Inference of alveolar capillary network connectivity from blood flow dynamics

Abstract

The intricate lung structure is crucial for gas exchange within the alveolar region. Despite extensive research, questions remain about the connection between capillaries and the vascular tree. We propose a computational approach combining three-dimensional morphological modeling with computational fluid dynamics simulations to explore alveolar capillary network connectivity based on blood flow dynamics.We developed three-dimensional sheet-flow models to accurately represent alveolar capillary morphology and conducted simulations to predict flow velocities and pressure distributions. Our approach leverages functional features to identify plausible system architectures. Given capillary flow velocities and arteriole-to-venule pressure drops, we deduced arteriole connectivity details. Preliminary analyses for non-human species indicate a single alveolus connects to at least two 20 µm arterioles or one 30 µm arteriole. Hence, our approach narrows down potential connectivity scenarios, but a unique solution may not always be expected.Integrating our blood flow model results into our previously published gas exchange application, Alvin, we linked these scenarios to gas exchange efficiency. We found that increased blood flow velocity correlates with higher gas exchange efficiency.Our study provides insights into pulmonary microvasculature structure by evaluating blood flow dynamics, offering a new strategy to explore the morphology-physiology relationship that is applicable to other tissues and organs. Future availability of experimental data will be crucial in validating and refining our computational models and hypotheses.