Hybrid physics-based and data-driven modeling of vascular bifurcation pressure differences.

Reduced-order models allow for the simulation of blood flow in patient-specific vasculatures. They offer a significant reduction in computational cost and wait time compared to traditional computational fluid dynamics models. Unfortunately, due to the simplifications made in their formulations, reduced-order models can suffer from significantly reduced accuracy.

FSGe: A fast and strongly-coupled 3D fluid-solid-growth interaction method.

Equilibrated fluid-solid-growth (FSGe) is a fast, open source, three-dimensional (3D) computational platform for simulating interactions between instantaneous hemodynamics and long-term vessel wall adaptation through mechanobiologically equilibrated growth and remodeling (G&R). Such models can capture evolving geometry, composition, and material properties in health and disease and following clinical interventions. In traditional G&R models, this feedback is modeled through highly simplified fluid solutions, neglecting local variations in blood pressure and wall shear stress (WSS).

Assessment of aortic dissection remodeling with patient-specific fluid-structure interaction models.

Aortic dissection leads to late complications due to chronic degeneration and dilatation of the false lumen. However, the interaction between hemodynamics and microstructural remodeling driving long-term changes is not fully understood. This study examines the progression of a patient's aortic dissection, tracked from pre-dissection to the chronic phase using computed tomography angiography.

Adaptive integration of history variables in constrained mixture models for organ-scale growth and remodeling.

In the last decades, many computational models have been developed to predict soft tissue growth and remodeling (G&R). The constrained mixture theory describes fundamental mechanobiological processes in soft tissue G&R and has been widely adopted in cardiovascular models of G&R. However, even after two decades of work, large organ-scale models are rare, mainly due to high computational costs (model evaluation and memory consumption), especially in long-range simulations.