Application of physics-based flow models in cardiovascular medicine: Current practices and challenges.

Personalized physics-based flow models are becoming increasingly important in cardiovascular medicine. They are a powerful complement to traditional methods of clinical decision-making and offer a wealth of physiological information beyond conventional anatomic viewing using medical imaging data. These models have been used to identify key hemodynamic biomarkers, such as pressure gradient and wall shear stress, which are associated with determining the functional severity of cardiovascular diseases. Importantly, simulation-driven diagnostics can help researchers understand the complex interplay between geometric and fluid dynamic parameters, which can ultimately improve patient outcomes and treatment planning. The possibility to compute and predict diagnostic variables and hemodynamics biomarkers can therefore play a pivotal role in reducing adverse treatment outcomes and accelerate development of novel strategies for cardiovascular disease management.

Examining metastatic behavior within 3D bioprinted vasculature for the validation of a 3D computational flow model.

Understanding the dynamics of circulating tumor cell (CTC) behavior within the vasculature has remained an elusive goal in cancer biology. To elucidate the contribution of hydrodynamics in determining sites of CTC vascular colonization, the physical forces affecting these cells must be evaluated in a highly controlled manner. To this end, we have bioprinted endothelialized vascular beds and perfused these constructs with metastatic mammary gland cells under physiological flow rates. By pairing these in vitro devices with an advanced computational flow model, we found that the bioprinted analog was readily capable of evaluating the accuracy and integrated complexity of a computational flow model, while also highlighting the discrete contribution of hydrodynamics in vascular colonization. This intersection of these two technologies, bioprinting and computational simulation, is a key demonstration in the establishment of an experimentation pipeline for the understanding of complex biophysical events.

A Framework for Comparing Vascular Hemodynamics at Different Points in Time.

Computational simulations of blood flow contribute to our understanding of the interplay between vascular geometry and hemodynamics. With an improved understanding of this interplay from computational fluid dynamics (CFD), there is potential to improve basic research and the targeting of clinical care. One avenue for further analysis concerns the influence of time on the vascular geometries used in CFD simulations. The shape of blood vessels changes frequently, as in deformation within the cardiac cycle, and over long periods of time, such as the development of a stenotic plaque or an aneurysm. These changes in the vascular geometry will, in turn, influence flow within these blood vessels. By performing CFD simulations in geometries representing the blood vessels at different points in time, the interplay of these geometric changes with hemodynamics can be quantified. However, performing CFD simulations on different discrete grids leads to an additional challenge: how does one directly and quantitatively compare simulation results from different vascular geometries? In a previous study, we began to address this problem by proposing a method for the simplified case where the two geometries share a common centerline. In this companion paper, we generalize this method to address geometric changes which alter the vessel centerline. We demonstrate applications of this method to the study of wall shear stress in the left coronary artery. First, we compute the difference in wall shear stress between simulations using vascular geometries derived from patient imaging data at two points in the cardiac cycle. Second, we evaluate the relationship between changes in wall shear stress and the progressive development of a coronary aneurysm or stenosis.