Epicardial fat attenuation, not volume, predicts obstructive coronary artery disease and high risk plaque features in patients with atypical chest pain

The change of epicardial adipose tissue characteristics and vulnerability for atrial fibrillation upon drastic weight loss

BACKGROUND

Obesity increases the risk of atrial fibrillation (AF). We hypothesize that 'obese' epicardial adipose tissue (EAT) is, regardless of comorbidities, associated with markers of AF vulnerability.

METHODS

Patients >40y of age undergoing bariatric surgery and using <2 antihypertensive drugs and no insulin were prospectively included. Study investigations were conducted before and 1y after surgery. Heart rhythm and p-wave duration were measured through ECGs and 7-d-holters. EAT-volume and attenuation were determined on non-enhanced CT scans. Serum markers were quantified by ELISA.

RESULTS

Thirty-seven patients underwent surgery (age: 52.1 ± 5.9y; 27 women; no AF). Increased p-wave duration correlated with higher BMI, larger EAT volumes, and lower EAT attenuations (p < 0.05). Post-surgery, p-wave duration decreased from 109 ± 11 to 102 ± 11ms. Concurrently, EAT volume decreased from 132 ± 49 to 87 ± 52ml, BMI from 43.2 ± 5.2 to 28.9 ± 4.6kg/m2, and EAT attenuation increased from -76.1 ± 4.0 to -71.7 ± 4.4HU (p <0.001). Adiponectin increased from 8.7 ± 0.8 to 14.2 ± 1.0 μg/ml (p <0.001). However, decreased p-wave durations were not related to changed EAT characteristics, BMI or adiponectin.

CONCLUSION

In this explorative study, longer p-wave durations related to higher BMIs, larger EAT volume, and lower EAT attenuations. P-wave duration and EAT volume decreased, and EAT attenuation increased upon drastic weightloss. However, there was no relation between decreased p-wave duration and changed BMI or EAT characteristics.

The influence of epicardial adipose tissue on the prognosis of atrial fibrillation patients undergoing radiofrequency ablation combined with left atrial appendage occlusion

Atrial fibrillation is the most common arrhythmia in adults. The interplay between epicardial adipose tissue and atrial fibrillation has garnered significant scientific interest. Recently, the combined approach of radiofrequency ablation and left atrial appendage occlusion has become a widely adopted strategy for managing non-valvular atrial fibrillation patients at high risk of thrombus formation. This study aims to assess the prognostic significance of epicardial adipose tissue volume in patients undergoing radiofrequency ablation in conjunction with left atrial appendage occlusion. This study results indicate that in patients undergoing the one-stop procedure, which comprises catheter radiofrequency ablation and percutaneous left atrial appendage occlusion, epicardial adipose tissue volume is significantly associated with AF recurrence post-strategy. Higher EATV predicts AF recurrence (HR = 1.17, 95%CI1.047-1.192, P = 0.001) and thromboembolism (P = 0.002) following the one-stop procedure. Epicardial adipose tissue volume serves as a significant predictor of atrial fibrillation recurrence following the one-stop procedure (area under the curve 0.648, 95%CI0.571-0.725, P = 0.002, sensitivity 0.88, specificity 0.50).

Chest-CT-based radiomics feature of epicardial adipose tissue for screening coronary atherosclerosis

BACKGROUND AND AIMS

This study aims to investigate the diagnostic value of chest-CT epicardial adipose tissue (EAT) radiomics feature in coronary atherosclerotic stenosis.

METHODS

Clinical data from 215 individuals who underwent coronary angiography and chest-CT scan from January to July 2022 at our institution were retrospectively analyzed. Based on the coronary angiography results, the total population, men, and women were divided into the CAD group and non-CAD group. radiomics feature of EAT at the level of the bifurcation of the left-main coronary artery on the transverse level of chest CT were measured. The features contain both first-order feature and shape-order feature.The differences between groups were analyzed using the t test or Chi-square test. The diagnostic efficacy of each parameter in diagnosing atherosclerotic stenosis of coronary arteries was assessed by plotting the receiver operating characteristic (ROC) curve.

RESULTS

First-order features: Mean, IntDen, Median, and RawIntDen; shape-order features: Area, Perim, Round, and BSA index; and clinical index: HbA1c showed statistical significance between the CAD group and the non-CAD group. The ROC curve analysis demonstrated high diagnostic efficacy, with the best for diagnostic efficacy being Median for the first-order feature parameter (AUC, 0.753; 95% confidence interval [CI], 0.689-0.817; t = 4.785, p < 0.001), Round for the shape-order feature (AUC, 0.775; 95% CI, 0.714-0.836; t = 7.842, p < 0.001), and HbA1c for the clinical index (AUC, 0.797; 95% CI, 0.783-0.856; t = 6.406, p < 0.001). After dividing the participants into male and female subgroups, the best diagnostic efficacy was observed with the BSA index for men (AUC, 0.743; 95% CI, 0.656-0.829; t = 5.128, p < 0.001) and Round for women (AUC, 0.871; 95% CI, 0.793-0.949; t = 7.247, p < 0.001).

CONCLUSIONS

Median, Round in radiomics feature of EAT on chest CT may play a role in the assessment of coronary atherosclerotic stenosis.

Effect of Vessel Attenuation, VMI Level, and Reconstruction Kernel on Pericoronary Adipose Tissue Attenuation for EID CT and PCD CT: An Ex Vivo Porcine Heart Study

BACKGROUND. Pericoronary adipose tissue (PCAT) attenuation and the fat attenuation index (FAI) may serve as markers of inflammation and the risk of adverse cardiac events. However, standardization of relevant CT acquisition and reconstruction parameters is lacking. OBJECTIVE. The purpose of this study was to investigate the influence of vessel attenuation, the virtual monoenergetic image (VMI) level, and the reconstruction kernel on PCAT attenuation and FAI by use of energy-integrating detector (EID) and photon-counting detector (PCD) CT systems in an ex vivo porcine heart model. METHODS. The right coronary artery (RCA) of a porcine heart was injected with saline or varying contrast medium dilutions to achieve vessel attenuation ranging from 0 to 1000 HU. After each injection, the heart was sequentially scanned by EID CT at 120 kVp and PCD CT at 140 kVp at a constant CTDIvol of 10 mGy. For EID CT, polychromatic images were reconstructed with a Qr40 kernel. For PCD CT, VMIs (obtained at 40-80 keV in 10-keV increments) were reconstructed with Qr40, Bv40, and Bv56 kernels. ROIs were placed to measure RCA and PCAT attenuation. FAI was determined using software; histogram analysis was performed to assess voxel attenuation in the volumes of interest for FAI calculation. RESULTS. Correlations were observed between attenuation in the RCA and attenuation in the adjacent PCAT (r = 0.3-1.0) and between vessel attenuation and the FAI (r = -0.9 to 1.0). For PCAT attenuation and the FAI, these associations became progressively weaker when progressively sharper kernels were used. For increasing vessel attenuation on EID CT and for increasing VMI level on PCD CT, FAI histograms showed right shifts in peak attenuation values; the percentage of histogram voxels that met the threshold range for inclusion in FAI calculation was 9-38% for EID CT and 6-39% for PCD CT at VMI levels of 70-80 keV. For PCD CT, use of sharper kernels was associated with left shifts in peak attenuation values and greater percentages of voxels within the threshold range for inclusion in FAI calculation. CONCLUSION. PCAT attenuation and the FAI are influenced by vessel lumen attenuation, the VMI level, and the reconstruction kernel. A minority of pericoronary voxels contribute to FAI measurements for polychromatic EID CT and for PCD CT at high VMI levels. CLINICAL IMPACT. These findings may help standardize acquisition and reconstruction parameters for PCAT attenuation and FAI measurements.

Epicardial fat density obtained with computed tomography imaging - more important than volume?

Epicardial adipose tissue (EAT) is a unique fat depot located between the myocardium and the visceral layer of pericardium. It can be further subdivided into pericoronary (PCAT), periatrial (PAAT) and periventricular adipose tissue (PVentAT), each of them exhibiting specific characteristics and association with the underlying tissue. Since no physical barrier separates EAT from the myocardium, this fat tissue can easily interact with the underlying cardiac structure. EAT can be visualized using various imaging modalities. Computed tomography provides not only information on EAT volume, but also on its density. Indeed, EAT density reflected by the recently developed fat attenuation index (FAI) is emerging as a useful index of PCAT inflammation, PAAT inflammation and fibrosis, while the relevance of density of PVentAT is much less known. The emerging data indicates that FAI can be an important diagnostic and prognostic tool in both coronary artery disease and atrial fibrillation. Future studies will demonstrate if it also could be used as a marker of efficacy of therapies and whether FAI PVentAT could indicate ventricular pathologies, such as heart failure. The aim of the review is to present computed tomography derived FAI as an important tool both to study and better understand the epicardial fat and as a potential predictive marker in cardiovascular disorders.

The pericoronary adipose tissue attenuation in CT strongly depends on kernels and iterative reconstructions

OBJECTIVES

To investigate the influence of kernels and iterative reconstructions on pericoronary adipose tissue (PCAT) attenuation in coronary CT angiography (CCTA).

MATERIALS AND METHODS

Twenty otherwise healthy subjects (16 females; median age 52 years) with atypical chest pain, low risk of coronary artery disease (CAD), and without CAD in photon-counting detector CCTA were included. Images were reconstructed with a quantitative smooth (Qr36) and three vascular kernels of increasing sharpness levels (Bv36, Bv44, Bv56). Quantum iterative reconstruction (QIR) was either switched-off (QIRoff) or was used with strength levels 2 and 4. The fat-attenuation-index (FAI) of the PCAT surrounding the right coronary artery was calculated in each dataset. Histograms of FAI measurements were created. Intra- and inter-reader agreements were determined. A CT edge phantom was used to determine the edge spread function (ESF) for the same datasets.

RESULTS

Intra- and inter-reader agreement of FAI was excellent (intra-class correlation coefficient = 0.99 and 0.98, respectively). Significant differences in FAI were observed depending on the kernel and iterative reconstruction strength level (each, p < 0.001), with considerable inter-individual variation up to 34 HU and intra-individual variation up to 33 HU, depending on kernels and iterative reconstruction levels. The ESFs showed a reduced range of edge-smoothing with increasing kernel sharpness, causing an FAI decrease. Histogram analyses revealed a narrower peak of PCAT values with increasing iterative reconstruction levels, causing a FAI increase.

CONCLUSIONS

PCAT attenuation determined with CCTA heavily depends on kernels and iterative reconstruction levels both within and across subjects. Standardization of CT reconstruction parameters is mandatory for FAI studies to enable meaningful interpretations.

KEY POINTS

Question Do kernels and iterative reconstructions influence pericoronary adipose tissue (PCAT) attenuation in coronary CT angiography (CCTA)? Findings Significant differences in fat-attenuation-index (FAI) were observed depending on the kernel and iterative reconstruction strength level with considerable inter- and intra-individual variation. Clinical relevance PCAT attenuation heavily depends on kernels and iterative reconstructions requiring CT reconstruction parameter standardization to enable meaningful interpretations of fat-attenuation differences across subjects.

Radiomics parameters of epicardial adipose tissue predict mortality in acute pulmonary embolism

BACKGROUND

Accurate prediction of short-term mortality in acute pulmonary embolism (APE) is very important. The aim of the present study was to analyze the prognostic role of radiomics values of epicardial adipose tissue (EAT) in APE.

METHODS

Overall, 508 patients were included into the study, 209 female (42.1%), mean age, 64.7 ± 14.8 years. 4.6%and 12.4% died (7- and 30-day mortality, respectively). For external validation, a cohort of 186 patients was further analysed. 20.2% and 27.7% died (7- and 30-day mortality, respectively). CTPA was performed at admission for every patient before any previous treatment on multi-slice CT scanners. A trained radiologist, blinded to patient outcomes, semiautomatically segmented the EAT on a dedicated workstation using ImageJ software. Extraction of radiomic features was applied using the pyradiomics library. After correction for correlation among features and feature cleansing by random forest and feature ranking, we implemented feature signatures using 247 features of each patient. In total, 26 feature combinations with different feature class combinations were identified. Patients were randomly assigned to a training and a validation cohort with a ratio of 7:3. We characterized two models (30-day and 7-day mortality). The models incorporate a combination of 13 features of seven different image feature classes.

FINDINGS

We fitted the characterized models to a validation cohort (n = 169) in order to test accuracy of our models. We observed an AUC of 0.776 (CI 0.671-0.881) and an AUC of 0.724 (CI 0.628-0.820) for the prediction of 30-day mortality and 7-day mortality, respectively. The overall percentage of correct prediction in this regard was 88% and 79% in the validation cohorts. Lastly, the AUC in an independent external validation cohort was 0.721 (CI 0.633-0.808) and 0.750 (CI 0.657-0.842), respectively.

INTERPRETATION

Radiomics parameters of EAT are strongly associated with mortality in patients with APE.

CLINICAL TRIAL NUMBER

Not applicable.

Intra-individual comparison of epicardial adipose tissue characteristics on coronary CT angiography between photon-counting detector and energy-integrating detector CT systems

PURPOSE

To explore the potential differences in epicardial adipose tissue (EAT) volume and attenuation measurements between photon-counting detector (PCD) and energy-integrating detector (EID)-CT systems.

METHODS

Fifty patients (mean age 69 ± 8 years, 41 male [82 %]) were prospectively enrolled for a research coronary CT angiography (CCTA) on a PCD-CT within 30 days after clinical EID-based CCTA. EID-CT acquisitions were reconstructed using a Bv40 kernel at 0.6 mm slice thickness. The PCD-CT acquisition was reconstructed at a down-sampled resolution (0.6 mm, Bv40; [PCD-DS]) and at ultra-high resolutions (PCD-UHR) with a 0.2 mm slice thickness and Bv40, Bv48, and Bv64 kernels. EAT segmentation was performed semi-automatically at about 1 cm intervals and interpolated to cover the whole epicardium within a threshold of -190 to -30 HU. A subgroup analysis was performed based on quartile groups created from EID-CT data and PCD-UHRBv48 data. Differences were measured using repeated-measures ANOVA and the Friedman test. Correlations were tested using Pearson's and Spearman's rho, and agreement using Bland-Altman plots.

RESULTS

EAT volumes significantly differed between some reconstructions (e.g.

EID-CT

138 ml [IQR 100, 188]; PCD-DS: 147 ml [110, 206]; P<0.001). Overall, correlations between PCD-UHR and EID-CT EAT volumes were excellent, e.g. PCD-UHRBv48: r: 0.976 (95 % CI: 0.958, 0.987); P<0.001; with good agreement (mean bias: -9.5 ml; limits of agreement [LoA]: -40.6, 21.6). On the other hand, correlations regarding EAT attenuation was moderate, e.g. PCD-UHRBV48: r: 0.655 (95 % CI: 0.461, 0.790); P<0.001; mean bias: 6.5 HU; LoA: -2.0, 15.0.

CONCLUSION

EAT attenuation and volume measurements demonstrated different absolute values between PCD-UHR, PCD-DS as well as EID-CT reconstructions, but showed similar tendencies on an intra-individual level. New protocols and threshold ranges need to be developed to allow comparison between PCD-CT and EID-CT data.

Association of epicardial adipose tissue on magnetic resonance imaging with cardiovascular outcomes: Quality over quantity?

OBJECTIVE

Epicardial adipose tissue (EAT) quantity is associated with poor cardiovascular outcomes. However, the quality of EAT may be of incremental prognostic value. Cardiac magnetic resonance (CMR) is the gold standard for tissue characterization but has never been applied for EAT quality assessment. We aimed to investigate EAT quality measured on CMR T1 mapping as a predictor of poor outcomes in an all-comer cohort.

METHODS

We investigated the association of EAT area and EAT T1 times (EAT-T1) with a composite endpoint of nonfatal myocardial infarction, heart failure hospitalization, and all-cause death.

RESULTS

A total of 966 participants were included (47.2% female; mean age: 58.4 years) in this prospective observational CMR registry. Mean EAT area and EAT-T1 were 7.3 cm2 and 268 ms, respectively. On linear regression, EAT-T1 was not associated with markers of obesity, dyslipidemia, or comorbidities such as diabetes (p > 0.05 for all). During a follow-up of 57.7 months, a total of 280 (29.0%) events occurred. EAT-T1 was independently associated (adjusted hazard ratio per SD: 1.202; 95% CI: 1.022-1.413; p = 0.026) with the composite endpoint when adjusted for established clinical risk.

CONCLUSIONS

EAT quality (as assessed via CMR T1 times), but not EAT quantity, is independently associated with a composite endpoint of nonfatal myocardial infarction, heart failure hospitalization, and all-cause death.

Epicardial adipose tissue dispersion at CT and recurrent atrial fibrillation after pulmonary vein isolation

OBJECTIVES

Epicardial adipose tissue (EAT) remodeling is associated with atrial fibrillation (AF). Left atrial (LA) EAT dispersion on cardiac CT is a non-invasive imaging biomarker reflecting EAT heterogeneity. We aimed to investigate the association of LA EAT dispersion with AF recurrence after pulmonary vein isolation (PVI).

METHODS

In a prospective registry of consecutive patients undergoing first PVI, mean EAT attenuation values were measured on contrast-enhanced cardiac CT scans in Hounsfield units (HU) within low (- 195 to - 45 HU) and high (- 44 to - 15 HU) threshold EAT compartments around the left atrium (LA). EAT dispersion was defined as the difference between the mean HU values within the two EAT compartments. Continuous variables were compared between groups using the Mann-Whitney U test and cox proportional hazard models were used to calculate hazard ratios of predictors of 1-year AF recurrence.

RESULTS

A total of 208 patients were included, 135 with paroxysmal AF and 73 with persistent AF. LA EAT dispersion was significantly larger in patients with persistent compared to paroxysmal AF (52.6 HU vs. 49.9 HU; p = 0.001). After 1 year of follow-up, LA EAT dispersion above the mean (> 50.8 HU) was associated with a higher risk of AF recurrence (HR 2.3, 95% CI 1.5-3.6; p < 0.001). It retained its predictive value when corrected for age, sex, body mass index, LA volume, and AF type (HR 2.8, 95% CI 1.6-4.6; p < 0.001).

CONCLUSION

A larger LA EAT dispersion on contrast-enhanced cardiac CT scans, reflecting EAT heterogeneity, is independently associated with AF recurrence after PVI.

CLINICAL RELEVANCE STATEMENT

Based on LA EAT dispersion assessment, a more accurate risk stratification and patient selection may be possible based on a pre-procedural cardiac CT when planning PVI.

KEY POINTS

• Epicardial adipose tissue (EAT) remodeling is associated with atrial fibrillation (AF). • A larger left atrial EAT dispersion in a pre-procedural cardiac CT was associated with a higher 1-year AF recurrence risk after pulmonary vein isolation. • A pre-procedural cardiac CT with left atrial EAT dispersion assessment may provide a more accurate risk stratification and patient selection for PVI.

A cloud-based medical device for predicting cardiac risk in suspected coronary artery disease: a rapid review and conceptual economic model

Background

The CaRi-Heart® device estimates risk of 8-year cardiac death, using a prognostic model, which includes perivascular fat attenuation index, atherosclerotic plaque burden and clinical risk factors.

Objectives

To provide an Early Value Assessment of the potential of CaRi-Heart Risk to be an effective and cost-effective adjunctive investigation for assessment of cardiac risk, in people with stable chest pain/suspected coronary artery disease, undergoing computed tomography coronary angiography. This assessment includes conceptual modelling which explores the structure and evidence about parameters required for model development, but not development of a full executable cost-effectiveness model.

Data sources

Twenty-four databases, including MEDLINE, MEDLINE In-Process and EMBASE, were searched from inception to October 2022.

Methods

Review methods followed published guidelines. Study quality was assessed using Prediction model Risk Of Bias ASsessment Tool. Results were summarised by research question: prognostic performance; prevalence of risk categories; clinical effects; costs of CaRi-Heart. Exploratory searches were conducted to inform conceptual cost-effectiveness modelling.

Results

The only included study indicated that CaRi-Heart Risk may be predictive of 8 years cardiac death. The hazard ratio, per unit increase in CaRi-Heart Risk, adjusted for smoking, hypercholesterolaemia, hypertension, diabetes mellitus, Duke index, presence of high-risk plaque features and epicardial adipose tissue volume, was 1.04 (95% confidence interval 1.03 to 1.06) in the model validation cohort. Based on Prediction model Risk Of Bias ASsessment Tool, this study was rated as having high risk of bias and high concerns regarding its applicability to the decision problem specified for this Early Value Assessment. We did not identify any studies that reported information about the clinical effects or costs of using CaRi-Heart to assess cardiac risk. Exploratory searches, conducted to inform the conceptual cost-effectiveness modelling, indicated that there is a deficiency with respect to evidence about the effects of changing existing treatments or introducing new treatments, based on assessment of cardiac risk (by any method), or on measures of vascular inflammation (e.g. fat attenuation index). A de novo conceptual decision-analytic model that could be used to inform an early assessment of the cost effectiveness of CaRi-Heart is described. A combination of a short-term diagnostic model component and a long-term model component that evaluates the downstream consequences is anticipated to capture the diagnosis and the progression of coronary artery disease.

Limitations

The rapid review methods and pragmatic additional searches used to inform this Early Value Assessment mean that, although areas of potential uncertainty have been described, we cannot definitively state where there are evidence gaps.

Conclusions

The evidence about the clinical utility of CaRi-Heart Risk is underdeveloped and has considerable limitations, both in terms of risk of bias and applicability to United Kingdom clinical practice. There is some evidence that CaRi-Heart Risk may be predictive of 8-year risk of cardiac death, for patients undergoing computed tomography coronary angiography for suspected coronary artery disease. However, whether and to what extent CaRi-Heart represents an improvement relative to current standard of care remains uncertain. The evaluation of the CaRi-Heart device is ongoing and currently available data are insufficient to fully inform the cost-effectiveness modelling.

Future work

A large (n = 15,000) ongoing study, NCT05169333, the Oxford risk factors and non-invasive imaging study, with an estimated completion date of February 2030, may address some of the uncertainties identified in this Early Value Assessment.

Study registration

This study is registered as PROSPERO CRD42022366496.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR135672) and is published in full in Health Technology Assessment; Vol. 28, No. 31. See the NIHR Funding and Awards website for further award information.

Analysis of Epicardial Adipose Tissue Texture in Relation to Coronary Artery Calcification in PCCT: The EAT Signature!

(1) Background: Epicardial adipose tissue influences cardiac biology in physiological and pathological terms. As it is suspected to be linked to coronary artery calcification, identifying improved methods of diagnostics for these patients is important. The use of radiomics and the new Photon-Counting computed tomography (PCCT) may offer a feasible step toward improved diagnostics in these patients. (2) Methods: In this retrospective single-centre study epicardial adipose tissue was segmented manually on axial unenhanced images. Patients were divided into three groups, depending on the severity of coronary artery calcification. Features were extracted using pyradiomics. Mean and standard deviation were calculated with the Pearson correlation coefficient for feature correlation. Random Forest classification was applied for feature selection and ANOVA was performed for group comparison. (3) Results: A total of 53 patients (32 male, 21 female, mean age 57, range from 21 to 80 years) were enrolled in this study and scanned on the novel PCCT. "Original_glrlm_LongRunEmphasis", "original_glrlm_RunVariance", "original_glszm_HighGrayLevelZoneEmphasis", and "original_glszm_SizeZoneNonUniformity" were found to show significant differences between patients with coronary artery calcification (Agatston score 1-99/≥100) and those without. (4) Conclusions: Four texture features of epicardial adipose tissue are associated with coronary artery calcification and may reflect inflammatory reactions of epicardial adipose tissue, offering a potential imaging biomarker for atherosclerosis detection.

Epicardial and thoracic subcutaneous fat texture analysis in patients undergoing cardiac CT

Introduction

The aim of our study was to evaluate the feasibility of texture analysis of epicardial fat (EF) and thoracic subcutaneous fat (TSF) in patients undergoing cardiac CT (CCT).

Materials and methods

We compared a consecutive population of 30 patients with BMI ≤25 kg/m² (Group A, 60.6 ± 13.7 years) with a control population of 30 patients with BMI >25 kg/m² (Group B, 63.3 ± 11 years). A dedicated computer application for quantification of EF and a texture analysis application for the study of EF and TSF were employed.

Results

The volume of EF was higher in group B (mean 116.1 cm³ vs. 86.3 cm³, p = 0.014), despite no differences were found neither in terms of mean density (-69.5 ± 5 HU vs. -68 ± 5 HU, p = 0.28), nor in terms of quartiles distribution (Q1, p = 0.83; Q2, p = 0.22, Q3, p = 0.83, Q4, p = 0.34). The discriminating parameters of the histogram class were mean (p = 0.02), 0,1st (p = 0.001), 10_th (p = 0.002), and 50_th percentiles (p = 0.02). DifVarnc was the discriminating parameter of the co-occurrence matrix class (p = 0.007).The TSF thickness was 15 ± 6 mm in group A and 19.5 ± 5 mm in group B (p = 0.003). The TSF had a mean density of -97 ± 19 HU in group A and -95.8 ± 19 HU in group B (p = 0.75). The discriminating parameters of texture analysis were 10_th (p = 0.03), 50_th (p = 0.01), 90_th percentiles (p = 0.04), S(0,1)SumAverg (p = 0.02), S(1,-1)SumOfSqs (p = 0.02), S(3,0)Contrast (p = 0.03), S(3,0)SumAverg (p = 0.02), S(4,0)SumAverg (p = 0.04), Horzl_RLNonUni (p = 0.02), and Vertl_LngREmph (p = 0.0005).

Conclusions

Texture analysis provides distinctive radiomic parameters of EF and TSF. EF and TSF had different radiomic features as the BMI varies.

Epicardial adipose tissue density is a better predictor of cardiometabolic risk in HFpEF patients: a prospective cohort study

BACKGROUND

Epicardial adipose tissue (EAT) accumulation is associated with multiple cardiometabolic risk factors and prognosis of heart failure with preserved ejection fraction (HFpEF). The correlation between EAT density and cardiometabolic risk and the effect of EAT density on clinical outcome in HFpEF remain unclear. We evaluated the relationship between EAT density and cardiometabolic risk factors, also the prognostic value of EAT density in patients with HFpEF.

METHODS

We included 154 HFpEF patients who underwent noncontrast cardiac computed tomography (CT) and all patients received follow-up. EAT density and volume were quantified semi-automatically. The associations of EAT density and volume with cardiometabolic risk factors, metabolic syndrome and the prognostic impact of EAT density were analyzed.

RESULTS

Lower EAT density was associated with adverse changes in cardiometabolic risk factors. Each 1 HU increase in fat density, BMI was 0.14 kg/m² lower (95% CI 0.08-0.21), waist circumference was 0.34 cm lower (95% CI 0.12-0.55), non-HDL-cholesterol was 0.02 mmol/L lower (95% CI 0-0.04), triglyceride was 0.03 mmol/L lower (95% CI 0.01-0.04), fasting plasma glucose was 0.05 mmol/L lower (95% CI 0.02-0.08), TyG index was 0.03 lower (95% CI 0.02-0.04), Log₂(TG/HDL-C) was 0.03 lower (95% CI 0.02-0.05), METS-IR was 0.36 lower (95% CI 0.23-0.49), MetS Z-score was 0.04 lower (95% CI 0.02-0.06), and Log₂(CACS + 1) was 0.09 lower (95% CI 0.02-0.15). After adjusting for BMI and EAT volume, the associations of non-HDL-cholesterol, triglyceride, fasting plasma glucose, insulin resistance indexes, MetS Z-score, and CACS with fat density remained significant. The area under the curve (AUC) for the presence and severity of metabolic syndrome was greater in EAT density than volume (AUC: 0.731 vs 0.694, 0.735 vs 0.662, respectively). Over a median follow-up of 16 months, the cumulative incidence of heart failure readmission and composite endpoint increased with lower level of EAT density (both p < 0.05).

CONCLUSIONS

EAT density was an independent impact factor of cardiometabolic risk in HFpEF. EAT density might have better predictive value than EAT volume for metabolic syndrome and it might have prognostic value in patients with HFpEF.

Measurement of epicardial adipose tissue using non-contrast routine chest-CT: a consideration of threshold adjustment for fatty attenuation

Background

Epicardial adipose tissue (EAT) is known as an important imaging indicator for cardiovascular risk stratification. The present study aimed to determine whether the EAT volume (EV) and mean EAT attenuation (mEA) measured by non-contrast routine chest CT (RCCT) could be more consistent with those measured by coronary CT angiography (CCTA) by adjusting the threshold of fatty attenuation.

Methods

In total, 83 subjects who simultaneously underwent CCTA and RCCT were enrolled. EV and mEA were quantified by CCTA using a threshold of (N30) (− 190 HU, − 30 HU) as a reference and measured by RCCT using thresholds of N30, N40 (− 190 HU, − 40 HU), and N45 (− 190 HU, − 45 HU). The correlation and agreement of EAT metrics between the two imaging modalities and differences between patients with coronary plaques (plaque ( +)) and without plaques (plaque ( −)) were analyzed.

Results

EV obtained from RCCT showed very strong correlation with the reference (r = 0.974, 0.976, 0.972 (N30, N40, N45), P < 0.001), whereas mEA showed a moderate correlation (r = 0.516, 0.500, 0.477 (N30, N40, N45), P < 0.001). Threshold adjustment was able to reduce the bias of EV, while increase the bias of mEA. Data obtained by CCTA and RCCT both demonstrated a significantly larger EV in the plaque ( +) group than in the plaque ( −) group (P < 0.05). A significant difference in mEA was shown only by RCCT using a threshold of N30 (plaque ( +) vs ( −): − 80.0 ± 4.4 HU vs − 78.0 ± 4.0 HU, P = 0.030). The mEA measured on RCCT using threshold of N40 and N45 showed no significant statistical difference between the two groups (P = 0.092 and 0.075), which was consistent with the result obtained on CCTA (P = 0.204).

Conclusion

Applying more negative threshold, the consistency of EV measurements between the two techniques improves and a consistent result can be obtained when comparing EF measurements between groups, although the bias of mEA increases. Threshold adjustment is necessary when measuring EF with non-contrast RCCT.

The Relationship between Enhancing Left Atrial Adipose Tissue at CT and Recurrent Atrial Fibrillation

Background The association of epicardial adipose tissue (EAT) and its metabolic activity with atrial fibrillation (AF) is an area of active investigation. Left atrial (LA) enhancing EAT (e-EAT) at cardiac CT may be a noninvasive surrogate marker for the metabolic activity of EAT. Purpose To determine the relationship between LA e-EAT and recurrence after AF ablation. Materials and Methods In a secondary analysis of a prospective registry of consecutive patients (from July 2018 to December 2019) undergoing first AF ablation, total and LA EAT were segmented on preprocedural noncontrast- and contrast-enhanced cardiac CT scans. LA e-EAT volume fraction was defined as the LA EAT volume difference between the noncontrast- and contrast-enhanced scan divided by the total LA EAT volume on the noncontrast-enhanced scan (threshold values, -15 HU to -195 HU). Continuous variables were compared between groups by using the Mann-Whitney U test. Cox proportional hazard models were used to calculate hazard ratios of predictors of 1-year AF recurrence. Results A total of 212 patients (mean age, 64 years; 159 men) who underwent a first AF ablation were included (paroxysmal AF, 64%; persistent AF, 36%). The LA EAT volume was higher in patients with persistent versus paroxysmal AF (50 cm³ [IQR, 37-72] vs 37 [IQR, 27-49]; P < .001), but no difference was found for LA e-EAT (P = .09). After 1 year of follow-up, AF recurrence rate was 77 of 212 (36%). LA e-EAT above the mean (>33%) was associated with a higher risk of AF recurrence (hazard ratio [HR], 2.1; 95% CI: 1.3, 3.3; P < .01). In a multivariable Cox regression analysis, LA e-EAT retained its predictive value when corrected for sex, age, AF phenotype, LA volume index, and LA EAT volume (HR, 1.9; 95% CI: 1.1, 3.1; P = .02). Conclusion Left atrial enhancing epicardial adipose tissue was independently associated with recurrence after atrial fibrillation ablation. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Stojanovska in this issue.

Association of epicardial adipose tissue with different stages of coronary artery disease: A cross-sectional UK Biobank cardiovascular magnetic resonance imaging substudy

Objective

Increased epicardial adipose tissue (EAT) has been identified as a risk factor for the development of coronary artery disease (CAD). However, the exact role of EAT in the development of CAD is unclear. This study aims to compare EAT volumes between healthy controls and individuals with stable CAD and a history of myocardial infarction (MI). Furthermore, associations between clinical and biochemical parameters with EAT volumes are examined.

Methods

This retrospective cross-sectional study included 171 participants from the United Kingdom Biobank (56 healthy controls; 60 stable CAD; 55 post MI), whom were balanced for age, sex and body mass index (BMI). EAT volumes were quantified on end-diastolic cardiac magnetic resonance (CMR) imaging short-axis slices along the left and right ventricle and indexed for body surface area (iEAT) and iEAT volumes were compared between groups.

Results

iEAT volumes were comparable between control, CAD and MI cases (median [IQR]: 66.1[54.4-77.0] vs. 70.9[55.8-85.5] vs. 67.6[58.6-82.3] mL/m2, respectively (p > 0.005 for all). Increased HDL-cholesterol was associated with decreased iEAT volume (β = -14.8, CI = -24.6 to -4.97, p = 0.003) and suggestive associations (P-value < 0.05 and ≥ 0.005) were observed between iEAT and triglycerides (β = 3.26, CI = 0.42 to 6.09, p = 0.02), Apo-lipoprotein A (β = -16.3, CI = -30.3 to -2.24, p = 0.02) and LDL-cholesterol (β = 3.99, CI = -7.15 to -0.84, p = 0.01).

Conclusions

No significant differences in iEAT volumes were observed between patients with CAD, MI and healthy controls. Our results indicate the importance of correcting for confounding by CVD risk factors, including circulating lipid levels, when studying the relationship between EAT volume and CAD. Further mechanistic studies on causal pathways and the role of EAT composition are warranted.

Deep learning segmentation and quantification method for assessing epicardial adipose tissue in CT calcium score scans

Epicardial adipose tissue volume (EAT) has been linked to coronary artery disease and the risk of major adverse cardiac events. As manual quantification of EAT is time-consuming, requires specialized training, and is prone to human error, we developed a deep learning method (DeepFat) for the automatic assessment of EAT on non-contrast low-dose CT calcium score images. Our DeepFat intuitively segmented the tissue enclosed by the pericardial sac on axial slices, using two preprocessing steps. First, we applied a HU-attention-window with a window/level 350/40-HU to draw attention to the sac and reduce numerical errors. Second, we applied a novel look ahead slab-of-slices with bisection ("bisect") in which we split the heart into halves and sequenced the lower half from bottom-to-middle and the upper half from top-to-middle, thereby presenting an always increasing curvature of the sac to the network. EAT volume was obtained by thresholding voxels within the sac in the fat window (- 190/- 30-HU). Compared to manual segmentation, our algorithm gave excellent results with volume Dice = 88.52% ± 3.3, slice Dice = 87.70% ± 7.5, EAT error = 0.5% ± 8.1, and R = 98.52% (p < 0.001). HU-attention-window and bisect improved Dice volume scores by 0.49% and 3.2% absolute, respectively. Variability between analysts was comparable to variability with DeepFat. Results compared favorably to those of previous publications.

Influence of local aortic calcification on periaortic adipose tissue radiomics texture features-a primary analysis on PCCT

Perivascular adipose tissue is known to be metabolically active. Volume and density of periaortic adipose tissue are associated with aortic calcification as well as aortic diameter indicating a possible influence of periaortic adipose tissue on the development of aortic calcification. Due to better spatial resolution and signal-to-noise ratio, new CT technologies such as photon-counting computed tomography may allow the detection of texture alterations of periaortic adipose tissue depending on the existence of local aortic calcification possibly outlining a biomarker for the development of arteriosclerosis. In this retrospective, single-center, IRB-approved study, periaortic adipose tissue was segmented semiautomatically and radiomics features were extracted using pyradiomics. Statistical analysis was performed in R statistics calculating mean and standard deviation with Pearson correlation coefficient for feature correlation. For feature selection Random Forest classification was performed. A two-tailed unpaired t test was applied to the final feature set. Results were visualized as boxplots and heatmaps. A total of 30 patients (66.6% female, median age 57 years) were enrolled in this study. Patients were divided into two subgroups depending on the presence of local aortic calcification. By Random Forest feature selection a set of seven higher-order features could be defined to discriminate periaortic adipose tissue texture between these two groups. The t test showed a statistic significant discrimination for all features (p < 0.05). Texture changes of periaortic adipose tissue associated with the existence of local aortic calcification may lay the foundation for finding a biomarker for development of arteriosclerosis.

The relationship between quantitative epicardial adipose tissue based on CT and coronary artery disease: A protocol for systematic review and meta-analysis

BACKGROUND

Epicardial adipose tissue (EAT) is a kind of visceral adipose tissue with close proximity to coronary artery and myocardium, which can secrete cell factor, and influence the physiological function and pathophysiological process of myocardium and coronary artery. Clinical imaging diagnosis showed that the volume and thickness of EAT exists a certain relevance with coronary artery disease, but it lacked evidence of evidence-based medicine. The research on the implementation of this program will systematically evaluate the relationship of computed tomography (CT) quantitative EAT and coronary artery disease.

METHOD

The English databases (Embase, PubMed, the Cochrane Library, Web of Science) and Chinese database (CNKI, Wanfang, China biomedical database, VIP) of computer retrieval has collected the case control clinical study of relationship between EAT and coronary artery disease from the establishment of the database to October 2020, which was conducted extraction and quality evaluation by 2 researchers independently for data included in the study, and was conducted Meta-analysis for the included literature by adopting RevMan5.3 software.

RESULT

The research evaluated the correlation between EAT and coronary artery disease through the EAT thickness, EAT volume, and other indexes.

CONCLUSION

The research has provided reliable evidence-based evidence for the correlation between CT EAT quantification and coronary artery disease.

ETHICS AND DISSEMINATION

We will not publish private information from individuals. This kind of systematic review does not involve harming the rights of participants. No ethical approval was required. The results can be published in peer-reviewed journals or at relevant conferences.

OSF REGISTRATION NUMBER

DOI 10.17605/OSF.IO/DVQNE.