A distributed lumped parameter model of blood flow with fluid-structure interaction

Simple Models of Complex Mechanics for Improved Hypertension Care: Learning to De-stiffen Arteries

Arteries can stiffen via different mechanisms due to the distending effects of blood pressure, the extracellular (ECM) and vascular smooth muscle cells (VSMC). This short review discusses how these simple models can be applied to the complex biomechanics of arteries to gain physiological insight into why an individual's arteries are stiff and identify new therapeutic strategies. In the Multi-Ethnic Study of Atherosclerosis, the important question of whether arteries stiffen with aging due to load-dependent or structural stiffening was investigated. Structural stiffening was consistently observed with aging, but load-dependent stiffening was highly variable. Importantly, the high load-dependent stiffness was associated with future cardiovascular disease events, but structural stiffness was not. Clinical studies in older, hypertensive adults surprisingly show that decreasing vascular smooth muscle tone can cause clinically significant increases in arterial stiffness. To understand this paradox, the author developed a model simple enough for clinical data but with biologically relevant extracellular matrix (ECM) and vascular smooth muscle cell (VSMC) stiffness parameters. The effect of VSMC tone on arterial stiffness depends on the ECM-VSMC stiffness ratio. Future research is needed to develop a framework that incorporates both the blood pressure dependence of arterial stiffness and the VSMC-ECM interaction on hemodynamics. This could result in personalized arterial stiffness treatments and improved CVD outcomes. The subtitle of this review is "Learning to De-Stiffen Arteries" because our results have so far only shown that we can acutely make arteries stiffer. We are optimistic though that the findings and the analytic techniques covered here will be one of the many steps along the path of the arterial stiffness research community learning how to de-stiffen arteries.

Enhanced 4D Flow MRI-Based CFD with Adaptive Mesh Refinement for Flow Dynamics Assessment in Coarctation of the Aorta

4D Flow MRI is a diagnostic tool that can visualize and quantify patient-specific hemodynamics and help interventionalists optimize treatment strategies for repairing coarctation of the aorta (COA). Despite recent developments in 4D Flow MRI, shortcomings include phase-offset errors, limited spatiotemporal resolution, aliasing, inaccuracies due to slow aneurysmal flows, and distortion of images due to metallic artifact from vascular stents. To address these limitations, we developed a framework utilizing Computational Fluid Dynamics (CFD) with Adaptive Mesh Refinement (AMR) that enhances 4D Flow MRI visualization/quantification. We applied this framework to five pediatric patients with COA, providing in-vivo and in-silico datasets, pre- and post-intervention. These two data sets were compared and showed that CFD flow rates were within 9.6% of 4D Flow MRI, which is within a clinically acceptable range. CFD simulated slow aneurysmal flow, which MRI failed to capture due to high relative velocity encoding (Venc). CFD successfully predicted in-stent blood flow, which was not visible in the in-vivo data due to susceptibility artifact. AMR improved spatial resolution by factors of 101 to 103 and temporal resolution four-fold. This computational framework has strong potential to optimize visualization/quantification of aneurysmal and in-stent flows, improve spatiotemporal resolution, and assess hemodynamic efficiency post-COA treatment.