Predicting alveolar ventilation heterogeneity in pulmonary fibrosis using a non-uniform polyhedral spring network...

Area of Science:

• Computational biology
• Biophysics
• Respiratory medicine

Background:

• Pulmonary fibrosis (PF) stiffens lung tissue due to collagen, impairing alveolar ventilation.
• Existing computational models use uniform shapes, failing to capture lung tissue's complex, isotropic geometry.
• The link between lung structure and function in PF is not fully understood.

Purpose of the Study:

• To develop a novel, physiologically accurate computational model of lung parenchyma.
• To investigate the impact of simulated fibrosis on lung mechanics and ventilation heterogeneity.
• To explore mechanotransduction in fibrotic lung tissue.

Main Methods:

• Developed a 3D Voronoi-based spring network model (Amorphous Network) simulating lung parenchyma.
• Incorporated agent-based modeling to mimic fibroblast migration and collagen deposition.
• Simulated progressive fibrosis by increasing spring stiffness along agent paths.

Main Results:

• The Amorphous Network model demonstrates greater geometric similarity to lung tissue than regular networks.
• Structural randomness in the model dissipates anisotropic force transmission, crucial for mechanotransduction.
• Simulated fibrosis increased alveolar ventilation heterogeneity and bulk modulus, correlating with fibrosis extent and agent path length.

Conclusions:

• The Amorphous Network model provides a more accurate representation of lung tissue geometry and mechanics.
• Fibrosis progression significantly impacts lung ventilation heterogeneity and tissue stiffness.
• This model advances computational approaches for studying lung diseases like pulmonary fibrosis.