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

Frontiers in Network Physiology

Network Physiology

Dylan T. Casey¹  Joseph K. Hall²  Kenneth R. Lutchen²  Erzsébet Bartolák-Suki²  Béla Suki²  Jason H. T. Bates³ 

[1] Complex Systems Center, University of Vermont, Burlington, VT, United States;Department of Biomedical Engineering, Boston University, Boston, MA, United States;Department of Medicine, University of Vermont, Burlington, VT, United States;

关键词: random networks;    isotropy;    stiffness;    bulk modulus;    force transmission;    percolation;   

DOI  :  10.3389/fnetp.2023.1124223

 received in 2022-12-14, accepted in 2023-01-20,  发布年份 2023

来源: Frontiers

【 摘 要 】

Pulmonary Fibrosis (PF) is a deadly disease that has limited treatment options and is caused by excessive deposition and cross-linking of collagen leading to stiffening of the lung parenchyma. The link between lung structure and function in PF remains poorly understood, although its spatially heterogeneous nature has important implications for alveolar ventilation. Computational models of lung parenchyma utilize uniform arrays of space-filling shapes to represent individual alveoli, but have inherent anisotropy, whereas actual lung tissue is isotropic on average. We developed a novel Voronoi-based 3D spring network model of the lung parenchyma, the Amorphous Network, that exhibits more 2D and 3D similarity to lung geometry than regular polyhedral networks. In contrast to regular networks that show anisotropic force transmission, the structural randomness in the Amorphous Network dissipates this anisotropy with important implications for mechanotransduction. We then added agents to the network that were allowed to carry out a random walk to mimic the migratory behavior of fibroblasts. To model progressive fibrosis, agents were moved around the network and increased the stiffness of springs along their path. Agents migrated at various path lengths until a certain percentage of the network was stiffened. Alveolar ventilation heterogeneity increased with both percent of the network stiffened, and walk length of the agents, until the percolation threshold was reached. The bulk modulus of the network also increased with both percent of network stiffened and path length. This model thus represents a step forward in the creation of physiologically accurate computational models of lung tissue disease.

【 授权许可】

Unknown   
Copyright © 2023 Hall, Bates, Casey, Bartolák-Suki, Lutchen and Suki.