Comprehensive biomechanical and anatomical atherosclerotic plaque metrics predict major adverse cardiovascular events: A new tool for clinical decision making.

BACKGROUND AND AIMS: Anatomical imaging alone of coronary atherosclerotic plaques is insufficient to identify risk of future adverse events and guide management of non-culprit lesions. Low endothelial shear stress (ESS) and high plaque structural stress (PSS) are associated with events, but individually their predictive value is insufficient for risk prediction. We determined whether combining multiple complementary, biomechanical and anatomical plaque characteristics improves outcome prediction sufficiently to inform clinical decision-making. METHODS: We examined baseline ESS, ESS gradient (ESSG), PSS, and PSS heterogeneity index (HI), and plaque burden in 22 lesions that developed subsequent events and 64 control lesions that remained quiescent from the PROSPECT study. RESULTS: 86 fibroatheromas were analysed from 67 patients. Lesions with events showed higher PSS HI (0.32 vs. 0.24, p<0.001), lower local ESS (0.56Pa vs. 0.91Pa, p = 0.007), and higher ESSG (3.82 Pa/mm vs. 1.96 Pa/mm, p = 0.007), while high PSS HI (hazard ratio [HR] 3.9, p = 0.006), high ESSG (HR 3.4, p = 0.007) and plaque burden>70 % (HR 2.6, p = 0.02) were independent outcome predictors in multivariate analysis. Combining low ESS, high ESSG, and high PSS HI gave both high positive predictive value (80 %), which increased further combined with plaque burden>70 %, and negative predictive value (81.6 %). Low ESS, high ESSG, and high PSS HI co-localised spatially within 1 mm in lesions with events, and importantly, this cluster was distant from the minimum lumen area site. CONCLUSIONS: Combining complementary biomechanical and anatomical metrics significantly improves risk-stratification of individual coronary lesions. If confirmed from larger prospective studies, our results may inform targeted revascularisation vs. conservative management strategies.

The role of endothelial shear stress, shear stress gradient, and plaque topography in plaque erosion.

BACKGROUND AND AIMS: Plaque erosion is a common underlying cause of acute coronary syndromes. The role of endothelial shear stress (ESS) and endothelial shear stress gradient (ESSG) in plaque erosion remains unknown. We aimed to determine the role of ESS metrics and maximum plaque slope steepness in plaques with erosion versus stable plaques. METHODS: This analysis included 46 patients/plaques from TOTAL and COMPLETE trials and Brigham and Women's Hospital's database who underwent angiography and OCT. Plaques were divided into those with erosion (n = 24) and matched stable coronary plaques (n = 22). Angiographic views were used to generate a 3-D arterial reconstruction, with centerlines merged from angiography and OCT pullback. Local ESS metrics were assessed by computational fluid dynamics. Among plaque erosions, the up- and down-slope (Δ lumen area/frame) was calculated for each culprit plaque. RESULTS: Compared with stable plaque controls, plaques with an erosion were associated with higher max ESS (8.3 ± 4.8 vs. 5.0 ± 1.9 Pa, p = 0.02) and max ESSG any direction (9.2 ± 7.5 vs. 4.3 ± 3.11 Pa/mm, p = 0.005). Proximal erosion was associated with a steeper plaque upslope while distal erosion with a steeper plaque downslope. Max ESS and Max ESSG any direction were independent factors in the development of plaque erosion (OR 1.32, 95%CI 1.06-1.65, p = 0.014; OR 1.22, 95% CI 1.03-1.45, p = 0.009, respectively). CONCLUSIONS: In plaques with similar luminal stenosis, plaque erosion was strongly associated with higher ESS, ESS gradients, and plaque slope as compared with stable plaques. These data support that ESS and slope metrics play a key role in the development of plaque erosion and may help prognosticate individual plaques at risk for future erosion.

Endothelial shear stress computed from coronary computed tomography angiography: A direct comparison to intravascular ultrasound.

INTRODUCTION: Intravascular ultrasound (IVUS) studies have shown that biomechanical variables, particularly endothelial shear stress (ESS), add synergistic prognostic insight when combined with anatomic high-risk plaque features. Non-invasive risk assessment of coronary plaques with coronary computed tomography angiography (CCTA) would be helpful to enable broad population risk-screening. AIM: To compare the accuracy of ESS computation of local ESS metrics by CCTA vs IVUS imaging. METHODS: We analyzed 59 patients from a registry of patients who underwent both IVUS and CCTA for suspected CAD. CCTA images were acquired using either a 64- or 256-slice scanner. Lumen, vessel, and plaque areas were segmented from both IVUS and CCTA (59 arteries, 686 3-mm segments). Images were co-registered and used to generate a 3-D arterial reconstruction, and local ESS distribution was assessed by computational fluid dynamics (CFD) and reported in consecutive 3-mm segments. RESULTS: Anatomical plaque characteristics (vessel, lumen, plaque area and minimal luminal area [MLA] per artery) were correlated when measured with IVUS and CCTA: 12.7 â€‹± â€‹4.3 vs 10.7 â€‹± â€‹4.5 â€‹mm2, r â€‹= â€‹0.63; 6.8 â€‹± â€‹2.7 vs 5.6 â€‹± â€‹2.7 â€‹mm2, r â€‹= â€‹0.43; 5.9 â€‹± â€‹2.9 vs 5.1 â€‹± â€‹3.2 â€‹mm2, r â€‹= â€‹0.52; 4.5 â€‹± â€‹1.3 vs 4.1 â€‹± â€‹1.5 â€‹mm2, r â€‹= â€‹0.67 respectively. ESS metrics of local minimal, maximal, and average ESS were also moderately correlated when measured with IVUS and CCTA (2.0 â€‹± â€‹1.4 vs 2.5 â€‹± â€‹2.6 â€‹Pa, r â€‹= â€‹0.28; 3.3 â€‹± â€‹1.6 vs 4.2 â€‹± â€‹3.6 â€‹Pa, r â€‹= â€‹0.42; 2.6 â€‹± â€‹1.5 vs 3.3 â€‹± â€‹3.0 â€‹Pa, r â€‹= â€‹0.35, respectively). CCTA-based computation accurately identified the spatial localization of local ESS heterogeneity compared to IVUS, with Bland-Altman analyses indicating that the absolute ESS differences between the two CCTA methods were pathobiologically minor. CONCLUSION: Local ESS evaluation by CCTA is possible and similar to IVUS; and is useful for identifying local flow patterns that are relevant to plaque development, progression, and destabilization.

Sex-related differences in plaque characteristics and endothelial shear stress related plaque-progression in human coronary arteries.

BACKGROUND AND AIMS: Clinical atherosclerosis manifestations are different in women compared to men. Since endothelial shear stress (ESS) is known to play a critical role in coronary atherosclerosis development, we investigated differences in anatomical characteristics and endothelial shear stress (ESS)-related plaque growth in human coronary arteries in men compared to women. METHODS: 1183 coronary arteries (male/female: 944/239) from the PREDICTION study were studied for differences in artery/plaque and ESS characteristics, and ESS-related plaque progression (6-10 months follow-up) among men and women and after stratification for age. All characteristics were derived from IVUS-based vascular profiling and reported per 3 mm-segments (13,030 3-mm-segments (male/female: 10,465/2,565)). RESULTS: Coronary arteries and plaques were significantly smaller in females compared to males; but no important differences were observed in plaque burden, ESS and rate of plaque progression. Change in plaque burden was inversely related to ESS (p<0.001) with no difference between women versus men (ß: -0.62 ± 0.13 vs -0.68 ± 0.05, p=0.62). However, stratification for age demonstrated that ESS-related plaque growth was more marked in young women compared to men (<55 years, ß: -2.02 ± 0.61 vs -0.33 ± 0.10, p=0.007), reducing in magnitude over the age-categories up till 75 years. CONCLUSIONS: Coronary artery and plaque size are smaller in women compared to men, but ESS and ESS- related plaque progression were similar. Sex-related differences in ESS-related plaque growth were evident after stratification for age. These observations suggest that although the fundamental processes of atherosclerosis progression are similar in men versus women, plaque progression may be influenced by age within gender.

Spatial relationships among hemodynamic, anatomic, and biochemical plaque characteristics in patients with coronary artery disease.

BACKGROUND AND AIMS: We aimed to characterize the spatial proximity of plaque destabilizing features local endothelial shear stress (ESS), minimal luminal area (MLA), plaque burden (PB), and near-infrared spectroscopy (NIRS) lipid signal in high- vs. low-risk plaques. METHODS: Coronary arteries imaged with angiography and NIRS-intravascular ultrasound (IVUS) underwent 3D reconstruction and computational fluid dynamics calculations of local ESS. ESS, PB, MLA, and lipid core burden index (LCBI), for each 3-mm arterial segment were obtained in arteries with large lipid-rich plaque (LRP) vs. arteries with smaller LRP. The locations of the MLA, minimum ESS (minESS), maximum ESS (maxESS), maximum PB (maxPB), and maximum LCBI in a 4-mm segment (maxLCBI4mm) were determined along the length of each plaque. RESULTS: The spatial distributions of minESS, maxESS, maxPB, and maxLCBI4mm, in reference to the MLA, were significantly heterogeneous within and between each variable. The location of maxLCBI4mm was spatially discordant from sites of the MLA (p<0.0001), minESS (p = 0.003), and maxESS (p = 0.003) in arteries with large LRP (maxLCBI4mm ≥ 400) and non-large LRP. Large LRP arteries had higher maxESS (9.31 ± 4.78 vs. 6.32 ± 5.54 Pa; p = 0.023), lower minESS (0.41 ± 0.16 vs. 0.61 ± 0.26 Pa; p = 0.007), smaller MLA (3.54 ± 1.22 vs. 5.14 ± 2.65 mm2; p = 0.002), and larger maxPB (70.64 ± 9.95% vs. 56.70 ± 13.34%, p<0.001) compared with non-large LRP arteries. CONCLUSIONS: There is significant spatial heterogeneity of destabilizing plaque features along the course of both large and non-large LRPs. Large LRPs exhibit significantly more abnormal destabilizing plaque features than non-large LRPs. Prospective, longitudinal studies are required to determine which patterns of heterogeneous destabilizing features act synergistically to cause plaque destabilization.

Validation of Wall Shear Stress Assessment in Non-invasive Coronary CTA versus Invasive Imaging: A Patient-Specific Computational Study.

Endothelial shear stress (ESS) identifies coronary plaques at high risk for progression and/or rupture leading to a future acute coronary syndrome. In this study an optimized methodology was developed to derive ESS, pressure drop and oscillatory shear index using computational fluid dynamics (CFD) in 3D models of coronary arteries derived from non-invasive coronary computed tomography angiography (CTA). These CTA-based ESS calculations were compared to the ESS calculations using the gold standard with fusion of invasive imaging and CTA. In 14 patients paired patient-specific CFD models based on invasive and non-invasive imaging of the left anterior descending (LAD) coronary arteries were created. Ten patients were used to optimize the methodology, and four patients to test this methodology. Time-averaged ESS (TAESS) was calculated for both coronary models applying patient-specific physiological data available at the time of imaging. For data analysis, each 3D reconstructed coronary artery was divided into 2 mm segments and each segment was subdivided into 8 arcs (45°).TAESS and other hemodynamic parameters were averaged per segment as well as per arc. Furthermore, the paired segment- and arc-averaged TAESS were categorized into patient-specific tertiles (low, medium and high). In the ten LADs, used for optimization of the methodology, we found high correlations between invasively-derived and non-invasively-derived TAESS averaged over segments (n = 263, r = 0.86) as well as arcs (n = 2104, r = 0.85, p < 0.001). The correlation was also strong in the four testing-patients with r = 0.95 (n = 117 segments, p = 0.001) and r = 0.93 (n = 936 arcs, p = 0.001).There was an overall high concordance of 78% of the three TAESS categories comparing both methodologies using the segment- and 76% for the arc-averages in the first ten patients. This concordance was lower in the four testing patients (64 and 64% in segment- and arc-averaged TAESS). Although the correlation and concordance were high for both patient groups, the absolute TAESS values averaged per segment and arc were overestimated using non-invasive vs. invasive imaging [testing patients: TAESS segment: 30.1(17.1-83.8) vs. 15.8(8.8-63.4) and TAESS arc: 29.4(16.2-74.7) vs 15.0(8.9-57.4) p < 0.001]. We showed that our methodology can accurately assess the TAESS distribution non-invasively from CTA and demonstrated a good correlation with TAESS calculated using IVUS/OCT 3D reconstructed models.