Evaluation of the effect of postural and gravitational variations on the distribution of pulmonary blood flow via an image-based computational model

Abstract

We have developed an image-based computational model of blood flow within the human pulmonary circulation in order to investigate the distribution of flow under various conditions of posture and gravity. Geometric models of the lobar surfaces and largest arterial and venous vessels were derived from multi-detector row X-ray computed tomography. The remaining blood vessels were generated using a volume-filling branching algorithm. Equations representing conservation of mass and momentum are solved within the vascular geometry to calculate pressure, radius, and velocity distributions. Flow solutions are obtained within the model in the upright, inverted, prone, and supine postures and in the upright posture with and without gravity. Additional equations representing large deformation mechanics are used to calculate the change in lung geometry and pressure distributions within the lung in the various postures - creating a coupled, co-dependent model of mechanics and flow. The embedded vascular meshes deform in accordance with the lung geometry. Results illustrate a persistent flow gradient from the top to the bottom of the lung even in the absence of gravity and in all postures, indicating that vascular branching structure is largely responsible for the distribution of flow.