Temporal and spatial heterogeneity in pulmonary perfusion: a mathematical model to predict interactions between macro- and micro-vessels in health and disease

Abstract

Heterogeneity in pulmonary microvascular blood flow (perfusion) provides an early indicator of lung disease or disease susceptibility. However, most computational models of the pulmonary vasculature neglect structural heterogeneities, and are thus not accurate predictors of lung function in disease that is not diffuse (spread evenly through the lung). Models that do incorporate structural heterogeneity have either neglected the temporal dynamics of blood flow, or the structure of the smallest blood vessels. Larger than normal oscillations in pulmonary capillary calibre, high oscillatory stress contribute to disease progression. Hence, a model that captures both spatial and temporal heterogeneity in pulmonary perfusion could provide new insights into the early stages of pulmonary vascular disease. Here, we present a model of the pulmonary vasculature, which captures both flow dynamics, and the anatomic structure of the pulmonary blood vessels from the right to left heart including the micro-vasculature. The model is compared to experimental data in normal lungs. We confirm that spatial heterogeneity in pulmonary perfusion is time-dependent, and predict key features of pulmonary hypertensive disease using a simple implementation of increased vascular stiffness. doi:10.1017/S1446181118000111