Topographic distribution of idiopathic pulmonary fibrosis: a hybrid physics- and agent-based model.

OBJECTIVE: Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal disease characterized by excessive deposition of collagen and associated stiffening of lung tissue. While it is known that inflammation and dysfunction of fibroblasts are involved in disease development, it remains poorly understood how cells and their microenvironment interact to produce a characteristic subpleural pattern of high and low tissue density variations, called honeycombing, on CT images of patients with IPF. Since the pleura is stiffer than the parenchyma, we hypothesized that local stiffness of the underlying extracellular matrix can influence fibroblast activation and consequently the deposition of collagen, which in turn influences tissue stiffness in a positive feedback loop.

APPROACH: We tested this hypothesis by developing a hybrid physics-based/agent-based computational model in which aberrant fibroblast activation is induced when cells migrate on stiff tissue. This activation then feeds back on itself via the altered mechanical environment that it creates by depositing collagen.

MAIN RESULTS: The model produces power law distributions of both low- and high-attenuation area clusters and predicts the development of honeycombing only when mechanical rupture is allowed to take place in highly strained normal tissue surrounded by stiff fibrotic tissue. These predictions compare well with histologic data computed from CT images of patients with IPF.

SIGNIFICANCE: We conclude that the clinical manifestation of subpleural honeycombing in IPF may result from fibroblasts entering into a positive feedback loop induced by the abnormally high tissue stiffness near the pleura.