Abstract
Background and purpose
Epicardial adipose tissue (EAT) plays a crucial role in the progression of heart failure (HF). This study employs cardiovascular magnetic resonance (CMR) imaging to investigate potential differences in EAT between patients with heart failure with reduced ejection fraction (HFrEF) and those with heart failure with preserved ejection fraction (HFpEF), as well as the correlation between EAT and biventricular function (myocardial strain).
Methods
We collected data from patients diagnosed with HF at the Second Affiliated Hospital of Kunming Medical University between January 2021 and December 2023. All patients underwent CMR imaging and were categorized into two groups based on left ventricular ejection fraction (LVEF): the HFrEF group and the HFpEF group. Patients without heart failure served as the control group. We gathered clinical baseline data and utilized CVI-42 post-processing software to obtain parameters related to cardiac structure and function, including LVEF, global radial strain (GRS), global longitudinal strain (GLS), EAT, pericardial adipose tissue (PeAT), paracardial adipose tissue (PaAT), and wall stress. We compared differences in parameters among the three groups and conducted pairwise comparisons. Additionally, we performed correlation analyses of EAT and PeAT with GLS and body mass index (BMI) within the HFrEF and HFpEF cohorts.
Results
A total of 104 patients with HFrEF, 226 patients with HFpEF, and 172 patients without heart failure were ultimately included in the study. Significant statistical differences were observed among the three groups regarding age, smoking status, diabetes, brain natriuretic peptide (BNP) levels, BMI, EAT, PeAT, PaAT, wall stress, GLS, and GRS of both ventricles (p<0.05). The EAT volume in HFrEF patients (32 ± 14 mL) was lower than that in HFpEF patients (51 ± 21 mL) and the control group (33 ± 19 mL). Additionally, PeAT and PaAT levels were higher in HFpEF patients compared to those in HFrEF and the control group. Correlation analysis revealed that in HFrEF patients, EAT accumulation was associated with better left ventricular (LV) function (LVGLS, r = 0.85, p<0.01) and right ventricular (RV) function (RVGLS, r = 0.73, p<0.01). Conversely, in HFpEF patients, EAT accumulation correlated with poorer LV (LVGLS, r = −0.67, p<0.01) and RV (RVGLS, r = 0.55, p<0.01) function.
Conclusion
EAT was greater in patients with HFpEF compared to HFrEF. In the HFpEF group, increased EAT was correlated with worsening biventricular function, while the opposite trend was observed in the HFrEF group.
Keywords: Epicardial adipose tissue, HFpEF, HFrEF, Cardiac magnetic resonance
Graphical abstract
1. Introduction
Epicardial adipose tissue (EAT) has gained considerable interest in recent years due to its distinct anatomical and histological features and its involvement in cardiovascular diseases. As the visceral adipose tissue in direct contact with the myocardium, EAT has been demonstrated to participate in the pathogenesis and progression of various cardiovascular diseases—including heart failure with preserved ejection fraction (HFpEF), heart failure with reduced ejection fraction (HFrEF), atrial fibrillation, and coronary atherosclerosis—through multiple pathophysiological mechanisms [1]. Notably, heart failure (HF) represents the terminal stage of these conditions, characterized by high morbidity and mortality rates [2], with significant etiological differences observed between HFpEF and HFrEF [3]. EAT exerts distinct pathological effects during this process, driving divergent ventricular remodeling patterns: microvascular inflammation predominates in HFpEF, whereas myocardial fibrosis is central in HFrEF [4].
Recent research has increasingly emphasized the quantification and pathophysiological significance of EAT in various HF phenotypes. Evidence suggests that in HFpEF, EAT accumulation correlates with myocardial diastolic dysfunction, diminished exercise tolerance, and elevated mortality risk, whereas in HFrEF, the association appears inverse [5], [6]. Some studies propose that EAT expansion is not directly implicated in HFrEF pathogenesis but is primarily associated with HFpEF onset [7]. Prior investigations predominantly focused on the impact of EAT on left ventricular (LV) systolic and diastolic function, whereas right ventricular (RV) dysfunction has emerged as a pivotal determinant of HF-related morbidity, mortality, and health-related quality of life [8]. Data indicate that HFpEF patients frequently exhibit RV impairment [9], with increased EAT linked to elevated right atrial pressures and pulmonary hypertension [10]. Additionally, the prognostic significance of RV dysfunction in HFpEF has been substantiated [11]. Monitoring right heart functional parameters can thus enhance clinical stratification and management strategies. Although some evidence indicates an independent association between EAT and RV strain impairment in diabetic cohorts [12], the prevalence, mechanistic pathways, and clinical relevance of this relationship in non-diabetic populations and broader cardiovascular disease contexts remain to be elucidated. Consequently, this study aims to employ cardiovascular magnetic resonance (CMR) to quantify EAT volume in HFpEF and HFrEF patients and to investigate the correlation between EAT and biventricular strain across different HF subtypes.
2. Methods
2.1. Study populations
Between January 2021 and December 2023, patients diagnosed with HF at the Cardiology Department of the Second Affiliated Hospital of Kunming Medical University were evaluated according to the Heart Failure Association (HFA)-PEFF diagnostic criteria (Step 1: P, pre-test assessment; Step 2: E, echocardiography and natriuretic peptide scoring; Step 3: F1, functional testing; Step 4: F2, final cause) [13]. Patients were stratified into two groups based on left ventricular ejection fraction (LVEF): HFpEF (LVEF ≥50%) and HFrEF (LVEF <50%). The control group comprised individuals without current or previous heart failure symptoms or signs, and without evidence of structural heart disease or relevant biomarkers.
Exclusion criteria encompassed the following: (1) Severe valvular heart disease; (2) End-stage renal failure or patients undergoing renal replacement therapy; (3) Specific heart failure subtypes, including constrictive pericarditis, complex adult congenital heart disease, hypertrophic cardiomyopathy, eosinophilic myocarditis, cardiac amyloidosis, and acute chemotherapy-induced cardiomyopathy; (4) Patients with prior cardiac surgery, pericardial effusion causing artifacts, inadequate image quality precluding post-processing analysis, and those lacking essential clinical data for accurate post-processing measurements.(Fig. 1). The study protocol was approved by the Ethics Committee of the Second Affiliated Hospital of Kunming Medical University.
Fig. 1.
Technology roadmap. CMR cardiovascular magnetic resonance, HFpEF heart failure with preserved ejection fraction, HFrEF heart failure with reduced ejection fraction
2.2. Imaging protocol
CMR imaging was performed with a Philips Achieva 3.0T MRI system (Philips Healthcare, Best, The Netherlands). Patients were positioned supine for CMR imaging, utilizing MRI-compatible chest lead ECG gating and a 16-channel phased-array cardiac coil. Cine imaging in short-axis and long-axis views (four-chamber, left ventricular two-chamber, and two-chamber short-axis) was acquired using a fast steady-state free precession sequence with the following parameters: TE 1.61 ms, TR 3.22 ms; flip angle 45°, FOV: 350 mm × 350 mm, single acquisition, 25 cardiac cycles per slice, and a slice thickness of 8 mm. Delayed enhancement imaging was performed following the intravenous administration of gadodiamide (0.2 mmol/kg, flow rate 3 mL/s) via power injector. Multiplanar late gadolinium enhancement (LGE) images were acquired 3–15 min post-contrast administration, with the following acquisition parameters: TE 2.41 ms, TR 5.11 ms, flip angle 25°, FOV: 320 mm × 320 mm, and a slice thickness of 10 mm.
2.3. Post-processing analysis of CMR images
CMR images were processed using CVI 42 software (Circle Cardiovascular Imaging, Calgary, Alberta, Canada). EAT, the fat depot confined within the visceral pericardium, directly adjacent to the myocardium; PeAT, the fat from the visceral pericardium to the external surface of the extracardiac; PaAT, the sum of EAT + PeAT [14]. Due to the difficulty in accurately distinguishing the pericardial wall layer in 3.0T CMR, the subepicardial fat and extracardiac fat are grouped together as one "PeAT" category. EAT quantification was performed on end-diastolic short-axis two-chamber balanced steady-state free precession (bSSFP) sequences using the tissue signal intensity module. The outer boundary was defined by the visceral pericardium, and the inner boundary was defined by the myocardial surface. EAT was delineated from the apex to the posterior wall of the left atrium layer by layer (excluding the coronary artery region), and the volume was automatically generated. The PeAT was measured in the same planes as the adipose tissue beyond the parietal pericardium. The EAT and PeAT were summed as PaAT. (Fig. 2A-D). Strain analysis was performed based on end-diastolic short-axis two-chamber, three-chamber, and four-chamber bSSFP sequences using the strain module. The software automatically delineated the endocardial and epicardial contours of the left ventricle and the endocardial contour of the right ventricle, while the right ventricular epicardial contour was manually delineated by the researchers to obtain left and right ventricular myocardial strain parameters. Due to the delicate trabecular wall thickness (<3 mm) and crescentic morphology of the RV, partial volume effects inherent in CMR may impair the precision of automated segmentation algorithms. Furthermore, in basal slices, motion artifacts obscure the pericardium, requiring manual delineation to distinguish adipose tissue from myocardium. Prior research has established that manual tracing remains the gold standard for quantifying right ventricular adiposity, demonstrating high interobserver reproducibility [15]. Overall myocardial strain parameters for the left and right ventricles included GRS and GLS. The collection of perivascular adipose tissue and strain data was performed by two observers (S.YJ and T.N). Fig. 3, Fig. 4 present a comparison of EAT and strain in patients with different types of heart failure.
Fig. 2.
A-D illustrate a schematic diagram detailing pericardiac adipose tissue measurement. EAT: Fat depot confined within the visceral pericardium, directly contacting the myocardium and coronary vessels; PeAT：the adipose tissue beyond the parietal pericardium, separated from myocardium by pericardial fluid; PaAT：Collective term encompassing both EAT and PeAT.
Fig. 3.
Pericardial fat and strain in patients with heart failure with preserved ejection fraction EAT =61 mL, PeAT =69 mL, PaAT = 130 mL, LVGRS = 43%, LVGLS = −11%, RVGRS = 39%, RVGLS = −20%. EAT epicardial adipose tissue, PeAT pericardial adipose tissue, PaAT paracardial adipose tissue, LVGRS left ventricular global radial strain, LVGLS left ventricular global longitudinal strain.
Fig. 4.
Pericardial fat and strain in patients with HFrEF. EAT = 23 mL, PeAT = 31 mL, PaAT = 54 mL, LVGRS = 25%, LVGLS = −6%, RVGRS = 28%, RVGLS = −9%
2.4. Statistical methods
R software version 4.0.0 (http://www.r-project.org, Vienna, Austria) was used for data analysis. The χ2 test was employed for count data comparisons; independent sample t-test was used for comparing measurement data among three groups, with results presented as x ± s for normally distributed measurement data; Wilcoxon rank-sum test was utilized for non-normally distributed measurement data, with results presented as median and quartiles M (P25, P75). Specifically, EAT, PeAT, and PaAT do not retain decimal places, accounting for actual measurement precision. Applying Spearman correlation analysis to examine the relationships between EAT and PeAT with LVGLS and RVGLS in HFpEF and HFrEF, respectively, and analyzing the association between EAT and BMI within these heart failure subtypes. Considering the close correlation between BMI and EAT, BMI was included as a covariate in partial correlation analysis to re-evaluate the relationship between EAT and biventricular function across different HF phenotypes, this approach statistically adjusts for the confounding effects of systemic obesity, isolating the specific impact of EAT related to its anatomical proximity. A p value of less than 0.05 was considered statistically significant.
3. Results
3.1. Clinical characteristics and laboratory test comparisons
A cohort of 104 patients with HFrEF, 226 patients with HFpEF, and 172 subjects in the non-heart failure control group were enrolled. Baseline clinical characteristics were compared across the three groups, as detailed in Table 1. The key differences are as follows: Demographic characteristics: The proportion of females was highest in the HFrEF group (72.12%,75/104), while the HFpEF group had the oldest median age (57 years). Metabolic features: The HFpEF group exhibited significantly higher BMI (25.6 kg/m²) and diabetes prevalence (26.1%,59/226) compared to the HFrEF group. The HFrEF group had the lowest high-density lipoprotein (HDL) cholesterol levels (1.03 mmol/L). Biomarkers: BNP levels were higher in the HFrEF group than in the HFpEF group (655.5 vs. 575.5 pg/mL). After multivariate adjustment, only HDL cholesterol remained significantly different among the three groups (p<0.05).
Table 1.
Comparison of baseline clinical data, laboratory tests, and CMR feature parameters among three groups.
| control (n = 172) | HFpEF (n = 226) | HFrEF (n = 104) | χ2/t/ Z value | p value | |
|---|---|---|---|---|---|
| Female[n(%)] | 104(60.47) | 147(65.04) | 75(72.12)b | 3.87 | 0.15 |
| Age(years) | 49.00(34.00,59.00) | 57.00(48.00,65.00)a | 51.00(43.25,61.00)c | 28.87 | ＜0.01* |
| BMI(kg/m2) | 23.94(21.61,26.69) | 25.57(22.63,27.69)a | 24.88(21.64,27.60) | 7.95 | 0.02* |
| Stroke[n(%)] | 28(16.28) | 58(25.67)a | 37(35.58)b | 12.75 | ＜0.01* |
| Hypertension[n(%)] | 68(39.53) | 110(48.67) | 47(45.19) | 3.31 | 0.19 |
| Diabetes[n(%)] | 18(10.47) | 59(26.11)a | 11(10.58)c | 20.91 | ＜0.01* |
| LDL(mmol/L) | 2.59(2.10,3.23) | 2.59(2.01,3.33) | 2.66(2.14,3.27) | 0.15 | 0.93 |
| HDL(mmol/L) | 1.10(0.97,1.30) | 1.10(0.93,1.28) | 1.03(0.79,1.21)b, c | 10.82 | ＜0.01* |
| TC (mmol/L) | 4.30(3.70,5.10) | 4.33(3.61,5.22) | 4.29(3.41,4.95) | 0.67 | 0.72 |
| TG (mmol/L) | 1.45(0.99,2.01) | 1.51(1.11,2.12) | 1.51(1.05,1.92) | 2.96 | 0.22 |
| BNP\pro-BNP(ng/L) | 69.00(32.25,124.75) | 575.50(465.00,765.00)a | 695.00(529.00,1083.00)b, c | 340.18 | ＜0.01* |
| Homocysteine(μmol/L) | 12.15(9.93,15.14) | 14.38(11.69,17.85)a | 13.13(10.58,19.33)b | 26.07 | ＜0.01* |
| EAT(mL) | 33±19 | 51±21a | 32±14c | 85.58 | ＜0.01* |
| PeAT(mL) | 31±24 | 56±32a | 40±13b, c | 70.53 | ＜0.01* |
| PaAT(mL) | 65±42 | 106±52a | 66±22c | 78.81 | ＜0.01* |
| Wall stress(Pa) | 47.00(40.25,52.00) | 50.00(42.00,63.00)a | 72.00(64.00,84.00)b, c | 142.20 | ＜0.01* |
| LVGRS(%) | 37.93(30.27,43.54) | 35.82(26.23,51.06) | 29.91(23.21,39.78)b, c | 12.62 | ＜0.01* |
| LVGLS(%) | −13.20(−15.55，−11.44) | −11.44(−13.60,−9.49)a | −9.86(−12.47,−7.10)b, c | 77.28 | ＜0.01* |
| RVGRS(%) | 43.62(33.33,71.67) | 38.83(26.34,65.92)a | 31.70(21.07,44.01)b, c | 36.02 | ＜0.01* |
| RVGLS(%) | −14.73(−18.37，−12.35) | −12.62(−14.19,−10.38)a | −10.67(−12.09,−8.61)b, c | 72.56 | ＜0.01* |
Values are given as mean ± standard deviation, n (%), or median [25th, 75th percentile].
BMI body mass index, LDL low-density lipoprotein, HDL high-density lipoprotein, TC total cholesterol, TG Triglycerides, BNP brain natriuretic peptide, EAT epicardial adipose tissue, PeAT pericardial adipose tissue, PaAT paracardiac adipose tissue, LVGRS left ventricular global radial strain, LVGLS left ventricular global longitudinal strain, RVGRS right ventricular global radial strain, RVGLS right ventricular global longitudinal strain
p<0.05 for comparison of HFpEF versus controls.
p<0.05 for comparison of HFrEF/HFmrEF versus controls.
p<0.05 for comparison of HFrEF/HFmrEF versus HFpEF.
3.2. Comparing CMR characteristic parameters
Table 1 presents a comparative analysis of EAT and cardiac function parameters across three patient cohorts. The key differences are as follows: differences in adipose tissue volume: patients with HFpEF exhibited significantly higher EAT (51 ± 21 vs 33 ± 19 mL), PeAT (56 ± 32 vs 31 ± 24 mL), and PaAT (106 ± 52 vs 65 ± 42 mL) compared to controls (p<0.05), and EAT: HFpEF > HFrEF (51 ± 21 vs 32 ± 14 mL). Strain parameters: the absolute ventricular strain in the HFpEF group was significantly greater than in the HFrEF group (p<0.05), including LVGLS (35.82% vs 29.91%) and RVGLS (−12.62% vs −10.67%). Myocardial wall stress: the HFrEF group exhibited the highest myocardial wall stress (72.0 mmHg), significantly exceeding that of the HFpEF group (50.0 mmHg) and the control group (47.0 mmHg) (p<0.05).
3.3. Correlation of pericardial fat with biventricular function
In HFrEF patients, EAT (32 ± 14 mL) was significantly reduced compared to HFpEF patients (51 ± 21 mL, p<0.05) and the control group (33 ± 19 mL, p<0.05). The mean EAT in HFrEF patients was slightly lower than that of the control group, although this difference did not reach statistical significance. Conversely, significant differences in EAT were observed between HFpEF patients and the control group, as well as between the two HF cohorts. Furthermore, PeAT and PaAT in HFpEF is significantly higher than HFrEF and the control group (Fig. 5 A-C). Correlation analysis revealed that in HFrEF patients, EAT accumulation correlated with improved LV function (LVGLS, r = 0.85, p<0.01) and RV function (RVGLS, r = 0.73, p<0.01). Conversely, in HFpEF patients, EAT accumulation correlated with impaired LV (LVGLS, r = −0.67, p<0.01) and RV (RVGLS, r = −0.55, p<0.01) function. In HFpEF patients, PeAT accumulation was also associated with impaired LV (LVGLS, r = −0.58, p<0.01) and RV (RVGLS, r = −0.48, p<0.01) function, although the correlation was less robust than that of EAT (Fig. 6 A-D).
Fig. 5.
A-C compares the EAT, PeAT, PaAT of HFpEF patients, HFrEF patients, and control group patients in bar charts. HFpEF heart failure with preserved ejection fraction, HFrEF heart failure with reduced ejection fraction, EAT epicardial adipose tissue volume, PeAT pericardial adipose tissue, PaAT paracardiac adipose tissue.
Fig. 6.
A-D Association of EAT/PeAT with LV and RV function in HFpEF and HFrEF. EAT epicardial adipose tissue volume, PeAT pericardial adipose tissue, RVGLS right ventricular global longitudinal strain, LVGLS left ventricular global longitudinal strain, HFpEF heart failure with preserved ejection fraction, HFrEF heart failure with reduced ejection fraction.
3.4. Association of EAT and PeAT with BMI in HFpEF and HFrEF group
In individuals diagnosed with HFpEF, EAT (r = 0.298, p<0.001) and PeAT (r = 0.577, p<0.001) demonstrate significant positive correlations with BMI. Similarly, in patients with HFrEF, EAT (r = 0.245, p<0.001) and PeAT (r = 0.114, p<0.001) are also positively associated with BMI. Fig. 7.
Fig. 7.
Association of EAT and PeAT with BMI in HFpEF and HFrEF group. EAT epicardial adipose tissue volume, PeAT pericardial adipose tissue, BMI body mass index, HFpEF heart failure with preserved ejection fraction, HFrEF heart failure with reduced ejection fraction.
3.5. Partial correlation of EAT with biventricular function
Following adjustment for BMI as a covariate, correlation analyses demonstrated that in HFrEF patients, EAT correlated positively with improved LV function (LVGLS, r = 0.84, p<0.01) and RV function (RVGLS, r = 0.79, p<0.01). Conversely, in HFpEF patients, EAT correlated negatively with diminished LV (LVGLS, r = −0.63, p<0.01) and RV (RVGLS, r = −0.58, p<0.01) function (Table 2).
Table 2.
The partial correlation between EAT and biventricular function.
|
HFpEF |
HFrEF |
|||
|---|---|---|---|---|
| rs | p Value | rs | p Value | |
| LVGLS | −0.63 | ＜0.01* | 0.84 | ＜0.01* |
| RVGLS | −0.58 | ＜0.01* | 0.79 | ＜0.01* |
EAT epicardial adipose tissue, LVGLS left ventricular global longitudinal strain, RVGLS right ventricular global longitudinal strain, HFpEF heart failure with preserved ejection fraction, HFrEF heart failure with reduced ejection fraction.
3.6. Correlation of EAT with late gadolinium enhancement (LGE)
In HFrEF patients, EAT accumulation correlated with a significantly increased LGE burden (r = 0.23, p = 0.02). Conversely, in HFpEF patients, EAT accumulation demonstrated an inverse relationship with LGE burden (r = −0.13, p = 0.06), although this trend did not achieve statistical significance within the HFpEF cohort (Fig. 8).
Fig. 8.
Association of EAT with LGE in HFpEF and HFrEF group. EAT epicardial adipose tissue volume, LGE late gadolinium enhancement, HFpEF heart failure with preserved ejection fraction, HFrEF heart failure with reduced ejection fraction.
4. Discussion
This investigation assessed EAT characteristics in HFpEF and HFrEF patients, and its association with LV and RV function via CMR. Initially, EAT volume was elevated in HFpEF patients relative to HFrEF patients, with the HFrEF cohort demonstrating slightly reduced volumes compared to controls. Furthermore, in HFpEF patients, both PeAT and PaAT were increased compared to HFrEF patients and the control group. Second, in HFpEF patients, EAT accumulation correlated with impaired LV and RV function, while in HFrEF patients, it correlated with improved LV and RV function. Table 3.
Table 3.
Intra- and Interobserver variability of pericardial fat.
| Parameter | Interobserver ICC | 95% CI | Intra-observer ICC | 95% CI |
|---|---|---|---|---|
| EAT(ml) | 0.85 | 0.79–0.90 | 0.89 | 0.84–0.93 |
| PeAT(ml) | 0.91 | 0.85–0.94 | 0.93 | 0.89–0.96 |
| PaAT(ml) | 0.92 | 0.87–0.95 | 0.95 | 0.92–0.97 |
EAT epicardial adipose tissue volume, PeAT pericardial adipose tissue, PaAT paracardiac adipose tissue. ICC intra class correlation coefficient, CI confidence interval.
4.1. Pericardial adipose tissue measurement and pathophysiological pathways
The escalating global prevalence of obesity has been identified as a principal and modifiable risk factor for cardiovascular diseases. However, the impact of obesity varies; for example, abdominal obesity is linked to a greater cardiovascular disease risk compared to subcutaneous obesity. Furthermore, PaAT is recognized as an independent cardiovascular risk factor. PaAT comprises EAT and PeAT. EAT, an intrinsic component of the heart, is located adjacent to the myocardium. It is a metabolically active fat depot in direct contact with the myocardium and coronary arteries, receiving its blood supply from the coronary circulation. Under physiological conditions, EAT exhibits cardioprotective properties, preventing lipotoxicity and secreting anti-inflammatory and anti-atherogenic adipokines. However, in the setting of metabolic injury, it adversely affects the heart by secreting pro-inflammatory cytokines and fatty acids, which can trigger cardiac remodeling and HF [16]. Conversely, PeAT, an ectopic abdominal visceral fat, is situated external to the heart. Consequently, PeAT lacks the proximity of EAT and its specificity as a therapeutic target [17]. Currently, various examination methods are available for detecting EAT; CMR imaging serves as a comprehensive examination modality, which is currently regarded as the reference standard for quantitative assessment of EAT, with its primary advantage being the ability to observe cardiac and myocardial changes across multiple sequences while visually displaying fat.
4.2. Epicardial adipose tissue content in different types of heart failure
The association between EAT content and various HF phenotypes remains a subject of ongoing investigation, although increased EAT volume is generally observed in HFpEF [3], [18]. However, the heterogeneity of the HFpEF population may contribute to conflicting results. For instance, Tromp J et al. [19]. found increased EAT mass in HFrEF patients compared to HFpEF patients using CMR imaging. They suggested that this discrepancy might be due to differences in inclusion criteria and measurement methods, as CMR assesses total EAT volume, while echocardiography evaluates right ventricular free wall EAT thickness. After indexing EAT by cardiac mass, their results indicated that the indexed EAT mass in the HFrEF group was lower compared to the control group. Our study observed greater EAT in HFpEF patients compared to HFrEF patients, who had slightly less than the control group. This may be attributed to the higher BMI in HFpEF patients, indicating increased overall adiposity, which leads to increased vascular volume and myocardial workload, imposing hemodynamic stress [20]. Severe HFrEF patients may exhibit systemic fat reduction, leading to decreased EAT. Additionally, HFrEF patients often present with cardiac injuries and conditions associated with increased cardiac workload. The primary etiologies are ischemic and dilated cardiomyopathy, with most patients experiencing advanced heart failure characterized by biventricular dysfunction. This dysfunction can subsequently manifest in gastrointestinal symptoms, such as intestinal congestion, which may result in malabsorption and metabolic disorders. This phenomenon may also be linked to the reduction of EAT in HFrEF patients [21]. Therefore, our findings are generally consistent with previous studies. Furthermore, PeAT, being ectopic abdominal visceral fat, shows a strong correlation with BMI, making it most prevalent in patients with HFpEF, followed by those with HFrEF. In the case of PaAT, since PeAT constitutes the majority, its quantity is similar to that of PeAT.
4.3. The relationship between epicardial adipose tissue and strain in different types of heart failure
Previous studies have shown that, in the initial phases of cardiac pathology, myocardial mechanical parameters serve as predictive markers for the progression of distinct heart failure phenotypes [22]. Among them, LVGLS has been clearly demonstrated to reflect LV systolic function early on [23], while RVGLS has been proven to be a prospective indicator for evaluating right ventricular function, with higher sensitivity in assessing longitudinal dysfunction [24]. Current comparative analyses of EAT and GLS across various HF subtypes versus control groups predominantly employ echocardiographic modalities [4], emphasizing left heart function [25]. For instance, Pugliese NR et al. [18]. reported that decreased EAT thickness correlated with more severe LV dysfunction and higher mortality in HFrEF patients, whereas in HFpEF, increased EAT was linked to impaired cardiopulmonary reserve, adverse biomarker profiles, and right ventricular-pulmonary artery uncoupling. Currently, there is a paucity of studies examining the relationship between EAT and RV function across different HF phenotypes; however, existing literature suggests that RV dysfunction is more prevalent in HFpEF populations , and Obokata M et al. [26]. reported that obese HFpEF subjects exhibited increased EAT thickness and a higher incidence of RV dysfunction compared to non-obese HFpEF individuals and healthy controls.
In this investigation, the absolute strain values in patients with HFrEF were consistently lower than those observed in HFpEF, indicating a more profound impairment of myocardial contractility in HFrEF subjects. Concerning the association between EAT and biventricular function, an increase in EAT volume in HFpEF patients correlated with a downward trend in both LVGLS and RVGLS, implying progressive biventricular dysfunction. Conversely, this correlation was reversed in HFrEF patients. This divergence may be attributable to the differential pathophysiological impact of EAT in HFpEF [27], Tromp J et al. [19] reported that, relative to HFrEF, increased EAT mass in HFpEF is more closely linked to left ventricular systolic impairment and fibrotic remodeling. Variations in the adipocyte composition of EAT may also influence these outcomes, EAT comprises three distinct lipid components, each exerting differential effects on cardiovascular diseases [28]. The primary component is white adipose tissue, which exerts an inhibitory effect on the heart; its increase is associated with a higher risk of cardiovascular disease [29]. Conversely, brown adipose tissue actively participates in lipid and energy metabolism [30], contributing to the improvement of cardiac function and contractility [31]. In HFpEF, white adipose tissue predominates within EAT, conversely, HFrEF patients exhibit a higher proportion of metabolically active brown adipose tissue within EAT. Furthermore, the overall cardiac metabolic profile varies between these phenotypes; in HFrEF, elevated EAT correlates with decreased levels of C-reactive protein, troponin T, and interleukin-6, indicating a more favorable metabolic milieu [16]. However, this relationship is reversed in HFpEF. In this cohort, HFpEF patients displayed relatively elevated HDL and adipokine levels, potentially due to augmented adiposity that amplifies pro-inflammatory activity within cardiac tissue, ultimately impairing myocardial function. We hypothesize that excessive white adipose tissue accumulation in EAT may induce local inflammation and microvascular fibrosis through cytokine secretion (e.g., adiponectin), thereby contributing to ventricular dysfunction. The compositional differences in EAT between HFrEF and HFpEF may underpin their distinct relationships with biventricular performance. Additionally, PeAT primarily composed of white adipocytes, can undergo browning under specific conditions, although the precise triggers remain undefined. In HFpEF, ventricular decline appears linked to WAT accumulation, whereas in HFrEF, some adipocytes may undergo browning, potentially exerting cardioprotective effects, albeit without statistical significance.
5. Limitations
The limitations of this study are as follows: first, manual delineation of pericardial fat may introduce interobserver variability and quantitative results are software-dependent, acquisition of pericardial fat and cardiac functional parameters using CVI42 post-processing software may introduce quantitative differences compared to other post-processing software. Second, the relatively small sample size limited further subgroup analysis of HFpEF and HFrEF, including many HFmrEF patients. Third, incomplete information on inflammatory biomarkers hindered further analysis of the EAT inflammatory pathway. Moreover, the absence of a ventricular mass index could not exclude its impact on corresponding variables.
6. Conclusions
Recent comprehensive analyses of EAT have identified it as a quantifiable and modifiable cardiovascular risk biomarker, providing critical insights for risk stratification in heart failure. EAT volume is significantly elevated in patients with HFpEF compared to those with HFrEF, and increased EAT deposition correlates with progressive ventricular dysfunction across both cohorts. These findings highlight the imperative for focused clinical attention on HFpEF and underscore the necessity for future investigations into targeted interventions for EAT modulation, which will continue to be a central and emerging domain within cardiovascular research.
Funding
This research was supported by the Yunnan Provincial Science and Technology Platform Talent Project (Academician Expert Workstation) (202305AF150033); Yunnan Revitalization Talent Support Program(XDYC-YLWS-2023–0022).;Kunming Medical University's Intelligent Imaging Precision Medicine Team(2024XKTDTS03);Basic Research Program Supported by Yunnan Fundamental Research Kunming Medical University Joint Projects(202501AY070001–103).
Author contributions
Yu-jiao Song: Writing – original draft, Conceptualization. Ting Ning: Data curation. Ming-tian Chen: Formal analysis. Xiao-ying Zhao: Supervision. Wan-qiu Zhang: Methodology. Lu-jing Wang: Project administration. Xin-xiang Zhao: Writing – review & editing.
Declaration of competing interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
Xin-Xiang Zhao performed the research and contributed essential tools. Yu-jiao Song and Ting Ning analyzed the data and wrote the paper. Ming-tian Chen and Xiao-ying Zhao edited the paper. Wan-qiu Zhang and Lu-Jing Wang assisted in submitting articles.
Disclosures
All authors have no conflicts of interest.
References
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