A Direct Comparison of Node and Element-Based Finite Element Modeling Approaches to Study Tissue Growth

Author:

Howe Danielle1,Dixit Nikhil N.2,Saul Katherine R.3,Fisher Matthew B.4

Affiliation:

1. Joint Department of Biomedical Engineering, North Carolina State University & University of North Carolina at Chapel Hill, Raleigh, NC 27695; Comparative Medicine Institute, North Carolina State University, Raleigh, NC 27695

2. Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695

3. Department of Mechanical and Aerospace Engineering, North Carolina State University, 3162 Engineering Building III, 1840 Entrepreneur Dr, CB 7910, Raleigh, NC 27695

4. Joint Department of Biomedical Engineering, North Carolina State University & University of North Carolina at Chapel Hill, 4130 Engineering Building III, 1840 Entrepreneur Drive, CB 7115, Raleigh, NC 27695; Comparative Medicine Institute, North Carolina State University, Raleigh, NC 27695; Department of Orthopaedics, University of North Carolina at Chapel Hill, NC 27599

Abstract

Abstract Finite element analysis is a useful tool to model growth of biological tissues and predict how growth can be impacted by stimuli. Previous work has simulated growth using node-based or element-based approaches, and this implementation choice may influence predicted growth, irrespective of the applied growth model. This study directly compared node-based and element-based approaches to understand the isolated impact of implementation method on growth predictions by simulating growth of a bone rudiment geometry, and determined what conditions produce similar results between the approaches. We used a previously reported node-based approach implemented via thermal expansion and an element-based approach implemented via osmotic swelling, and we derived a mathematical relationship to relate the growth resulting from these approaches. We found that material properties (modulus) affected growth in the element-based approach, with growth completely restricted for high modulus values relative to the growth stimulus, and no restriction for low modulus values. The node-based approach was unaffected by modulus. Node- and element-based approaches matched marginally better when the conversion coefficient to relate the approaches was optimized based on the results of initial simulations, rather than using the theoretically predicted conversion coefficient (median difference in node position 0.042 cm versus 0.052 cm, respectively). In summary, we illustrate here the importance of the choice of implementation approach for modeling growth, provide a framework for converting models between implementation approaches, and highlight important considerations for comparing results in prior work and developing new models of tissue growth.

Funder

National Institute of Arthritis and Musculoskeletal and Skin Diseases

National Institute of Child Health and Human Development

Publisher

ASME International

Subject

Physiology (medical),Biomedical Engineering

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