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Updated: May 13, 2026

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Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics
Published on: April 16, 2017
Stretching skin: The physiological limit and beyond.
Adrián Buganza Tepole1, Arun K Gosain, Ellen Kuhl
1Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA.
Summary
This study introduces a new computational model for skin mechanics, simulating both normal behavior and irreversible growth under stretch. The model aids in optimizing tissue expansion for reconstructive surgery.
Area of Science:
- Computational mechanics
- Biomaterials science
- Tissue engineering
Background:
- Skin exhibits complex, nonlinear, and anisotropic behavior within physiological limits.
- Beyond physiological limits, mechanical stretch induces irreversible skin growth.
- Understanding these behaviors is crucial for applications like tissue expansion in reconstructive surgery.
Purpose of the Study:
- To develop a novel computational model for skin's constitutive behavior under stretch.
- To characterize reversible and irreversible skin responses, including growth.
- To simulate stretch-induced skin growth during tissue expansion procedures.
Main Methods:
- A transversely isotropic chain network model with eight wormlike chains for physiological behavior.
- A transversely isotropic growth model using a scalar-valued growth multiplier for irreversible growth.
- Implicit Euler backward scheme for temporal discretization and finite element method for spatial discretization, with nested Newton iterations.
Main Results:
- The model accurately captures skin's nonlinear, anisotropic, and stretch-locking properties.
- It simulates irreversible area growth as a transversely isotropic process.
- Simulations of tissue expander geometries reveal spatio-temporal evolution of stress, strain, and area gain.
Conclusions:
- The proposed computational model provides a robust framework for understanding skin mechanics and growth.
- It has the potential to advance reconstructive surgery by optimizing tissue expansion parameters.
- The model can inform decisions on expander geometry, size, placement, and inflation timing.
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