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The function of the pulmonary circulation is truly multi-scale, with blood transported through vessels from centimeter to micron scale. There are scale-dependent mechanisms that govern the flow in the pulmonary vascular system. However, very few computational models of pulmonary hemodynamics capture the physics of pulmonary perfusion across the spatial scales of functional importance in the lung. Here we present a multi-scale model that incorporates the 3-dimensional (3D) complexities of pulmonary blood flow in the major vessels, coupled to an anatomically-based vascular network model incorporating the multiple contributing factors to capillary perfusion, including gravity. Using the model we demonstrate how we can predict the impact of vascular remodeling and occlusion on both macro-scale functional drivers (flow distribution between lungs, and wall shear stress) and micro-scale contributors to gas exchange. The model predicts interactions between 3D and 1D models that lead to a redistribution of blood between postures, both on a macro- and a micro-scale. This allows us to estimate the effect of posture on left and right pulmonary artery wall shear stress, with predictions varying by 0.75–1.35 dyne/cm2 between postures.

Pulmonary hypertension has multiple etiologies and so can be difficult to diagnose, prognose, and treat. Diagnosis is typically made via invasive hemodynamic measurements in the main pulmonary artery and is based on observed elevation of mean pulmonary artery pressure. This static mean pressure enables diagnosis, but does not easily allow assessment of the severity of pulmonary hypertension, nor the etiology of the disease, which may impact treatment. Assessment of the dynamic properties of pressure and flow data obtained from catheterization potentially allows more meaningful assessment of the strain on the right heart and may help to distinguish between disease phenotypes. However, mechanistic understanding of how the distribution of disease in the lung leading to pulmonary hypertension impacts the dynamics of blood flow in the main pulmonary artery and/or the pulmonary capillaries is lacking. We present a computational model of the pulmonary vasculature, parameterized to characteristic features of pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension to help understand how the two conditions differ in terms of pulmonary vascular response to disease. Our model incorporates key features known to contribute to pulmonary vascular function in health and disease, including anatomical structure and multiple contributions from gravity. The model suggests that dynamic measurements obtained from catheterization potentially distinguish between distal and proximal vasculopathy typical of pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension. However, the model suggests a non-linear relationship between these data and vascular structural changes typical of pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension which may impede analysis of these metrics to distinguish between cohorts.

Pulmonary hypertension is a disease of the pulmonary vasculature which can occur for many different reasons, including pathological remodeling of the pulmonary vessels and occlusion of these vessels (amongst others). Pulmonary hypertension can lead to right heart failure and significantly reduces the quality of life of patients living with the condition. It is difficult to distinguish clinically between different classifications of pulmonary hypertension, and doing so accurately is critical for the management of an individual’s condition. In addition, different presentations of the disease (e.g. occlusion versus remodeling) can put different strains on the right heart, despite patients having very similar elevations in pulmonary artery pressure. In this study we use an anatomically based model of the pulmonary circulation to predict pressure and flow wave transmission and reflection in two different kinds of pulmonary hypertension – primary pulmonary hypertension, and chronic thrombotic pulmonary embolism (CTEPH), to enable analysis of the impact of disease type on impedance spectra in the main pulmonary artery.

Purpose: Diseases of the coronary arteries represent critical cardiovascular bleakness and mortality around the world. The main focus of this study is to simulate hemodialysis patients undergoing Coronary Artery Bypass Graft (CABG) surgery by the left internal mammary artery. The survey is to investigate whether subclavian-coronary steal syndrome will occur in patients with stenosis in their left subclavian. Methods: A three-dimensional model of Brachial—Radial—Ulnar tree arterial system and dialysis graft are constructed and then simulated by the implementation of fluid–structure interaction (FSI) and non-FSI models. After consent was obtained, data attributed to dialysis patients who had undergone coronary bypass surgery at the Tehran Heart Center (THD) was collected. Results: Stenosis in the subclavian artery causes the left internal mammary artery (LIMA) graft to lack flow that, in CABG cases, is supplying the heart muscle. With the increase of stenosis from zero to 54%, the flow results show a negative flow indicating reversed flow in the artery. Meanwhile, the comparison between flow quantity of a normal Left Anterior Descending (LAD) and LIMA in case of 38% stenosis in subclavian shows that the amount of flow reaching the heart is less than standard. The threshold stenosis in the subclavian artery for which subclavian-coronary steal phenomena occurs is simulated to be around 54%. Furthermore, investigation of the effect of flow quantity in cases of hemodialysis versus nonhemodialysis shows that the flow is lessened in case of hemodialysis. Conclusions: In hemodialysis patients with more than 38% stenosis in left subclavian, it is well advised that LIMA bypass graft is not the preferred graft choice, and at 54% of subclavian stenosis, the steal phenomenon occurs.