Rapid Fire Session

Session: Rapid Fire Session 5: Coronary Artery Disease, Coronary Microvascular Dysfunction, and Perfusion (Monitor 13)

Epicardial Adipose Tissue Composition is More Strongly Associated than Quantity with the diagnosis of HFpEF and HFpEF-related Coronary Microvascular Dysfunction

Saturday, February 7, 2026

10:22 AM - 10:29 AM

Location: Galapagos / Aruba / Ilhabela (2nd Lower Level)

Presenting Author(s)

John T. Echols, PhD

Post-doctoral Research Associate
University of Virginia
Charlottesville, Virginia, United States

Primary Author(s)

SW

Shuo Wang, MD, PhD

Research Associate
University of Virginia Health System
Charlottesville, Virginia, United States

Co-Author(s)

JC

Jamey Cutts, MD

Advanced Cardiac Imaging Fellow
University of Virginia Medical center
Charlottesville, Virginia, United States
JB

Julia Bresticker, MS

MD/PhD Student
University of Virginia
Charlottesville, Virginia, United States
Jonathan A. Pan, MD, MSc, MBA

Assistant Professor
University of Virginia Health System
Charlottesville, Virginia, United States
RH

Rohan Herur

MD Candidate
University of Virginia, United States
AA

Aayush C. Amin

MRI technolgist
University of Virginia Health System, Virginia, United States
MW

Matthew Wolf, MD, PhD

Associate Professor, Medicine: Cardiovascular Medicine
University of Virginia, United States
PK

Peter Kellman, PhD

Dr.
National Institutes of Health, Maryland, United States
Christopher M. Kramer, MD

Professor
University of Virginia Health
Charlottesville, Virginia, United States
Frederick H. Epstein, PhD

Professor
University of Virginia
Charlottesville, Virginia, United States
Amit R. Patel, MD, FSCMR

Professor of Medicine
Division of Cardiology, University of Virginia Health System, Charlottesville, Virginia, USA.
Charlottesville, Virginia, United States

Background: Coronary microvascular dysfunction (CMD) is a key pathophysiologic feature of heart failure with preserved ejection fraction (HFpEF). Epicardial adipose tissue (EAT) contributes to the development of HFpEF. In a murine model of HFpEF, using a novel CMR method, we have shown that M1 macrophage-related proinflammatory pathways are activated when the fatty acid composition (FAC) of EAT consists of increased saturated fatty acids (SFA) and decreased polyunsaturated fatty acids (PUFA)^[1]. We hypothesize that, in individuals with HFpEF, the FAC of EAT (a) will be characterized by a high fraction of SFA and low fraction of PUFA and (b) also be associated with the degree of CMD.

Methods: We prospectively enrolled 12 subjects with and 17 without a history of HFpEF who were referred for clinically indicated vasodilator stress CMR. Imaging was performed on a 1.5T scanner using a standardized protocol per SCMR guidelines. Quantitative rest and stress perfusion CMR were acquired using the dual-sequence inline technique, and myocardial perfusion reserve (MPR), a biomarker of CMD, was calculated as stress/rest myocardial blood flow (MBF). FAC imaging was acquired using a novel multi-echo gradient-echo chemical shift–encoded technique to quantify the fraction of SFA and PUFA within the EAT, subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT)^[2]. EAT FAC parameters were indexed to those of SAT to account for inter-individual differences in the propensity to store, mobilize, and synthesize lipid in different depots. EAT volume was quantified from the short-axis cine images and indexed to body surface area (EATVi). EAT T1, a biomarker of pro-inflammatory EAT, was measured using the short-axis T1-maps. Comparisons between history of HFpEF and non-history of HFpEF groups were made using t-tests, and linear regression assessed associations between imaging parameters and MPR.

Results: Baseline characteristics and images are shown in Table 1 and Figure 1. In the HFpEF group, both EAT SFA fraction (39 ± 4% vs 34 ± 3%, p=0.011), and EAT SFA index (1.18 ± 0.18 vs 1.00 ± 0.18, p=0.042) were significantly greater when compared to those without HFpEF, while the EAT PUFA fraction was lower in those with HFpEF (15 ± 2% vs 17 ± 3%, p=0.094). No significant differences were observed in the SAT or VAT FAC between groups. EAT SFA was significantly correlated with EAT T1 (r=–0.62, p=0.007) (figure 2a). The EAT SFA (r=–0.52, p=0.026), EAT SFA index (r=-0.65, p=0.004) and PUFA (r=0.51, p=0.03) fractions, but not the EATVi, were correlated with MPR (figure 2b-e).

Conclusion: We show for the first time that individuals with HFpEF have a pro-inflammatory EAT characterized by increased SFA and decreased PUFA – and that the FAC of EAT is more strongly associated than the amount of EAT with the severity of CMD. Future studies are needed to determine if alterations in the FAC of EAT can lead to improvements in HFpEF and its associated CMD.

Patient Demographics and Clinical Characteristics.

	Overall (n=29)	No hx of HFpEF (n=17)		Hx of HFpEF (n=12)	P value
Parameters	Mean ± SD or Median (interquartile range) or n (%)
Age, yrs	62 ± 12		59 ± 12	67 ± 11	0.077
BMI, kg/m2	31 ± 7		29 ± 6	34 ± 8	0.080
BSA, m2	1.9 ± 0.3		1.9 ± 0.3	1.9 ± 0.3	0.803
Gender, female, n (%)	20 (69%)		10 (58%)	10 (83%)	0.234
Ethnicity, n (%)					0.345
White	27 (93%)		16 (94%)	11 (92%)
African American	1 (3%)		0 (0)	1 (8%)
Others	1 (3%)		1 (6%)	0 (0)
Comorbidities, n (%)
Prior smoker	10 (35%)		3 (17%)	7 (58%)	0.030
Current smoker	3 (10%)		0 (0)	3 (25%)	0.060
Obesity	14 (48%)		6 (35%)	8 (67%)	0.099
CAD	6 (21%)		1 (6%)	5 (42%)	0.030
CV family hx	16 (55%)		10 (59%)	6 (50%)	0.463
Prior MI	3 (10%)		2 (12%)	1 (8%)	0.663
Diabetes	9 (31%)		4 (24%)	5 (42%)	0.263
Hypertension	18 (62%)		9 (53%)	9 (75%)	0.208
Hyperlipidemia	19 (66%)		10 (59%)	9 (75%)	0.309
OSA	9 (31%)		4 (24%)	5 (42%)	0.263
Chronic renal disease	5 (17%)		0 (0)	5 (42%)	0.007
Paroxysmal Atrial arrhythmia	2 (7%)		1 (6%)	1 (8%)	0.665
Medication, n (%)
Diuretics, n (%)	13 (45%)		4 (24%)	9 (75%)	0.008
MRA, n (%)	4 (14%)		1 (6%)	3 (25%)	0.178
SLG2i, n (%)	4 (14%)		0 (0)	4 (33%)	0.021
GLP-RA, n (%)	5 (17%)		1 (6%)	4 (33%)	0.078
CMR parameters
LVEF, %	61 ± 6		61 ± 6	62 ± 6	0.836
LVEDVI, ml/m²	68 ± 16		69 ± 17	67 ± 16	0.732
LVESVI, ml/m²	28 ± 9		28 ± 9	27 ± 9	0.853
LVMI, g/m²	49 ± 11		46 ± 9	53 ± 13	0.118
RVEF, %	56 ± 7		56 ± 8	56 ± 7	0.853
RVEDVI, ml/m²	71 ± 23		74 ± 27	67 ± 18	0.421
RVESVI, ml/m²	31 ± 12		33 ± 14	29 ± 8	0.387
LAVi, ml/m²	29 ± 12		28 ± 12	30 ± 12	0.694
LGE, n (%)	7 (22%)		0 (12%)	5 (42%)	0.080
Estimated LVFP (mmhg)	12 ± 2		12 ± 2	13 ± 3	0.336
Myocardial Native T1, ms	1008 ± 38		996 ± 32	1027 ± 39	0.031
ECV, %	28 ± 3		26 ± 3	30 ± 3	0.002
T2, ms	49 ± 3		48 ± 2	50 ± 3	0.044
EAT volume, ml	89 ± 33		78 ± 22	104 ± 40	0.031
EAT volume index, ml/m²	46 ± 13		41 ± 10	53 ± 15	0.134
EAT Native T1	N=22		N=12	N=10
EAT Native T1, ms	270 ± 18		273 ± 21	270 ± 15	0.405
PAT Native T1, ms	272 ± 31		273 ± 42	271 ± 25	0.756
Quantitative Perfusion
Rest MBF, ml/min/g	0.98 ± 0.31		0.87 ± 0.31	1.14 ± 0.23	0.028
Stress MBF, ml/min/g	2.12 ± 0.50		2.11 ± 0.54	2.13 ± 0.45	0.933
MPR	2.30 ± 0.71		2.58 ± 0.76	1.88 ± 0.32	0.011
Circumferential systolic peak strain	-18 ± 2		-19 ± 2	-18 ± 3	0.196
Longitudinal systolic peak strain	-17 ± 2		-18 ± 2	-16 ± 2	0.039
SFA
SFA_EAT	0.36 ± 0.04		0.34 ± 0.03	0.39 ± 0.04	0.011
SFA_SAT	0.34 ± 0.04		0.35 ± 0.05	0.33 ± 0.03	0.429
SFA_VAT	0.36 ± 0.03		0.36 ± 0.03	0.36 ± 0.04	0.946
SFA index	1.07 ± 0.20		1.00 ± 0.18	1.18 ± 0.18	0.042
PUFA
PUFA_EAT	0.16 ± 0.03		0.17 ± 0.03	0.15 ± 0.02	0.094
PUFA_SAT	0.14 ± 0.18		0.15 ± 0.18	0.14 ± 0.20	0.449
PUFA_VAT	0.18 ± 0.03		0.17 ± 0.02	0.18 ± 0.03	0.345

Figure 1. Epicardial adipose tissue (EAT) fatty acid composition (FAC) and quantitative myocardial perfusion CMR pixel-wise mapping on subjects with and without HFpEF. The top row shows a representative subject with HFpEF, with elevated EAT SFA fraction(a), reduced EAT PUFA fraction(b), and impaired MPR (c). The bottom row shows a subject without HFpEF, with lower EAT SFA fraction(d), higher EAT PUFA fraction(e), and preserved MPR (f). Red arrows indicate the EAT.

Figure 2. Linear regression plots demonstrating associations between epicardial adipose tissue (EAT) fatty acid composition and cardiovascular magnetic resonance (CMR) parameters. Significantly good correlations observed between EAT SFA fraction and native EAT T1 (a), EAT SFA fraction and myocardial perfusion reserve (MPR) (b), EAT SFA index and MPR (c), and EAT PUFA fraction and MPR (d). No significant correlation was observed between EAT volume index (EATVi) and MPR (e).