Computational simulations of hemodynamic changes within thoracic, coronary, and cerebral arteries following early wall remodeling in response to distal aortic coarctation

Abstract

Mounting evidence suggests that the pulsatile character of blood pressure and flow within large arteries plays a particularly important role as a mechano-biological stimulus for wall growth and remodeling. Nevertheless, understanding better the highly coupled interactions between evolving wall geometry, structure, and properties and the hemodynamics will require significantly more experimental data. Computational fluid-solid-growth models promise to aid in the design and interpretation of such experiments and to identify candidate mechanobiological mechanisms for the observed arterial adaptations. Motivated by recent aortic coarctation models in animals, we used a computational fluid-solid interaction model to study possible local and systemic effects on the hemodynamics within the thoracic aorta and coronary, carotid, and cerebral arteries due to a distal aortic coarctation and subsequent spatial variations in wall adaptation. In particular, we studied an initial stage of acute cardiac compensation (i.e., maintenance of cardiac output) followed by early arterial wall remodeling (i.e., spatially varying wall thickening and stiffening). Results suggested, for example, that while coarctation increased both the mean and pulse pressure in the proximal vessels, the locations nearest to the coarctation experienced the greatest changes in pulse pressure. In addition, after introducing a spatially varying wall adaptation, pressure, left ventricular work, and wave speed all increased. Finally, vessel wall strain similarly experienced spatial variations consistent with the degree of vascular wall adaptation.

Figures

Fig. 1

Schematic of the process for generating the final three-dimensional computational model of the human thoracic aorta, coronary arteries, and head and neck vessels based on CT images from two normal male subjects

Fig. 2

Close-up view of the finite element mesh in the aortic arch (left) and circle of Willis (right). Field-based adaptive mesh refinement techniques facilitated adequate resolution throughout the computational domain while keeping a reasonable bound on the final mesh size

Fig. 3

Schematic of the various lumped parameter models utilized to specify boundary conditions for the 3D computational model. The Windkessel model was applied at all outlets except the coronary tree; the heart model was applied at the aortic root, and the coronary model was prescribed at all outlets of the coronary tree

Fig. 4

Sections of the model with different wall properties. Color scale represents values of material stiffness adopted for each section. The acute cardiac compensation time frame refers to the introduction of coarctation and subsequent cardiac compensation, while the early arterial remodeling shows the differential stiffening observed in animal experiments in various regions of the vasculature

Fig. 5

Results for the baseline simulation. Pressure, flow, and wall strain are shown in each of the four primary arteries of interest. The location of the stars corresponds to the descending thoracic aorta, left anterior descending (LAD) coronary artery, left internal carotid artery, basilar artery (BA), and left middle cerebral artery (LMCA). The diameter of each of these vessels is: descending thoracic aorta = 2.1 cm, LAD coronary artery = 0.5 cm, left internal carotid artery = 0.7 cm, basilar artery = 0.3 cm, and left middle cerebral artery = 0.3 cm. For the coronary vasculature, pressure, and strain are calculated in the LAD, whereas the flow corresponds to the sum over the large coronary vessels (LAD; left circumflex, LCX; and right coronary artery, RCA). For the cerebral vasculature, pressure and strain are calculated in the LMCA and BA, and flow is calculated as the total flow in the right and left cerebral hemispheres as well as in the BA

Fig. 6

Results comparing pressure, flow, and wall strain in baseline, acute cardiac compensation, and early arterial remodeling conditions. The location of each measurement is denoted by the color-coded stars

Fig. 7

Pressure–volume loops reflecting the workload of the left ventricle during baseline conditions, acute cardiac compensation, and early arterial wall remodeling. The cardiac workload was 8,476, 9,890, and 11,059 mmHg mL for the baseline, acute cardiac compensation, and early arterial remodeling simulations, respectively

Fig. 8

Pressure contours during baseline conditions and early arterial remodeling. Increased wave speed is apparent in the vascular adaptation case. L denotes the path length from the aortic root to the LMCA, Δt denotes the time between the feet of the aortic and LMCA pressure contours, and c denotes the wave speed