devices; Original Paper; Radius - diagnostic imaging; Radius - physiology; Rodents; Stimuli; Strain gauges; Strain measurement; Stress, Mechanical; Theoretical and Applied Mechanics; Ulna - diagnostic imaging; Ulna - physiology; X-Ray Microtomography; Forearm; Finite element analysis; Strain gage; Mechanical loading; Digital image correlation; Strain
• ISSN: 1617-7959; 1617-7940; 1617-7940
• DOI: 10.1007/s10237-017-0885-7

Mechanical loading in bone leads to the activation of bone-forming pathways that are most likely associated with a minimum strain threshold being experienced by the osteocyte. To investigate the correlation between cellular response and mechanical stimuli, researchers must develop accurate ways to measure/compute strain both externally on the bone surface and internally at the osteocyte level. This study investigates the use of finite element (FE) models to compute bone surface strains on the mouse forearm. Strains from three FE models were compared to data collected experimentally through strain gaging and digital image correlation (DIC). Each FE model was assigned subject-specific bone properties and consisted of one-dimensional springs representing the interosseous membrane. After three-point bending was performed on the ulnae and radii, moment of inertia was determined from microCT analysis of the bone region between the supports and then used along with standard beam analyses to calculate the Young’s modulus. Non-contact strain measurements from DIC were determined to be more suitable for validating numerical results than experimental data obtained through conventional strain gaging. When comparing strain responses in the three ulnae, we observed a 3–14% difference between numerical and DIC strains while the strain gage values were 37–56% lower than numerical values. This study demonstrates a computational approach for capturing bone surface strains in the mouse forearm. Ultimately, strains from these macroscale models can be used as inputs for microscale and nanoscale FE models designed to analyze strains directly in the osteocyte lacunae.