Towards Patient-Specific Modeling of Coronary Hemodynamics in Healthy and Diseased State

Abstract

A model describing the primary relations between the cardiac muscle and coronary circulation might be useful for interpreting coronary hemodynamics in case multiple types of coronary circulatory disease are present. The main contribution of the present study is the coupling of a microstructure-based heart contraction model with a 1D wave propagation model. The 1D representation of the vessels enables patient-specific modeling of the arteries and/or can serve as boundary conditions for detailed 3D models, while the heart model enables the simulation of cardiac disease, with physiology-based parameter changes. Here, the different components of the model are explained and the ability of the model to describe coronary hemodynamics in health and disease is evaluated. Two disease types are modeled: coronary epicardial stenoses and left ventricular hypertrophy with an aortic valve stenosis. In all simulations (healthy and diseased), the dynamics of pressure and flow qualitatively agreed with observations described in literature. We conclude that the model adequately can predict coronary hemodynamics in both normal and diseased state based on patient-specific clinical data.

Fast and Accurate Pressure-Drop Prediction in Straightened Atherosclerotic Coronary Arteries

“…3,12,30 These models are based on 1D formulations of the NS equation. 1,8,9,11,14,16,19,29 These studies were able to obtain valuable time-dependent solutions. However, the models require an estimate for the capacitance of vessel wall, which is difficult to obtain for diseased wall segments.…”

Impact of coronary bifurcation morphology on wave propagation

“…Two simpler assumptions are to impose a constant uniform PWS (37) (which implies decreasing β* distally) or uniform material property (implying an increase in the PWS distally) (42) throughout the network. A third common approach (43, 69) relies on an empirical relationship described by Olufsen (45), based on measurements from mostly the systemic circulation: $\frac{Eh}{r_0}=k_1{e}^{k_2{r}_0}+k_3$…”

Scalability and in vivo validation of a multiscale numerical model of the left coronary circulation

“…In constructing our model, gross anatomical measurements of only the largest conduit arteries were combined with a lumped parameter representation of the small intramyocardial vessels, with extravascular compression effects applied via a time-varying pressure source and variable resistance. This approach, also adopted by others (52,71), allows the model to be easily adapted to differing normal or pathological anatomies via anatomical studies (16), known common vascular abnormalities (44), or angiography from specific subjects. An alternative approach is to use stochastic vascular networks based on morphometric data, which allows many more vessels generations to be included in the 1D part of the model (25, 58) but increases computational demands.…”

“…That these effects play a role in shaping the coronary arterial flow waveform was first suggested by Rumberger et al (54,55) on the basis of flow transients ("oscillations") observed in early systole and diastole in the left anterior descending artery of horses, features that are also evident in published waveforms from humans and other species (5,14,38,76). More recently, therefore, a number of one-dimensional (1D) or multiscale (i.e., combined 0D/1D) models of the coronary circulation, which are best suited to the study of wave propagation effects, have been described (25,45,52,57,58,71). Validation of such models requires direct comparison of simulated and experimental waveform shapes, including any high-frequency flow transients.…”