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Iliac Vein Compression Syndrome (IVCS) is a common risk factor for deep vein thrombosis in the lower extremities. The objective of this study was to investigate whether employing a porous medium model to simulate the compressed region of an iliac vein could improve the reliability and accuracy of Computational Fluid Dynamics (CFD) analysis outcomes of IVCS. Pre-operative Computed Tomography (CT) scan images of patients with IVCS were utilized to reconstruct models illustrating both the compression and collateral circulation of the iliac vein. A porous medium model was employed to simulate the compressed region of the iliac vein. The agreements of times to peak between discrete phase particles in CFD analysis and contrast agent particles in Digital Subtraction Angiography (DSA) were compared. Furthermore, comparisons were made between the CFD analysis results that incorporated the porous media and those that did not. The results revealed that in the CFD analysis incorporating the porous media model, more than 80% of discrete phase particles reached the inferior vena cava via collateral circulation. Additionally, the concentration variation curve of discrete phase particles demonstrated a high concordance rate of 92.4% compared to that obtained in DSA. In comparison to CFD analysis conducted without the porous medium model, the incorporation of the porous medium model resulted in a substantial decrease in blood flow velocity by 87.5% within the compressed region, a significant increase in pressure gradient of 141 Pa between the inferior vena cava and left iliac vein, and a wider distribution of wall shear stress exceeding 2.0 Pa in collateral vessels rather than in the compressed region. The study suggests that the introduction of a porous medium model improves the hemodynamic analysis of patients with IVCS, resulting in a closer alignment with clinical observations. This provides a novel theoretical framework for the assessment and treatment of patients with IVCS.

Chronic obstructive pulmonary disease (COPD) is a primary chronic respiratory disease associated with pulmonary congestion that restricts airflow and thereby affects the exchange of gases between the alveoli and the blood capillaries in the lungs. Dual scale-global and local-porous medium models have been developed and reported in this work, to study the effects of air-side congestion on the blood-oxygen content in the alveolar region of the human lung. The human lung is model as a global, equivalent, heterogeneous porous medium comprising three zones with distinct permeabilities related to their progressively complex branching structure. Airflow for each breathing cycle is determined by solving mass and momentum transfer equations across the three porous medium zones. The congestion is introduced by appropriate modification of the porous medium properties of the zones considered. The congestion-affected air velocity reaching Zone 3 is given as input to a separate "local model" employed at several locations of the alveoli of Zone 3. The local model determines the oxygen content in the blood flow in the capillaries of the alveoli by solving suitable mass, momentum and species transport equations. The transient simulation results performed for a long duration of multiple breathing cycles, demonstrate that a normal, healthy human lung is functional for up to 40% volume congestion or when 50% of the lung is congested to about 23.5%. Increasing congestion beyond this value, quickly-within a few hours-depletes the oxygen exchange in the blood flow of the alveolar region (of Zone 3), leading to hypoxemia. The effects of congestion progression on oxygen exchange dynamics determined through the dual-scale porous medium modelling approach provide researchers and medical professionals with in silico predictive estimates to generate treatment strategies for chronic respiratory diseases., (© 2024 John Wiley & Sons Ltd.)