Acute COVID-19 infection frequently affects the cardiovascular system and causes acute myocardial injury. Epicardial Adipose Tissue (EAT), a visceral adipose tissue surrounding the myocardium and coronary arteries, has unique paracrine and endocrine effects, modulating the heart's inflammatory environment. Systemic inflammation stimulates TNF-α and Interleukin-6 secretion from EAT, contributing to cytokine storms and intensifying systemic responses. We aimed to determine whether EAT amount differs in patients with and without acute COVID-19 infection and myocardial injury.

This study analyzed the CoV-COR registry cohort, conducted at the University Hospital Essen, including patients with symptoms suggestive of COVID-19 infection. The infection was confirmed by PCR. EAT thickness was measured by two-dimensional TTE.

A total of 296 patients (mean age 63.6 ± 17.26 years, 55.4 % male) were included. Patients with confirmed COVID-19 infection were younger, more frequently treated with antihypertensive medication, and had higher BMI and systolic blood pressures. Univariate logistic regression showed no association between EAT and myocardial injury 0.97 (0.74; 1.28, p = 0.82). A trend towards an association was observed between increasing EAT thickness and COVID-19 infection 1.25 (0.99; 1.59, p = 0.060). Adjusting for age and gender strengthened the association, with a 48 % (1.14; 1.93, p = 0.004) increased odds of COVID-19 infection per increase in EAT thickness. Multivariable regression yielded consistent effect sizes 1.47 (1.01; 2.16, p = 0.047).

EAT thickness is associated with the presence of an acute COVID-19 infection but not with a myocardial injury. Further research is needed to assess if systemic viral infection induces dynamic changes in EAT.

Cardiac allograft vasculopathy (CAV) remains a significant challenge after heart transplantation, necessitating effective surveillance methods. This review centers around the role of coronary computed tomography angiography (CCTA) in CAV surveillance, given its unique capabilities to visualize and quantify CAV in comparison with other imaging modalities, including invasive coronary angiography and intravascular ultrasound. CCTA has shown good diagnostic performance for detecting and monitoring CAV, exemplified by a higher sensitivity and negative predictive value compared with invasive coronary angiography. Additionally, CCTA can provide valuable functional insights with fractional flow reserve integration. An additional, considerable benefit of CCTA is that it allows for the opportunity to assess other imaging markers of cardiometabolic and general health, including coronary artery calcium score, epicardial fat volume, liver fat, vertebral bone density, and lung density, which allows for a comprehensive assessment of the overall health of the patient.

BackgroundThe accumulation of adipose tissue, such as increased epicardial adipose tissue volume (EATV) and visceral fat area (VFA), is associated with the development of cardiovascular (CV) disease. However, little information is available regarding the relationship between EATV and CV death in patients who undergo open surgical repair (OSR) for abdominal aortic aneurysms (AAAs). The aim of this study was to evaluate the association between adipose tissue and CV death and to identify factors related to CV death after AAA repair.MethodsBetween June 2005 and December 2019, a total of 739 patients underwent OSR for AAA with or without iliac artery aneurysm and isolated iliac artery aneurysm at our institution. AAA with a diameter of 50 mm or more and iliac artery aneurysm with 35 mm or greater were considered to be a surgical indication. Patients with ruptured AAAs and infected AAAs were excluded. Four hundred ninety-two patients with preoperative optimal computed tomography (CT) scans were included in this study. The EATV, VFA, and subcutaneous fat area (SFA) were retrospectively quantified from preoperative noncontrast CT images. The EATV index was defined as the EATV divided by the body surface area, and the VFA index and SFA index were defined as each number divided by height squared. The correlations among the EATV, VFA, and SFA indices were analyzed, and the cut-off values of the parameters for predicting CV death after OSR for AAA patients were determined via receiver operating characteristic curves. Regression analysis was used to assess predictors of CV death during the follow-up period. Cox hazard regression analysis was performed.ResultsThe median age was 71 years, and 12% of the patients were female. The median body mass index was 23.1 kg/m2. The prevalence of comorbidities was 31% for coronary artery disease, 9% for stroke, 15% for diabetes, and 41% for chronic kidney disease. The median follow-up period for overall patients was 62.5 months (interquartile range: 33.7-99.6). The EATV index was positively correlated with the VFA (R = 0.615, p < .001) and SFA (R = 0.421, p < .001) indices. The cut-off value of the EATV index was 73.8 cm3/m2 (area under the curve (AUC); 0.566). Multivariate analysis revealed that age ≥75 years and an EATV index ≥73.8 cm3/m2 were significantly associated with CV death after AAA repair.ConclusionsThis study demonstrated that the EATV index was associated with CV death in patients who underwent OSR for AAA, suggesting its potential utility as a novel risk stratification tool for personalized postoperative management.

Diabetic cardiomyopathy (DCM) is a complex metabolic disorder resulting from chronic hyperglycemia and lipid toxicity, which leads to cardiac dysfunction, fibrosis, inflammation, and mitochondrial impairment. Traditional two-dimensional (2D) cell cultures and animal models have limitations in replicating human cardiac physiology and pathophysiology. In this study, we successfully developed a three-dimensional (3D) model of DCM using cardiac organoids generated from human induced pluripotent stem cells (hiPSCs). These organoids were treated with varying concentrations of glucose and sodium palmitate to mimic the high-glucose and high-lipid environment associated with diabetes. At lower concentrations, glucose and sodium palmitate enhanced cell viability, while higher concentrations induced significant cardiotoxic effects, including apoptosis, oxidative stress, and mitochondrial dysfunction. The cardiac organoids also exhibited increased expression of cardiac injury markers, fibrosis-related genes, and inflammatory cytokines under high-glucose and high-lipid conditions. Treatment with metformin, a widely used antidiabetic drug, mitigated these adverse effects, indicating the model's potential for drug testing and evaluation. Our findings demonstrate that this human-derived 3D cardiac organoid model provides a more physiologically relevant platform for studying DCM and can effectively complement traditional models. This model holds promise for advancing the understanding of diabetic heart disease and for assessing the efficacy of potential therapeutic interventions.

Excessive accumulation of epicardial adipose tissue (EAT) is known to be a risk factor for coronary artery disease and heart failure. In particular, it is thought that inflammation of pericoronary adipose tissue (PCAT) affects the pathology of various coronary artery diseases (CAD). EAT and PCAT are thought to be new therapeutic targets for preventing cardiovascular disease. Although there are no established drugs that specifically reduce inflammation of EAT or PCAT, the basic approach is to improve lifestyle-related diseases through exercise and diet, and to use metabolic improvement drugs and anti-inflammatory drugs as soft support. Potential candidates include statins, SGLT2 inhibitors, and GLP- 1 receptor agonists. In addition to conventional treatments that target substances within blood vessels, treatments that target EAT and PCAT by directly enveloping the coronary arteries and myocardium from outside the body are expected to further suppress cardiovascular events.

We hypothesize that epicardial adipose tissue (EAT) structure differs between patients with coronary disease and healthy individuals and that EAT may undergo changes during an acute coronary syndrome (ACS). This study aimed to investigate EAT thickness (EATt) and structure using ultrasound radiomics in patients with ACS, patients with chronic coronary syndrome (CCS), and controls and compare the findings between the three groups. This prospective monocentric comparative cohort study included three patient groups: ACS, CCS, and asymptomatic controls. EATt was assessed using transthoracic echocardiography. Geometrical features (as mean gray value and raw integrated density) and texture features (as angular second moment, contrast and correlation) were computed from grayscale Tagged Image File Format biplane images using ImageJ software. EATt did not significantly differ between the ACS group (8.14 ± 3.17 mm) and the control group (6.92 ± 2.50 mm), whereas CCS patients (9.96 ± 3.19 mm) had significantly thicker EAT compared to both the ACS group (p = 0.025) and the control group (p < 0.001). Radiomics analysis revealed differences in geometrical parameters with discriminatory capabilities between both ACS group and controls and CCS group and controls. A multivariate analysis comparing ACS and CCS patients revealed that differences in EAT characteristics were significant only in patients with a body mass index below 26.25 kg/m². In this subgroup, patients older than 68 exhibited a higher modal gray value (p = 0.016), whereas those younger than 68 had a lower minimum gray value (p = 0.05). Radiomic analysis highlights its potential in developing imaging biomarkers for early diagnosis and coronary artery disease progression monitoring.

Epicardial adipose tissue (EAT) plays a significant role in several cardiovascular diseases. As a correctable risk factor and potential therapeutic target, reducing EAT has multiple cardiovascular benefits, especially in those with abnormal glucolipid metabolism. The objective of this research was to compare the effects of sodium-glucose cotransporter 2 (SGLT2) inhibitors, glucagon-like peptide-1 (GLP-1) agonists, and exercise on the thickness of EAT and indicators of glucolipid metabolism in people with type 2 diabetes mellitus (T2DM), obesity, and T2DM with obesity.

We searched four electronic databases: PubMed, EMBASE, the Cochrane Library, and Web of Science for articles before 31 January 2024, regardless of language. We included randomized controlled trials and a small number of case-control studies in this network meta-analysis. Differences in mean changes in EAT, body mass index, and glucolipid metabolism-related metrics were assessed.

A comprehensive analysis was conducted on 16 trials (15 randomized controlled trials and one case-control study), comprising a total of 867 people. SGLT2 inhibitors were significantly better at reducing EAT than placebo (standard mean different [SMD] = -0.85 cm [95% confidence interval (CI) -1.39, -0.31]); a similar result was observed for exercise compared with placebo (SMD = -0.78 cm [95% CI -1.37, -0.18]). SGLT2 inhibitors were also significantly better at reducing EAT than GLP-1 agonists and conventional hypoglycaemic therapy (e.g., metformin or insulin; SMD = -0.74 cm [95% CI -1.45, -0.02] and SMD = -1.69 cm [95% CI -2.38, -0.99], respectively). SGLT2 inhibitors were significantly better than placebo at reducing body mass index (MD = -0.90 kg/m2 [95% CI -1.14, -0.66]) and glycosylated haemoglobin (MD = -0.52% [95%CI -0.86, -0.18]). A similar result was observed when comparing GLP-1 agonists and placebo (MD = -0.48% [95% CI -0.93, -0.03]). Changes in total cholesterol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol were not statistically significant between interventions.

SGLT2 inhibitors have a distinct advantage over both placebo and other therapies at lowering EAT thickness, a result supported by direct comparisons and surface under the cumulative ranking curve analysis. Therefore, SGLT2 inhibitors should be prioritized as a treatment to reduce EAT in individuals with aberrant glucolipid levels, such as patients with T2DM and/or obesity.

Dyslipidemia is a metabolic disorder characterized by quantitative and/or qualitative abnormalities in serum lipid levels. Elevated serum cholesterol levels can modify the turnover and recruitment of ionic channels in myocytes and cellular homeostasis, including those of inflammatory cells. Experimental and clinical data indicate that inflammation is implicated in the pathophysiology of atrial remodeling, which is the substrate of atrial fibrillation (AF). Data about the association between increased lipid serum levels and AF are few and contrasting. Lipoprotein (a), adiposity, and inflammation seem to be the main drivers of AF; in contrast, low-density lipoproteins, high-density lipoproteins and triglycerides are not directly involved in AF onset. The present review aimed to describe the pathophysiological link between dyslipidemia and AF, the efficacy of lipid-lowering therapies in atherosclerotic cardiovascular disease (ASCVD) patients with and without AF, and the impact of lipid-lowering therapies on AF incidence.

Although the epidemic of atherosclerosis has slowed down in industrialized nations, it has increased in speed and severity in developing countries. The worldwide expanding incidence and prevalence of obesity, insulin resistance, and diabetes mellitus may be among the most important drivers of this trend, and the role of visceral adipose tissue as a promoter of atherosclerosis has come under intense scrutiny. Epicardial adipose tissue (EAT) is embryologically similar to the visceral fat in the intraperitoneal space. Both adipose compartments are capable of secreting numerous pro-atherosclerotic cytokines and have been shown to promote inflammation in patients with dysmetabolic syndromes and in patients with established coronary artery disease. The adverse cardiovascular effects of EAT extend to influencing the development of atrial fibrillation and heart failure, mostly with preserved ejection fraction, through a combination of inflammatory, pro-fibrotic, and pro-arrhythmogenic pathways. In this work we provide an overview of the current understanding of the role of EAT in the development of several cardiovascular conditions as well as some of the therapeutic advances in the field.

Coronary computed tomography angiography (CTA) can be used to quantitatively and qualitatively evaluate the characteristics of perivascular adipose tissue (PVAT), including PVAT volume and perivascular fat attenuation index (FAI). Moreover, PVAT volume and perivascular FAI on CTA are reportedly high in patients with vasospastic angina (VSA); however, previous investigations have focused on the patient rather than vessel-level analyses. Therefore, this study aimed to assess the relationship between coronary vasospasm and PVAT or FAI by using coronary CTA at the vessel level.

This retrospective study included 51 patients who underwent intracoronary acetylcholine (ACh) provocation testing for the VSA diagnosis and coronary CTA within a 6-month interval. A total of 125 coronary vessels were evaluated. PVAT and FAI on CTA were quantitatively evaluated. The primary interest of the present study was to determine the relationship between PVAT volume and FAI- and ACh-induced coronary vasospasms at the vessel level.

Of the 51 patients, 24 (47.1%) had a positive ACh provocation test (VSA), with 40 of 125 (32.0%) vessels having ACh-induced vasospasm. Obstructive epicardial coronary artery disease was observed in 12 vessels (9.6%). No significant differences in PVAT volume or FAI were identified between vessels with and without ACh-induced vasospasms. Similarly, PVAT volume and FAI did not differ significantly in the individual major coronary arteries between patients with and without positive ACh provocation test results. In contrast, FAI was significantly higher in vessels with obstructive coronary artery disease than in those without.

In patients undergoing intracoronary ACh provocation tests and coronary CTA, no significant association was observed between ACh-induced coronary vasospasm and PVAT volume or FAI at the vessel level. However, FAI significantly increased in vessels with epicardial coronary disease.

The quantification of coronary artery calcifications (CAC) is a mainstay in radiological assessment of coronary atherosclerosis and cardiovascular risk, but reflect advanced, possibly late-stage changes in the arteries. Increased volume and changes in attenuation of the epicardial adipose tissue (EAT) on computed tomography (CT) have been linked to adverse cardiovascular events, and these changes in the EAT might reflect earlier stages of the processes leading to clinically manifest atherosclerosis. The relationship between EAT and CAC is subject to a knowledge gap, especially in individuals with no previously known coronary artery disease.

Fully automated EAT analysis with an artificial intelligence-based model was performed in a population sample enriched for pre-diabetics, comprising a total of 1,945 individuals aged 50-64 years, where non-contrast CT images, anthropometric and laboratory data was available on established cardiovascular risk factors. Uni- and multivariable linear regression, gradient-boosting and correlation analyses were performed to determine the explanatory value of EAT volume and attenuation data with regards to CAC data.

Neither EAT volume nor EAT attenuation was associated with the presence or severity of CAC, when adjusting for established cardiovascular risk factors, and had only weak explanatory value in gradient-boosting and correlation analyses. Age was the strongest predictor of CAC in both sexes.

No independent association was found between CAC and total EAT volume or attenuation. Importantly, these findings do not rule out early stage or local effects on coronary atherosclerosis from the EAT immediately surrounding the coronary arteries.

Artificial intelligence (AI) has transformed medical imaging by detecting insights and patterns often imperceptible to the human eye, enhancing diagnostic accuracy and efficiency. In cardiovascular imaging, numerous AI models have been developed for cardiac computed tomography (CCT), a primary tool for assessing coronary artery disease (CAD). CCT provides comprehensive, non-invasive assessment, including plaque burden, stenosis severity, and functional assessments such as CT-derived fractional flow reserve (FFRct). Its prognostic value in predicting major adverse cardiovascular events (MACE) has increased the demand for CCT, consequently adding to radiologists' workloads. This review aims to examine AI's role in CCT for ischemic heart disease, highlighting its potential to streamline workflows and improve the efficiency of cardiac care through machine learning and deep learning applications.

Despite TSH suppressive therapy improve the prognosis for the patient with differentiated thyroid cancer (DTC), there is an increasing concern regarding the potentially harmful effects of lifelong TSH suppression. Therefore, we aimed to examine the changes in body composition under TSH suppression in postmenopausal women with DTC.

The body composition was assessed by the volumes as following; fat tissues of the epicardium and abdominal visceral and subcutaneous areas; bilateral psoas muscle or thigh muscle. Each volumetric measurements were performed using computed tomography (CT) scans using baseline and follow-up fluorine-18 fluorodeoxyglucose positron emission tomography/CT (18F-FDG PET/CT)s for 2-year follow up period in Pusan National University Hospital, South Korea.

The 43 patients' median age was 50.0 years, and median body mass index (BMI) was 23.53 (interquartile range[IQR]: 22.19- 24.92) at the initial 18F-FDG PET/CT. The median follow-up period was 19.24 months (IQR: 17.24-21.79). No significant change in weight or BMI were observed during follow-up. Volumes of fat and muscles was not changed significantly except epicardial fat volume. The epicardial fat volume significantly increased during the follow-up period. The epicardial fat volumes were correlated with visceral fat volume, respectively, however, the changing ratio was only correlated with TSH suppression on multiple regression analysis.

Both skeletal muscle and abdominal fat volumes did not change, whereas epicardial fat volume increased over less than 2 years of observation under TSH suppressive therapy. Further research is needed for the harmonization of benefits or losses with the optimal TSH concentration in postmenopausal women.

Lifestyle-related diseases, such as atherosclerosis and diabetes, are now considered to be a series of diseases caused by chronic inflammation. Adipose tissue is considered to be an endocrine organ that not only plays a role in lipid storage, heat production, and buffering, but also produces physiologically active substances and is involved in chronic inflammation. Perivascular adipose tissue (PVAT) surrounding blood vessels similarly produces inflammatory and anti-inflammatory physiologically active substances that act on blood vessels either directly or via the bloodstream. Epicardial adipose tissue (EAT), which is in direct contact with the coronary arteries inside the pericardium, is thought to have a direct effect on the coronary arteries as well. The presence and inflammatory status of these adipose tissues can be evaluated by imaging tests, and has been shown to be associated with the presence of current cardiovascular disease (CVD) and to be a prognostic factor. It is also expected to become a new diagnostic and therapeutic target for CVD.

Epicardial adipose tissue (EAT) is an important imaging indicator of cardiovascular risk. EAT volume is usually measured using electrocardiogram (ECG) gating. However, there are concerns regarding the influence of motion artifacts when measuring EAT volume on non-ECG-gated plain chest computed tomography (CT) images. Few studies have evaluated the EAT volume using non-ECG gating. This study aimed to validate the accuracy of EAT quantification using non-ECG-gated chest CT imaging.

We included 100 patients (64 males, 36 females) who underwent simultaneous coronary artery calcification score imaging (ECG gated) and plain chest CT imaging (non-ECG gated). Images taken using non-ECG gating were reconstructed using the same field of view and slice thickness as those obtained with ECG gating. The EAT capacity of each image was measured and compared. An AZE Virtual Place (Canon) was used for the measurements. The Mann-Whitney U test and intraclass correlation coefficient were used for statistical analyses. P values <0.05 were considered statistically significant. Concordance was evaluated using Bland-Altman analysis.

The mean EAT volume measured by ECG-gated imaging was 156.5 ± 66.9 mL and 155.4 ± 67.9 mL by non-ECG-gated imaging, with no significant difference between the two groups ( P = 0.86). Furthermore, the EAT volumes measured using ECG-gated and non-ECG-gated imaging showed a strong correlation ( r = 0.95, P < 0.05). Bland-Altman analysis revealed that the mean error of the EAT volume (non-ECG-gated imaging - ECG-gated imaging) was -1.02 ± 2.95 mL (95% confidence interval, -6.49 to 4.76).

The EAT volume obtained using non-ECG-gated imaging was equivalent to that obtained using ECG-gated imaging.

Recently, epicardial adipose tissue (EAT) assessed by CT was identified as an independent mortality predictor in patients with various cardiac diseases. Our goal was to develop a deep learning pipeline for robust automatic EAT assessment in CT.

Contrast-enhanced ECG-gated cardiac and thoraco-abdominal spiral CT imaging from 1502 patients undergoing transcatheter aortic valve replacement (TAVR) was included. Slice selection at aortic valve (AV)-level and EAT segmentation were performed manually as ground truth. For slice extraction, two approaches were compared: A regression model with a 2D convolutional neural network (CNN) and a 3D CNN utilizing reinforcement learning (RL). Performance evaluation was based on mean absolute z-deviation to the manually selected AV-level (Δz). For tissue segmentation, a 2D U-Net was trained on single-slice images at AV-level and compared to the open-source body and organ analysis (BOA) framework using Dice score. Superior methods were selected for end-to-end evaluation, where mean absolute difference (MAD) of EAT area and tissue density were compared. 95% confidence intervals (CI) were assessed for all metrics.

Slice extraction using RL was slightly more precise (Δz: RL 1.8 mm (95% CI: [1.6, 2.0]), 2D CNN 2.0 mm (95% CI: [1.8, 2.3])). For EAT segmentation at AV-level, the 2D U-Net outperformed BOA significantly (Dice score: 2D U-Net 91.3% (95% CI: [90.7, 91.8]), BOA 85.6% (95% CI: [84.7, 86.5])). The end-to-end evaluation revealed high agreement between automatic and manual measurements of EAT (MAD area: 1.1 cm2 (95% CI: [1.0, 1.3]), MAD density: 2.2 Hounsfield units (95% CI: [2.0, 2.5])).

We propose a method for robust automatic EAT assessment in spiral CT scans enabling opportunistic evaluation in clinical routine.

Since inflammatory changes in epicardial adipose tissue (EAT) are associated with an increased risk of cardiac diseases, automated evaluation can serve as a basis for developing automated cardiac risk assessment tools, which are essential for efficient, large-scale assessment in opportunistic settings.

Deep learning methods for automatic assessment of epicardial adipose tissue (EAT) have great potential. A 2-step approach with slice extraction and tissue segmentation enables robust automated evaluation of EAT. End-to-end automation enables large-scale research on the value of EAT for outcome analysis.

Risk stratification for sudden cardiac death (SCD) in patients with nonischemic cardiomyopathy (NICM) remains challenging.

This study aimed to investigate the impact of epicardial adipose tissue (EAT) on SCD in NICM patients.

Our study cohort included 173 consecutive patients (age 53 ± 14 years, 73% men) scheduled for primary prevention implantable cardioverter-defibrillators (ICDs) implantation who underwent preimplant cardiovascular magnetic resonance. EAT volume surrounding both ventricles was manually quantified from cine left ventricular short-axis images by summation of the EAT volume of each slice using the modified Simpson rule. The primary endpoint was appropriate ICD therapy.

During the mean follow-up of 3.6 years, 24 patients (14%) experienced an endpoint. An inverse and proportional relationship was evident between EAT and subsequent ICD therapies (P = 0.004). Even after adjusting for left ventricular mass and ejection fraction, EAT was significantly lower in patients with ICD therapy than those without. Low EAT was independently associated with an increased risk of ICD therapy in NICM patients (HRad per 10 mL/m2 decrease, 1.65; 95% CI: 1.17-2.42; P = 0.007). EAT ≤50 mL/m2 demonstrated a 3-fold increase in SCD event risk, with an estimated likelihood of 57% at 5 years. When considered with other potential risk factors, EAT provided incremental prognostic value in predicting ICD therapy.

Low ventricular EAT was associated with increased SCD risk in NICM patients receiving primary prevention ICD implantation, even in the presence of other risk markers. These data suggest a potential clinical role of EAT in selecting NICM patients who would benefit most from ICD implantation.

Non-alcoholic fatty liver disease (NAFLD) is closely related to metabolic syndrome and remains a major global health burden. The increased prevalence of obesity and type 2 diabetes mellitus (T2DM) worldwide has contributed to the rising incidence of NAFLD. It is widely believed that atherosclerotic cardiovascular disease (ASCVD) is associated with NAFLD. In the past decade, the clinical implications of NAFLD have gone beyond liver-related morbidity and mortality, with a majority of patient deaths attributed to malignancy, coronary heart disease (CHD), and other cardiovascular (CVD) complications. To better define fatty liver disease associated with metabolic disorders, experts proposed a new term in 2020 - metabolic dysfunction associated with fatty liver disease (MAFLD). Along with this new designation, updated diagnostic criteria were introduced, resulting in some differentiation between NAFLD and MAFLD patient populations, although there is overlap. The aim of this review is to explore the relationship between MAFLD and ASCVD based on the new definitions and diagnostic criteria, while briefly discussing potential mechanisms underlying cardiovascular disease in patients with MAFLD.

Background: In adults, epicardial adipose tissue (EAT) is associated with metabolic syndrome (MS) and coronary artery disease. EAT thickness is increased in obese youth, but total EAT volume and its correlation with cardiovascular risk factors have not been studied. Objectives: To determine EAT volume in adolescents and its association with obesity and cardiovascular risk factors. Methods: We performed a cross-sectional study including 48 pubertal adolescents (24 obese and 24 lean subjects, aged 13.6 ± 1.5 yr). EAT volume as well as visceral and subcutaneous abdominal adipose tissue volumes were obtained by magnetic resonance imaging. Anthropometrical parameters; blood pressure (BP); fasting serum triglycerides; total and low- and high-density lipoprotein (HDL-C) cholesterol; glucose; and insulin levels were measured. Results: Obese adolescents had higher EAT volume compared to lean controls (49.6 ± 18.0 vs. 17.6 ± 6.7 cm3, p < 0.0005). They also had significantly increased visceral abdominal fat volumes, systolic BP, serum triglycerides, and insulin levels, and decreased HDL-C concentration. EAT volume was significantly associated with anthropometrical indices and cardiovascular risk factors: waist circumference, systolic BP, triglycerides, HDL-C levels, and insulin resistance indices. Metabolic syndrome was present in 25% of obese adolescents. EAT volume was significantly higher in obese adolescents with MS compared to those without MS (63.5 ± 21.4 vs. 44.9 ± 14.6 cm3, p = 0.026). Conclusions: EAT volume, which is known to contribute to atherogenesis in adults, is increased in obese adolescents, and is associated with abdominal visceral fat, cardiovascular risk factors, and MS. Excessive EAT early in life may contribute to the development of premature cardiometabolic disease.

The aim of this study is to conduct a comprehensive bibliometric analysis of CT-based adipose tissue imaging related to coronary artery disease (CAD) to investigate the dynamic development of this field. Web of Science Core Collection was used as our data source to identify relevant documents limited to articles or review articles and written in English with no time restrictions. Then we analyzed the whole trend of publications and utilized VOSviewer and Bibliometrix to conduct a bibliometric analysis including citations, keywords, countries, institutions, authors as well as co-citation analyses of cited references and sources. A total of 629 documents including 560 articles and 69 reviews from 1992 to 2023 were included. The trend of publications was divided into 3 phases and overall exhibited a constant rise. Based on the co-occurrence network of keywords analysis, 3 clusters centered on visceral, epicardial, pericoronary adipose tissue respectively and 1 cluster related to cardiovascular risk factors were identified, meanwhile determining the evolution of fat research. Co-citation analysis suggested that sources were divided into metabolism-related and cardiovascular-related journals. The USA ranked first with 228 documents and 12,086 citations among 47 countries and 1002 institutions, both at the author and institutional levels. In conclusion, this study demonstrated the thriving research field of the impact of CT-based adipose tissue assessment on coronary artery disease, offering a better understanding of the current state of research and valuable insights for future studies and collaborations.

Cardiovascular magnetic resonance (CMR) chemical shift encoding (CSE) enables myocardial fat imaging. We sought to develop a deep learning network (fast chemical shift encoding [FastCSE]) to accelerate CSE.

FastCSE was built on a super-resolution generative adversarial network extended to enhance complex-valued image sharpness. FastCSE enhances each echo image independently before water-fat separation. FastCSE was trained with retrospectively identified cines from 1519 patients (56 ± 16 years; 866 men) referred for clinical 3T CMR. In a prospective study of 16 participants (58 ± 19 years; 7 females) and 5 healthy individuals (32 ± 17 years; 5 females), dual-echo CSE images were collected with 1.5 × 1.5 mm2, 2.5 × 1.5 mm2, and 3.8 × 1.9 mm2 resolution using generalized autocalibrating partially parallel acquisition (GRAPPA). FastCSE was applied to images collected with resolution of 2.5 × 1.5 mm2 and 3.8 × 1.9 mm2 to restore sharpness. Fat images obtained from two-point Dixon reconstruction were evaluated using a quantitative blur metric and analyzed with a five-way analysis of variance.

FastCSE successfully reconstructed CSE images inline. FastCSE acquisition, with a resolution of 2.5 × 1.5 mm2 and 3.8 × 1.9 mm2, reduced the number of breath-holds without impacting visualization of fat by approximately 1.5-fold and 3-fold compared to GRAPPA acquisition with a resolution of 1.5 × 1.5 mm2, from 3.0 ± 0.8 breath-holds to 2.0 ± 0.2 and 1.1 ± 0.4 breath-holds, respectively. FastCSE improved image sharpness and removed ringing artifacts in GRAPPA fat images acquired with a resolution of 2.5 × 1.5 mm2 (0.32 ± 0.03 vs 0.35 ± 0.04, P < 0.001) and 3.8 × 1.9 mm2 (0.32 ± 0.03 vs 0.43 ± 0.06, P < 0.001). Blurring in FastCSE images was similar to blurring in images with 1.5 × 1.5 mm2 resolution (0.32 ± 0.03 vs 0.31 ± 0.03, P = 0.57; 0.32 ± 0.03 vs 0.31 ± 0.03, P = 0.66).

We showed that a deep learning-accelerated CSE technique based on complex-valued resolution enhancement can reduce the number of breath-holds in CSE imaging without impacting the visualization of fat. FastCSE showed similar image sharpness compared to a standardized parallel imaging method.

The aim of this study (EPIDIAB) was to assess the relationship between epicardial adipose tissue (EAT) and the micro and macrovascular complications (MVC) of type 2 diabetes (T2D).

EPIDIAB is a post hoc analysis from the AngioSafe T2D study, which is a multicentric study aimed at determining the safety of antihyperglycemic drugs on retina and including patients with T2D screened for diabetic retinopathy (DR) (n = 7200) and deeply phenotyped for MVC. Patients included who had undergone cardiac CT for CAC (Coronary Artery Calcium) scoring after inclusion (n = 1253) were tested with a validated deep learning segmentation pipeline for EAT volume quantification.

Median age of the study population was 61 [54;67], with a majority of men (57%) a median duration of the disease 11 years [5;18] and a mean HbA1c of7.8 ± 1.4%. EAT was significantly associated with all traditional CV risk factors. EAT volume significantly increased with chronic kidney disease (CKD vs no CKD: 87.8 [63.5;118.6] vs 82.7 mL [58.8;110.8], p = 0.008), coronary artery disease (CAD vs no CAD: 112.2 [82.7;133.3] vs 83.8 mL [59.4;112.1], p = 0.0004, peripheral arterial disease (PAD vs no PAD: 107 [76.2;141] vs 84.6 mL[59.2; 114], p = 0.0005 and elevated CAC score (> 100 vs  < 100 AU: 96.8 mL [69.1;130] vs 77.9 mL [53.8;107.7], p < 0.0001). By contrast, EAT volume was neither associated with DR, nor with peripheral neuropathy. We further evidenced a subgroup of patients with high EAT volume and a null CAC score. Interestingly, this group were more likely to be composed of young women with a high BMI, a lower duration of T2D, a lower prevalence of microvascular complications, and a higher inflammatory profile.

Fully-automated EAT volume quantification could provide useful information about the risk of both renal and macrovascular complications in T2D patients.

Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) supplementation lower triglyceride levels. The impact on epicardial adipose tissue volume (EATV), which is associated with cardiovascular events, is unclear.

To determine if triglyceride reduction with EPA+DHA supplementation decreases EATV and whether EATV affects coronary plaque.

139 subjects with coronary artery disease (CAD) on statins were randomized to 3.36 g EPA+DHA daily or none (control) for 30 months. EATV, coronary plaque volumes and coronary artery calcium score were measured with coronary computed tomographic angiography.

Change in triglyceride level correlated with change in EATV (r=0.236; p=0.006). Despite a 6.7% triglyceride reduction (p=0.021) with EPA+DHA supplementation compared to no change in control (between group p=0.034); both groups had similar reductions in EATV possibly due to statin treatment. EATV above the median (>115.6 cm3) was the only determinant of baseline coronary fatty plaque volume (β=2.4, p=0.010). After multivariate adjustment, waist circumference, a surrogate of abdominal visceral adiposity, was the only determinant of baseline EATV (odds ratio {OR]:1.093; 95% confidence interval [CI]:1.003-1.192, p=0.042). Moreover, increase in waist circumference was the only predictor of an increase in EATV at 30 months (β=0.320, p=0.018).

EATV is associated with higher coronary fatty plaque volume and is regulated by waist circumference but not EPA+DHA supplementation at 30-month follow-up in CAD patients on statin treatment. The direct correlation between waist circumference and EATV suggests that maintaining a healthy weight may limit EATV and coronary fatty plaque volume, potentially leading to a decrease in cardiovascular events.

To analyse the relevance of body composition and blood markers for long-term outcomes in very old patients after transcatheter aortic valve replacement (TAVR).

A total of 403 very old patients were characterized with regard to subcutaneous, visceral, and epicardial fat, psoas muscle area, plasma growth differentiation factor 15 (GDF-15), and leptin. Cohorts grouped by body mass index (BMI) were analysed for long-term outcomes. Patients underwent transapical and transfemoral TAVR (similar 30-day/1-year survival). Body mass index >35 kg/m2 showed increased 2- and 3-year mortality compared with BMI 25-34.9 kg/m2 but not compared with BMI <25 kg/m2. Fat areas correlated positively to BMI (epicardial: R 2 = 0.05, P < 0.01; visceral: R 2 = 0.20, P < 0.001; subcutaneous: R 2 = 0.13, P < 0.001). Increased epicardial or visceral but not subcutaneous fat area resulted in higher long-term mortality. Patients with high BMI (1781.3 mm2 ± 75.8, P < 0.05) and lean patients (1729.4 ± 52.8, P < 0.01) showed lower psoas muscle area compared with those with mildly elevated BMI (2055.2 ± 91.7). Reduced psoas muscle area and increased visceral fat and epicardial fat areas were independent predictors of long-term mortality. The levels of serum GDF-15 were the highest in BMI >40 kg/m2 (2793.5 pg/mL ± 123.2) vs. BMI <25 kg/m2 (2017.6 pg/mL ±130.8), BMI 25-30 kg/m2 (1881.8 pg/mL ±127.4), or BMI 30-35 kg/m2 (2054.2 pg/mL ±124.1, all P < 0.05). Increased GDF-15 level predicted mortality (2587 pg/mL, area under the receiver operating characteristic curve 0.94). Serum leptin level increased with BMI without predictive value for long-term mortality.

Morbidly visceral and epicardial fat accumulation, reduction in muscle area, and GDF-15 increase are strong predictors of adverse outcomes in very old patients post-TAVR.

Myocardial perfusion imaging (MPI), using either single photon emission computed tomography (SPECT) or positron emission tomography (PET), is one of the most commonly ordered cardiac imaging tests, with prominent clinical roles for disease diagnosis and risk prediction. Artificial intelligence (AI) could potentially play a role in many steps along the typical MPI workflow, from image acquisition through to clinical reporting and risk estimation. AI can be utilized to improve image quality, reducing radiation exposure and image acquisition times. Once images are acquired, AI can help optimize motion correction and image registration during image reconstruction or provide direct image attenuation correction. Utilizing these image sets, AI can segment a number of anatomic features from associated computed tomographic imaging or even generate synthetic attenuation imaging. Lastly, AI may play an important role in disease diagnosis or risk prediction by combining the large number of potentially important clinical, stress, and imaging-related variables. This review will focus on the most recent developments in the field, providing clinicians and researchers with a timely update on the field. Additionally, it will discuss future trends including applications of AI during multiple points of the typical MPI workflow to maximize clinical utility and methods to maximize the information that can be obtained from hybrid 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.

This study aimed to identify the impact of increased epicardial adipose tissue (EAT) and its regional distribution on cardiac function in patients with diastolic dysfunction.

Sixty-eight patients with exertional dyspnoea (New York Heart Association ≥II), preserved ejection fraction (≥50%), and diastolic dysfunction (E/e' ≥ 8) underwent rest and stress right heart catheterization, transthoracic echocardiography, and cardiovascular magnetic resonance (CMR). EAT volumes were depicted from CMR short-axis stacks. First, the impact of increased EAT above the median was investigated. Second, the association of ventricular and atrial EAT with myocardial deformation at rest and during exercise stress was analysed in a multivariable regression analysis. Patients with high EAT had higher HFA-PEFF and H2FPEFF scores as well as N-terminal prohormone of brain natriuretic peptide levels (all P < 0.048). They were diagnosed with manifest heart failure with preserved ejection fraction (HFpEF) more frequently (low EAT: 37% vs. high EAT: 64%; P = 0.029) and had signs of adverse remodelling indicated by higher T1 times (P < 0.001). No differences in biventricular volumetry and left ventricular mass (all P > 0.074) were observed. Patients with high EAT had impaired atrial strain at rest and during exercise stress, and impaired ventricular strain during exercise stress. Regionally increased EAT was independently associated with functional impairment of the adjacent chambers.

Patients with diastolic dysfunction and increased EAT show more pronounced signs of diastolic functional failure and adverse structural remodelling. Despite similar morphological characteristics, patients with high EAT show significant cardiac functional impairment, in particular in the atria. Our results indicate that regionally increased EAT directly induces atrial functional failure, which represents a distinct pathophysiological feature in HFpEF.

Patients with myocardial ischemia without obstructive coronary artery disease often have coronary microvascular dysfunction (CMD) and associated increased risk of cardiovascular (CV) events and anginal hospitalizations. Epicardial adipose tissue (EAT) covers much of the myocardium and coronary arteries and when dysfunctional, secretes proinflammatory cytokines and is associated with CV events. While oxidative stress and systemic inflammation are associated with CMD, the relationship between EAT and CMD in women is not well known.

Women diagnosed with CMD (n = 21) who underwent coronary computed tomography with coronary artery calcium (CAC) scoring were compared to a reference group (RG) of women referred for CAC screening for preventive risk assessment (n = 181). EAT attenuation (Hounsfield units (HU)) was measured adjacent to the proximal right coronary artery, along with subcutaneous adipose tissue (SCAT). Two-sample t-tests with unequal variances were utilized.

Mean age of the CMD group was 56 ± 8 years and body mass index (BMI) was 31.6 ± 6.8 kg/m2. CV risk factors in the CMD group were prevalent: 67 % hypertension, 44 % hyperlipidemia, and 33 % diabetes. Both CMD and RG had similar CAC score (25.86 ± 59.54 vs. 24.17 ± 104.6; p = 0.21. In the CMD group, 67 % had a CAC of 0. Minimal atherosclerosis (CAD-RADS 1) was present in 76 % of women with CMD. The CMD group had lower EAT attenuation than RG (-103.3 ± 6.33 HU vs. -97.9 ± 8.3 HU, p = 0.009, respectively). There were no differences in SCAT attenuation. Hypertension, smoking history, age, BMI, and CAC score did not correlate with EAT in either of the groups.

Women with CMD have decreased EAT attenuation compared to RG women. EAT-mediated inflammation and changes in vascular tone may be a mechanistic contributor to abnormal microvascular reactivity. Clinical trials testing therapeutic strategies to decrease EAT may be warranted in the management of CMD.

Myocardial perfusion imaging (MPI) is one of the most commonly ordered cardiac imaging tests. Accurate motion correction, image registration, and reconstruction are critical for high-quality imaging, but this can be technically challenging and has traditionally relied on expert manual processing. With accurate processing, there is a rich variety of clinical, stress, functional, and anatomic data that can be integrated to guide patient management.

PubMed and Google Scholar were reviewed for articles related to artificial intelligence in nuclear cardiology published between 2020 and 2024. We will outline the prominent roles for artificial intelligence (AI) solutions to provide motion correction, image registration, and reconstruction. We will review the role for AI in extracting anatomic data for hybrid MPI which is otherwise neglected. Lastly, we will discuss AI methods to integrate the wealth of data to improve disease diagnosis or risk stratification.

There is growing evidence that AI will transform the performance of MPI by automating and improving on aspects of image acquisition and reconstruction. Physicians and researchers will need to understand the potential strengths of AI in order to benefit from the full clinical utility of MPI.

It has been shown that obesity and a higher body mass index (BMI) are associated with a higher recurrence rate of atrial fibrillation (AF) after successful catheter ablation (CA). The same has been proven for the left atrial volume index (LAVI). It has also been shown that there is a correlation between LAVI and BMI. However, whether the LAVI's prognostic impact on AF recurrence is BMI-independent remains unclear.

We prospectively included 62 patients with paroxysmal AF who were referred to our institution for CA. All patients underwent radiofrequency CA with standard pulmonary veins isolation. Transthoracic 2-D echocardiography was performed one day after CA to obtain standard measures of cardiac function and morphology. Recurrence was defined as documented AF within 6 months of the follow-up period. Patients were also instructed to visit our outpatient clinic earlier in case of symptoms suggesting AF recurrence.

We observed AF recurrence in 27% of patients after 6 months. The mean BMI in our cohort was 29.65 ± 5.08 kg/cm2 and the mean LAVI was 38.04 ± 11.38 mL/m2. We further divided patients into two groups according to BMI. Even though the LAVI was similar in both groups, we found it to be a significant predictor of AF recurrence only in obese patients (BMI ≥ 30) and not in the non-obese group (BMI < 30). There was also no significant difference in AF recurrence between both cohorts. The significance of the LAVI as an AF recurrence predictor in the obesity group was also confirmed in a multivariate model.

According to our results, the LAVI tends to be a significant predictor of AF recurrence after successful catheter ablation in obese patients, but not in normal-weight or overweight patients. This would suggest different mechanisms of AF in non-obese patients in comparison to obese patients. Further studies are needed in this regard.

Inflammatory changes in epicardial (EAT) and pericardial adipose tissue (PAT) are associated with increased overall cardiovascular risk. Using routine, preinterventional cardiac CT data, we examined the predictive value of quantity and quality of EAT and PAT for outcome after transcatheter aortic valve replacement (TAVR).

Cardiac CT data of 1197 patients who underwent TAVR at the in-house heart center between 2011 and 2020 were retrospectively analyzed. The amount and density of EAT and PAT were quantified from single-slice CT images at the level of the aortic valve. Using established risk scores and known independent risk factors, a clinical benchmark model (BMI, Chronic kidney disease stage, EuroSCORE 2, STS Prom, year of intervention) for outcome prediction (2-year mortality) after TAVR was established. Subsequently, we tested whether the additional inclusion of area and density values of EAT and PAT in the clinical benchmark model improved prediction. For this purpose, the cohort was divided into a training (n=798) and a test cohort (n=399).

Within the 2-year follow-up, 264 patients died. In the training cohort, particularly the addition of EAT density to the clinical benchmark model showed a significant association with outcome (hazard ratio 1.04, 95% CI: 1.01-1.07; P =0.013). In the test cohort, the outcome prediction of the clinical benchmark model was also significantly improved with the inclusion of EAT density (c-statistic: 0.589 vs. 0.628; P =0.026).

EAT density as a surrogate marker of EAT inflammation was associated with 2-year mortality after TAVR and may improve outcome prediction independent of established risk parameters.

Epicardial adipose tissue is a novel cardiometabolic risk factor and indicator of subclinical atherosclerosis. We aimed to evaluate the epicardial adipose tissue thickness in rheumatoid arthritis (RA) patients and its association with disease activity scores. A total of 81 rheumatoid arthritis patients and 70 age- and sex-matched healthy individuals were recruited for this cross-sectional study. Epicardial adipose tissue thickness (EATT) was measured by transthoracic two-dimensional echocardiography. Tender and swollen joint counts were recorded at the time of inclusion. The laboratory tests included erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), rheumatoid factor, anti-citrullinated protein antibodies, and serum lipid levels. Disease activity was calculated based on Disease Activity Scores for 28 joints (DAS-28) ESR and CRP, the Simple Disease Activity Index (SDAI), and the Clinical Disease Activity Index (CDAI). Epicardial adipose tissue thickness was significantly higher in the RA patients compared to the healthy controls (p < 0.001). We found statistically significant correlations of EATT with all disease activity indices (p < 0.001) and CRP (p = 0.002). According to a cut-off value of 6.4 mm determined for epicardial adipose tissue thickness, the RA patients with thickness ≥ 6.4 mm had higher disease activity scores and CRP levels. In the multivariable regression analysis, only SDAI score was found as an independent risk factor for increased EATT (OR, (95%CI), 13.70 (3.88-48.43), p < 0.001). Epicardial adipose tissue thickness measurement by echocardiography is a reliable method for assessing subclinical atherosclerosis in rheumatoid arthritis patients, and a higher disease activity score is an independent risk factor for coronary artery disease.

Coronary artery, aortic valve, and descending aorta calcification (CAC, AVC, DAC) are manifestations of atherosclerosis, and cardiac epicardial adipose tissue (EAT) indicates heart adiposity. This study explored the association between cardiac adipose tissue and cardiovascular calcification in participants with long-standing T1D.

EAT and intra-thoracic adipose tissue (IAT) were measured in 100 T1D subjects with cardiac computed tomography (CT) scans in the EDIC study. Volume analysis software was used to measure fat volumes. Spearman correlations were calculated between CAC, AVC, DAC with EAT, and IAT. Associations were evaluated using multiple linear and logistic regression models.

Participants ranged in age from 32 to 57. Mean EAT, and IAT were 38.5 and 50.8 mm3, respectively, and the prevalence of CAC, AVC, and DAC was 43.6 %, 4.7 %, and 26.8 %, respectively. CAC was positively correlated with age (p-value = 0.0001) and EAT (p-value = 0.0149) but not with AVC and DAC; IAT was not associated with calcified lesions. In models adjusted for age and sex, higher levels of EAT and IAT were associated with higher CAC (p-value < 0.0001 for both) and higher AVC (p-values of 0.0111 and 0.0053, respectively), but not with DAC. The associations with CAC remained significant (p-value < 0.0001) after further adjustment for smoking, systolic blood pressure, BMI, and LDL, while the associations with AVC did not remain significant.

In participants with T1D, higher EAT and IAT levels are correlated with higher CAC scores. EAT and IAT were not independently correlated with DAC or AVC.

Amidst an aging population and escalating obesity prevalence, elucidating the impact of obesity on transcatheter aortic valve replacement (TAVR) outcomes becomes paramount. The so-called "obesity paradox"-a term denoting the counterintuitive association of obesity, typically a risk factor for cardiovascular diseases, with improved survival outcomes in TAVR patients relative to their leaner or normal-weight counterparts-merits rigorous examination. This review comprehensively investigates the complex relationship between obesity and the clinical outcomes associated with TAVR, with a specific focus on mortality and periprocedural complications. This study aims to deepen our understanding of obesity's role in TAVR and the underlying mechanisms of the obesity paradox, thereby optimizing management strategies for this patient demographic, tailored to their unique physiological and metabolic profiles.

Epicardial adipose tissue (EAT) is the cardiac visceral fat depot proposed to play a role in the etiology of various cardiovascular disease outcomes. Little is known about EAT determinants in a general population. We examined cardiometabolic, dietary, lifestyle and socioeconomic determinants of echocardiograpghically measured EAT in early adulthood. Data on cardiometabolic, dietary, lifestyle and socioeconomic factors were collected from participants of the Cardiovascular Risk in Young Finns Study (YFS; N = 1667; age 34-49 years). EAT thickness was measured from parasternal long axis echocardiograms. Multivariable regression analysis was used to study potential EAT determinants. Possible effect modification of sex was addressed. Mean EAT thickness was 4.07 mm (95% CI 4.00-4.17). Multivariable analysis [β indicating percentage of change in EAT(mm) per one unit increase in determinant variable] indicated female sex (β = 11.0, P < 0.0001), type 2 diabetes (β = 14.0, P = 0.02), waist circumference (cm) (β = 0.38, P < 0.0001), systolic blood pressure (mmHg) (β = 0.18, P = 0.02) and red meat intake (g/day) (β = 0.02, P = 0.05) as EAT determinants. Sex-specific analysis revealed age (year) (β = 0.59, P = 0.01), alcohol intake (drinks/day) (β = 4.69, P = 0.006), heavy drinking (yes/no) (β = 30.4, P < 0.0001) as EAT determinants in women and fruit intake (g/day) (β = -1.0, P = 0.04) in men. In the YFS cohort, waist circumference, systolic blood pressure and red meat intake were directly associated with EAT among all participants. In women, age, alcohol intake, heavy drinking and type 2 diabetes associated directly with EAT, while an inverse association was observed between fruit intake and EAT in men.

Artificial intelligence (AI) is having a significant impact in medical imaging, advancing almost every aspect of the field, from image acquisition and postprocessing to automated image analysis with outreach toward supporting decision making. Noninvasive cardiac imaging is one of the main and most exciting fields for AI development. The aim of this review is to describe the main applications of AI in cardiac imaging, including CT and MR imaging, and provide an overview of recent advancements and available clinical applications that can improve clinical workflow, disease detection, and prognostication in cardiac disease.

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.

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.

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.

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

With increased ageing of the population, cardiovascular disease (CVD) has become the most important factor endangering human health worldwide. Although the treatment of CVD has become increasingly advanced, there are still a considerable number of patients with conditions that have not improved. According to the latest clinical guidelines of the European Cardiovascular Association, obesity has become an independent risk factor for CVD. Adipose tissue includes visceral adipose tissue and subcutaneous adipose tissue. Many previous studies have focused on subcutaneous adipose tissue, but visceral adipose tissue has been rarely studied. However, as a type of visceral adipose tissue, epicardial adipose tissue (EAT) has attracted the attention of researchers because of its unique anatomical and physiological characteristics. This review will systematically describe the physiological characteristics and evaluation methods of EAT and emphasize the important role and treatment measures of EAT in CVD.