Computer Simulation of Post-Burn Skin

Scope of the method

The Method relates to
  • Human health
The Method is situated in
  • Translational - Applied Research
Type of method
  • In silico
This method makes use of
  • Human derived cells / tissues / organs
Specify the type of cells/tissues/organs
human skin

Description

Method keywords
  • mathematical modelling
  • finite element methods
  • uncertainty quantification
  • skin contraction
  • hypertrophic scar
Scientific area keywords
  • dermal contraction
  • fibroblasts
  • cellular traction forces
  • momentum balance
  • morphoelasticity
  • statistical sampling
  • uncertainty assessment
  • stochastic models
  • partial differential equations
Method description

Severely burned skin can exhibit serious contractions that may negatively impact the mobility of joints of patients. The method deals with post-burn evolution of skin, in which one considers the balance of momentum, cells, collagen and chemokines. The balances are represented in terms of partial differential equations, of which the solution is approximated by the use of numerical techniques. These techniques combine finite element discretization, time integration and root finding problem to solve the resulting nonlinear algebraic equations. Since many of the input parameters are unknown, uncertainty assessment is done in order to obtain output results in terms of estimations of probability distributions. The main output variables are the wound area and total dermal stress energy as a function of time after injury, since these parameters quantify the extent of dermal contraction.

Lab equipment

For this method one only needs a computer with software.

Method status
  • Still in development
  • Internally validated
  • Published in peer reviewed journal

Pros, cons & Future potential

Advantages
  • - The method is useful for the prediction of skin behavior over time;
  • - The method is allows results to be interpreted in a probabilistic sense ;
  • - The method does not need additional animal experiments.
Challenges
  • - Incorporation of treatments;
  • - Using machine learning to decrease simulation times.
Modifications
  • - Implementation of therapies;
  • - Machine learning to decrease simulation times;
  • - Improvements in describing the underlying physics.
Future & Other applications

The mathematical method is generic in nature, we expect many principles to be applicable to cancer, diabetic wounds and organ development.

References, associated documents and other information

References
  • G Egberts, FJ Vermolen, PPM van Zuijlen (2023). Stability of a two-dimensional biomorphoelastic model for post-burn contraction. Journal of Mathematical Biology 86 (4): 59
  •  
  • G Egberts, A Desmoulière, FJ Vermolen, PPM van Zuijlen (2023). Sensitivity of a two-dimensional biomorphoelastic model for post-burn contraction. Biomechanics and Modeling in Mechanobiology 22 (1): 105-121
  •  
  • G Egberts, FJ Vermolen, PPM van Zuijlen (2023). High-speed predictions of post-burn contraction using a neural network trained on 2D-finite element simulations. FRONTIERS MEDIA Statistics and Applied Mathematics
Associated documents
Sensitivity of a two-dimensional biomorphoelastic model for post-burn contraction.pdf
s00285-023-01893-w.pdf
High-speed predictions of post-burn contraction using a neural network trained on 2D-finite element simulations.pdf

Contact person

Fred Vermolen

Organisations

University of Hasselt (UHasselt)
Mathematics and Statistics
Belgium