Chang Min Lee

Purpose: Despite substantial advances in computational cardiovascular modeling, simplifying assumptions often overlook key compensatory mechanisms. To better capture physiological responses under pathological conditions, we incorporate two essential compensatory mechanisms—collateral circulation and arteriolar vasodilation—into a multiscale blood perfusion simulation framework. Methods: Collateral vessels are stochastically generated to supply ischemic regions, with model parameters systematically varied to control vessel density, caliber, and spatial distribution. Arteriolar vasodilation is modeled to represent the combined response of vascular smooth muscle cells to local metabolic and hemodynamic stimuli. To assess their impact on perfusion, artificial stenoses are introduced into both an idealized geometry and a subject-specific cerebrovascular model. Results: Simulation results across varying collateral configurations and vasodilation capacities demonstrate that perfusion enhancement from sub-resolution collateral vessels alone is limited and highly dependent on vessel caliber and density. In contrast, combining collateral flow with vasodilation produces a more pronounced improvement in tissue perfusion. These findings suggest that arteriolar vasodilation serves as the primary mechanism for ischemic compensation, with collateral circulation providing secondary support which is consistent with clinical observations. Conclusion: The proposed methods enable multiscale blood flow simulations while accounting for the main autoregulatory mechanisms. The models have been verified using literature data and are shown to provide accurate results.

Purpose: Simulating tissue deformation and flow alterations induced by external compression typically requires fluid–structure interaction (FSI) analysis, which is computationally demanding. This study presents a multi-fidelity FSI framework that efficiently captures tissue mechanics and hemodynamic responses to dynamic external pressure and demonstrates its applicability to compression therapy. Methods: We developed an FSI model that couples a one-dimensional deformable blood flow formulation with the three-dimensional (3D) Cauchy equation of motion. Model performance was evaluated by comparing the multi-fidelity and full FSI solutions in simplified cylindrical and subject-specific geometries. As a practical demonstration, the framework was applied to simulate a full-cycle pulsatile intermittent pneumatic compression (IPC) operation. Results: The model efficiently reproduced tissue deformation and hemodynamic changes under external compression, yielding Conclusion: This multi-fidelity FSI framework enables efficient and accurate simulation of tissue deformation and hemodynamic responses under external pressure, providing a tractable platform for large-scale parametric and optimization studies. Its application to IPC highlights potential to enhance therapeutic device design and support broader applications in biomedical modeling and medical device development.