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Finite element modeling of soft tissues: material models, tissue interaction and challenges
Maren Freutel1, Hendrik Schmidt2, Lutz Dürselen1
1Institute of Orthopaedic Research and Biomechanics, Center of Musculoskeletal Research Ulm, University of Ulm, Ulm, Germany.
Clinical Biomechanics (Bristol, Avon)
|February 18, 2014
Summary
Mathematical models enhance understanding of musculoskeletal soft tissue biomechanics, aiding clinical insights. Awareness of model limitations is crucial for accurate simulation of knee joint and intervertebral disk tissues.
Area of Science:
- Biomechanics
- Biomaterials Science
- Computational Biology
Background:
- Musculoskeletal soft tissues (articular cartilage, ligaments, menisci, intervertebral discs) possess complex, multiphasic structures enabling load support and elasticity.
- Their mechanical behavior is nonlinear and time-dependent, governed by extracellular matrix components like collagen and proteoglycans.
- Modeling these intricate systems presents challenges due to their complex structure and mechanical response.
Purpose of the Study:
- To summarize diverse modeling strategies for musculoskeletal soft tissues.
- To review material properties, contact interactions, and validation methods for soft tissue models.
- To discuss clinical findings from finite element simulations of knee joint and intervertebral disk tissues.
Main Methods:
- Non-systematic literature review.
Main Results:
- Overview of various modeling approaches for soft tissues, including material properties and contact interactions.
- Summary of validation and sensitivity analyses for soft tissue models, with emphasis on knee and intervertebral disk.
- Review of clinical insights derived from finite element simulations of soft tissues.
Conclusions:
- Computational models significantly advance the understanding of soft tissue functional biomechanics.
- Models effectively address clinically relevant questions regarding soft tissue behavior.
- Users must recognize the inherent complexity of soft tissues and the capabilities/limitations of modeling approaches for accurate in vivo/in vitro simulations.
