Tandem lesions associate with angiographic progression of coronary artery stenoses.

Background: Although the clinical factors associated with progression of coronary artery disease have been well studied, the angiographic predictors are less defined. Objectives: Our objective was to study the clinical and angiographic factors that associate with progression of coronary artery stenoses. Methods: We conducted a retrospective analysis of consecutive patients undergoing multiple, clinically indicated invasive coronary angiograms with an interval greater than 6 months, between January 2013 and December 2016. Lesion segments were analysed using Quantitative Coronary Angiography (QCA) if a stenosis ≥ 20 % was identified on either angiogram. Stenosis progression was defined as an increase ≥ 10 % in stenosis severity, with progressor groups analysed on both patient and lesion levels. Mixed-effects regression analyses were performed to evaluate factors associated with progression of individual stenoses. Results: 199 patients were included with 881 lesions analysed. 108 (54.3 %) patients and 186 (21.1 %) stenoses were classified as progressors. The median age was 65 years (IQR 56-73) and the median interval between angiograms was 2.1 years (IQR 1.2-3.0). On a patient level, age, number of lesions and presence of multivessel disease at baseline were each associated with progressor status. On a lesion level, presence of a stenosis downstream (OR 3.07, 95 % CI 2.04-4.63, p < 0.001) and circumflex artery stenosis location (OR 1.81, 95 % CI 1.21-2.7, p = 0.004) were associated with progressor status. Other lesion characteristics did not significantly impact progressor status or change in stenosis severity. Conclusion: Coronary lesions which have a downstream stenosis may be at increased risk of stenosis progression. Further research into the mechanistic basis of this finding is required, along with its implications for plaque vulnerability and clinical outcomes.

Pericoronary adipose tissue attenuation on coronary computed tomography angiography associates with male sex and Indigenous Australian status.

To evaluate if Indigenous Australians have higher coronary inflammation demonstrated non-invasively using pericoronary adipose tissue attenuation on coronary computed tomography angiography (CCTA). We retrospectively obtained a cohort 54 Indigenous patients age- and sex-matched to 54 non-Indigenous controls (age: 46.5 ± 13.1 years; male: n = 66) undergoing CCTA at the Royal Darwin Hospital and Monash Medical Centre. Patient groups were defined to investigate the interaction of ethnicity and sex: Indigenous + male, Indigenous + female, control + male, control + female. Semi-automated software was used to assess pericoronary adipose tissue attenuation (PCAT-a) and volume (PCAT-v). Males had significantly higher PCAT-a (- 86.7 ± 7.8 HU vs. - 91.3 ± 7.1 HU, p = 0.003) than females. Indigenous patients had significantly higher PCAT-v (1.5 ± 0.5cm3 vs. 1.3 ± 0.4cm3, p = 0.032), but only numerically higher PCAT-a (p = 0.133) than controls. There was a significant difference in PCAT-a and PCAT-v across groups defined by Indigenous status and sex (p = 0.010 and p = 0.030, respectively). Among patients with matching CCTA contrast density, multivariable linear regression analysis showed an independent association between Indigenous status and PCAT-a. Indigenous men have increased PCAT-a in an age- and sex-matched cohort. Male sex is strongly associated with increased PCAT-a. Coronary inflammation may contribute to adverse cardiovascular outcomes in Indigenous Australians, but larger studies are required to validate these findings.

Inter-software and inter-scan variability in measurement of epicardial adipose tissue: a three-way comparison of a research-specific, a freeware and a coronary application software platform.

OBJECTIVES: Epicardial adipose tissue (EAT) is a proposed marker of cardiovascular risk; however, clinical application may be limited by variability in post-processing software platforms. We assessed inter-vendor agreement of EAT volume (EATv) and attenuation on both contrast-enhanced (CE) and non-contrast CT (NCT) using a standard coronary CT reporting software (Vitrea), an EAT research-specific software (QFAT) and a freeware imaging software (OsiriX). METHODS: Seventy-six consecutive patients undergoing simultaneous CE and NCT had complete volumetric EAT measurement. Between-software, within-software NCT vs. CE, and inter- and intra-observer agreement were evaluated with analysis by ANOVA (with post hoc adjustment), Bland-Altman with 95% levels of agreement (LoA) and intraclass correlation coefficient (ICC). RESULTS: Mean EATv (freeware 53 ± 31 mL vs. research 93 ± 43 mL vs. coronary 157 ± 64 mL) and attenuation (freeware - 72 ± 25 HU vs. research - 75 ± 3 HU vs. coronary - 61 ± 10 HU) were significantly different between all vendors (ANOVA p < 0.001). EATv was consistently higher in NCT vs. CE for all software packages, with most reproducibility found in research software (bias 26 mL, 95% LoA: 2 to 56 mL), compared to freeware (bias 11 mL 95% LoA: - 46 mL to 69 mL) and coronary software (bias 10 mL 95% LoA: - 127 to 147 mL). Research software had more comparable NCT vs. CE attenuation (- 75 vs. - 72 HU) compared to freeware (- 72 vs. - 57 HU) and coronary (- 61 vs. - 39 HU). Excellent inter-observer agreement was seen with research (ICC 0.98) compared to freeware (ICC 0.73) and coronary software (ICC 0.75) with narrow LoA on Bland-Altman analysis. CONCLUSION: There are significant inter-vendor differences in EAT assessment. Our study suggests that research-specific software has better agreement and reproducibility compared to freeware or coronary software platforms. KEY POINTS: • There are significant differences between EAT volume and attenuation values between software platforms, regardless of scan type. • Non-contrast scans routinely have higher mean EAT volume and attenuation; however, this finding is only consistently seen with research-specific software. • Of the three analyzed packages, research-specific software demonstrates the highest reproducibility, agreement, and reliability for both inter-scan and inter-observer agreement.

Peri-Coronary Adipose Tissue Is a Predictor of Stent Failure in Patients Undergoing Percutaneous Coronary Intervention.

PURPOSE: Coronary inflammation is postulated as a driver of atherosclerosis and dysfunctional arterial healing which may trigger stent failure. Pericoronary adipose tissue (PCAT) attenuation, detected on computer tomography coronary angiography (CTCA), is an emerging non-invasive marker of coronary inflammation. This propensity matched study assessed the utility of both lesion specific (PCATLesion) and standardized PCAT attenuation as assessed in the proximal RCA (PCATRCA) as a predictor of stent failure in patients undergoing elective percutaneous coronary intervention. This is the first study to our knowledge that assesses the association of PCAT with stent failure. METHODS: Patients undergoing CTCA assessment for coronary artery disease with subsequent stent insertion within 60 days and repeat coronary angiography for any clinical reason within 5 years were included in the study. Stent failure was defined as binary restenosis of >50 % on quantitative coronary angiography analysis or stent thrombosis. Both PCATLesion and PCATRCA was assessed utilizing semi-automated proprietary software on baseline CTCA. Patients with stent failure were propensity matched utilizing age, sex, cardiovascular risk factors and procedural characteristics. RESULTS: One hundred and fifty-one patients met inclusion criteria. Of these, 26 (17.2 %) had study-defined failure. A significant difference in PCATLesion attenuation between patients with and without failure was observed (-79.0 ± 12.6 vs. -85.9 ± 10.3HU, p = 0.035). There was no significant difference in PCATRCA attenuation between the two groups (-79.5 ± 10.1 vs -81.0 ± 12.3HU, p = 0.50). Univariate regression analysis showed PCATLesion attenuation was independently associated with stent failure (OR 1.06, 95 % CI 1.01-1.12, P = 0.035). CONCLUSIONS: Patients with stent failure exhibit significantly increased PCATLesion attenuation at baseline. These data suggest that baseline plaque inflammation may be an important driver for coronary stent failure.

Noninvasive Plaque Imaging to Accelerate Coronary Artery Disease Drug Development.

Coronary artery disease (CAD) remains the leading cause of adult mortality globally. Targeting known modifiable risk factors has had substantial benefit, but there remains a need for new approaches. Improvements in invasive and noninvasive imaging techniques have enabled an increasing recognition of distinct quantitative phenotypes of coronary atherosclerosis that are prognostically relevant. There are marked differences in plaque phenotype, from the high-risk, lipid-rich, thin-capped atheroma to the low-risk, quiescent, eccentric, nonobstructive calcified plaque. Such distinct phenotypes reflect different pathophysiologic pathways and are associated with different risks for acute ischemic events. Noninvasive coronary imaging techniques, such as computed tomography, positron emission tomography, and coronary magnetic resonance imaging, have major potential to accelerate cardiovascular drug development, which has been affected by the high costs and protracted timelines of cardiovascular outcome trials. This may be achieved through enrichment of high-risk phenotypes with higher event rates or as primary end points of drug efficacy, at least in phase 2 trials, in a manner historically performed through intravascular coronary imaging studies. Herein, we provide a comprehensive review of the current technology available and its application in clinical trials, including implications for sample size requirements, as well as potential limitations. In its effort to accelerate drug development, the US Food and Drug Administration has approved surrogate end points for 120 conditions, but not for CAD. There are robust data showing the beneficial effects of drugs, including statins, on CAD progression and plaque stabilization in a manner that correlates with established clinical end points of mortality and major adverse cardiovascular events. This, together with a clear mechanistic rationale for using imaging as a surrogate CAD end point, makes it timely for CAD imaging end points to be considered. We discuss the importance of global consensus on these imaging end points and protocols and partnership with regulatory bodies to build a more informed, sustainable staged pathway for novel therapies.

Quantitative flow ratio to predict long-term coronary artery bypass graft patency in patients with left main coronary artery disease.

PURPOSE: Fractional flow reserve (FFR) has been demonstrated in some studies to predict long-term coronary artery bypass graft (CABG) patency. Quantitative flow ratio (QFR) is an emerging technology which may predict FFR. In this study, we hypothesised that QFR would predict long-term CABG patency and that QFR would offer superior diagnostic performance to quantitative coronary angiography (QCA) and intravascular ultrasound (IVUS). METHODS: A prospective study was performed on patients with left main coronary artery disease who were undergoing CABG. QFR, QCA and IVUS assessment was performed. Follow-up computed tomography coronary angiography and invasive coronary angiography was undertaken to assess graft patency. RESULTS: A total of 22 patients, comprising of 65 vessels were included in the analysis. At a median follow-up of 3.6 years post CABG (interquartile range, 2.3 to 4.8 years), 12 grafts (18.4%) were occluded. QFR was not statistically significantly higher in occluded grafts (0.81 ± 0.19 vs. 0.69 ± 0.21; P = 0.08). QFR demonstrated a discriminatory power to predict graft occlusion (area under the receiver operating characteristic curve, 0.70; 95% confidence interval [CI], 0.52 to 0.88; P = 0.03). At long-term follow-up, the risk of graft occlusion was higher in vessels with a QFR > 0.80 (58.6% vs. 17.0%; hazard ratio, 3.89; 95% CI, 1.05 to 14.42; P = 0.03 by log-rank test). QCA (minimum lumen diameter, lesion length, diameter stenosis) and IVUS (minimum lumen area, minimum lumen diameter, diameter stenosis) parameters were not predictive of long-term graft patency. CONCLUSIONS: QFR may predict long-term graft patency in patients undergoing CABG.

Quantitative plaque characterisation and association with acute coronary syndrome on medium to long term follow up: insights from computed tomography coronary angiography.

Background: Computed tomography coronary angiography (CTCA) is an established imaging modality widely used for diagnosing coronary artery stenosis with expanding potential for comprehensive assessment of coronary artery disease (CAD). Lesion-based analyses of high-risk plaques (HRP) on CTCA may aid further in prognostication presenting with stable chest pain. We conduct qualitative and quantitative assessments to identify HRPs that are associated with acute coronary syndrome (ACS) on a medium to long term follow-up. Methods: Retrospective cohort study of patients who underwent CTCA for suspected CAD. Obstructive stenosis (OS) is defined as ≥50% and the presence of HRP and its constituents: positive-remodelling (PR), low-attenuation-plaque (LAP; <56 HU), very-low-attenuation-plaque (vLAP; <30 HU) and spotty-calcification (SC) were recorded. A cross-sectional quantitative analysis of HRP was performed at the site of minimum-luminal-area (MLA). The primary endpoint was fatal or non-fatal ACS on follow-up. Results: A total of 1,257 patients were included (mean age 61±14 years old and 51% male) with a median follow-up of 7.24 years (interquartile range 5.5 to 7.7 years). The occurrence of ACS was significantly higher in HRP (+) patients compared to HRP (-) patients and patients with no plaques (20.5% vs. 1.6% vs. 0.4%, log-rank test P<0.001). ACS was more frequent in HRP (+)/OS (+) patients (20.7%) compared to HRP (+)/OS (-) patients (8.6%), HRP (-)/OS (+) patients (1.8%) and HRP (-)/OS (-) patients (1.0%). OS, cross-sectional plaque area (PA) and the presence of vLAP identified those HRP lesions that were more likely to cause future ACS. Cross-sectional LAP area (<56 HU) in HRP lesions added incremental prognostic value to OS in predicting ACS (P=0.008). Conclusions: The presence of OS and the LAP area at the site of MLA identify the HRP lesions that have the greatest association with development of future ACS.

Diagnostic performance of quantitative flow ratio, non-hyperaemic pressure indices and fractional flow reserve for the assessment of coronary lesions in severe aortic stenosis.

Background: Quantitative flow ratio (QFR) may be used to assess the functional significance of coronary lesions. Only limited validation exists for this technology in the setting of severe aortic stenosis. Methods: A prospective study was performed on patients who were being considered for transcatheter aortic valve implantation. QFR analysis was performed (Medis Medical Imaging System, Leiden, The Netherlands) and compared to invasive measurements of haemodynamic assessment [fractional flow reserve (FFR), instantaneous wave-free ratio (iFR), diastolic pressure ratio during the wave-free period (dPR) and distal arterial pressure/arterial pressure (Pd/Pa)]. Results: A total of 35 patients were included in the study. Mean age was 75.5±6.5 and mean aortic valve gradient was 44.3±11.8 mmHg. There were 57 vessels analysed. The mean FFR was 0.83±0.10 and 22 vessels (39%) had a functionally significant FFR ≤0.80. QFR demonstrated a discriminatory power to predict functionally significant FFR [area under the receiver operating characteristic curve (AUC), 0.92; 95% confidence interval (CI): 0.84 to 1.00], representing a sensitivity of 73%, specificity of 91%, positive predictive value of 84%, negative predictive value of 84% and an accuracy of 84%. QFR also demonstrated a discriminatory power to predict functionally significant iFR ≤0.89 (AUC =0.92; 95% CI: 0.85 to 0.99), dPR ≤0.89 (AUC =0.90; 95% CI: 0.83 to 0.98) and Pd/Pa ≤0.92 (AUC =0.89; 95% CI: 0.80 to 0.97). Conclusions: QFR demonstrates acceptable diagnostic performance in patients with severe aortic stenosis when both FFR and non-hyperaemic pressure indices are used as reference standards.

Atherogenic index of plasma is associated with epicardial adipose tissue volume assessed on coronary computed tomography angiography.

The atherogenic index of plasma (AIP) is a novel biomarker of atherogenic dyslipidaemia (AD), but its relationship with cardiac adipose tissue depots is unknown. We aimed to assess the association of AD with cardiac adipose tissue parameters on coronary computed tomography angiography (CCTA). We studied 161 patients who underwent CCTA between 2008 and 2011 (age 59.0 ± 14.0 years). AD was defined as triglyceride (TG) > 1.7 mmol/L and HDL < 1.0 mmol/L (n = 34). AIP was defined as the base 10 logarithmic ratio of TG to HDL. Plaque burden was assessed using the CT-Leaman score (CT-LeSc). We studied volume and attenuation of epicardial adipose tissue (EAT-v and EAT-a) and pericoronary adipose tissue (PCAT-v and PCAT-a) on CCTA using semi-automated software. Patients with AD had higher PCAT-v (p = 0.042) and EAT-v (p = 0.041). AIP was associated with EAT-v (p = 0.006), type II diabetes (p = 0.009) and male sex (p < 0.001) and correlated with CT-LeSc (p = 0.040). On multivariable analysis, AIP was associated with EAT-v ≥ 52.3 cm3, age, male sex and type II diabetes when corrected for traditional risk factors and plaque burden. AIP is associated with increased EAT volume, but not PCAT-a, after multivariable adjustment. These findings indicate AIP is associated with adverse adipose tissue changes which may increase coronary risk.

Radiomics-Based Precision Phenotyping Identifies Unstable Coronary Plaques From Computed Tomography Angiography.

OBJECTIVES: The aim of this study was to precisely phenotype culprit and nonculprit lesions in myocardial infarction (MI) and lesions in stable coronary artery disease (CAD) using coronary computed tomography angiography (CTA)-based radiomic analysis. BACKGROUND: It remains debated whether any single coronary atherosclerotic plaque within the vulnerable patient exhibits unique morphology conferring an increased risk of clinical events. METHODS: A total of 60 patients with acute MI prospectively underwent coronary CTA before invasive angiography and were matched to 60 patients with stable CAD. For all coronary lesions, high-risk plaque (HRP) characteristics were qualitatively assessed, followed by semiautomated plaque quantification and extraction of 1,103 radiomic features. Machine learning models were built to examine the additive value of radiomic features for discriminating culprit lesions over and above HRP and plaque volumes. RESULTS: Culprit lesions had higher mean volumes of noncalcified plaque (NCP) and low-density noncalcified plaque (LDNCP) compared with the highest-grade stenosis nonculprits and highest-grade stenosis stable CAD lesions (NCP: 138.1 mm3 vs 110.7 mm3 vs 102.7 mm3; LDNCP: 14.2 mm3 vs 9.8 mm3 vs 8.4 mm3; both Ptrend < 0.01). In multivariable linear regression adjusted for NCP and LDNCP volumes, 14.9% (164 of 1,103) of radiomic features were associated with culprits and 9.7% (107 of 1,103) were associated with the highest-grade stenosis nonculprits (critical P < 0.0007) when compared with highest-grade stenosis stable CAD lesions as reference. Hierarchical clustering of significant radiomic features identified 9 unique data clusters (latent phenotypes): 5 contained radiomic features specific to culprits, 1 contained features specific to highest-grade stenosis nonculprits, and 3 contained features associated with either lesion type. Radiomic features provided incremental value for discriminating culprit lesions when added to a machine learning model containing HRP and plaque volumes (area under the receiver-operating characteristic curve 0.86 vs 0.76; P = 0.004). CONCLUSIONS: Culprit lesions and highest-grade stenosis nonculprit lesions in MI have distinct radiomic signatures compared with lesions in stable CAD. Within the vulnerable patient may exist individual vulnerable plaques identifiable by coronary CTA-based precision phenotyping.

Coronary computed tomography angiography-based assessment of vascular inflammation in patients with obstructive sleep apnoea and coronary artery disease.

Background: Obstructive sleep apnoea (OSA) is associated with increased coronary artery disease (CAD) plaque burden, but the role of vascular inflammation in this relationship is unclear. Coronary computed tomography angiography (CTA) enables surrogate assessment of systemic inflammation via subcutaneous adipose tissue attenuation (SCAT-a), and of coronary inflammation via epicardial adipose tissue volume and attenuation (EAT-v and EAT-a) and pericoronary adipose tissue attenuation (PCAT-a). We investigated whether patients with severe OSA and high plaque burden have increased vascular inflammation. Methods: Patients with overnight polysomnography within ≤12 months of coronary CTA were included. Severe OSA was classified as apnoea/hypopnoea index (AHI) >30. High plaque burden was defined as a CT-adapted Leaman score (CT-LeSc) ≥8.3. Patients with both severe OSA and high plaque burden were defined as 'Group 1', all other patients were classified as 'Group 2'. ScAT, PCAT and EAT attenuation and volume were assessed on semi-automated software. Results: A total of 91 patients were studied (59.3±11.1 years). Severe OSA was associated with high plaque burden (P=0.02). AHI correlated with CT-LeSc (r=0.24, P=0.023). Group 1 had lower EAT-a and PCAT-a compared to Group 2 (EAT-a: -87.6 vs. -84.0 HU, P=0.011; PCAT-a: -90.4 vs. -83.4 HU, P<0.01). However, among patients with low plaque burden, EAT-a was higher in the presence of severe OSA versus mild-moderate OSA (-80.3 vs. -84.0 HU, P=0.020). On multivariable analysis, severe OSA and high plaque burden associated with EAT-a (P<0.02), and severe OSA and high plaque burden (P<0.01) and hypertension (P<0.01) associated with PCAT-a. Conclusions: EAT and PCAT attenuation are decreased in patients with severe OSA and high plaque burden, but EAT attenuation was increased in patients with severe OSA and low plaque burden. These divergent results suggest vascular inflammation may be increased in OSA independent of CAD, but larger studies are required to validate these findings.

Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study.

BACKGROUND: Atherosclerotic plaque quantification from coronary CT angiography (CCTA) enables accurate assessment of coronary artery disease burden and prognosis. We sought to develop and validate a deep learning system for CCTA-derived measures of plaque volume and stenosis severity. METHODS: This international, multicentre study included nine cohorts of patients undergoing CCTA at 11 sites, who were assigned into training and test sets. Data were retrospectively collected on patients with a wide range of clinical presentations of coronary artery disease who underwent CCTA between Nov 18, 2010, and Jan 25, 2019. A novel deep learning convolutional neural network was trained to segment coronary plaque in 921 patients (5045 lesions). The deep learning network was then applied to an independent test set, which included an external validation cohort of 175 patients (1081 lesions) and 50 patients (84 lesions) assessed by intravascular ultrasound within 1 month of CCTA. We evaluated the prognostic value of deep learning-based plaque measurements for fatal or non-fatal myocardial infarction (our primary outcome) in 1611 patients from the prospective SCOT-HEART trial, assessed as dichotomous variables using multivariable Cox regression analysis, with adjustment for the ASSIGN clinical risk score. FINDINGS: In the overall test set, there was excellent or good agreement, respectively, between deep learning and expert reader measurements of total plaque volume (intraclass correlation coefficient [ICC] 0·964) and percent diameter stenosis (ICC 0·879; both p<0·0001). When compared with intravascular ultrasound, there was excellent agreement for deep learning total plaque volume (ICC 0·949) and minimal luminal area (ICC 0·904). The mean per-patient deep learning plaque analysis time was 5·65 s (SD 1·87) versus 25·66 min (6·79) taken by experts. Over a median follow-up of 4·7 years (IQR 4·0-5·7), myocardial infarction occurred in 41 (2·5%) of 1611 patients from the SCOT-HEART trial. A deep learning-based total plaque volume of 238·5 mm3 or higher was associated with an increased risk of myocardial infarction (hazard ratio [HR] 5·36, 95% CI 1·70-16·86; p=0·0042) after adjustment for the presence of deep learning-based obstructive stenosis (HR 2·49, 1·07-5·50; p=0·0089) and the ASSIGN clinical risk score (HR 1·01, 0·99-1·04; p=0·35). INTERPRETATION: Our novel, externally validated deep learning system provides rapid measurements of plaque volume and stenosis severity from CCTA that agree closely with expert readers and intravascular ultrasound, and could have prognostic value for future myocardial infarction. FUNDING: National Heart, Lung, and Blood Institute and the Miriam & Sheldon G Adelson Medical Research Foundation.

Assessing the Impact of Colchicine on Coronary Plaque Phenotype After Myocardial Infarction with Optical Coherence Tomography: Rationale and Design of the COCOMO-ACS Study.

INTRODUCTION: Recurrent event rates after myocardial infarction (MI) remain unacceptably high, in part because of the continued growth and destabilization of residual coronary atherosclerotic plaques, which may occur despite lipid-lowering therapy. Inflammation is an important contributor to this ongoing risk. Recent studies have shown that the broad-acting anti-inflammatory agent, colchicine, may reduce adverse cardiovascular events in patients post-MI, although the mechanistic basis for this remains unclear. Advances in endovascular arterial wall imaging have allowed detailed characterization of the burden and compositional phenotype of coronary plaque, along with its natural history and responsiveness to treatment. One such example has been the use of optical coherence tomography (OCT) to demonstrate the plaque-stabilizing effects of statins on both fibrous cap thickness and the size of lipid pools within plaque. METHODS: The Phase 2, multi-centre, double-blind colchicine for coronary plaque modification in acute coronary syndrome (COCOMO-ACS) study will evaluate the effect of colchicine 0.5 mg daily on coronary plaque features using serial OCT imaging in patients following MI. Recruitment for the trial has been completed with 64 participants with non-ST elevation MI randomized 1:1 to colchicine or placebo in addition to guideline recommended therapies, including high-intensity statins. The primary endpoint is the effect of colchicine on the minimal fibrous cap thickness of non-culprit plaque over an 18-month period. The COCOMO-ACS study will determine whether addition of colchicine 0.5 mg daily to standard post-MI treatment has incremental benefits on high-risk features of coronary artery plaques. If confirmed, this will provide new mechanistic insights into how colchicine may confer clinical benefits in patients with atherosclerotic cardiovascular disease. TRIAL REGISTRATION: ANZCTR trial registration number: ACTRN12618000809235. Date of trial registration: 11th of May 2018.

Inflammation in Coronary Atherosclerosis and Its Therapeutic Implications.

Atherosclerotic coronary artery disease has a complex pathogenesis which extends beyond cholesterol intimal infiltration. It involves chronic inflammation of the coronary artery wall driven by systemic and local activation of both the adaptive and innate immune systems, which can ultimately result in the rupture or erosion of atherosclerotic plaque, leading to thrombosis and myocardial infarction (MI). Despite current best practice care, including the widespread use of cholesterol-lowering statins, atherothrombotic cardiovascular events recur at alarming rates post-MI. To a large extent, this reflects residual inflammation that is not adequately controlled by contemporary treatment. Consequently, there has been increasing interest in the pharmacological targeting of inflammation to improve outcomes in atherosclerotic cardiovascular disease. This has comprised both novel pathway-specific agents, most notably the anti-interleukin-1 beta monoclonal antibody, canakinumab, and the repurposing of established, broad-acting drugs, such as colchicine, that are already approved for the management of other inflammatory conditions. Here we discuss the importance of inflammation in mediating atherosclerosis and its complications and provide a timely update on "new" and "old" anti-inflammatory therapies currently being investigated to target it.

The Emerging Role of CT-Based Imaging in Adipose Tissue and Coronary Inflammation.

A large body of evidence arising from recent randomized clinical trials demonstrate the association of vascular inflammatory mediators with coronary artery disease (CAD). Vascular inflammation localized in the coronary arteries leads to an increased risk of CAD-related events, and produces unique biological alterations to local cardiac adipose tissue depots. Coronary computed tomography angiography (CTA) provides a means of mapping inflammatory changes to both epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT) as independent markers of coronary risk. Radiodensity or attenuation of PCAT on coronary CTA, notably, provides indirect quantification of coronary inflammation and is emerging as a promising non-invasive imaging implement. An increasing number of observational studies have shown robust associations between PCAT attenuation and major coronary events, including acute coronary syndrome, and 'vulnerable' atherosclerotic plaque phenotypes that are associated with an increased risk of the said events. This review outlines the biological characteristics of both EAT and PCAT and provides an overview of the current literature on PCAT attenuation as a surrogate marker of coronary inflammation.

Pericoronary Adipose Tissue Attenuation Is Associated with High-Risk Plaque and Subsequent Acute Coronary Syndrome in Patients with Stable Coronary Artery Disease.

BACKGROUND: High-risk plaques (HRP) detected on coronary computed tomography angiography (CTA) confer an increased risk of acute coronary syndrome (ACS). Pericoronary adipose tissue attenuation (PCAT) is a novel biomarker of coronary inflammation. This study aimed to evaluate the association of PCAT with HRP and subsequent ACS development in patients with stable coronary artery disease (CAD). METHODS: Patients with stable CAD who underwent coronary CTA from 2011 to 2016 and had available outcome data were included. We studied 41 patients with HRP propensity matched to 41 controls without HRP (60 ± 10 years, 67% males). PCAT was assessed using semi-automated software on a per-patient basis in the proximal right coronary artery (PCATRCA) and a per-lesion basis (PCATLesion) around HRP in cases and the highest-grade stenosis lesions in controls. RESULTS: PCATRCA and PCATLesion were higher in HRP patients than controls (PCATRCA: -80.7 ± 6.50 HU vs. -84.2 ± 8.09 HU, p = 0.03; PCATLesion: -79.6 ± 7.86 HU vs. -84.2 ± 10.3 HU, p = 0.04), and were also higher in men (PCATRCA: -80.5 ± 7.03 HU vs. -86.1 ± 7.08 HU, p < 0.001; PCATLesion: -79.6 ± 9.06 HU vs. -85.2 ± 7.96 HU, p = 0.02). Median time to ACS was 1.9 years, within a median follow-up of 5.3 years. PCATRCA alone was higher in HRP patients who subsequently presented with ACS (-76.8 ± 5.69 HU vs. -82.0 ± 6.32 HU, p = 0.03). In time-dependent analysis, ACS was associated with HRP and PCATRCA. CONCLUSIONS: PCAT attenuation is increased in stable CAD patients with HRP and is associated with subsequent ACS development. Further investigation is required to determine the clinical implications of these findings.

Cardiac Computed Tomography Radiomics for the Non-Invasive Assessment of Coronary Inflammation.

Radiomics, via the extraction of quantitative information from conventional radiologic images, can identify imperceptible imaging biomarkers that can advance the characterization of coronary plaques and the surrounding adipose tissue. Such an approach can unravel the underlying pathophysiology of atherosclerosis which has the potential to aid diagnostic, prognostic and, therapeutic decision making. Several studies have demonstrated that radiomic analysis can characterize coronary atherosclerotic plaques with a level of accuracy comparable, if not superior, to current conventional qualitative and quantitative image analysis. While there are many milestones still to be reached before radiomics can be integrated into current clinical practice, such techniques hold great promise for improving the imaging phenotyping of coronary artery disease.

Metabolic syndrome, fatty liver, and artificial intelligence-based epicardial adipose tissue measures predict long-term risk of cardiac events: a prospective study.

BACKGROUND: We sought to evaluate the association of metabolic syndrome (MetS) and computed tomography (CT)-derived cardiometabolic biomarkers (non-alcoholic fatty liver disease [NAFLD] and epicardial adipose tissue [EAT] measures) with long-term risk of major adverse cardiovascular events (MACE) in asymptomatic individuals. METHODS: This was a post-hoc analysis of the prospective EISNER (Early-Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research) study of participants who underwent baseline coronary artery calcium (CAC) scoring CT and 14-year follow-up for MACE (myocardial infarction, late revascularization, or cardiac death). EAT volume (cm3) and attenuation (Hounsfield units [HU]) were quantified from CT using fully automated deep learning software (< 30 s per case). NAFLD was defined as liver-to-spleen attenuation ratio < 1.0 and/or average liver attenuation < 40 HU. RESULTS: In the final population of 2068 participants (59% males, 56 ± 9 years), those with MetS (n = 280;13.5%) had a greater prevalence of NAFLD (26.0% vs. 9.9%), higher EAT volume (114.1 cm3 vs. 73.7 cm3), and lower EAT attenuation (-76.9 HU vs. -73.4 HU; all p < 0.001) compared to those without MetS. At 14 ± 3 years, MACE occurred in 223 (10.8%) participants. In multivariable Cox regression, MetS was associated with increased risk of MACE (HR 1.58 [95% CI 1.10-2.27], p = 0.01) independently of CAC score; however, not after adjustment for EAT measures (p = 0.27). In a separate Cox analysis, NAFLD predicted MACE (HR 1.78 [95% CI 1.21-2.61], p = 0.003) independently of MetS, CAC score, and EAT measures. Addition of EAT volume to current risk assessment tools resulted in significant net reclassification improvement for MACE (22% over ASCVD risk score; 17% over ASCVD risk score plus CAC score). CONCLUSIONS: MetS, NAFLD, and artificial intelligence-based EAT measures predict long-term MACE risk in asymptomatic individuals. Imaging biomarkers of cardiometabolic disease have the potential for integration into routine reporting of CAC scoring CT to enhance cardiovascular risk stratification. Trial registration NCT00927693.

Pericoronary adipose tissue computed tomography attenuation distinguishes different stages of coronary artery disease: a cross-sectional study.

AIMS: Vascular inflammation inhibits local adipogenesis in pericoronary adipose tissue (PCAT) and this can be detected on coronary computed tomography angiography (CCTA) as an increase in CT attenuation of PCAT surrounding the proximal right coronary artery (RCA). In this cross-sectional study, we assessed the utility of PCAT CT attenuation as an imaging biomarker of coronary inflammation in distinguishing different stages of coronary artery disease (CAD). METHODS AND RESULTS: Sixty patients with acute myocardial infarction (MI) were prospectively recruited to undergo CCTA within 48 h of admission, prior to invasive angiography. These participants were matched to patients with stable CAD (n = 60) and controls with no CAD (n = 60) by age, gender, BMI, risk factors, medications, and CT tube voltage. PCAT attenuation around the proximal RCA was quantified per-patient using semi-automated software. Patients with MI had a higher PCAT attenuation (-82.3 ± 5.5 HU) compared with patients with stable CAD (-90.6 ± 5.7 HU, P < 0.001) and controls (-95.8 ± 6.2 HU, P < 0.001). PCAT attenuation was significantly increased in stable CAD patients over controls (P = 0.01). The association of PCAT attenuation with stage of CAD was independent of age, gender, cardiovascular risk factors, epicardial adipose tissue volume, and CCTA-derived quantitative plaque burden. No interaction was observed for clinical presentation (MI vs. stable CAD) and plaque burden on PCAT attenuation. CONCLUSION: PCAT CT attenuation as a quantitative measure of global coronary inflammation independently distinguishes patients with MI vs. stable CAD vs. no CAD. Future studies should assess whether this imaging biomarker can track patient responses to therapies in different stages of CAD.