Modeling the effect of tumor compression on airflow dynamics in trachea using contact simulation and CFD analysis

Area of Science:

• Biomedical Engineering
• Computational Fluid Dynamics
• Medical Imaging

Background:

• Malignant central airway obstruction causes severe breathing difficulty.
• Surgical intervention or stent implantation is often required.
• Predictive models are needed for timely clinical planning.

Purpose of the Study:

• To develop and validate a predictive model for central airway obstruction.
• To simulate tumor compression and its effect on airflow dynamics.
• To estimate stenosis levels causing severe breathing difficulties.

Main Methods:

• Patient-specific tracheal models generated from CT scans.
• Nonlinear contact simulations for tumor compression.
• Computational fluid dynamics (CFD) for airflow analysis and power loss calculation.

Main Results:

• A 50% tracheal obstruction increased power loss by over 66% compared to the undeformed model.
• Breathing difficulty can be correlated with calculated power loss.
• The model predicts intervention needs based on stenosis-induced power loss.

Conclusions:

• The developed model effectively simulates tumor compression and airflow changes.
• Power loss is a viable metric for quantifying breathing difficulty.
• This predictive model aids clinicians in planning interventions for airway obstruction.