|Year : 2020 | Volume
| Issue : 1 | Page : 303-308
Epicardial fat measured by multidetector computed tomography and coronary artery disease
Neveen I Samy1, Walaa F Abdalzez1, Mohammad F Alnaggar2
1 Department of Cardiology, Faculty of Medicine, Menoufia University, Menoufia, Egypt
2 Department of Specialist in Cardiology, Nasser Institute, Cairo, Egypt
|Date of Submission||26-Aug-2018|
|Date of Decision||01-Nov-2018|
|Date of Acceptance||04-Nov-2018|
|Date of Web Publication||25-Mar-2020|
Mohammad F Alnaggar
Source of Support: None, Conflict of Interest: None
To assess the relationship between epicardial fat (EF) as well as pericoronary fat measured by multidetector computed tomography (CT) and coronary calcium score, and coronary artery disease (CAD).
EF is associated with increased risk of cardiovascular events. CT is an accurate and highly reproducible method to measure EF and can be used as a noninvasive tool to assess the cardiovascular risk.
Patients and methods
The current study included 70 patients with suspected CAD (low-intermediate probability). All patients were subjected to 256-row multidetector CT coronary angiography scans and were divided into three groups: group 1: no atherosclerosis (20 patients), group 2: nonobstructive atherosclerosis (luminal narrowing <50% in diameter) (25 patients), and group 3: obstructive atherosclerosis (luminal narrowing ≥50%) (25 patients). EF thickness and the mean thickness of the pericoronary fat surrounding the three coronary arteries were measured by CT.
Calcium score, the average EF thickness, and the average pericoronary fat thickness (PCFT) were significantly higher in group 3 compared with other groups (P < 0.001, 0.013, and <0.001, respectively). Receiver operating characteristic curve was used to define the best cutoff value of the thickness of both epicardial and pericoronary fat in predicting obstructive CAD (group 3), and it was more than or equal to 7.2 and 12.6 mm for epicardial and pericoronary fat, respectively.
There was a positive correlation between both epicardial and PCFT and the severity of coronary stenosis. Epicardial and PCFT can be used in predicting the severity of CAD.
Keywords: cardiovascular events, coronary artery disease, computed tomography coronary angiography, epicardial fat thickness, pericoronary fat thickness
|How to cite this article:|
Samy NI, Abdalzez WF, Alnaggar MF. Epicardial fat measured by multidetector computed tomography and coronary artery disease. Menoufia Med J 2020;33:303-8
|How to cite this URL:|
Samy NI, Abdalzez WF, Alnaggar MF. Epicardial fat measured by multidetector computed tomography and coronary artery disease. Menoufia Med J [serial online] 2020 [cited 2020 Mar 30];33:303-8. Available from: http://www.mmj.eg.net/text.asp?2020/33/1/303/281285
| Introduction|| |
Epicardial fat (EF) is the visceral fat of the heart deposited under the visceral layer of the pericardium and has the same origin as abdominal visceral fat, which is shown to be strongly related to the development of coronary artery disease (CAD). The EF is a main source of free fatty acids and some inflammatory cytokines,,.
Multislice computed tomography (CT) provides an accurate and reproducible quantification of epicardial adipose tissues (EAT) owing to its high temporal and spatial resolution.
Previous studies have shown a strong correlation between pericardial fat and coronary artery calcium (Ca) score as well as cardiac events,,,. Therefore, measurement of EF thickness by CT can be used as a predictor of cardiovascular risk.
| Patients and Methods|| |
The current study included 70 patients with suspected CAD (low-intermediate probability), which was defined according to Diamond and Forrester pretest probability of CAD by age, sex, and symptoms, as shown in [Table 1]. The study was performed between February 2017 and September 2017 in Dabbous Cardiac Center, Aladan Hospital, Kuwait. After approval of the ethical committee of the hospital and a written consent was taken from every patient. CT coronary angiography scans were performed using 256-row multidetectors (Revolution CT; GE Healthcare, Milwaukee, Wisconsin, USA). The patients were divided into three groups according to the CT scan findings: group 1: no atherosclerosis (20 patients), group 2: nonobstructive atherosclerosis (luminal narrowing < 50% in diameter) (25 patients), and group 3: obstructive atherosclerosis (luminal narrowing ≥50%) (25 patients). The following patients were excluded: patients with renal insufficiency (serum creatinine >1.5 mg/dl), previous history of percutaneous coronary intervention (PCI), or previous coronary artery bypass grafting (CABG). All patients were subjected to detailed history taking, full clinical examination, 12-lead ECG, and routine blood investigations. Hypertension was defined according to the American Heart Association (AHA) as systolic blood pressure more than 140 mmHg and/or diastolic blood pressure more than 90 mmHg. Diabetes mellitus was defined according to the AHA as fasting plasma glucose level of more than or equal to 126 mg/dl or treatment with either insulin or a hypoglycemic agent. BMI was defined as weight (kg) divided by the square of height (m), where normal BMI, 18.5–24.9 kg/m2, and overweight, if more than or equal to 25 kg/m2. Dyslipidemia is considered in patients with a history of taking lipid-lowering agents, total cholesterol more than or equal to 200 mg/dl, or low-density lipoprotein more than or equal to 130 mg/dl. Regarding smoking, we considered patients who regularly smoke cigarettes or who had stopped smoking within the past 1 month as smokers. Full measurements of EF thickness were performed in the most motionless phase of the cardiac cycle, which was most frequently the mid-diastolic phase, with retrospective cardiac gating at 70–80% of the R-R interval. Measurements were performed at the basal level of the ventricles on short-axis views. Three measurements of EF thickness were made, namely, inferior, center, and superior, corresponding to measurements at the 25, 50%, and 75% level of the RV wall, respectively, from the visceral epicardium to the outside of the myocardium and perpendicular to the surface of the heart. The mean of the three measurements (referred to as 'EAT') was used for the analyses. Pericoronary fat thickness (PCFT) (mm) was quantified on axial views. To avoid overestimating the pericoronary fat owing to obliquity, thickness measurements were performed on images in which the axial sections were perpendicular to the surface of the heart. In each of the regions of the right coronary artery, left coronary artery, and left circumflex, the maximum fat thickness, assessed as the largest distance from the myocardium to the visceral epicardium, was measured. The mean thickness of the pericoronary fat surrounding the three coronary arteries was used to measure the PCFT. Coronary angiography was performed to patients in group 3 [≥50%stenosis by multidetector computed tomography (MDCT)] in the catheterization laboratory under local anesthesia by an expert cardiologist. Significant coronary stenosis was defined according to the American College of Cardiology/AHA as more than or equal to 50% narrowing of the lumen diameter in at least one major coronary artery. Both syntax score and Gensini score were calculated.
|Table 1: Diamond and Forrester pretest probability of coronary artery disease by age, sex, and symptoms|
Click here to view
Data were analyzed using IBM SPSS 23.0 for Windows (SPSS Inc., Chicago, Illinois, USA) and NCSS 11 for Windows (NCSS LCC, Kaysville, Utah, USA).
| Results|| |
Of the 70 patients, 45 (64.3%) were males and 25 (35.7%) were females. The mean age of the patients was 50.6 ± 9.3 years, with a significant difference between group 1 and both groups 2 and 3. A total of 32 (45.7%) patients have hypertension, with higher incidence of hypertension in groups 2 and 3 compared with group 1, but without statistical significance. A total of 19 (27.1%) patients have diabetes mellitus, with higher incidence (statistically significant) in groups 2 (40%) and 3 (32%) compared with group 1 (5%). There was no significant difference in the incidence of dyslipidemia, obesity, smoking, and family history of premature CAD among the three groups [Table 2].
|Table 2: Comparison between the studied groups regarding the demographic data|
Click here to view
Ca score was significantly higher in group 3 (320 ± 454.5) compared with group 2 (69.4 ± 132.8) and group 1 (0). The average epicardial adipose tissues thickness (EAT) was significantly larger in group 3 (8.5 ± 3.1 mm) compared with group 2 (7.2 ± 1.4 mm) and group 1 (6.2 ± 1.2). The average PCFT was significantly larger in group 3 (14 ± 2.4 mm) compared with group 2 (12.6 ± 2.0 mm) and group 1 (10.8 ± 1.7 mm) [Table 3].
|Table 3: Epicardial fat thickness, pericoronary fat thickness, and calcium score in different groups|
Click here to view
Receiver operating characteristic curve was used to define the best cutoff value of EAT and PCFT in predicting obstructive CAD (group 3), and it was more than or equal to 7.2 and 12.6 mm for EAT and PCFT, respectively, with sensitivity of 67 and 72%, respectively; specificity of 67.4 and 62.2%, respectively; positive predictive value of 50 and 51.4%, respectively; negative predictive value of 76.3 and 80%, respectively; and diagnostic accuracy of 64.3 and 65.7%, respectively [Table 4].
|Table 4: Epicardial adipose tissue thickness (mm) and pericoronary fat thickness (mm) as predictors for obstructive coronary artery disease; receiver operating characteristic curve analysis|
Click here to view
EAT and PCFT showed a statistically significance positive correlation with each other (P < 0.001). EAT and Ca score showed a statistically significance positive correlation with each other (P = 0.004). PCFT and Ca score showed a statistically significance positive correlation with each other (P < 0.001) [Table 5].
|Table 5: Correlation between age, calcium score, epicardial adipose tissue, and pericoronary fat thickness (Spearman's correlation)|
Click here to view
There was a negative correlation between the Gensini score and both epicardial fat thickness (EFT) and PCFT in group 3. There was a positive correlation between the EFT and PCFT in group 3.
There was a positive correlation between the PCFT and age in group 3 [Table 6].
|Table 6: Correlation between Gensini score, age, calcium score, epicardial adipose tissue, and pericoronary fat thickness within the obstructive group (Spearman's correlation)|
Click here to view
| Discussion|| |
We found a significant relation between the thickness of both EF and pericoronary fat as well as the Ca score and the severity of CAD, with higher values in group 3 with obstructive CAD compared with groups 1 and 2. Several studies showed results consistent with our findings. Some of these studies used also EF thickness. Demircelik et al. evaluated the relationship between epicardial adipose tissue and PCFT measured with 64-MDCT. They concluded that epicardial adipose tissue and PCFT scores were higher in patients with obstructive CADs. Other studies used pericardial fat volume.
Matsumoto et al.studied 197 patients with suspected CAD who underwent 64-MDCT and coronary angiography. Cross-sectional tomographic cardiac slices (3.0 mm thick) from base to apex (30–40 slices per heart) were traced semiautomatically, and epicardial fat volume (EFV) was measured by assigning Hounsfield units ranging from −30 to −250. EFV was associated with coronary atherosclerosis, and EFV increased steeply in patients with significant coronary artery stenosis and in those with severe coronary artery calcification. Quantitation of EF may be useful, in addition to coronary artery Ca score and coronary angiography, to identify patients at risk for CAD.
We found also that EAT and PFT can be used as a predictor of obstructive CAD. The results of our study were similar to the results of the study done by Demircelik et al..
There was no correlation between the severity of CAD as assessed by syntax and Gensini scores and the EFT, PCFT, and Ca scores in group 3 patients who underwent invasive coronary angiography. Hodas et al. evaluated the correlation between the EF volume, determined by multislice CT, and the severity of coronary lesions expressed by the coronary Ca score and the syntax score in patients with clinical suspicion of CAD. There is a good relationship between the EF volume (measured by multislice CT) and the coronary atherosclerotic burden in patients with CAD. Increased volumes of EFV were associated with other biomarkers of disease severity, such as the coronary Ca score and the syntax score.
Ghaderi et al. conducted a cross-sectional study on 100 patients (44 women and 56 men), with an average age of 56.4 ± 9.9 years to evaluate the association between the EAT and PCFT with the severity of coronary artery. They used Gensini score for CAD severity, and they found that Gensini score had a strong correlation with amount of EAT.
In our study, we measured the EAT and PCFT by multislice CT. Multislice CT provides an accurate and reproducible quantification of EAT owing to its high temporal and spatial resolution. Multiple studies used different imaging modality to measure EF thickness such as Kim et al. and Iacobellis et al.. Salami et al. measured EF thickness by two-dimensional transthoracic echocardiography. They stated that The two-dimensional echocardiography was a safe easily reproducible, and noninvasive method; however, Iacobellis and colleagues, found that despite these advantages, echocardiography is not an optimal technique for the quantification of EAT, as it does not reflect its total volume. There is no consensus regarding its use in clinical practice, but some recommendations suggest EF measurement by echocardiography. EF thickness should be measured on the right ventricular free wall in at least two locations, from both parasternal longitudinal and transverse parasternal views using the mean of three consecutive beats. These measurements show good correlation with the values found on MRI. There is a controversy regarding which time in the cardiac cycle is most suitable for measuring EF thickness in echocardiography. Iacobellis et al. recommend the measurement during systole to prevent possible deformation by EF compression during diastole, whereas Nelson et al. recommend to measure it in diastole, to coincide with other imaging modalities (CT and MRI). MRI is considered the gold standard for the assessment of total body fat and reference modality for the analysis of ventricular volumes and mass,,; thus, making it a natural choice for the detection and quantification of EF.
Our study has some limitation, including limited number of patients and no follow-up of patients to evaluate the outcome. Moreover, only one modality was used to assess EF thickness. Therefore, other studies comparing different modalities are needed.
| Conclusion|| |
There is a positive correlation between both EF and PCFT and the severity of coronary stenosis. EF and PCFT can be used in predicting the severity of CAD.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Mazurek T, Zhang L, Zalewski A, Mannion JD, Diehl JT, Arafat H, et al
. Human epicardial adipose tissue is a source of inflammatory mediators. Circulation 2003; 108
Iacobellis G, Pistilli D, Gucciardo M, Leonetti F, Miraldi F, Brancaccio G, et al
. Adiponectin expression in human epicardial adipose tissue in vivo
is lower in patients with coronary artery disease. Cytokine 2005; 29
Baker AR, Silva NF, Quinn DW, Harte AL, Pagano D, Bonser RS, et al
. Human epicardial adipose tissue expresses a pathogenic profile of adipocytokines in patients with cardiovascular disease. Cardiovasc Diabetol 2006; 5
Ahn SG, Lim HS, Joe DY, Kang SJ, Choi BJ, Choi SY, et al
. Relationship of epicardial adipose tissue by echocardiography to coronary artery disease. Heart 2008; 94
Dey D, Wong ND, Tamarappoo B, Nakazato R, Gransar H, Cheng VY, et al
. Computer-aided non-contrast CT-based quantification of pericardial and thoracic fat and their associations with coronary calcium and metabolic syndrome. Atherosclerosis 2010; 209
Ding J, Hsu FC, Harris TB, Liu Y, Kritchevsky SB, Szklo M, et al
. The association of pericardial fat with incident coronary heart disease: the Multi-Ethnic Study of Atherosclerosis (MESA). Am J Clin Nutr 2009; 90
Greif M, Becker A, von Ziegler F, Lebherz C, Lehrke M, Broedl UC, et al
. Pericardial adipose tissue determined by dual source CT is a risk factor for coronary atherosclerosis. Arterioscler Thromb Vasc Biol 2009; 29
Mahabadi AA, Reinsch N, Lehmann N, Altenbernd J, Kälsch H, Seibel RM, et al
. Association of pericoronary fat volume with atherosclerotic plaque burden in the underlying coronary artery: a segment analysis. Atherosclerosis 2010; 211
Diamond GA, Forrester JS. Analysis of probability as an aid in the clinical diagnosis of coronary-artery disease. N
Engl J Med 1979; 300
Demircelik MB, Yilmaz OC, Gurel OM, Selcoki Y, Atar IA, Bozkurt A, et al
. Epicardial adipose tissue and pericoronary fat thickness measured with 64-multidetector computed tomography: potential predictors of the severity of coronary artery disease. Clinics 2014; 69
Iwasaki K, Matsumoto T, Aono H, Furukawa H, Samukawa M. Relationship between epicardial fat measured by 64-multidetector computed tomography and coronary artery disease. Clin Cardiol. 2011; 34
Hodaş R, Pop S, Opincariu D, Rat N, Jani L, Stanescu A, et al
. Correlations between severity of coronary lesions and epicardial fat volume in patients with coronary artery disease – A multislice CT-based study. J Interdisciplinary Med 2016; 1
Ghaderi F, Eshraghi A, Shamloo AS, Mousavi S. Assosiation of epicardial and pericardial fat thickness with coronary artery disease. Electron Physician 2016; 8
Kim MK, Tanaka K, Kim MJ, Matuso T, Endo T, Tomita T, et al
. Comparison of epicardial, abdominal and regional fat compartments in response to weight loss. Nutr Metab Cardiovasc Dis 2009; 19
Salami SS, Tucciarone M, Bess R, Kolluru A, Szpunar S, Rosman H, et al
. Race and epicardial fat: the impact of anthropometric measurements, percent body fat and sex. Ethn Dis 2013; 23
Iacobellis G, Ribaudo MC, Zappaterreno A, Iannucci CV, Leonetti F. Relation between epicardial adipose tissue and left ventricular mass. Am J Cardiol 2004; 94
Iacobellis G, Assael F, Ribaudo MC, Zappaterreno A, Alessi G, Di Mario U, et al
. Epicardial fat from echocardiography: a new method for visceral adipose tissue prediction. Obesity Res 2003; 11
Ross R, Shaw KD, Martel Y, de Guise J, Avruch L. Adipose tissue distribution measured by magnetic resonance imaging in obese women. Am J Clin Nutr 1993; 57
Iacobellis G, Willens HJ. Echocardiographic epicardial fat: a review of research and clinical applications. J Am Soc Echocardiogr 2009; 22
Nelson AJ, Worthley MI, Psaltis PJ, Carbone A, Dundon BK, Duncan RF, et al
. Validation of cardiovascular magnetic resonance assessment of pericardial adipose tissue volume. J Cardiovasc Magn Reson 2009; 11
Machann J, Thamer C, Schnoedt B, Haap M, Haring HU, Caussen CD, et al
. Standardized assessment of whole body adipose tissue topography by MRI. J Magn Reson Imaging 2005; 21
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]