Background
Several studies using echocardiography identified epicardial adipose tissue (EPI) as an important cardiometabolic risk marker. However, validation compared with magnetic resonance imaging (MRI) or computed tomography has not been performed. Moreover, pericardial adipose tissue (PERI) has recently been shown to have some correlation with cardiovascular disease risk factors. The aims of this study were to validate echocardiographic analyses compared with MRI and to evaluate which cardiac fat depot (EPI or PERI) is the most appropriate cardiovascular risk marker.
Methods
Forty-nine healthy subjects were studied (age range, 25–68 years; body mass index, 21–40 kg/m 2 ), and PERI and EPI fat depots were measured using echocardiography and MRI. Findings were correlated with MRI visceral fat and subcutaneous fat, blood pressure, insulin sensitivity, triglycerides, cholesterol, insulin, glucose, and 10-year coronary heart disease risk.
Results
Most cardiac fat was constituted by PERI (about 77%). PERI thickness by echocardiography was well correlated with MRI area ( r = 0.36, P = .009), and independently of the technique used for quantification, PERI was correlated with body mass index, waist circumference, visceral fat, subcutaneous fat, blood pressure, insulin sensitivity, triglycerides, cholesterol, glucose, and coronary heart disease risk. On the contrary, EPI thicknesses correlated only with age did not correlate significantly with MRI EPI areas, which were found to correlate with age, body mass index, subcutaneous fat, and hip and waist circumferences.
Conclusions
Increased cardiac fat in the pericardial area is strongly associated with features of the metabolic syndrome, whereas no correlation was found with EPI, indicating that in clinical practice, PERI is a better cardiometabolic risk marker than EPI.
Several studies have shown that increased accumulation of fat around the heart is associated with an increased risk for cardiovascular disease and metabolic disease. Cardiac fat can be distinguished in two depots: (1) epicardial adipose tissue (EPI), the fat concentrated in the atrioventricular and interventricular grooves, along the major branches of the coronary arteries and, to a lesser extent, around the atria, over the free wall of the right ventricle and over the apex of the left ventricle, and (2) pericardial adipose tissue (PERI), the fat situated on the external surface of the parietal pericardium within the mediastinum (alternatively termed mediastinal or intrathoracic fat).
Both EPI and PERI have been found to be strongly associated with obesity, preferential visceral fat accumulation, and hypertension. In human hearts randomly collected from diagnostic autopsies, EPI was associated with body mass index (BMI), but it was not related to either hypertension or ischemia. Recently, the 1 H magnetic resonance spectroscopic technique has been used to study the intracellular lipid content of cardiomyocytes. Visceral fat deposition has been recognized as an important risk factor for cardiovascular diseases and is correlated with insulin resistance, cardiovascular risk factors, and the metabolic syndrome.
Several techniques, including echocardiography, computed tomography (CT), and magnetic resonance imaging (MRI), have been used to quantify fat deposition around the heart. However, most published studies have used ultrasound and measured EPI thickness. Recently, it has been demonstrated that EPI thickness ≥ 5 mm measured by ultrasound may identify an individual with a higher likelihood of having detectable carotid atherosclerosis. More expensive imaging techniques such as MRI and CT have the advantage of measuring fat area and/or volume and quantifying separately EPI, PERI, and total cardiac adipose tissue, but these methods can be expensive and time consuming and, in the case of CT, expose patients to radiation. Ultrasound may be an appealing alternative to these imaging techniques because of its wide availability, low cost, and lack of radiation exposure. The aim of this study was to assess agreement between MRI (area) and ultrasound (thickness) for the measurement of EPI and PERI and its correlation with metabolic parameters.
Methods
Subjects
The patient population under investigation was a subset of subjects who participated in previously published studies, selected according to the following criteria: (1) absence of diabetes at enrollment, (2) BMI < 40 kg/m 2 , (3) absence of metabolic or nonmetabolic diseases (except essential hypertension), and (4) no treatment with drugs known to affect glucose tolerance. A subset of subjects enrolled for the metabolic study also agreed to undergo complete rest echocardiography. Thus, the final group was composed of 49 subjects (38 men, 11 women). The study protocol was approved by the institutional review board of the University of Pisa, and each subject gave written informed consent at the time of enrollment.
Study Design
Subjects underwent (1) measurement of global cardiac function and regional left ventricular function by MRI and echocardiography, (2) quantitation of abdominal subcutaneous and visceral fat and EPI content by MRI, and (3) quantitation of PERI and EPI by echocardiography or MRI (see below). An individual 10-year coronary heart disease (CHD) risk was estimated using the Framingham Heart Study prediction score sheet.
Anthropometrics Measurements
Weight (to the nearest 0.1 kg) and height (to the nearest 0.5 cm) were measured while the subjects were fasting and wearing only their undergarments. BMI was calculated as body weight divided by height squared and was used as a marker of obesity degree. The ratio of waist circumference to hip circumference was determined by measuring the waist circumference at the narrowest part of the torso and the hip circumference in a horizontal plane at the level of the maximal extension of the buttocks.
MRI
Abdominal visceral fat and subcutaneous fat depots were measured by MRI, using imaging procedures that have been published previously. Briefly, images were acquired on a GE Signa Excite HD 1.5-T scanner (GE Medical Systems, Milwaukee, WI; slew rate, maximum 150 T/m/sec) that operates with a 50 mT/m gradient using a body coil. A sagittal localizing image was used to center transverse sections on the line through the space between L4 and L5. Thirty-two transverse, T1-weighted 256 × 256 images (repetition time, 135 msec; echo time, 4.2 msec; flip angle, 90°; field of view, 50 cm; pixel size, 1.875 × 1.875 mm) were acquired during a breath hold with a slice thickness of 5 mm and no overlap. Data were transferred to a dedicated workstation and analyzed using software developed ad hoc to determine abdominal subcutaneous and visceral fat areas and volumes. Subcutaneous fat area was analyzed by automatic detection of the outer and inner margins of subcutaneous adipose tissue as a region of interest from the cross-sectional images and by counting the number of pixels between the outer and inner margins of subcutaneous adipose tissue. Visceral (intra-abdominal) fat area was determined using histograms specific to the visceral regions. The histograms were summed over the range of pixel values designated as fat by fitting two normal analysis distribution curves to them. A factor of 0.92 was used to convert adipose tissue volume into adipose tissue mass.
MRI acquisition of the heart involved a standardized protocol. A cardiac coil and electrocardiographic triggering were used for the sequences; during the acquisition time, patients were in breath hold (10–12 sec). Cardiac adipose tissue scans were obtained by fast spin-echo T1-weighted sequences with oblique axial orientation, for a correct study of horizontal long axes of the heart in diastole (echo time, 42 msec; echo train length, 23 msec; bandwidth, 62.50 KHz; slice thickness, 8 mm; slice gap, 0 mm; field of view, 28.5 cm; matrix size, 288 × 224; number of signals acquired, 1; trigger delay, minimum; 8-mm-thick section, 0-mm intersection gap, field of view, and a 256 × 256 matrix). EPI was defined as any adipose tissue located within the pericardial sac. PERI and EPI areas were measured using an in-house semiautomatic program to determinate the margin of fat around the heart, identifying region of interest and measuring the number of pixels, as previously described.
Echocardiography
Each subject underwent transthoracic two-dimensional echocardiography according to the recommendations of the European Association of Echocardiography (Vivid 7; GE Vingmed Ultrasound AS, Horten, Norway), with an M3S matrix-array transducer. Echocardiography was performed using standard techniques with subjects in the left lateral decubitus position. Depth was adjusted as the aortic and mitral valves were positioned lowest on the screen. The adipose fat depot was measured on the free wall of the right ventricle from both parasternal long-axis and short-axis views at end-diastole in three cardiac cycles. The maximum value at any site was measured, and the average value was considered. EPI was defined as an echolucent space between the linear echodense parietal pericardium and the right ventricular epicardium, and PERI was defined as an echolucent area above the parietal pericardium. EPI and PERI were measured on the still images of the two-dimensional echocardiogram obtained at end-diastole on both parasternal long-axis and short-axis views, as described previously. Echocardiograms were preliminarily read by a first reader and subsequently reread by a highly experienced reader. Both readers were blinded to subjects’ anthropometric features. The coefficient of variation between the two different echocardiographers was 4%, indicating good reproducibility of the echocardiographic measurements.
Statistical Analysis
Data are expressed as mean ± SEM. Data with a skewed distribution (plasma triglyceride, cholesterol, and insulin concentrations) are expressed as medians and interquartile ranges and were log-transformed for use in statistical analysis. The two methods (echocardiography and MRI) were compared using Bland Altman plots. Given the different units (millimeters vs square millimeters), we normalized the data to the total cardiac fat, calculated as the sum of either extra-PERI and PERI thickness (millimeters) or area (square millimeters). In this way, both methods gave values ranging from 0 and 1.
Insulin sensitivity was calculated as quantitative insulin sensitivity check index and using the oral glucose insulin sensitivity index, which equals the average metabolic clearance rate of glucose during the oral glucose tolerance test and has been validated against the euglycemic insulin clamp technique. Ten-year CHD risk was calculated using the Framingham score. Correlations were calculated using Spearman’s coefficient.
Results
Clinical, echocardiographic, and MRI characteristics of the study population are reported in Table 1 . As shown in the table, in this group of subjects with a wide range of BMIs, most cardiac fat was constituted by PERI (77%). In Figure 1 , we report two sample cases acquired with MRI and echocardiography.
| Variable | Value |
|---|---|
| Men/women | 38/11 |
| NGT/IGT/T2DM | 34/13/1 |
| Age (y) | 48 ± 1 (25–68) |
| BMI (kg/m 2 ) | 28.8 ± 0.5 (21–40) |
| Waist circumference (cm) | 97 ± 2 (68–125) |
| Hip circumference (cm) | 105 ± 1 (80–138) |
| Waist-to-hip ratio | 0.92 ± 0.10 (0.72–1.09) |
| Echocardiographic EPI thickness (mm) | 3.1 ± 0.3 (0.5–8.5) |
| Echocardiographic PERI thickness (mm) | 4.7 ± 0.3 (1–10) |
| MRI EPI area (mm 2 ) | 827 ± 54 (172–2,008) |
| MRI PERI area (mm 2 ) | 1,813 ± 128 (100–4,014) |
| MRI TCAT area (mm 2 ) | 264 ± 152 (467–5,007) |
| SC (kg) | 3.5 ± 0.2 (1.1–8.3) |
| VF (kg) | 1.3 ± 0.1 (0.1–2.6) |
| VF/SC ratio | 0.39 ± 0.3 (0.06–0.86) |
| Triglyceride (mmol/L) | 0.9 (0.8) (0.3–4.0) |
| Cholesterol (mmol/L) | 5.1 (0.9) (2.1–7.6) |
| HDL cholesterol (mmol/L) | 1.2 (0.3) (0.7–2.4) |
| Systolic blood pressure (mm Hg) | 131 ± 2 (100–181) |
| Diastolic blood pressure (mm Hg) | 77 ± 2 (46–102) |
| Glucose (mmol/L) | 5.5 ± 0.1 (4.6–8.2) |
| Insulin (pmol/L) | 72 (45) (16–237) |
| QUICKI | 0.142 ± 0.002 (0.119–0.183) |
| 10-year CHD risk | 7.7 ± 0.8 (2–25) |
Concordance in the Assessment of Cardiac Fat
A good correlation was found between the PERI measurements obtained with the two techniques, but not for EPI ( Figure 2 ). On Bland-Altman analysis, when the EPI and PERI values were normalized to total fat, the agreement between the two techniques was good, with a nonsignificant trend toward overestimation of EPI and underestimation of PERI with echocardiography ( Figure 2 ).
The Relationship Between Cardiac Fat and Metabolic Parameters
As shown in Table 2 , PERI, but not EPI, measured with both techniques was correlated with the parameters of metabolic syndrome such as triglyceride and glucose concentrations, blood pressure, insulin sensitivity, and BMI. PERI thickness on echocardiography showed a strong correlation with 10-year CHD Framingham risk score, whereas no correlation was found with epicardial risk score ( Table 2 ).
| Variable | Echocardiographic EPI | Echocardiographic PERI | MRI EPI | MRI PERI | MRI TCAT |
|---|---|---|---|---|---|
| BMI | NS | 0.37 (.008) | 0.38 (.006) | 0.44 (.001) | 0.51 (.0001) |
| Age | 0.32 (.02) | 0.52 (<.0001) | 0.29 (.04) | NS | NS |
| Triglyceride | NS | 0.33 (.02) | NS | 0.55 (.0001) | 0.47 (.0006) |
| Cholesterol | NS | NS | NS | 0.35 (.02) | 0.29 (.04) |
| HDL cholesterol | NS | NS | NS | NS | NS |
| VF | NS | 0.32 (.03) | NS | 0.56 (<.0001) | 0.54 (<.0001) |
| SC | NS | NS | 0.39 (.006) | 0.28 (.05) | 0.37 (.009) |
| Systolic blood pressure | NS | 0.37 (.009) | NS | 0.35 (.01) | 0.31 (.3) |
| Diastolic blood pressure | NS | 0.41 (.003) | NS | 0.31 (.3) | 0.32 (.3) |
| Glucose | NS | 0.49 (.003) | NS | 0.27 (.06) | 0.29 (.05) |
| Insulin | NS | NS | NS | NS | NS |
| QUICKI | NS | −0.30 (.04) | NS | −0.26 (.08) | −0.26 (.08) |
| Waist circumference | NS | NS | 0.34 (.02) | 0.51 (.0002) | 0.56 (.0001) |
| Hip circumference | NS | NS | 0.32 (.3) | 0.37 (.01) | 0.43 (.003) |
| 10-year CHD risk | NS | 0.51 (.0001) | NS | 0.35 (.01) | 0.34 (.02) |
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