Oscillatory wall shear stress is a dominant flow characteristic affecting lesion progression patterns and plaque vulnerability in patients with coronary artery disease

Abstract

Although experimental studies suggest that low and oscillatory wall shear stress (WSS) promotes plaque transformation to a more vulnerable phenotype, this relationship has not been examined in human atherosclerosis progression. Thus, the aim of this investigation was to examine the association between oscillatory WSS, in combination with WSS magnitude, and coronary atherosclerosis progression. We hypothesized that regions of low and oscillatory WSS will demonstrate progression towards more vulnerable lesions, while regions exposed to low and non-oscillatory WSS will exhibit progression towards more stable lesions. Patients (n = 20) with non-flow-limiting coronary artery disease (CAD) underwent baseline and six-month follow-up angiography, Doppler velocity and radiofrequency intravascular ultrasound (VH-IVUS) acquisition. Computational fluid dynamics models were constructed to compute time-averaged WSS magnitude and oscillatory WSS. Changes in VH-IVUS-defined total plaque and constituent areas were quantified in focal regions (i.e. sectors; n = 14 235) and compared across haemodynamic categories. Compared with sectors exposed to low WSS magnitude, high WSS sectors demonstrated regression of total plaque area (p < 0.001) and fibrous tissue (p < 0.001), and similar progression of necrotic core. Sectors subjected to low and oscillatory WSS exhibited total plaque area regression, while low and non-oscillatory WSS sectors demonstrated total plaque progression (p < 0.001). Furthermore, compared with low and non-oscillatory WSS areas, sectors exposed to low and oscillatory WSS demonstrated regression of fibrous (p < 0.001) and fibrofatty (p < 0.001) tissue and similar progression of necrotic core (p = 0.82) and dense calcium (p = 0.40). Herein, we demonstrate that, in patients with non-obstructive CAD, sectors subjected to low and oscillatory WSS demonstrated regression of total plaque, fibrous and fibrofatty tissue, and progression of necrotic core and dense calcium, which suggest a transformation to a more vulnerable phenotype.

Keywords: atherosclerosis; computational fluid dynamics; coronary artery disease; haemodynamics; intravascular ultrasound; wall shear stress.

Figure 1.

Schematic of the presented study. Multi-modal clinical imaging data and intracoronary haemodynamic measures were collected in the cardiac catheterization laboratory. The imaging data were used to construct the 3D lumen geometry, flow extensions were added and the geometry discretized. Acquired patient-specific haemodynamic data were prescribed as boundary conditions, and pulsatile simulations were performed to evaluate the flow field. These computed data were post-processed to quantify the haemodynamics metrics of interest (e.g. wall shear stress).

Figure 2.

Example time-averaged WSS (magnitude), oscillatory WSS and co-localized regions of low WSS and high oscillatory WSS (i.e. low and oscillatory WSS) distributions. Polar plots indicate the time-varying changes in WSS magnitude and direction throughout the cardiac cycle; 0° indicates the time-averaged WSS vector direction. Note the large variation in instantaneous WSS vector directions (high oscillatory WSS) and low WSS magnitudes in a region immediately near branching vessels (location A), while WSS vectors have a uniform direction (low oscillatory WSS) with instantaneous magnitudes > 50 dynes cm⁻² in a straight segment not near a coronary branch (location B).

Figure 3.

Evaluation of focal coronary artery disease progression. (a) Baseline and co-registered follow-up images divided into focal regions (sectors). (b) Quantification of focal (sector) changes in total plaque and VH-IVUS-defined constituent areas. (Online version in colour.)

Figure 4.

Quantification of the focal haemodynamic environment. (a) WSS data are extracted from the computational geometry at the location of the VH-IVUS images. (b,c) Time-averaged WSS magnitude and oscillatory WSS data are divided up into sectors, and values are averaged within each sector. Sectors with nodes within branching vessels were excluded from the analysis.

Figure 5.

Distribution of sectors across haemodynamic classifications. (a) Time-averaged WSS and oscillatory WSS categories. (b) Co-localization of low time-averaged WSS and oscillatory WSS categories. (Online version in colour.)

Figure 6.

Changes in plaque area in low, intermediate and high time-averaged WSS sectors over six months. (a) Total plaque area. (b) VH-IVUS-derived plaque constituents. Sectors exposed to intermediate or high WSS were associated with a decrease in total plaque area, while sectors exposed to high WSS sectors demonstrated an increase in necrotic core and dense calcium. Error bars are 95% CIs. p < 0.05: low versus intermediate (*), intermediate versus high (#) and low versus high WSS (†).

Figure 7.

Changes in total plaque and VH-IVUS derived plaque constituent areas in sectors subjected to low and non-oscillatory (low time-averaged WSS, low oscillatory WSS) or low and oscillatory (low time-averaged WSS, high oscillatory WSS) WSS. Notably, focal regions of low and oscillatory WSS demonstrated regression of total plaque, fibrous and fibrofatty tissue area, and progression of necrotic core and dense calcium, suggestive of a transformation to a more vulnerable phenotype. Error bars are 95% CIs.

Figure 8.

Example IVUS images at baseline and follow-up demonstrating focal changes in plaque area (greyscale IVUS) and constituents (VH-IVUS) stratified by haemodynamic categories. Sectors exposed to low time-averaged WSS and oscillatory WSS or high time-averaged WSS exhibited a decrease in total plaque area with progression of necrotic core and dense calcium tissue.