A spatial healing metric for wound healing modeling

Area of Science:

• Biomedical Engineering
• Computational Biology
• Mathematical Modeling

Background:

• Accurate tracking of wound healing is crucial for effective treatment.
• Existing metrics often rely on fixed thresholds, which may not capture complex healing dynamics.
• The influence of wound geometry and parameter variations on healing progression requires further investigation.

Purpose of the Study:

• To introduce a novel spatial healing metric (β) for enhanced wound healing assessment.
• To evaluate the proposed metric's performance across diverse wound geometries.
• To compare the proposed metric against traditional threshold-based approaches.

Main Methods:

• Solving a Fickian diffusion equation with a logistic nonlinear term using the FEniCSx finite element framework.
• Verifying and calibrating the model against experimental data from rabbit ear wound literature.
• Introducing and analyzing a spatial healing metric (β) representing average cell density.

Main Results:

• The spatial healing metric (β) effectively captures healing variations due to geometry and parameter differences.
• Parametric sweeps demonstrated that different parameter combinations can lead to similar healing times but distinct spatial cell density profiles.
• The β metric highlighted limitations of threshold-based methods, particularly in scenarios with high diffusion and low cell proliferation.

Conclusions:

• The proposed spatial healing metric (β) offers a more comprehensive assessment of wound healing than traditional methods.
• This metric is applicable to various wound geometries and parameter settings.
• The findings underscore the importance of considering spatial cell distribution for accurate wound healing evaluation.