Epicardial adipose tissue density, myocardial fibrosis, and heart failure with preserved ejection fraction in postmenopausal women: a mediation analysis

Introduction

Heart failure with preserved ejection fraction (HFpEF) has become a major public health concern due to its high morbidity and substantial mortality burden (1). Despite its increasing prevalence, therapeutic options remain limited due to the syndrome’s heterogeneity. The incidence of HFpEF differs between the sexes and predominantly affects postmenopausal women (2,3), reflecting the loss of cardiovascular protection conferred by oestrogen (3). Although the pathophysiology of HFpEF is complex and heterogeneous, systemic inflammation is recognised as a central driving mechanism. Traditionally, this inflammation has been understood as primarily comorbidity-driven, initiated by conditions such as obesity, hypertension, diabetes, and physical inactivity (4). More recently, evidence suggests that the postmenopausal decline in oestrogen also acts as a key instigator of this systemic inflammatory response, thereby contributing significantly to the pathogenesis of HFpEF (3). However, the specific mechanisms through which HFpEF develops and progresses in postmenopausal women remain incompletely understood.

Epicardial adipose tissue (EAT) is a metabolically active visceral fat located between the myocardial surface and the visceral pericardium, sharing the same microcirculation with the myocardium (5). Given the proximity of EAT to the myocardium, numerous studies have investigated its association with cardiac function and the occurrence of HFpEF. Previous studies have reported contradictory associations between EAT thickness or volume, measured by echocardiography or magnetic resonance imaging (MRI), and HFpEF (6), which is thought to reflect the heterogeneity of the syndrome. In addition to three-dimensional measurement of EAT volume, computed tomography (CT) scans enable estimation of EAT density. However, as a potential imaging biomarker of cardiovascular risk related to inflammatory activity (7), EAT density has rarely been examined in previous investigations of HFpEF. We therefore hypothesise that, in the context of postmenopausal oestrogen decline driving systemic inflammation, EAT density may represent a critical local manifestation of this inflammatory response and play a pivotal role in the pathogenesis of HFpEF in postmenopausal women.

In the progression of HFpEF, myocardial fibrosis has been shown to play a key role in cardiac remodelling leading to diastolic dysfunction (8). The extracellular volume (ECV) fraction, derived from dual-energy computed tomography with late iodine enhancement (LIE-DECT), has been validated as a reliable non-invasive parameter for quantifying myocardial interstitial fibrosis (MIF) (9).

Accordingly, this study aimed to investigate the associations of EAT volume, EAT density, and their interplay with HFpEF in the postmenopausal population. Furthermore, we applied ECV derived from LIE-DECT to examine whether myocardial fibrosis mediates the relationship between EAT characteristics and HFpEF. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2744/rc).

Methods

Study population

This single-center, retrospective study utilised data from a prospectively maintained database of postmenopausal women at Affiliated Nantong Clinical College of Nantong University, Nantong First People’s Hospital, who underwent coronary artery calcium scoring (CACS), cardiac computed tomography angiography (CCTA), and LIE-DECT between January 2020 and December 2022 for clinical indications, primarily for the evaluation of suspected coronary artery disease (e.g., stable or atypical chest pain). All participants had natural menopause (last menstrual period more than one year earlier) and had not received hormone replacement therapy. Patients with HFpEF were identified from this registry according to the following criteria: (I) symptoms and signs of HF (New York Heart Association class II or higher); (II) left ventricular ejection fraction (LVEF) ≥50%; (III) N-terminal pro-brain natriuretic peptide levels >125 pg/mL or >365 pg/mL (in patients with atrial fibrillation); (IV) at least one echocardiographic finding of cardiac structural or functional abnormalities consistent with left ventricular (LV) diastolic dysfunction (4,10). Exclusion criteria applied to all participants were: (I) severe coronary artery stenosis diagnosed by angiography (≥70%); (II) active or prior myocardial infarction defined by clear late iodine-enhancement scars (subendocardial or transmural); (III) chronic pulmonary disease; (IV) significant valvular heart disease; (V) other cardiomyopathies including hypertrophic cardiomyopathy and cardiac amyloidosis; (VI) history of pericardial disease. The non-heart failure (HF) control pool consisted of 149 consecutive postmenopausal women from the same database who were asymptomatic for HF and met all exclusion criteria during the enrolment period. From this pool, 70 individuals were selected and age-matched 1:1 to the HFpEF patients. The flowchart of this study is shown in Figure 1.

Figure 1 Flowchart illustrating participant inclusion and exclusion. CACS, coronary artery calcium scoring; CCTA, cardiac computed tomography angiography; HF, heart failure; HFpEF, heart failure with preserved ejection fraction; LIE-DECT, dual-energy computed tomography with late iodine enhancement.

This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Nantong First People’s Hospital (No. 2025KT046) and informed consent was taken from all the patients.

Cardiac CT

All cardiac CT examinations were performed using a third-generation dual-source CT scanner (Somatom Force; Siemens Healthineers, Erlangen, Germany). CACS, CCTA, and LIE-DECT were acquired. CACS with prospective electrocardiogram triggering was performed at 120 kV and 80 mA with automated tube current modulation (CARE Dose 4D, Siemens Healthineers), a slice thickness of 2 mm, and an increment of 1.5 mm. CCTA was performed with tube current modulation, CARE kV (reference 100 kV), CARE Dose 4D (reference 288 mAs), 66 ms temporal resolution, and an acquisition phase of 65–80% of the RR-interval. CCTA was acquired after injection of 50 mL Ultravist 370 (Bayer Healthcare, Berlin, Germany) into the left brachial vein at 4 mL/s, followed by 50 mL saline at the same rate. After CCTA, 50 mL Ultravist 370 and 30 mL saline were injected again at 2.5 mL/s. LIE-DECT with prospective ECG gating was performed 7 minutes after CCTA (11) using the following parameters: 230 mAs at 90 kV and 177 mAs at Sn150 kV; full-cycle reconstruction, 250 ms; acquisition phase at 70% R-R interval; reconstructed slice thickness 0.6 mm, increment 0.4 mm. Iterative reconstruction (ADMIRE, strength level 3) and a convolution kernel (Qr36) were applied.

Echocardiography

Echocardiography was performed by cardiac sonographers with at least 5 years of experience, using a Philips IE33 ultrasound system (Philips Ultrasound, Washington, USA) equipped with an S5-1 transducer (1–5 MHz). The following parameters were collected: left atrial volume (LAV), left ventricular end-diastolic volume (LVEDV), left ventricular end-systolic volume (LVESV), LVEF, interventricular septal thickness (IVST), left ventricular myocardial mass (LVMM), early diastolic mitral inflow velocity (E wave), septal mitral annular early diastolic peak velocity (septal e’), lateral mitral annular early diastolic peak velocity (lateral e’), and average septal-lateral E/e’ ratio (mean E/e’). LVMM, LVEDV, LVESV, and LAV were indexed to body surface area (LVMM index, LVEDV index, LVESV index, and LAV index). In the present study, echocardiography and cardiac CT were performed within 2 days of each other in all participants.

EAT assessment

The CACS images were used to quantify EAT volume and density with post-processing software (Cardiac Risk Analysis, Research Frontier, SyngoVia, Siemens Healthineers). EAT was automatically traced between the visceral pericardium and the outer myocardium wall, from the pulmonary artery bifurcation to the apex of the heart (Figure 2A-2C). Within the region of interest, fat tissue was defined as voxels between −190 and −30 Hounsfield unit (HU) (12). The software calculated EAT volume and mean density, and EAT volume was indexed to body surface area for analysis.

Figure 2 Representative images illustrating the measurement of EAT and ECV. Axial (A), coronal (B), and sagittal (C) views show quantification of EAT, highlighted in red. (D) Corresponding ECV distribution map of the left ventricle. EAT, epicardial adipose tissue; ECV, extracellular volume.

ECV assessment

ECV measurement was performed using post-processing software (Cardiac Functional Analysis, Research Frontier, SyngoVia, Siemens Healthineers). Before ECV analysis, iodine maps were generated at the workstation. Diastolic CCTA images, delayed 90-kV images, and iodine maps were imported into the software, and haematocrit values obtained from venous blood samples drawn within 24 h of the CT scan were entered manually. The software then calculated the 17-segment and global mean ECV of the LV myocardium (Figure 2D).

Statistical analysis

Statistical analyses were performed using IBM SPSS Statistics (version 20.0; SPSS Inc., Chicago, IL, USA) and SAS (version 9.4; SAS Institute, Cary, NC, USA). Statistical significance was defined as P<0.05. Controls were matched 1:1 to cases by age (±3 years). The normality of continuous variables was assessed with the Shapiro-Wilk test. Continuous variables were presented as mean ± standard deviation for normally distributed data, or as median and interquartile range for skewed data. Categorical variables were presented as absolute numbers and percentages. Differences between the HFpEF and control groups were evaluated using the independent samples t-test or the Mann-Whitney U test for continuous variables, and the Chi-squared test for categorical variables. To identify independent associations of EAT parameters and ECV with HFpEF, multivariate logistic regression analysis was performed. Variables with P<0.05 in univariate analysis or those of clinical relevance were included in the multivariate model. Multicollinearity among predictors was assessed using variance inflation factors (VIFs). The difference in the association between EAT volume index and EAT density across HFpEF and control groups was tested with a multiple linear regression model including an interaction term (EAT volume index × group). A mediation analysis was conducted to examine whether ECV mediated the association between EAT density or volume index (independent variable) and HFpEF (dependent variable) (Figure 3). Significance was tested with bias-corrected bootstrap confidence intervals (CIs) based on 5,000 resamples. A 95% CI excluding zero indicated a significant mediation effect. Previous simulation studies have evaluated sample size requirements for detecting mediation effects under different effect size scenarios (13).

Figure 3 Schematic illustration of the mediation models evaluating the role of ECV in the associations between EAT characteristics and HFpEF. (A) Basic mediation model. (B,C) Path diagram of mediation analysis showing ECV as mediator of the association between EAT characteristics and HFpEF. Coefficient c = total effect of independent variable (X) on dependent variable (Y); a = effect of X on mediator (M); coefficient b = effect of M on Y after controlling for X; c’ = direct effect of X on Y after controlling for M. *, P<0.05. EAT, epicardial adipose tissue; ECV, extracellular volume; HFpEF, heart failure with preserved ejection fraction.

Results

Baseline characteristics of patients

A total of 140 postmenopausal women (70 with HFpEF and 70 age-matched non-HF controls) were included in this study. The baseline clinical characteristics of the two groups are summarised in Table 1. Compared with the non-HF controls, the HFpEF group showed significantly higher levels of N-terminal pro-brain natriuretic peptide, lower haematocrit, and poorer renal function (all P<0.001). The prevalence of hypertension and atrial fibrillation was also significantly higher in the HFpEF group (all P<0.05). No significant intergroup differences were observed in body mass index (BMI), obesity (BMI ≥28 kg/m²) (14), diabetes, or dyslipidaemia.

Echocardiographic parameters

The echocardiographic parameters are presented in Table 2. Postmenopausal women with HFpEF demonstrated significant differences in multiple parameters compared with controls, including greater LVMM, LVMM index, LVEDV index, LVESV index, LAV index, IVST, and mean E/e’, alongside lower septal and lateral e' velocities (all P<0.05). However, LVEF and E-wave velocity did not differ significantly between the groups.

Cardiac CT parameters

EAT volume, volume index, density, and ECV were significantly higher in patients with HFpEF than in controls (all P<0.05; Table 2). There was no significant difference in radiation dose between the two groups (P>0.05; Table 2).

Relation between EAT parameters, ECV, and HFpEF in the entire population

In each multivariate logistic regression, Model 1 included BMI; Model 2 was adjusted for Model 1 plus cardiovascular risk factors (dyslipidaemia, hypertension, and diabetes); Model 3 was adjusted for Model 2 plus potential confounders [atrial fibrillation and estimated glomerular filtration rate (eGFR)]. The association between EAT volume index and HFpEF was statistically significant in both Model 1 and Model 2 (P=0.015 and P=0.019, respectively). The associations of EAT density and ECV with HFpEF remained significant across three models (all P<0.005). In Model 3, both EAT density [per 1-HU increase; odds ratio (OR) =1.209; 95% CI: 1.073–1.362; P=0.002] and ECV (per 1% increase; OR =1.306; 95% CI: 1.104–1.510; P=0.001) were independently associated with HFpEF (Table 3).

Associations between EAT volume index and density

An inverse association was observed between EAT volume index and EAT density in both the HFpEF group (β =−0.25, P=0.037) and the non-HF group (β =−0.64, P<0.001). This inverse association was significantly attenuated in the HFpEF group compared with the control group (P_interaction=0.015) (Figure 4). These findings indicate that for comparable EAT volume index values, EAT density was consistently higher in patients with HFpEF than in controls.

Figure 4 The inverse relationship between EAT volume index and density in HFpEF and non-HF groups. For any value of EAT volume index, EAT density was higher in HFpEF compared with non-HF. EAT, epicardial adipose tissue; HF, heart failure; HFpEF, heart failure with preserved ejection fraction; HU, Hounsfield unit.

Mediation effects of ECV in the relation between EAT density and HFpEF

Mediation analysis was performed to assess whether ECV mediated the association between EAT parameters and HFpEF (Table 4, Figure 3). The association between EAT density and HFpEF was partially mediated by ECV. The total effect consisted of a significant direct effect (0.223; 95% CI: 0.005–0.342) and a significant indirect effect via ECV (0.188; 95% CI: 0.094–0.296), which accounted for 47.7% of the total effect. Multiple linear regression analysis showed that EAT density was independently associated with ECV in the postmenopausal population after adjustment for BMI, eGFR, and metabolic and cardiovascular diseases (β =0.39, P<0.001) (Figure 5). No significant association was found between the EAT volume index and ECV (P=0.719), providing no evidence of a mediating role of ECV in the association between EAT volume index and HFpEF. Given the cross-sectional design, the mediation analysis reflects statistical associations rather than causal inference.

Figure 5 Scatter plot showing the positive relationship between EAT density and ECV in the overall postmenopausal population. EAT, epicardial adipose tissue; ECV, extracellular volume; HU, Hounsfield unit.

Discussion

In this cross-sectional study of postmenopausal women, we compared EAT characteristics and ECV between patients with HFpEF and controls, and examined the interrelationships among these parameters. The main findings were: (I) patients with HFpEF had higher EAT volume, volume index, density, and ECV than controls; (II) multivariate logistic regression showed that both EAT density and ECV were more strongly and independently associated with HFpEF than the EAT volume index; (III) the EAT volume index was inversely related to density, and this association was significantly weaker in patients with HFpEF than in non-HF controls; (IV) the association between EAT density and HFpEF was partially mediated by ECV, which explained 47.7% of the effect; (V) EAT density was independently associated with ECV. To our knowledge, this is the first study to simultaneously investigate the interplay between EAT volume, density, and myocardial ECV, and to propose a mediating role of myocardial fibrosis in the relation between EAT phenotype and HFpEF in postmenopausal women.

We found expanded EAT volume in postmenopausal women with HFpEF, consistent with previous studies in general HFpEF populations (15,16). This expansion may exacerbate cardiac dysfunction through pericardial restraint, haemodynamic derangement, and ventricular interdependence (17-19). Moreover, EAT provides energetic substrates to the myocardium during the high energy demands of HFpEF (7). After menopause, a distinct change caused by oestrogen deficiency is the redistribution of subcutaneous fat to the visceral compartment (20). In our study, EAT accumulation was independent of BMI. We therefore speculate that this redistribution is more prominent in the pathophysiology of HFpEF after menopause. However, the association between the EAT volume index and HFpEF was no longer significant after adjustment for clinical covariates, suggesting that the contribution of EAT volume may not be independent but rather closely linked to the overall burden of cardiometabolic risk factors common in HFpEF.

Some studies have demonstrated that the pathogenic function of EAT does not solely depend on the quantity and size of adipocytes (6,17,21). Beyond volume, CT-derived EAT density has emerged as a marker of adipose tissue quality. Elevated EAT density serves as an imaging surrogate for local and systemic inflammation and is linked to adverse metabolic profiles, cardiovascular risk, and all-cause and cardiovascular mortality (7,22). Our study showed that a higher EAT density was independently associated with HFpEF after adjusting for traditional risk factors, metabolic and cardiovascular diseases. Our finding of elevated EAT density provides direct imaging evidence of a localised cardiac inflammation. This is consistent with the concept that systemic inflammation, potentially triggered by postmenopausal oestrogen deficiency (23), may contribute to a pro-inflammatory transformation of EAT (3,24), which may be reflected by increased density. We propose that this inflammation-related EAT phenotype may represent a possible local contributor to HFpEF in postmenopausal women.

Another interesting finding was the altered relationship between EAT parameters. An inverse association between EAT volume index and density was observed in both groups, and this relation was significantly attenuated in the HFpEF group. This weakened inverse relationship may reflect a pathological remodelling of EAT specific to HFpEF in postmenopausal patients. Under physiological conditions, adipocyte hypertrophy and proliferation are accompanied by angiogenesis (25). It is plausible that the increase in low-attenuation lipid content exceeds the addition of higher-attenuation vascular tissue, resulting in the inverse relationship between EAT volume and density. However, in postmenopausal patients with HFpEF, the expansion of pro-inflammatory white adipose tissue (26) is coupled with inadequate neo-angiogenesis, resulting in adipose tissue hypoxia (27). This hypoxic stress triggers an inflammatory response, leading to the secretion of interleukin (IL)-1β, IL-6, IL-8, IL-10, and tumour necrosis factor-α (TNF-α) (28,29). These inflammatory cytokines are subsequently released into the bloodstream, potentially exacerbating systemic inflammation (3), thereby creating a vicious cycle. This process ultimately manifests on CT imaging as a weakened inverse relationship between EAT density and volume index. The perturbation of the EAT volume-density relationship, reflecting a loss of EAT homeostasis, provides complementary imaging evidence that underscores the role of EAT in the pathogenesis of postmenopausal HFpEF.

MIF is closely linked to diastolic dysfunction in HFpEF (4), and its extent can be assessed by measuring ECV using DECT (11). Oestrogen deficiency has been implicated in abnormal diastolic function and MIF (30). Evidence suggests that systemic inflammation induces coronary microvascular endothelial dysfunction and oxidative stress. This pro-oxidant and inflammatory milieu, in turn, activates profibrotic signalling pathways, leading to myocardial fibrosis. However, as an active inflammatory organ in postmenopausal women (3), with unique anatomical proximity to the myocardium and shared microcirculation (31), the relationship between EAT-derived inflammation, myocardial fibrosis, and HFpEF in this population has not been adequately studied. To investigate whether EAT promotes HFpEF via myocardial fibrosis, we performed mediation analysis. We found that ECV mediated 47.7% of the total effect of EAT density on HFpEF, indicating that pro-inflammatory EAT exerts nearly half of its detrimental effect by promoting myocardial fibrosis. Moreover, we found that EAT density was independently associated with ECV after adjusting for cardiometabolic risk factors and comorbidities. These findings provide clinical evidence for the ‘infiltrative-lipotoxic hypothesis’ of EAT pathogenesis (32). This hypothesis posits that inflamed EAT promotes myocardial fibrosis through paracrine secretion of pro-inflammatory and pro-fibrotic cytokines (e.g., IL-1β, IL-6, TNF-α), leading to diastolic dysfunction and the clinical syndrome of HFpEF (32). The remaining 52.3% of the effect suggests additional direct pathways, such as impaired coronary microvascular function or direct lipotoxicity. In contrast, ECV did not mediate the effect of the EAT volume index on HFpEF, implying that expansion of EAT may influence HFpEF through distinct mechanisms, such as mechanical compression or systemic metabolic effects. Our study provides direct clinical evidence linking EAT inflammation to MIF in postmenopausal women with HFpEF.

The role of EAT, especially EAT density, has garnered increasing attention in cardiovascular disease. A recent study found that EAT density is a stronger predictor of readmission and endpoint events than EAT volume in patients with HFpEF (21). Our findings align with and extend this concept by showing that increased EAT density, indicative of an inflammatory state, was independently associated with HFpEF in postmenopausal women, even after adjustment for traditional risk factors and comorbidities. In contrast, EAT volume index did not remain significant after multivariable adjustment and was not associated with ECV, suggesting that EAT density may represent a more robust independent imaging marker in this study. Crucially, our mediation analysis suggests that this effect is substantially mediated by MIF, as quantified by ECV. This provides a mechanistic link between EAT inflammation and HFpEF pathogenesis in this population. The potential clinical relevance is supported by work from Pugliese et al., which showed that statins can reduce EAT density independent of lipid-lowering effects in postmenopausal women (7). Beyond statins, other cardiometabolic therapies, including renin-angiotensin system inhibitors and, more recently, sodium-glucose cotransporter 2 (SGLT2) inhibitors, have also been implicated in myocardial remodelling and fibrosis, while SGLT2 inhibitors may additionally influence EAT characteristics (33-35). Similarly, dietary factors may also influence EAT characteristics and inflammatory activity (36,37). Future prospective studies with systematic assessment of both pharmacological treatments and dietary factors are warranted to explore whether these interventions may modify EAT-related imaging characteristics and ECV-derived myocardial fibrotic changes, and thereby influence the HFpEF phenotype. Taken together, these findings suggest that EAT, particularly its inflammation-related imaging phenotype and its association with ECV-derived myocardial fibrosis, may represent a promising therapeutic target in HFpEF, particularly in postmenopausal women. Whether a similar EAT-fibrosis axis exists in other HFpEF populations, including men and women with different hormonal states, requires further investigation.

The present study has some limitations. First, inflammatory biomarkers (e.g., high-sensitivity C-reactive protein), which could have provided valuable insights into the systemic inflammatory status and its correlation with EAT density, were not systematically collected. While such biomarkers do not directly reflect local EAT inflammation, this omission precludes a more comprehensive analysis of the systemic inflammation-EAT-cardiac fibrosis axis. Second, the relatively modest sample size, although sufficient for the primary mediation analysis, may limit the statistical power for broader multivariate analyses and subgroup investigations. Future studies with larger cohorts are needed to validate and extend our findings. Third, ECV was quantified using DECT rather than cardiac magnetic resonance T1 mapping, the reference standard. However, prior studies have established an excellent correlation between DECT- and CMR-derived ECV values (38). Moreover, DECT offers practical advantages in clinical settings, including wider availability, simpler acquisition, and the absence of ECV calculation mismatch, making these findings more generalisable to routine practice. Fourth, EAT and ECV measurements were derived using dedicated post-processing software with largely automated workflows; however, formal intra- and inter-observer reproducibility analyses were not performed in the present study.

Conclusions

In conclusion, this study demonstrates that increased EAT density, indicative of local and systemic inflammation, contributes to the development of HFpEF in postmenopausal women by promoting myocardial fibrosis. In the era of precision medicine, unenhanced CT-derived EAT parameters represent promising non-invasive imaging biomarkers for the assessment and treatment of post-menopause-specific HFpEF, and EAT itself may represent a novel therapeutic target.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2744/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2744/dss

Funding: This study was supported by the 2023 Jiangsu Provincial Health Commission Medical Research Project (No. Z2023048) and Science and Technology Project of Nantong (Nos. MS2023068 and MS12021101).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2744/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Nantong First People’s Hospital (No. 2025KT046) and informed consent was taken from all the patients.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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