Advances in the Computational Assessment of Disturbed Coronary Flow and Wall Shear Stress: A Contemporary Review

Abstract

Coronary artery blood flow is influenced by various factors including vessel geometry, hemodynamic conditions, timing in the cardiac cycle, and rheological conditions. Multiple patterns of disturbed coronary flow may occur when blood flow separates from the laminar plane, associated with inefficient blood transit, and pathological processes modulated by the vascular endothelium in response to abnormal wall shear stress. Current simulation techniques, including computational fluid dynamics and fluid-structure interaction, can provide substantial detail on disturbed coronary flow and have advanced the contemporary understanding of the natural history of coronary disease. However, the clinical application of these techniques has been limited to hemodynamic assessment of coronary disease severity, with the potential to refine the assessment and management of coronary disease. Improved computational efficiency and large clinical trials are required to provide an incremental clinical benefit of these techniques beyond existing tools. This contemporary review is a clinically relevant overview of the disturbed coronary flow and its associated pathological consequences. The contemporary methods to assess disturbed flow are reviewed, including clinical applications of these techniques. Current limitations and future opportunities in the field are also discussed.

Keywords: CFD; FSI; WSS; coronary geometry; disturbed coronary flow.

Figure 1. Advances in the computational assessment of disturbed coronary flow and wall shear stress.

Complexities in coronary geometry and biomechanical forces within the coronary artery result in various patterns of disturbed coronary flow. Disturbed flow results in unfavorable interactions with the vascular endothelium and inefficient blood transit. Computational fluid dynamics and fluid–structure interaction are contemporary computational techniques incorporating clinical data such as imaging and hemodynamic measurements to characterize disturbed coronary flow. These technologies have been applied meaningfully in research and have a role in the pressure‐based assessment and prognostication of coronary disease, however, more clinical research and improved computational efficiency are required to gain further value in its clinical application.

Figure 2. Patterns of disturbed coronary flow and multidirectional patterns of WSS.

There are various patterns of disturbed coronary flow relating to various biomechanical forces. Flow may recirculate into helical patterns, vortices, or eddies. Flow may also oscillate in various directions. These flow patterns disperse energy into the arterial wall in various directions resulting in WSS of varying magnitude and direction. The multidirectional quantification of the cycle‐averaged WSS orthogonal to the mean WSS vector is represented by transverse WSS. WSS_ax refers to WSS in the axial direction (ie, perpendicular to the tangent of the vessel centerline), and WSS_circ or secondary WSS is parallel to the vessel circumference. A more detailed computation of the variability in the WSS vector field can be carried out to analyze WSS divergence, which measures the contraction/expansion action of the WSS vector field/forces acting on the endothelium. The variability of these contraction/expansion regions over the cardiac cycle is represented by the topological shear variation index. Oscillatory shear index measures the degree of oscillatory WSS at the intimal surface of the vessel wall and occurs in a direction perpendicular to the vessel wall (opposite to the direction of flow). Pressure is the sum of the static pressure and dynamic pressure and is exerted in a direction perpendicular to the vessel wall. WSS indicates wall shear stress; WSS_ax, axial wall shear stress; WSS_circ; and circumferential wall shear stress.

Figure 3. Complex coronary geometries and subsequent flow patterns.

This figure depicts flow through a geometrically complex coronary artery, including concentric stenosis, tortuous segment, eccentric stenosis, surface roughness, and a bifurcation, as the blood flows from left to right. Convective acceleration is seen in the prestenotic segment approaching concentric stenosis. There is viscous energy loss across the stenosis and flow separation poststenosis. High WSS and velocities are observed on the outer walls of tortuous segments, and lower on the inner walls. Eccentric lesions are associated with increased poststenotic delaminarization and recirculation of flow. Oscillatory flow is observed in the cavities of the roughened intimal surface of the vessel wall. The inner walls at the carina of a bifurcation are associated with higher velocities and recirculation, with higher associated WSS. Lower WSS is observed on the outer walls of bifurcations, explaining the observation of preferential plaque progression on the outer walls of bifurcations. WSS indicates wall shear stress.

Figure 4. Workflow of coronary computational fluid dynamics and fluid–structure interaction.

There are multiple steps in the workflow of CFD and FSI. A, Geometric data acquisition using CTCA or ICA images, often incorporating intravascular imaging for increased resolution. B, Segmentation of acquired images and aligning images on the vessel's centerline is required to reconstruct a 3‐dimensional model. C, Boundary hemodynamic conditions are applied to the geometric model. D, A 3‐dimensional mesh is generated to discretize the 3‐dimensional model (ie, transferring continuous variables and equations into discrete, mathematically distinct counterparts). E, The Navier–Stokes equations are solved to simulate flow in coronary arteries. FSI incorporates the pulsatile nature of flow into the simulation. CFD indicates computational fluid dynamics; CTCA, computed tomography coronary angiography; FSI, fluid–structure interaction; and ICA, invasive coronary angiography.