Contribution to the 3R Principle: Description of a Specimen-Specific Finite Element Model Simulating 3-Point-Bending Tests in Mouse Tibiae.
Xiaowei HuangAndreas K NusslerMarie K ReumannPeter AugatMaximilian M MengerAhmed GhallabJan G HengstlerTina HistingSabrina EhnertPublished in: Bioengineering (Basel, Switzerland) (2022)
Bone mechanical properties are classically determined by biomechanical tests, which normally destroy the bones and disable further histological or molecular analyses. Thus, obtaining biomechanical data from bone usually requires an additional group of animals within the experimental setup. Finite element models (FEMs) may non-invasively and non-destructively simulate mechanical characteristics based on material properties. The present study aimed to establish and validate an FEM to predict the mechanical properties of mice tibiae. The FEM was established based on µCT (micro-Computed Tomography) data of 16 mouse tibiae. For validating the FEM, simulated parameters were compared to biomechanical data obtained from 3-point bending tests of the identical bones. The simulated and the measured parameters correlated well for bending stiffness (R 2 = 0.9104, p < 0.0001) and yield displacement (R 2 = 0.9003, p < 0.0001). The FEM has the advantage that it preserves the bones' integrity, which can then be used for other analytical methods. By eliminating the need for an additional group of animals for biomechanical tests, the established FEM can contribute to reducing the number of research animals in studies focusing on bone biomechanics. This is especially true when in vivo µCT data can be utilized where multiple bone scans can be performed with the same animal at different time points. Thus, by partially replacing biomechanical experiments, FEM simulations may reduce the overall number of animals required for an experimental setup investigating bone biomechanics, which supports the 3R (replace, reduce, and refine) principle.
Keyphrases
- finite element
- computed tomography
- bone mineral density
- finite element analysis
- electronic health record
- soft tissue
- bone loss
- big data
- bone regeneration
- positron emission tomography
- contrast enhanced
- postmenopausal women
- image quality
- body composition
- metabolic syndrome
- data analysis
- type diabetes
- mass spectrometry
- molecular dynamics
- adipose tissue
- artificial intelligence
- single molecule
- liquid chromatography