Relation Between Epicardial Fat and Subclinical Atherosclerosis in Asymptomatic Individuals

Exploring the relationship between epicardial fat and coronary plaque burden and characteristics: insights from cardiac ct imaging

Epicardial adipose tissue (EAT) may enhance the risk of coronary artery disease (CAD). We investigated the relationship between EAT density (a maker of local inflammation) and coronary plaque characteristics in stable CAD patients. This study included 123 individuals who underwent coronary artery calcium scan and coronary CT angiography to evaluate CAD. Plaque characteristics were analyzed by semi-automated software (QAngio, Leiden, Netherlands). Non-contrast CT scans were used to measure EAT density (HU) and volume (cc) (Philips, Cleveland, OH). Multivariate regression models were used to evaluate the association of EAT density and volume with different plaque types. The mean (SD) age was 59.4±10.1 years, 53% were male, the mean (SD) EAT density was -77.2±4.6 HU and the volume was 118.5±41.2 cc. After adjustment for cardiovascular risk factors, EAT density was associated with fibrous fatty (FF) plaque (p<0.03). A 1 unit increase in HU was associated with a 7% higher FF plaque, and lower EAT density is independently associated to FF plaque. The association between EAT density and fibrous (p=0.08), and total noncalcified (p=0.09) plaque trended toward but did not reach significance. There was no association between EAT volume and any plaque type. These results suggest that inflammatory EAT may promote coronary atherosclerosis. Therefore, non-contrast cardiac CT evaluation of EAT quality can help better assess cardiovascular risk.

Pericardial Fat Is Associated With Less Severe Multiorgan Failure Over Time in Patients With Coronavirus Disease-19: The Maastricht Intensive Care COVID Cohort

PURPOSE

Pericardial fat (PF) and epicardial adipose tissue (EAT) may enhance the proinflammatory response in corona virus-19 (COVID-19) patients. Higher PF and EAT volumes might result in multiorgan failure and explain unfavorable trajectories.The aim of this study was to examine the association between the volume of PF and EAT and multiorgan failure over time.

MATERIALS AND METHODS

All mechanically ventilated COVID-19 patients with an available chest computed tomography were prospectively included (March-June 2020). PF and EAT volumes were quantified using chest computed tomography scans. Patients were categorized into sex-specific PF and EAT tertiles. Variables to calculate Sequential Organ Failure Assessment (SOFA) scores were collected daily to indicate multiorgan failure. Linear mixed-effects regression was used to investigate the association between tertiles for PF and EAT volumes separately and serial SOFA scores over time. All models were adjusted.

RESULTS

Sixty-three patients were divided into PF and EAT tertiles, with median PF volumes of 131.4 mL (IQR [interquartile range]: 115.7, 143.2 mL), 199.8 mL (IQR: 175.9, 221.6 mL), and 318.8 mL (IQR: 281.9, 376.8 mL) and median EAT volumes of 69.6 mL (IQR: 57.0, 79.4 mL), 107.9 mL (IQR: 104.6, 115.1 mL), and 163.8 mL (IQR: 146.5, 203.1 mL). Patients in the highest PF tertile had a statistically significantly lower SOFA score over time (1.3 [-2.5, -0.1], P =0.033) compared with the lowest PF tertile. EAT tertiles were not significantly associated with SOFA scores over time.

CONCLUSION

A higher PF volume is associated with less multiorgan failure in mechanically ventilated COVID-19 patients. EAT volumes were not associated with multiorgan failure.

Epicardial fat density, coronary artery disease and inflammation in people living with HIV

Studies have shown an increased risk of coronary artery disease (CAD) in the human immunodeficiency virus (HIV) population. Epicardial fat (EF) quality may be linked to this increased risk. In our study, we evaluated the associations between EF density, a qualitative characteristic of fat, and inflammatory markers, cardiovascular risk factors, HIV-related parameters, and CAD. Our study was cross-sectional, nested in the Canadian HIV and Aging Cohort Study, a large prospective cohort that includes participants living with HIV (PLHIV) and healthy controls. Participants underwent cardiac computed tomography angiography to measure volume and density of EF, coronary artery calcium score, coronary plaque, and low attenuation plaque volume. Association between EF density, cardiovascular risk factors, HIV parameters, and CAD were evaluated using adjusted regression analysis. A total of 177 PLHIV and 83 healthy controls were included in this study. EF density was similar between the two groups (-77.4 ± 5.6 HU for PLHIV and -77.0 ± 5.6 HU for uninfected controls, P = .162). Multivariable models showed positive association between EF density and coronary calcium score (odds ratio, 1.07, P = .023). Among the soluble biomarkers measured in our study, adjusted analyses showed that IL2Rα, tumor necrosis factor alpha and luteizing hormone were significantly associated with EF density. Our study showed that an increase in EF density was associated with a higher coronary calcium score and with inflammatory markers in a population that includes PLHIV.

The association of epicardial adipose tissue volume and density with coronary calcium in HIV-positive and HIV-negative patients

AIMS

We sought to assess and compare the association of epicardial adipose tissue (EAT) with cardiovascular disease (CVD) in HIV-positive and HIV-negative groups.

METHODS AND RESULTS

Using existing clinical databases, we analyzed 700 patients (195 HIV-positive, 505 HIV-negative). CVD was quantified by the presence of coronary calcification from both dedicated cardiac computed tomography (CT) and non-dedicated CT of the thorax. Epicardial adipose tissue (EAT) was quantified using dedicated software. The HIV-positive group had lower mean age (49.2 versus 57.8, p < 0.005), higher proportion of male sex (75.9 % versus 48.1 %, p < 0.005), and lower rates of coronary calcification (29.2 % versus 58.2 %, p < 0.005). Mean EAT volume was also lower in the HIV-positive group (68mm3 versus 118.3mm3, p < 0.005). Multiple linear regression demonstrated EAT volume was associated with hepatosteatosis (HS) in the HIV-positive group but not the HIV-negative group after adjustment for BMI (p < 0.005 versus p = 0.066). In the multivariate analysis, after adjustment for CVD risk factors, age, sex, statin use, and body mass index (BMI), EAT volume and hepatosteatosis were significantly associated with coronary calcification (odds ratio [OR] 1.14, p < 0.005 and OR 3.17, p < 0.005 respectively). In the HIV-negative group, the only significant association with EAT volume after adjustment was total cholesterol (OR 0.75, p = 0.012).

CONCLUSIONS

We demonstrated a strong and significant independent association of EAT volume and coronary calcium, after adjustment, in HIV-positive group but not in the HIV-negative group. This result hints at differences in the mechanistic drivers of atherosclerosis between HIV-positive and HIV-negative groups.

Cardiac Computed Tomography Evaluation of Association of Left Ventricle Disfunction and Epicardial Adipose Tissue Density in Patients with Low to Intermediate Cardiovascular Risk

Background and objectives: Epicardial adipose tissue density (EAD) has been associated with coronary arteries calcium score, a higher load of coronary artery disease (CAD) and plaque vulnerability. This effect can be related to endocrine and paracrine effect of molecules produced by epicardial adipose tissue (EAT), that may influence myocardial contractility. Using coronary computed tomography angiography (CCT) the evaluation of EAD is possible in basal scans. The aim of the study is to investigate possible associations between EAD and cardiac function. Material and Methods: 93 consecutive patients undergoing CCT without and with contrast medium for known or suspected coronary CAD were evaluated. EAD was measured on basal scans, at the level of the coronary ostia, the lateral free wall of the left ventricle, at the level of the cardiac apex, and at the origin of the posterior interventricular artery. Cardiac function was evaluated in post-contrast CT scans in order to calculate ejection fraction (EF), end-diastolic volume (EDV), end-systolic volume (ESV), and stroke volume (SV). Results: A statistically significant positive correlation between EAD and ejection fraction (r = 0.29, p-value < 0.01) was found. Additionally, a statistically significant negative correlation between EAD and ESV (r = -0.25, p-value < 0.01) was present. Conclusion: EAD could be considered a new risk factor associated with reduced cardiac function. The evaluation of this parameter with cardiac CT in patients with low to intermediate cardiovascular risk is possible.

Diabetes, Heart Failure and Beyond: Elucidating the Cardioprotective Mechanisms of Sodium Glucose Cotransporter 2 (SGLT2) Inhibitors

Approximately 5 million individuals in the US are living with congestive heart failure (CHF), with 650,000 new cases being diagnosed every year. CHF has a multifactorial etiology, ranging from coronary artery disease, hypertension, valvular abnormalities and diabetes mellitus. Currently, guidelines by the American College of Cardiology advocate the use of angiotensin-converting enzyme (ACE) inhibitors, angiotensin II receptor blockers, β-blockers, diuretics, aldosterone antagonists, and inotropes for the medical management of heart failure. The sodium glucose cotransporter 2 (SGLT2) inhibitors are a class of drug that have been widely used in the management of type 2 diabetes mellitus that work by inhibiting the reabsorption of glucose in the proximal convoluted tubule. Since the EMPA-REG OUTCOME trial, several studies have demonstrated the benefits of SGLT2 inhibitors in reducing cardiovascular risk related to heart failure. While the cardiovascular benefits could be explained by their ability to reduce weight, improve glycemic index and lower blood pressure, several recent trials have suggested that SGLT2 inhibitors exhibit pleiotropic effects that underlie their cardioprotective properties. These findings have led to an expansion in preclinical and clinical research aiming to understand the mechanisms by which SGLT2 inhibitors improve heart failure outcomes.

Dual-layer spectral detector CT to study the correlation between pericoronary adipose tissue and coronary artery stenosis

BACKGROUND

To investigate the relationship of pericoronary adipose tissue (PCAT) with coronary artery stenosis using dual-layer spectral detector CT (SDCT).

METHODS

99 patients were retrospectively divided into normal group, non-significant stenosis group and significant stenosis group (n = 33 in each group). Fat attenuation index (FAI) 40kev, spectral curve slope (λHU), effective atomic number (Eff-Z) and epicardial fat volume (EFV) were quantitatively evaluated of the narrowest part of the lesion tissue by SDCT.

RESULTS

There were significant differences in PCAT parameters on SDCT (FAI40keV, λHU, Eff-Z and EFV) among the three groups (P < 0.05). FAI40keV, λHU, and Eff-Z in significant stenosis group were statistically different from those in normal group and non-significant stenosis group (P < 0.05). FAI40keV, λHU, and Eff-Z in non-significant stenosis group were statistically different from significant stenosis group (P < 0.05). EFV in normal group were significantly lower in non-significant stenosis group and significant stenosis group (P < 0.001). Univariate and multivariate logistic regression analyses identified FAI40keV (OR = 1.50, 95%CI 1.01 to 1.09) and λHU (OR = 6.81, 95%CI 1.87 to 24.86) as independent predictors of significant stenosis. FAI40keV and λHU had quite good discrimination, with an AUC of 0.84 and 0.80 respectively.

CONCLUSION

FAI40keV, λHU, and Eff-Z on SDCT in significant stenosis group were significantly different from normal and non-significant stenosis group while EFV in normal group were significantly different from non-significant stenosis group and significant stenosis group. FAI40kev and λHU were risk factors for significant stenosis.

CT-derived epicardial adipose tissue density: Systematic review and meta-analysis

PURPOSE

The aim of our work was to systematically review and meta-analyze epicardial adipose tissue (EAT) density values reported in literature, assessing potential correlations of EAT density with segmentation thresholds and other technical and clinical variables.

METHOD

A systematic search was performed, aiming for papers reporting global EAT density values in Hounsfield Units (HU) in patients undergoing chest CT for any clinical indication. After screening titles, abstract and full text of each retrieved work, studies reporting mean and standard deviation for EAT density were ultimately included. Technical, clinical and EAT data were extracted, and divided into subgroups according to clinical conditions of reported subjects. Pooled density analyses were performed both overall and for subgroups according to clinical conditions. Metaregression analyses were done to appraise the impact of clinical and technical variables on EAT volume.

RESULTS

Out of 152 initially retrieved works, 13 were ultimately included, totaling for 7683 subjects. EAT density showed an overall pooled value of -85.86 HU (95% confidence interval [95% CI] -91.84, -79.89 HU), being -86.40 HU (95% CI -112.69, -60.12 HU) in healthy subjects and -80.71 HU (95% CI -87.43, -73.99 HU) in patients with coronary artery disease. EAT volume and lower and higher segmentation thresholds were found to be significantly correlated with EAT density (p = 0.044, p < 0.001 and p< 0.001 respectively).

CONCLUSIONS

Patients with coronary artery disease appear to present with higher EAT density values, while the correlations observed at metaregression highlight the need for well-established, shared thresholds for EAT segmentation.

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.

Association of Epicardial Fat Volume With the Extent of Coronary Atherosclerosis and Cardiovascular Adverse Events in Asymptomatic Patients With Diabetes

Epicardial adipose tissue has a paracrine effect, enhancing coronary artery atherosclerotic plaque development. This study evaluated epicardial fat volume (EFV), adipokines, coronary atherosclerosis, and adverse cardiovascular events in a cohort of asymptomatic patients with type 2 diabetes mellitus (T2DM). Epicardial fat volume was calculated using data from computed tomography coronary angiograms. Adipokines and inflammatory cytokines were also assayed and correlated with EFV. Epicardial fat volume was also assessed as a predictor of coronary artery calcium (CAC) score, number of coronary artery plaques, and significant plaque (>50% luminal stenosis). Data from the EFV analysis were available for 221 (85.7%) participants. Median EFV was 97.4 cm³, mean body mass index was 28.1 kg/m², and mean duration of T2DM was 13 years. Statistically significant, but weak, correlations were observed between several adipokines, inflammatory cytokines, and EFV. Epicardial fat volume was a significant univariate (P = .01), but not multivariate, predictor of the number of coronary plaques, but not of CAC score or significant plaque. After a mean follow-up of 22.8 months, 12 adverse cardiovascular events were reported, exclusively in participants with EFV >97.4 cm³. Epicardial fat volume has limited utility as a marker of coronary artery plaque in patients with T2DM and is weakly correlated with adipokine expression.

Understanding Diabetic Neuropathy-From Subclinical Nerve Lesions to Severe Nerve Fiber Deficits: A Cross-Sectional Study in Patients With Type 2 Diabetes and Healthy Control Subjects

Studies on magnetic resonance neurography (MRN) in diabetic polyneuropathy (DPN) have found proximal sciatic nerve lesions. The aim of this study was to evaluate the functional relevance of sciatic nerve lesions in DPN, with the expectation of correlations with the impairment of large-fiber function. Sixty-one patients with type 2 diabetes (48 with and 13 without DPN) and 12 control subjects were enrolled and underwent MRN, quantitative sensory testing, and electrophysiological examinations. There were differences in mechanical detection (Aβ fibers) and mechanical pain (Aδ fibers) but not in thermal pain and thermal detection clusters (C fibers) among the groups. Lesion load correlated with lower Aα-, Aβ-, and Aδ-fiber but not with C-fiber function in all participants. Patients with lower function showed a higher load of nerve lesions than patients with elevated function or no measurable deficit despite apparent DPN. Longer diabetes duration was associated with higher lesion load in patients with DPN, suggesting that nerve lesions in DPN may accumulate over time and become clinically relevant once a critical amount of nerve fascicles is affected. Moreover, MRN is an objective method for determining lower function mainly in medium and large fibers in DPN.

Fully Automated CT Quantification of Epicardial Adipose Tissue by Deep Learning: A Multicenter Study

Purpose

To evaluate the performance of deep learning for robust and fully automated quantification of epicardial adipose tissue (EAT) from multicenter cardiac CT data.

Materials and Methods

In this multicenter study, a convolutional neural network approach was trained to quantify EAT on non-contrast material-enhanced calcium-scoring CT scans from multiple cohorts, scanners, and protocols (n = 850). Deep learning performance was compared with the performance of three expert readers and with interobserver variability in a subset of 141 scans. The deep learning algorithm was incorporated into research software. Automated EAT progression was compared with expert measurements for 70 patients with baseline and follow-up scans.

Results

Automated quantification was performed in a mean (± standard deviation) time of 1.57 seconds ± 0.49, compared with 15 minutes for experts. Deep learning provided high agreement with expert manual quantification for all scans (R = 0.974; P < .001), with no significant bias (0.53 cm³; P = .13). Manual EAT volumes measured by two experienced readers were highly correlated (R = 0.984; P < .001) but with a bias of 4.35 cm³ (P < .001). Deep learning quantifications were highly correlated with the measurements of both experts (R = 0.973 and R = 0.979; P < .001), with significant bias for reader 1 (5.11 cm³; P < .001) but not for reader 2 (0.88 cm³; P = .26). EAT progression by deep learning correlated strongly with manual EAT progression (R = 0.905; P < .001) in 70 patients, with no significant bias (0.64 cm³; P = .43), and was related to an increased noncalcified plaque burden quantified from coronary CT angiography (5.7% vs 1.8%; P = .026).

Conclusion

Deep learning allows rapid, robust, and fully automated quantification of EAT from calcium scoring CT. It performs as well as an expert reader and can be implemented for routine cardiovascular risk assessment.© RSNA, 2019See also the commentary by Schoepf and Abadia in this issue.

Perivascular Adipose Tissue and Coronary Atherosclerosis: from Biology to Imaging Phenotyping

PURPOSE OF REVIEW

Perivascular adipose tissue (PVAT) has a complex, bidirectional relationship with the vascular wall. In disease states, PVAT secretes pro-inflammatory adipocytokines which may contribute to atherosclerosis. Recent evidence demonstrates that pericoronary adipose tissue (PCAT) may also function as a sensor of coronary inflammation. This review details PVAT biology and its clinical translation to current imaging phenotyping.

RECENT FINDINGS

PCAT attenuation derived from routine coronary computed tomography (CT) angiography is a novel noninvasive imaging biomarker of coronary inflammation. Pro-inflammatory cytokines released from the arterial wall diffuse directly into the surrounding PCAT and inhibit adipocyte lipid accumulation in a paracrine manner. This can be detected as an increased PCAT CT attenuation, a metric which associates with high-risk plaque features and independently predicts cardiac mortality. There is also evidence that PCAT attenuation relates to coronary plaque progression and is modified by systemic anti-inflammatory therapies. Due to its proximity to the coronary arteries, PCAT has emerged as an important fat depot in cardiovascular research. PCAT CT attenuation has the potential to improve cardiovascular risk stratification, and future clinical studies should examine its role in guiding targeted medical therapy.

Effects of Hormone Therapy on Heart Fat and Coronary Artery Calcification Progression: Secondary Analysis From the KEEPS Trial

Background Heart fats (epicardial and paracardial adipose tissue [PAT]) are greater after menopause. Endogenous estrogen may regulate these fat depots. We evaluated the differential effects of hormone therapy formulations on heart fat accumulations and their associations with coronary artery calcification (CAC) progression in recently menopausal women from KEEPS (Kronos Early Estrogen Prevention Study). Methods and Results KEEPS was a multicenter, randomized, placebo-controlled trial of the effects of 0.45 mg/d oral conjugated equine estrogens and 50 µg/d transdermal 17β-estradiol, compared with placebo, on 48-month progression of subclinical atherosclerosis among 727 early menopausal women. CAC progression was defined if baseline CAC score was 0 and 48-month CAC score was >0 or if baseline CAC score was >0 and <100 and annualized change in CAC score was ≥10. Of 727 KEEPS participants, 474 (mean age: 52.7 [SD: 2.6]; 78.1% white) had computed tomography-based heart fat and CAC measures at both baseline and 48 months. Compared with women on placebo, women on oral conjugated equine estrogens were less likely to have any increase in epicardial adipose tissue (odds ratio for oral conjugated equine estrogens versus placebo: 0.62 [95% CI, 0.40-0.97]; P=0.03). PAT did not change in any group. Changes in epicardial adipose tissue and PAT did not differ by treatment group. CAC increased in 14% of participants. The assigned treatment modified the association between PAT changes and CAC progression (P=0.02) such that PAT increases were associated with CAC increases only in the transdermal 17β-estradiol group. Conclusions In recently menopausal women, oral conjugated equine estrogens may slow epicardial adipose tissue accumulation, whereas transdermal 17β-estradiol may increase progression of CAC associated with PAT accumulation. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT00154180.

State-of-the-art review article. Atherosclerosis affecting fat: What can we learn by imaging perivascular adipose tissue?

Perivascular adipose tissue (PVAT) surrounding the human coronary arteries, secretes a wide range of adipocytokines affecting the biology of the adjacent vascular wall in a paracrine way. However, we have recently found that PVAT also behaves as a sensor of signals coming from the vascular wall, to which it reacts by changing its morphology and secretory profile. Indeed, vascular inflammation, a key feature of vascular disease pathogenesis, leads to the release of inflammatory signals that disseminate into local fat, inducing local lipolysis and inhibiting adipogenesis. This ability of PVAT to sense inflammatory signals from the vascular wall, can be used as a "thermometer" of the vascular wall, allowing for non-invasive detection of coronary inflammation. Vascular inflammation induces a shift of PVAT's composition from lipid to aqueous phase, resulting into increased computed tomography (CT) attenuation around the inflamed artery, forming a gradient with increasing attenuation closer to the inflamed coronary artery wall. These spatial changes in PVAT's attenuation are easily detected around culprit lesions during acute coronary syndromes. A new biomarker designed to captured these spatial changes in PVAT's attenuation around the human coronary arteries, the Fat Attenuation Index (FAI), has additional predictive value in stable patients for cardiac mortality and non-fatal heart attacks, above the prediction provided by the current state of the art that includes risk factors, calcium score and presence of high risk plaque features. The use of perivascular FAI in clinical practice may change the way we interpret cardiovascular CT angiography, as it is applicable to any coronary CT angiogram, and it offers dynamic information about the inflammatory burden of the coronary arteries, providing potential guidance for preventive measures and invasive treatments.

Fat volume measurements as a predictor of image noise in coronary computed tomography angiography

Introduction

Image noise can negatively affect the overall quality of coronary computed tomography angiography (CCTA).

Objectives

The purpose of this study was to evaluate the relationship between image noise and fat volumes in the chest wall. We also aimed to compare these with other patient-specific predictors of image noise, such as body weight (BW) and body mass index (BMI).

Methods

We undertook a cross-sectional, single-center study. A tube voltage of 100 kV was used for patients with BW <85 kg and 120 kV for BW ≥85 kg. The image noise in the aortic root, single-slice fat volume (SFV) at the level of the left main coronary artery and the total fat volume of the chest (TFV) were analyzed.

Results

A total of 132 consecutive patients were enrolled (mean age ± standard deviation, 51 ± 11 years; 64% male). The mean image noise was 30.5 ± 11 Hounsfield units (HU). We found that patients with image noise >30 HU had significantly higher SFV (75 ± 33 vs. 51 ± 24, p < 0.0001) and TFV (2206 ± 927 vs. 1815 ± 737, p < 0.01) compared with patients having noise ≤30 HU, whereas BW and BMI showed no significant difference (78 ± 13 vs. 81 ± 14, p < 0.34) and (28.7 ± 4.7 vs. 26.8 ± 3.8, p < 0.19), respectively. Linear regression analysis showed that image noise has better correlation with SFV (R = 0.399; p < 0.0001); and TFV (R = 0, p < 0.009) than BMI (R = 0.154, p < 0.039) and BW (R = -0.102, p = 0.12).

Conclusions

Fat volume measurements of the chest wall can predict CCTA image noise better than other patient-specific predictors, such as BW and BMI.

Effects of SGLT2 inhibitors on systemic and tissue low-grade inflammation: The potential contribution to diabetes complications and cardiovascular disease

Chronic low-grade inflammation is a recognized key feature associated with type 2 diabetes mellitus (T2DM) and its complications. In prospective randomized trials, sodium-glucose cotransporter type 2 (SGLT2) inhibitors have demonstrated benefits related to several cardiovascular and renal risk factors, including HbA_1c, blood pressure, body weight, renal hyperfiltration, and improvement of cardiorenal outcomes. SGLT2 inhibitors may improve adipose tissue function and induce decreases in serum leptin, TNF-α and IL-6 while increasing adiponectin. While data on high-sensitivity C-reactive protein and other inflammatory markers are relatively scarce in humans, in animals, a number of reports have shown reductions in cytokine and chemokine concentrations in parallel with protective effects against progression of atherosclerotic lesions. Experimental findings also suggest that part of the renoprotective effects of SGLT2 inhibition may be related to anti-inflammatory actions at the kidney level. Underlying mechanisms to explain this anti-inflammatory effect are multiple, but may involve weight loss, and reduction in adipose tissue inflammation, slight increase in ketone bodies and diminution of uric acid levels or attenuation of oxidative stress. However, further studies in diabetes patients with specific assessment of inflammatory markers are still necessary to determine the specific contribution of the anti-inflammatory action of SGLT2 inhibitors to the reduction of cardiovascular and renal complications and mortality observed with this class of antidiabetic drugs.

Deep Learning for Quantification of Epicardial and Thoracic Adipose Tissue From Non-Contrast CT

Epicardial adipose tissue (EAT) is a visceral fat deposit related to coronary artery disease. Fully automated quantification of EAT volume in clinical routine could be a timesaving and reliable tool for cardiovascular risk assessment. We propose a new fully automated deep learning framework for EAT and thoracic adipose tissue (TAT) quantification from non-contrast coronary artery calcium computed tomography (CT) scans. The first multi-task convolutional neural network (ConvNet) is used to determine heart limits and perform segmentation of heart and adipose tissues. The second ConvNet, combined with a statistical shape model, allows for pericardium detection. EAT and TAT segmentations are then obtained from outputs of both ConvNets. We evaluate the performance of the method on CT data sets from 250 asymptomatic individuals. Strong agreement between automatic and expert manual quantification is obtained for both EAT and TAT with median Dice score coefficients of 0.823 (inter-quartile range (IQR): 0.779-0.860) and 0.905 (IQR: 0.862-0.928), respectively; with excellent correlations of 0.924 and 0.945 for EAT and TAT volumes. Computations are performed in <6 s on a standard personal computer for one CT scan. Therefore, the proposed method represents a tool for rapid fully automated quantification of adipose tissue and may improve cardiovascular risk stratification in patients referred for routine CT calcium scans.

Comparison of epicardial adipose tissue radiodensity threshold between contrast and non-contrast enhanced computed tomography scans: A cohort study of derivation and validation

BACKGROUND AND AIMS

Epicardial adipose tissue (EAT) volume derived from contrast enhanced (CE) computed tomography (CT) scans is not well validated. We aim to establish a reliable threshold to accurately quantify EAT volume from CE datasets.

METHODS

We analyzed EAT volume on paired non-contrast (NC) and CE datasets from 25 patients to derive appropriate Hounsfield (HU) cutpoints to equalize two EAT volume estimates. The gold standard threshold (-190HU, -30HU) was used to assess EAT volume on NC datasets. For CE datasets, EAT volumes were estimated using three previously reported thresholds: (-190HU, -30HU), (-190HU, -15HU), (-175HU, -15HU) and were analyzed by a semi-automated 3D Fat analysis software. Subsequently, we applied a threshold correction to (-190HU, -30HU) based on mean differences in radiodensity between NC and CE images (ΔEATrd = CE radiodensity - NC radiodensity). We then validated our findings on EAT threshold in 21 additional patients with paired CT datasets.

RESULTS

EAT volume from CE datasets using previously published thresholds consistently underestimated EAT volume from NC dataset standard by a magnitude of 8.2%-19.1%. Using our corrected threshold (-190HU, -3HU) in CE datasets yielded statistically identical EAT volume to NC EAT volume in the validation cohort (186.1 ± 80.3 vs. 185.5 ± 80.1 cm³, Δ = 0.6 cm³, 0.3%, p = 0.374).

CONCLUSIONS

Estimating EAT volume from contrast enhanced CT scans using a corrected threshold of -190HU, -3HU provided excellent agreement with EAT volume from non-contrast CT scans using a standard threshold of -190HU, -30HU.

Perivascular adipose tissue and coronary atherosclerosis

Adipose tissue (AT) is no longer viewed as a passive, energy-storing depot, and a growing body of evidence supports the concept that both quantitative and qualitative aspects of AT are critical in determining an individual's cardiometabolic risk profile. Among all AT sites, perivascular AT (PVAT) has emerged as a depot with a distinctive biological significance in cardiovascular disease given its close anatomical proximity to the vasculature. Recent studies have suggested the presence of complex, bidirectional paracrine and vasocrine signalling pathways between the vascular wall and its PVAT, with far-reaching implications in cardiovascular diagnostics and therapeutics. In this review, we first discuss the biological role of PVAT in both cardiovascular health and disease, highlighting its dual pro-atherogenic and anti-atherogenic roles, as well as potential therapeutic targets in cardiovascular disease. We then review current evidence and promising new modalities on the non-invasive imaging of epicardial AT and PVAT. Specifically, we present how our expanding knowledge on the bidirectional interplay between the vascular wall and its PVAT can be translated into novel clinical diagnostics tools to assess coronary inflammation. To this end, we present the example of a new CT-based method that tracks spatial changes in PVAT phenotype to extract information about the inflammatory status of the adjacent vasculature, highlighting the numerous diagnostic and therapeutic opportunities that arise from our increased understanding of PVAT biology.

Epicardial adipose tissue density and volume are related to subclinical atherosclerosis, inflammation and major adverse cardiac events in asymptomatic subjects

BACKGROUND

We investigated whether epicardial adipose tissue (EAT) volume and density are related to early atherosclerosis, plaque inflammation and major adverse cardiac events (MACE, cardiac death and myocardial infarction) in asymptomatic subjects.

METHODS

EAT volume and density were quantified from non-contrast cardiac CT in 456 asymptomatic individuals (age 60.3 ± 8.3; 68% with CCS>0) from the prospective EISNER trial. EAT volume and density were examined in relation to coronary calcium score (CCS), inflammatory biomarkers and MACE.

RESULTS

EAT volume was higher and EAT density lower in subjects with coronary calcium compared to subjects without [89 vs 74 cm³, p < 0.001] [-76.9 vs -75.7 HU,p = 0.024]. EAT volume was lowest in individuals with no coronary calcium and was significant higher in subjects with early atherosclerosis (CCS 1-99) [74 vs 87 cm³,p = 0.016] and in subjects with more advanced atherosclerosis (CCS≥100) [89 cm³,p = 0.002]). EAT volume was independently related to serum levels of PAI-1, and MCP-1 and inversely related to adiponectin and HDL-cholesterol (p < 0.05). EAT density was inversely related to PAI-1 and LDL-cholesterol and positively associated to adiponectin, sICAM-1 and HDL-cholesterol (p < 0.05). EAT density was more significantly associated with MACE [(HR 0.8, 95%CI:0.7-0.98), p = 0.029] than EAT volume or CCS.

CONCLUSION

EAT volume was higher and density lower in subjects with coronary calcium compared to subjects with CCS = 0, with similar EAT volume in CCS<100 and CCS≥100. Lower EAT density and increased EAT volume were associated with coronary calcification, serum levels of plaque inflammatory markers and MACE, suggesting that dysfunctional EAT may be linked to early plaque formation and inflammation.