Objectives-Pericardial fat as a visceral fat depot may be involved in the pathogenesis of coronary atherosclerosis. To gain evidence for that concept we sought to investigate the relation of pericardial fat volumes to risk factors, serum adiponectin levels, inflammatory biomarkers, and the quantity and morphology of coronary atherosclerosis. PϾ0.001). No association was found between BMI and coronary atherosclerosis. PAT volumes Ͼ300 cm 3 were the strongest independent risk factor for coronary atherosclerosis (odds ratio 4.1; CI 3.63 to 4.33) also significantly stronger compared to the Framingham score. We furthermore demonstrated that elevated PAT volumes are significantly associated with low adiponectin levels, low HDL levels, elevated TNF-␣ levels, and hsCRP. Conclusion-In the present study we demonstrated that elevated PAT volumes are associated with coronary atherosclerosis, hypoadiponectinemia, and inflammation and represent the strongest risk factor for the presence of atherosclerosis and may be important for risk stratification and monitoring. Key Words: cardiac CT Ⅲ pericardial fat Ⅲ obesity Ⅲ adiponectin Ⅲ plaque imaging T here is growing evidence that regional visceral fat distribution may contribute to an unfavorable metabolic and cardiovascular risk profile. 1,2 In patients with obesity, insulin resistance, diabetes, and hyperlipidemia visceral fat hypertrophies and transforms into a multifunctional organ that produces and secretes multiple endocrine and paracrine factors promoting inflammation, neovascularization, and oxidative stress, features that also characterize atherosclerosis. 3 Pericardial fat as a local visceral fat depot with close proximity to coronary arteries may serve as a source of inflammatory cytokines and cells that may locally enhance systemic proatherogenic effects via outside to inside signaling. 4,5 Thus it may be a specific parameter indicating an unfavorable cardio-metabolic state and may be used for risk stratification. To date, however, only little attention has focused on this regional fat depot located around the heart and its relation to cardiovascular risk factors, and the quantity and composition of coronary atherosclerosis is not well studied yet. Methods and Results-UsingMulti-slice CT is a noninvasive tool that allows to reliably assess both obstructive and nonobstructive subclinical coronary artery disease in an earlier stage than invasive angiography. 6 -9 Based on density measurements, plaques can be further characterized in noncalcified, mixed, and calcified plaques. 7 By using the same scan data this tool furthermore allows to quantify the exact pericardial fat volume. 9 We thus sought to assess the relation of pericardial fat volume to cardiovascular risk factors, levels of inflammatory cytokines, adiponectin, and to the extent and the phenotype of coronary atherosclerosis.

Objectives: Chemerin is a recently discovered adipokine that regulates adipocyte differentiation and modulates chemotaxis and activation of dendritic cells and macrophages. Given the convergence of adipocyte and macrophage function, chemerin may provide an interesting link between obesity, inflammation and atherosclerosis in humans. We sought to examine the relationship of i) chemerin and markers of inflammation, ii) chemerin and components of the metabolic syndrome, and iii) chemerin and coronary atherosclerotic plaque burden and morphology. Design: Serum chemerin levels were determined in 303 patients with stable typical or atypical chest pain who underwent dual-source multi-slice CT-angiography to exclude coronary artery stenosis. Atherosclerotic plaques were classified as calcified, mixed, or non-calcified. Results: Chemerin levels were highly correlated with high sensitivity C-reactive protein (rZ0.44, P!0.0001), interleukin-6 (rZ0.18, PZ0.002), tumor necrosis factor-a (rZ0.24, P!0.0001), resistin (rZ0.28, P!0.0001), and leptin (rZ0.36, P!0.0001) concentrations. Furthermore, chemerin was associated with components of the metabolic syndrome including body mass index (rZ0.23, PZ0.0002), triglycerides (rZ0.29, P!0.0001), HDL-cholesterol (rZK0.18, PZ0.003), and hypertension (P!0.0001). In bivariate analysis, chemerin levels were weakly correlated with coronary plaque burden (rZ0.16, PZ0.006) and the number of non-calcified plaques (rZ0.14, PZ0.02). These associations, however, were lost after adjusting for established cardiovascular risk factors (odds ratio, OR 1.17, 95% confidence interval (CI) 0.97-1.41, PZ0.11 for coronary plaque burden; OR 1.06, 95% CI 0.96-1.17, PZ0.22 for non-calcified plaques). Conclusions: Chemerin is strongly associated with markers of inflammation and components of the metabolic syndrome. However, chemerin does not predict coronary atherosclerosis.

DSCT is a non-invasive tool that allows to accurately rule out coronary stenoses in patients with an intermediate pretest likelihood for CAD, independent of the HR.

BackgroundAtherosclerosis is the primary cause of coronary artery disease (CAD). There is increasing recognition that lesion composition rather than size determines the acute complications of atherosclerotic disease. Low serum adiponectin levels were reported to be associated with coronary artery disease and future incidence of acute coronary syndrome (ACS). The impact of adiponectin on lesion composition still remains to be determined.Methodology/Principal FindingsWe measured serum adiponectin levels in 303 patients with stable typical or atypical chest pain, who underwent dual-source multi-slice CT-angiography to exclude coronary artery stenosis. Atherosclerotic plaques were classified as calcified, mixed or non-calcified. In bivariate analysis adiponectin levels were inversely correlated with total coronary plaque burden (r = −0.21, p = 0.0004), mixed (r = −0.20, p = 0.0007) and non-calcified plaques (r = −0.18, p = 0.003). No correlation was seen with calcified plaques (r = −0.05, p = 0.39). In a fully adjusted multivariate model adiponectin levels remained predictive of total plaque burden (estimate: −0.036, 95%CI: −0.052 to −0.020, p<0.0001), mixed (estimate: −0.087, 95%CI: −0.132 to −0.042, p = 0.0001) and non-calcified plaques (estimate: −0.076, 95%CI: −0.115 to −0.038, p = 0.0001). Adiponectin levels were not associated with calcified plaques (estimate: −0.021, 95% CI: −0.043 to −0.001, p = 0.06). Since the majority of coronary plaques was calcified, adiponectin levels account for only 3% of the variability in total plaque number. In contrast, adiponectin accounts for approximately 20% of the variability in mixed and non-calcified plaque burden.Conclusions/SignificanceAdiponectin levels predict mixed and non-calcified coronary atherosclerotic plaque burden. Low adiponectin levels may contribute to coronary plaque vulnerability and may thus play a role in the pathophysiology of ACS.

Objectives To evaluate the diagnostic accuracy (DA) of CT-myocardial perfusion imaging (CT-MPI) and a combined approach with CT angiography (CTA) for the detection of haemodynamically relevant coronary stenoses in patients with both suspected and known coronary artery disease. Design Prospective, non-randomised, diagnostic study. Setting Academic hospital-based study. Patients 65 patients (42 men age 70.4±9) with typical or atypical chest pain. Interventions CTA and CT-MPI with adenosine stress using a fast dual-source CT system. At subsequent invasive angiography, FFR measurement was performed in coronary arteries to define haemodynamic relevance of stenosis. Main outcome measures We tried to correlate haemodynamically relevant stenosis (FFR < 0.80) to a reduced myocardial blood flow (MBF) as assessed by CT-MPI and determined the DA of CT-MPI for the detection of haemodynamically relevant stenosis. Results Sensitivity and negative predictive value (NPV) of CTA alone were very high (100% respectively) for ruling out haemodynamically significant stenoses, specificity, Positive predictive value (PPV) and DA were low (43.8, 67.3 and 72%, respectively). CT-MPI showed a significant increase in specificity, PPV and DA for the detection of haemodynamically relevant stenoses (65.6, 74.4 and 81.5%, respectively) with persisting high sensitivity and NPV for ruling out haemodynamically relevant stenoses (97% and 95.5% respectively). The combination of CTA and CT-MPI showed no further increase in detection of haemodynamically significant stenosis compared with CT-MPI alone. Conclusions Our data suggest that CT-MPI permits the detection of haemodynamically relevant coronary artery stenoses with a moderate DA. CT may, therefore, allow the simultaneous assessment of both coronary morphology and function.