A 3D Agent-Based Model of Lung Fibrosis

Abstract

Understanding the pathophysiology of lung fibrosis is of paramount importance to elaborate targeted and effective therapies. As it onsets, the randomly accumulating extracellular matrix (ECM) breaks the symmetry of the branching lung structure. Interestingly, similar pathways have been reported for both idiopathic pulmonary fibrosis and radiation-induced lung fibrosis (RILF). Individuals suffering from the disease, the worldwide incidence of which is growing, have poor prognosis and a short mean survival time. In this context, mathematical and computational models have the potential to shed light on key underlying pathological mechanisms, shorten the time needed for clinical trials, parallelize hypotheses testing, and improve personalized drug development. Agent-based modeling (ABM) has proven to be a reliable and versatile simulation tool, whose features make it a good candidate for recapitulating emergent behaviors in heterogeneous systems, such as those found at multiple scales in the human body. In this paper, we detail the implementation of a 3D agent-based model of lung fibrosis using a novel simulation platform, namely, BioDynaMo, and prove that it can qualitatively and quantitatively reproduce published results. Furthermore, we provide additional insights on late-fibrosis patterns through ECM density distribution histograms. The model recapitulates key intercellular mechanisms, while cell numbers and types are embodied by alveolar segments that act as agents and are spatially arranged by a custom algorithm. Finally, our model may hold potential for future applications in the context of lung disorders, ranging from RILF (by implementing radiation-induced cell damage mechanisms) to COVID-19 and inflammatory diseases (such as asthma or chronic obstructive pulmonary disease).

An Agent-Based Model of Radiation-Induced Lung Fibrosis

“…In this study, we implemented an ABM of a human alveolar segment and simulated the onset of RILF after the irradiation with single-fraction X-rays. We downscaled the model presented in our previous work [21] to the cellular level and added key cellular behaviours that have been documented both in RILF and IPF, such as cell repopulation, As expected, due to the ability of the healthy AEC2 to repopulate the depleted alveoli and the lack of damage-spreading cells, we observed larger fractions of surviving alveoli for lower AEC2 senescent-to-damaged fractions. Notably, full resolution of the RILF was achieved for ratios ≤ 50% and dose ≤ 10 Gy.…”

“…By secreting factors such as transforming growth factor beta (TGFβ), platelet-derived growth factor 2 of 21 (PDGF), and interleukin 13 (IL13), M2 stimulates fibroblasts' proliferation and differentiation into myofibroblasts [15][16][17][18]. Finally, extracellular matrix (ECM) secreted by both fibroblasts and myofibroblasts stiffen the alveolar walls leading to lung scarring, which hinders breathing [19,20] (see our previous work for more details [21]).…”

“…The model builds on our previous work [21] with an emphasis on cell senescence and cell repopulation. A finer spatial resolution allows for radiation-induced damage to AEC2 to spread to bystanders [12,31], while macrophages can phagocyte senescent cells [32,33].…”

“…Based on this, we stress the need to account for microenvironmental factors when estimating the risk of RILI. Finally, we combine the ECM dose-response curve The model builds on our previous work [21] with an emphasis on cell senescence and cell repopulation. A finer spatial resolution allows for radiation-induced damage to AEC2 to spread to bystanders [12,31], while macrophages can phagocyte senescent cells [32,33].…”

An agent-based modeling approach for lung fibrosis in response to COVID-19

“…The ABM of Warsinske et al [32] explored the co-regulatory relationship between epithelial cells and fibroblasts through TGF- β 1 during fibrosis. In another 3D ABM of lung fibrosis [33], the initial amount of damaged type 2 AECs activated the inactive TGF- β . The ABM of Ceresa et al [34] focused on emphysema progression (excess degradation of collagen) in chronic obstructive pulmonary disease and considered the transition of macrophages between the M1 and M2 phenotypes, secretion of TGF- β from M2 macrophages, recruitment of fibroblasts by TGF- β , fibroblast-mediated collagen deposition, and collagen degradation by MMP9.…”