Epicardial Adipose Tissue Attenuation Research Articles

Quality of epicardial adipose tissue predicts major adverse cerebral and cardiovascular events following transcatheter aortic valve implantation.

Epicardial adipose tissue (EAT) have been shown to be associated with several heart disease, including coronary artery disease (CAD), atrial fibrillation (AF), and heart failure (HF). It is reported that the quality of EAT, represented by fat attenuation determined using computed tomography (CT) imaging, can detect the histologically-assessed remodeled EAT. We tested the hypothesis that quality of EAT would predict major adverse cerebral and cardiovascular events (MACCE) following transcatheter aortic valve implantation (TAVI) in patients with aortic stenosis (AS). A total of 125 consecutive severe AS patients who underwent TAVI were enrolled (39 male, mean 85.4 ± 4.0years). Using CT imaging before TAVI, we measured the average CT fat attenuation of EAT (EAT attenuation) and investigated the association with MACCE. During the mean follow up period of 567 ± 371days, 21 cases of MACCE were observed. Patients with MACCE had greater levels of EAT attenuation compared to those without (- 74 ± 3.7 Hounsfield Units (HU) vs - 77 ± 5.5 HU, p = 0.010). Based on the ROC curves, the high EAT attenuation was defined as > - 74.3 HU. According to this cut-off index, 44 patients were classified into the high EAT attenuation group (28 female, mean age 87 ± 3.6years), whereas 81 patients were classified into the low EAT attenuation group (13 female, 85 ± 4.1years). Kaplan-Meier survival curve demonstrated that the patients in the high EAT attenuation group showed greater prevalence of MACCE (log-rank 6.64, p = 0.010). Cox proportional hazards regression analysis revealed that EAT attenuation and Logistic EuroSCORE were independently associated with the incidence of MACCE. Our results suggest that quality of EAT, assessed by EAT attenuation detected by CT imaging, can predict the cerebral and cardiovascular events after TAVI in patients with AS.

Denosumab Decreases Epicardial Adipose Tissue Attenuation in Dialysis Patients with Secondary Hyperparathyroidism and Low Bone Mass

Introduction: Denosumab preceding elective surgery is an alternative option when parathyroidectomy is not immediately possible. Denosumab (an osteoprotegerin mimic) may play a role in the cardiovascular system, which is reflected in the features of epicardial adipose tissue (EAT) and coronary artery calcification (CAC). Methods: We investigated the effects of denosumab on EAT attenuation (EATat) and CAC in dialysis patients with secondary hyperparathyroidism (SHPT). This cohort study included patients on dialysis with SHPT. The baseline characteristics of dialysis patients and propensity score-matched non-dialysis patients were compared. Computed tomography scans of the dialysis patients (dialysis group with denosumab, n = 24; dialysis group without denosumab, n = 21) were obtained at baseline and at 6 months of follow-up. Results: At baseline, the dialysis group patients had a higher EATat-median (−71.00 H ± 10.38 vs. −81.60 H ± 6.03; p p p = 0.001) without changes in EATat-median (−71.33 H ± 11.72 to −70.86 H ± 12.67; p = 0.15). The dialysis group with denosumab showed no change in Agatston score (1,132.2 A [252.25–3,260.5] to 1,199.50 A [324.25–2,995]; p = 0.19) but a significant decrease of EATat-median (−70.71 H ± 9.30 to −74.33 H ± 10.28; p = 0.01). Conclusions: Denosumab may reverse EATat and retard CAC progression in dialysis patients with SHPT.

AI-derived epicardial fat measurements improve cardiovascular risk prediction from myocardial perfusion imaging

Epicardial adipose tissue (EAT) volume and attenuation are associated with cardiovascular risk, but manual annotation is time-consuming. We evaluated whether automated deep learning-based EAT measurements from ungated computed tomography (CT) are associated with death or myocardial infarction (MI). We included 8781 patients from 4 sites without known coronary artery disease who underwent hybrid myocardial perfusion imaging. Of those, 500 patients from one site were used for model training and validation, with the remaining patients held out for testing (n = 3511 internal testing, n = 4770 external testing). We modified an existing deep learning model to first identify the cardiac silhouette, then automatically segment EAT based on attenuation thresholds. Deep learning EAT measurements were obtained in <2 s compared to 15 min for expert annotations. There was excellent agreement between EAT attenuation (Spearman correlation 0.90 internal, 0.82 external) and volume (Spearman correlation 0.90 internal, 0.91 external) by deep learning and expert segmentation in all 3 sites (Spearman correlation 0.90–0.98). During median follow-up of 2.7 years (IQR 1.6–4.9), 565 patients experienced death or MI. Elevated EAT volume and attenuation were independently associated with an increased risk of death or MI after adjustment for relevant confounders. Deep learning can automatically measure EAT volume and attenuation from low-dose, ungated CT with excellent correlation with expert annotations, but in a fraction of the time. EAT measurements offer additional prognostic insights within the context of hybrid perfusion imaging.

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

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). 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. 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 1year 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). A larger LA EAT dispersion on contrast-enhanced cardiac CT scans, reflecting EAT heterogeneity, is independently associated with AF recurrence after PVI. 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. • 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.

Semaglutide therapy decreases epicardial fat inflammation and improves psoriasis severity in patients affected by abdominal obesity and type-2 diabetes.

Psoriasis is often associated with abdominal obesity and type-2 diabetes (T2D). The inflammatory process in psoriasis can target adipose tissue depots, especially those surrounding the heart and coronary arteries, exposing to an increased risk of cardiovascular diseases. A 50-year-old female patient referred to us for abdominal obesity and T2D, which were not controlled with lifestyle modifications. She had suffered from psoriasis for some years and was treated with guselkumab, without success. Epicardial adipose tissue (EAT) attenuation and pericoronary adipose tissue (PCAT) attenuation for each coronary, defined as mean attenuation expressed in Hounsfield unit (HU), were assessed by routine coronary computed tomography angiography. At baseline, EAT attenuation was -80 HU and PCAT attenuation of the right coronary artery (RCA) was -68 HU, values associated with an increased cardiac mortality risk. Psoriasis area and severity index (PASI) was 12.0, indicating severe psoriasis, while dermatology life quality index (DLQI) was 20, indicating a negative effect on the patient's life. Semaglutide (starting with 0.25 mg/week for 4 weeks, increased to 0.50 mg/week for 16 weeks, and then to 1 mg/week) was started. After 10 months, semaglutide treatment normalized glycated hemoglobin and induced weight loss, particularly at abdominal level, also followed by a reduction in computed tomography-measured EAT volume. EAT attenuation and PCAT attenuation of RCA decreased, showing an important reduction of 17.5 and 5.9% respectively, compared with baseline. PASI and DLQI decreased by 98.3 and 95% respectively, indicating an improvement in psoriasis skin lesions and an important amelioration of the patient's quality of life, compared with baseline. Psoriasis patients affected by obesity and type-2 diabetes (T2D) are often resistant to biologic therapies. Psoriasis is often associated with abdominal obesity, T2D, and cardiovascular diseases (CVD), given their shared inflammatory properties and pathogenic similarities. Epicardial adipose tissue (EAT) inflammation can cause the distinctive pattern of CVD seen in psoriasis. EAT and pericoronary adipose tissue (PCAT) attenuation, assessed by routine coronary computed tomography angiography (CCTA), can be used as biomarkers of inflammation and allow monitoring of medical anti-inflammatory therapies. The actions of semaglutide to reduce energy intake, improve glycemic control, and produce effective weight loss, particularly at the visceral fat depot level, can diminish adipose tissue dysfunction, reduce EAT attenuation and PCAT attenuation of the right coronary artery (RCA) and concomitantly ameliorate the clinical severity of psoriasis. Semaglutide therapy may be considered in psoriasis patients affected by T2D and abdominal obesity, despite low cardiovascular risk by traditional risk scores, who are resistant to biologic therapies.

Epicardial adipose tissue: a novel cardiovascular risk factor

Epicardial adipose tissue (EAT) has various metabolic functions aiming at heart protection. When abnormal, it is related to atherosclerotic plaque development and adverse cardiovascular outcome. Additionally, in recent years, several studies have demonstrated its role in other settings such as atrial fibrillation and heart failure with preserved ejection fraction. Future studies should aim to assess diagnostic role of EAT and the effect of medical therapy on EAT volume and attenuation.

PO-02-088 CHANGES IN EPICARDIAL ADIPOSE TISSUE AND LEFT ATRIAL WALL SUBSTRATE AFTER ABLATION FOR ATRIAL FIBRILLATION

Previous studies have shown that epicardial adipose tissue (EAT) contributes to the presence of atrial fibrillation (AF), possibly due to atrial fatty infiltration and/or the release of cytokines from the EAT. Conversely, it remains unclear whether sinus rhythm maintenance after catheter ablation (CA) provide favorable effects on EAT volume, EAT quality and left atrial (LA) fatty infiltration (EAT quality and LA fatty infiltration can be estimated from attenuation measured by CT) (figure). This study aimed to determine changes in EAT volume and quality, LA fatty infiltration, before and after CA. Total 20 patients (62± 10 years, 16 males, 4 persistent AF) who had undergone CA. The multidetector CT was performed within 1 week before and 1 year after ablation. The EAT volume was measured as defined by -50 to -200 Hounsfield units (HU). We also evaluated CT attenuation of EAT (around the whole heart and LA), and LA wall CT attenuation (in the LA roof and LA posterior). The CT attenuation of EAT was measured automatically on 3D workstation. The LA wall attenuation was measured at 3 sites per segment, the average of the 3 values was calculated for each site, and these average values were used for the analysis. All patients had no recurrence 1 year after CA. The EAT volume decreased significantly from the before ablation to after (whole EAT: 108±46 ml to 93±35 ml; P=0.022, LA-EAT: 30± 14 ml to 23±12 ml; P=0.002). There was no significant difference in the EAT attenuation between before and after ablation (whole EAT: -92±3 HU to -92±4 HU; P=0.94, LA-EAT: -90±5 HU to -90±4 HU; P=0.93). The LA wall attenuation did not change either (LA roof: 23±7 HU to 24±10 HU; P=0.35, LA posterior: 34±7 HU to 30±8 HU; P=0.35). EAT volume decreased after the maintenance of sinus rhythm, but CT attenuation of EAT and LA wall was unchanged over time, suggesting that EAT is a consequence of AF, but EAT quality and LA substrate persists despite sinus rhythm maintenance.

Relationship between epicardial adipose tissue attenuation and coronary artery disease in type 2 diabetes mellitus patients.

High epicardial adipose tissue (EAT) attenuation is a key characteristic of adipose tissue dysfunction and associated with coronary artery disease (CAD). As little is known about the modulation of EAT attenuation by metabolic disorders, we investigated the association between EAT attenuation and CAD risk factors, CAD presence and CAD severity in type 2 diabetes mellitus (T2DM) patients. We included 276 inpatients with T2DM and 305 control patients with normal glucose metabolism (NGM), who underwent cardiac computed tomography angiography (CCTA) and coronary artery calcium (CAC) scoring. EAT attenuation and volume were evaluated by contrast-enhanced CCTA image analysis. Furthermore, segment stenosis scores (SSSs) of the left main coronary artery (LMCA), left anterior descending artery (LAD), left circumflex artery (LCX), right coronary artery (RCA), diagonal/intermediate branch (D/I) and obtuse marginal branch (OM) were calculated to assess CAD severity. T2DM patients showed higher significant CAC scores, coronary plaque prevalence, total SSSs and LMCA-SSSs, LAD-SSSs, LCX-SSSs, RCA-SSSs and D/I-SSSs compared with NGM controls. In contrast to NGM controls, EAT volume was significantly increased in T2DM patients, whereas EAT attenuation was similar. In T2DM patients, EAT attenuation was associated with discrete CAD risk factors, the presence of coronary and triple-vessel plaques, as well as LAD-SSSs, LCX-SSSs, RCA-SSSs and total SSSs. In addition, EAT attenuation was only associated with the total SSS of calcified plaques, but not with noncalcified plaques. In T2DM patients, high EAT attenuation is associated with the presence and severity of CAD in general and with coronary stenosis caused by calcified plaques in particular.

El tejido adiposo epicárdico no es un predictor independiente de recurrencia de fibrilación auricular tras ablación con catéter

Introduction and objectivesPrevious studies have suggested that epicardial adipose tissue (EAT) could exert a paracrine effect in the myocardium. However, few studies have assessed its role in the risk of atrial fibrillation (AF) recurrence. This study aimed to evaluate the association between EAT volume, and its attenuation, with the risk of AF recurrence after AF ablation. MethodsA total of 350 consecutive patients who underwent AF ablation were included. The median age was 57 [IQR 48-65] years and 21% had persistent AF. Epicardial fat was quantified by multidetector computed tomography using Syngo.via Frontier-Cardiac Risk Assessment software, measuring pericardial fat volume (PATV), EAT volume, and attenuation of EAT posterior to the left atrium. AF recurrence was defined as any documented episode of AF, atrial flutter, or atrial tachycardia more than 3 months after the procedure. ResultsAfter a median follow-up of 34 [range, 12-57] months, 114 patients (33%) had AF recurrence. Univariable Cox regression showed that patients with an EAT volume ≥ 80mL had an increased risk of AF recurrence (HR, 1.65; 95%CI, 1.14-2.39; P=.007). However, after multivariable adjustment, EAT volume did not remain an independent predictor of AF recurrence (HR, 1.24; 95%CI, 0.83-1.87; P=.3). Similar results were observed with PATV. Patients with lower attenuation of EAT did not have a higher risk of AF recurrence (log-rank test, P=.75). ConclusionsEAT parameters including the evaluation of EAT volume, PATV and EAT attenuation were not independent predictors of AF recurrence after catheter ablation.

Is There a Relationship Between Epicardial Adipose Tissue, Inflammatory Markers, and the Severity of COVID-19 Pneumonia?

Epicardial adipose tissue (EAT) is a type of visceral adipose tissue with pro-inflammatory properties. We sought to examine the relationship between the EAT volume and attenuation measured on non-contrast chest computed tomography (CT), inflammation markers, and the severity of COVID-19 pneumonia. One hundred and twenty-five patients who are over 18 years old who applied to our hospital and were found to have COVID-19 polymerase chain reaction (+) on nasopharyngeal swab sample and COVID-19 pneumonia on chest CT were included in the study. At admission, C-reactive protein (CRP), procalcitonin, fibrinogen, leukocytes, neutrophil-lymphocyte ratio, platelet-lymphocyte ratio, lactate dehydrogenase (LDH), ferritin, and d-dimer were evaluated. EAT volume and attenuation were measured on chest CT. Patients who were hospitalized and discharged from the ward were categorized as Group 1, whereas patients who required intensive care admission and/or died were classified as Group 2. The primary endpoint of our study was defined as death, hospitalization in the intensive care unit, and discharge. The relationship between disease severity and EAT and other inflammatory markers was investigated. One hundred and six individuals were in Group 1 and 19 patients were in Group 2. Of the 125 individuals, 46 were women and 79 were men. The mean age was 58.5±15.9 years. Group 2 patients were older. Regarding measurements of the EAT volume and attenuation; there was no statistically significant difference between the groups determined. The patients in Group 2 had statistically substantially higher values for urea, creatinine, LDH, d-dimer, troponin T, procalcitonin, CRP, and neutrophil/lymphocyte ratio in their laboratory tests. When compared to patients in Group 1, patients in Group 2 had statistically significantly lower albumin values (p<0.001). In obese patients, EAT volume was statistically significantly higher and EAT attenuation was found to be lower. In our study, no relationship was found between critical COVID-19 disease and EAT volume and attenuation, which is an indicator of EAT inflammation. Inflammatory markers from routine laboratory tests can be used to predict critical COVID-19 disease. No relationship was found between obesity and critical COVID-19 disease.

Quantification of Epicardial Adipose Tissue Volume and Attenuation for Cardiac CT Scans Using Deep Learning in a Single Multi-Task Framework

Background: Recent studies have shown that epicardial adipose tissue (EAT) is an independent atrial fibrillation (AF) prognostic marker and has influence on the myocardial function. In computed tomography (CT), EAT volume (EATv) and density (EATd) are parameters that are often used to quantify EAT. While increased EATv has been found to correlate with the prevalence and the recurrence of AF after ablation therapy, higher EATd correlates with inflammation due to arrest of lipid maturation and with high risk of plaque presence and plaque progression. Automation of the quantification task diminishes the variability in readings introduced by different observers in manual quantification and results in high reproducibility of studies and less time-consuming analysis. Our objective is to develop a fully automated quantification of EATv and EATd using a deep learning (DL) framework. Methods: We proposed a framework that consists of image classification and segmentation DL models and performs the task of selecting images with EAT from all the CT images acquired for a patient, and the task of segmenting the EAT from the output images of the preceding task. EATv and EATd are estimated using the segmentation masks to define the region of interest. For our experiments, a 300-patient dataset was divided into two subsets, each consisting of 150 patients: Dataset 1 (41,979 CT slices) for training the DL models, and Dataset 2 (36,428 CT slices) for evaluating the quantification of EATv and EATd. Results: The classification model achieved accuracies of 98% for precision, recall and F1 scores, and the segmentation model achieved accuracies in terms of mean (± std.) and median dice similarity coefficient scores of 0.844 (± 0.19) and 0.84, respectively. Using the evaluation set (Dataset 2), our approach resulted in a Pearson correlation coefficient of 0.971 (R2 = 0.943) between the label and predicted EATv, and the correlation coefficient of 0.972 (R2 = 0.945) between the label and predicted EATd. Conclusions: We proposed a framework that provides a fast and robust strategy for accurate EAT segmentation, and volume (EATv) and attenuation (EATd) quantification tasks. The framework will be useful to clinicians and other practitioners for carrying out reproducible EAT quantification at patient level or for large cohorts and high-throughput projects.

Assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary CTA datasets

ObjectivesTo assess epicardial adipose tissue (EAT) volume and attenuation of different virtual non-contrast (VNC) reconstructions derived from coronary CTA (CCTA) datasets of a photon-counting detector (PCD) CT-system to replace true non-contrast (TNC) series.MethodsConsecutive patients (n = 42) with clinically indicated CCTA and coronary TNC were included. Two VNC series were reconstructed, using a conventional (VNCConv) and a novel calcium-preserving (VNCPC) algorithm. EAT was segmented on TNC, VNCConv, VNCPC, and CCTA (CTA-30) series using thresholds of −190 to −30 HU and an additional segmentation on the CCTA series with an upper threshold of 0 HU (CTA0). EAT volumes and their histograms were assessed for each series. Linear regression was used to correlate EAT volumes and the Euclidian distance for histograms. The paired t-test and the Wilcoxon signed-rank test were used to assess differences for parametric and non-parametric data.ResultsEAT volumes from VNC and CCTA series showed significant differences compared to TNC (all p < .05), but excellent correlation (all R2 > 0.9). Measurements on the novel VNCPC series showed the best correlation (R2 = 0.99) and only minor absolute differences compared to TNC values. Mean volume differences were −12%, −3%, −13%, and +10% for VNCConv, VNCPC, CTA-30, and CTA0 compared to TNC. Distribution of CT values on VNCPC showed less difference to TNC than on VNCConv (mean attenuation difference +7% vs. +2%; Euclidean distance of histograms 0.029 vs. 0.016).ConclusionsVNCPC-reconstructions of PCD-CCTA datasets can be used to reliably assess EAT volume with a high accuracy and only minor differences in CT values compared to TNC. Substitution of TNC would significantly decrease patient’s radiation dose.Key points• Measurement of epicardial adipose tissue (EAT) volume and attenuation are feasible on virtual non-contrast (VNC) series with excellent correlation to true non-contrast series (all R2>0.9).• Differences in VNC algorithms have a significant impact on EAT volume and CT attenuation values.• A novel VNC algorithm (VNCPC) enables reliable assessment of EAT volume and attenuation with superior accuracy compared to measurements on conventional VNC- and CCTA-series.

Epicardial adipose tissue volume is not an independent predictor of atrial fibrillation recurrence after catheter ablation

Introduction and objectivesPrevious studies have suggested that epicardial adipose tissue (EAT) could exert a paracrine effect in the myocardium. However, few studies have assessed its role in the risk of atrial fibrillation (AF) recurrence. This study aimed to evaluate the association between EAT volume, and its attenuation, with the risk of AF recurrence after AF ablation. MethodsA total of 350 consecutive patients who underwent AF ablation were included. The median age was 57 [IQR 48-65] years and 21% had persistent AF. Epicardial fat was quantified by multidetector computed tomography using Syngo.via Frontier-Cardiac Risk Assessment software, measuring pericardial fat volume (PATV), EAT volume, and attenuation of EAT posterior to the left atrium. AF recurrence was defined as any documented episode of AF, atrial flutter, or atrial tachycardia more than 3 months after the procedure. ResultsAfter a median follow-up of 34 [range, 12-57] months, 114 patients (33%) had AF recurrence. Univariable Cox regression showed that patients with an EAT volume ≥ 80mL had an increased risk of AF recurrence (HR, 1.65; 95%CI, 1.14-2.39; P=.007). However, after multivariable adjustment, EAT volume did not remain an independent predictor of AF recurrence (HR, 1.24; 95%CI, 0.83-1.87; P=.3). Similar results were observed with PATV. Patients with lower attenuation of EAT did not have a higher risk of AF recurrence (log-rank test, P=.75). ConclusionsEAT parameters including the evaluation of EAT volume, PATV and EAT attenuation were not independent predictors of AF recurrence after catheter ablation.

Incremental value of the combined brain-cardiac CT protocol on prediction of atrial fibrillation after stroke.

Atrial fibrillation (AF) is one of the most common causes of ischemic stroke. It is essential to target patients at highest risk of AF detected after stroke (AFDAS), who should benefit from a prolonged rhythm screening strategy. Cardiac-CT angiography (CCTA) was added to the stroke protocol used in our institution in 2018. We sought to assess, for AFDAS, the predictive value of atrial cardiopathy markers by a CCTA performed on admission for acute ischemic stroke. From November 2018 to October 2019, consecutive stroke patients with no history of AF were included. Let atrial volume (LAV), epicardial adipose tissue (EAT) attenuation and volume, and LAA characteristics were measured on CCTA. The primary endpoint was the presence of AFDAS at follow-up, diagnosed by continuous electrocardiographic monitoring, long-term external Holter monitoring during hospital stay, or implantable cardiac monitor (ICM). Sixty of the 247 included patients developed AFDAS. Multivariable analysis shows independent predictors of AFDAS: age >80 years (HR 2.46; 95%CI (1.23-4.92), p = 0.011), indexed LAV >45 mL/m2 (HR 2.58; 95%CI (1.19-5.62), p = 0.017), EAT attenuation > -85HU (HR 2.16; 95%CI (1.13-4.15), p = 0.021) and LAA thrombus (HR 2.50; 95%CI (1.06-5.93), p = 0.037). Added consecutively to AFDAS prediction AS5F score (combining age and NIHSS >5), these markers had an incrementally better predictive value compared with the global Chi2 of the initial model (p = 0.001, 0.035, and 0.015 respectively). Adding CCTA to the acute stroke protocol to assess markers of atrial cardiopathy associated with AFDAS may help to better stratify the AF screening strategy, including the use of an ICM.

Abstract 13612: Using Pre-Operative Cardiac Computed Tomography and Echocardiography to Predict New-Onset Atrial Fibrillation Following TAVR

Introduction: New-onset atrial fibrillation (NOAF) following transcatheter aortic valve replacement (TAVR) has been associated with higher morbidity and mortality. Numerous studies have focused on clinical variables for NOAF prediction. In this study, we examine pre-operative cardiac computed tomography (cCT) and echocardiographic measurements for NOAF prediction following TAVR. Methods: This retrospective study includes 939 patients without pre-existing atrial fibrillation who underwent transfemoral TAVR between 2015 and 2020. Clinical data and standard pre-operative echocardiographic and cCT measurements were recorded. A machine learning method was used to derive left atrial volume and measures of epicardial adipose tissue from cCT. NOAF by 30-days was determined based on continuous electrocardiographic monitoring prior to hospital discharge and routine ECG at 2 and 4 weeks following TAVR. In a two-step analysis, random survival forest (RSF) was used to select variables of highest importance to NOAF prediction without assuming statistical models, followed by logistic regression analysis of the selected variables. Results: Among 939 patients, 47 (5%) experienced NOAF. Patients with NOAF had larger left atrial volume index (68.11 vs 56.96 cm 3 /kg/m 2 ; p&lt;0.001) but similar epicardial adipose tissue volume (71.78 vs 70.98 cm 3 ; p&gt;0.1) and epicardial adipose tissue attenuation (-81.16 vs -82.77 Hounsfield Units; p&gt;0.1). Among 28 covariates selected by RSF for variable importance, 4 covariates were predictive of NOAF in the multivariable logistic regression, including sinotubular junction short axis &gt;34mm [OR 5.687 (2.271-14.241); p=0.0002], maximum aortic valve pressure gradient [OR 1.037 (1.004-1.072); p=0.0266], mean aortic valve pressure gradient [OR 0.939 (0.894-0.986); p=0.0115], and body mass index &lt; 22kg/m 2 [OR 0.331 (0.150-0.729); p=0.006]. Model concordance was 0.75. Conclusions: Pre-operative cardiac computed tomography and echocardiographic measurements including sinotubular junction enlargement and aortic valve pressure gradient predict new-onset atrial fibrillation following TAVR.

Abstract 11812: Effects of Statins on Epicardial Adipose Tissue in Coronary Artery Disease

Introduction: Coronary artery disease (CAD) is linked to many modifiable cardiovascular risk factors (CVRF) like smoking, diabetes, hypertension, hyperlipidaemia and obesity. High Epicardial Adipose Tissue (EAT) Hounsfield Unit (HU) attenuation using Non-contrast Computed Tomography (NCCT) is associated with more inflammation. Statin is believed to stabilise coronary plaque and reduce inflammation. However, its effects on EAT volume (EATv) and EAT HU is unknown. In this study, we quantified EAT and compared total EATv, mean EAT HU and percentage of EATv within -60 to -30 HU and -70 to -30 HU between group with statin treatment (S) and group with no statin (NS) treatment in an Asian cohort. Methods: 343 patients presenting with stable chest pain and no previous known CAD were recruited. Pericardium was segmented from NCCT. EAT volume (in cm3) and mean attenuation (in HU) were quantified with -190 to -30 HU threshold within pericardium. In subanalysis, percentage of EAT volume in the HU limits of -60 to -30 and of -70 to -30 were calculated. EAT parameters were compared between S group and NS group, adjusting for hypertension, hyperlipidemia, diabetes and smoking history. Results: The cohort comprised 343 patients (M:F 65%:35%; mean age 59±10 years old), with prevalence of hypertension (54%), hyperlipidemia (74%) and diabetes (21%), and smoking (14%). Median coronary artery calcium score was 96.0 (21.0-324.0). Mean EAT HU was significantly lower in S than NS group (p=0.024). Percentage of total EAT within the -60 to -30 HU range was also significantly lower among S than NS (p = 0.026). This was also observed using -70 to -30 HU range (p = 0.025). EATv was not significantly different between S and NS groups (p = 0.159). Conclusions: Patients on statin treatment showed lower EAT attenuation, with lower EAT HU and percentage of EAT volume within the HU ranges of -60 to -30 and -70 to -30. This suggests that statin use is associated with reduced EAT inflammation independent of EAT volume.

The role of epicardial and pericoronary adipose tissue in cardiometabolic disease

Epicardial adipose tissue (EAT) is a metabolically active fat depot which modulates coronary arterial function. The measurement of EAT volume and attenuation from non-contrast cardiac computed tomography (CT) provides valuable information on cardiometabolic risk. Pericoronary adipose tissue (PCAT), a subset of EAT which directly surrounds the coronary vessels, may function as a sensor of coronary inflammation. PCAT attenuation on coronary CT angiography associates with coronary plaque morphology, stages of coronary artery disease, and risk of future cardiac events. Quantification of EAT and PCAT has incremental and complementary prognostic value over and above current risk assessment tools. This review covers the biological role of EAT in healthy and dysfunctional states, and CT-based assessment of EAT and PCAT towards the development of clinically meaningful imaging biomarkers.

Radiomic phenotype of epicardial adipose tissue in the prognosis of atrial fibrillation recurrence after catheter ablation in patients with lone atrial fibrillation.

BackgroundEpicardial adipose tissue (EAT) has been considered as one of the probable triggers of atrial fibrillation (AF). CT‐rediomics is a perspective noninvasive method of assessment of EAT. We evaluate the radiomic phenotype of EAT in patients with lone AF in the prognosis of AF recurrence after catheter ablation.MethodsA total of 43 patients with lone AF referred for CA and 20 out‐hospital patients without arrhythmia underwent multidetector computed tomography coronary angiography. Segmentation of EAT and extraction radiomic features were performed on calcium scoring series using by 3D‐Slicer. Clinical follow‐up was performed for 12 months period after the CA.ResultsEAT in patients with lone AF had a distinct radiomic phenotype. Thus, 45 of 93 calculated radiomic features, volume and attenuation of EAT were significantly different between patients with lone AF and persons without any arrhythmia. In addition, 17 radiomic features were significantly different in subgroups with and without AF recurrence. Multivariate regression analysis demonstrated that only gray level nonuniformity normalized (GLSZM) was an independent predictor of AF recurrence (OR 1.0027, 95%CI 1.0009–1.0044, p = 0.002). ROC analysis data showed that GLSZM >1227.4 indicates high probability of AF recurrence during 12 months (sensitivity 89.4%, specificity 70.8%, AUC: 0.809; p = 0.001).ConclusionThe radiomic parameter GLSZM is associated with late AF recurrence after CA in patients with lone AF. In current study GLSZM was a stronger predictor of lone AF recurrence in multivariate analysis comparing with other established risk factors and EAT volume and attenuation.

Epicardial Adipose Tissue Attenuation and Fat Attenuation Index: Phantom Study and In Vivo Measurements With Photon-Counting Detector CT.

BACKGROUND. Epicardial adipose tissue (EAT) attenuation is a vascular inflammation marker predictive of adverse cardiac events. The fat attenuation index (FAI) assesses fat attenuation for predefined coronary segments. Photon-counting detector (PCD) CT uses routine virtual monoenergetic image (VMI) reconstructions. VMI energy level may affect EAT attenuation and FAI measurements. OBJECTIVE. The purpose of this article was to assess EAT attenuation and FAI measurements at different monoenergetic energy levels in patients undergoing coronary CTA using a first-generation whole-body dual-source PCD CT scanner. METHODS. An anthropomorphic phantom at two sizes with a fat insert was imaged on a first-generation dual-source PCD CT scanner and, as a reference, on a conventional energy-integrating detector (EID) CT scanner at 120 kV. Thirty patients (11 women, 19 men; mean age, 48 ± 10 years; Agatston score < 60) who underwent an ECG-gated unenhanced calcium-scoring scan and contrast-enhanced coronary CTA by PCD CT were retrospectively evaluated. VMIs from 55 to 80 keV at 5-keV increments were reconstructed. EAT attenuation was manually measured on unenhanced and contrast-enhanced images. FAI was calculated using semiautomated software. RESULTS. The attenuation of the phantom fat insert was -69 HU for the reference EID CT; the closest attenuation for PCD CT was observed at 70 keV for the small (-69 HU) and large (-70 HU) phantoms. In patients, EAT attenuation increased for unenhanced acquisition from -111 ± 11 HU at 55 keV to -82 ± 9 HU at 80 keV and for contrast-enhanced acquisition from -104 ± 11 HU at 55 keV to -81 ± 9 HU at 80 keV. The mean attenuation difference between unenhanced and contrast-enhanced scans decreased with increasing energy level (from 7 ± 12 HU to 1 ± 10 HU). The FAI increased from -89 ± 8 HU at 55 keV to -77 ± 12 HU at 80 keV for the right coronary artery, -95 ± 11 HU at 55 keV to -85 ± 11 HU at 80 keV for the left anterior descending artery, and -87 ± 10 HU at 55 keV to -80 ± 12 HU at 80 keV for the circumflex artery. CONCLUSION. EAT attenuation and FAI measurements using PCD CT are impacted by VMI energy level and contrast enhancement. Use of VMI reconstruction at 70 keV provides fat attenuation approximating conventional polychromatic measurements. CLINICAL IMPACT. The findings may help standardize evaluation of pericoronary inflammation by PCD CT as a measure of patients' cardiac risk.

Artificial intelligence based automatic quantification of epicardial adipose tissue suitable for large scale population studies

To develop a fully automatic model capable of reliably quantifying epicardial adipose tissue (EAT) volumes and attenuation in large scale population studies to investigate their relation to markers of cardiometabolic risk. Non-contrast cardiac CT images from the SCAPIS study were used to train and test a convolutional neural network based model to quantify EAT by: segmenting the pericardium, suppressing noise-induced artifacts in the heart chambers, and, if image sets were incomplete, imputing missing EAT volumes. The model achieved a mean Dice coefficient of 0.90 when tested against expert manual segmentations on 25 image sets. Tested on 1400 image sets, the model successfully segmented 99.4% of the cases. Automatic imputation of missing EAT volumes had an error of less than 3.1% with up to 20% of the slices in image sets missing. The most important predictors of EAT volumes were weight and waist, while EAT attenuation was predicted mainly by EAT volume. A model with excellent performance, capable of fully automatic handling of the most common challenges in large scale EAT quantification has been developed. In studies of the importance of EAT in disease development, the strong co-variation with anthropometric measures needs to be carefully considered.