P3437Impact of epicardial adipose tissue on global longitudinal strain: a study in patients with normal left ventricular ejection fraction

Background

Epicardial adipose tissue (EAT) locates anatomically and functionally contiguous to the myocardium and coronary arteries. It has been suggested that EAT accumulation is associated with cardiac remodeling and impaired cardiac performance. However, its role in left ventricular (LV) wall strain remains unclear.

Purpose

In this study, we aimed to clarify: whether EAT accumulation is related to global longitudinal (GLS), circumferential (CS) and radial strain (RS); and if so, in which extent or by which amount of EAT are required to deteriorate these strain.

Methods

Total 180 patients who had no obstructive coronary artery disease (CAD) on multi-detector computed tomography (MDCT) coronary angiography and normal left ventricular ejection fraction (LVEF) on conventional echocardiography were recruited. Cardiac CT was used to quantify EAT volume (EATV) and echocardiographic speckle tracking was used to measure the GLS, CS and RS. EATV index (EATV/Body surface area) was determined as: EAT volume, the sum of the EAT area from the base to the apex of the heart (cm3)/body surface area (m2). Adipose tissue was determined as the density range between −190 and −30 Hounsfield unit. According to the median value (68 cm3/m2), patients were divided into lower and higher EATV index two groups.

Results

In higher EATV index group (95±19 cm3/m2), mean age, body mass index (BMI), prevalence of hyperlipidemia and prevalence of CAD were larger than in lower EATV index group (48±14 cm3/m2). Male gender, hypertension, diabetes, smoking and LV mass index were comparable between two groups. Patients in higher EATV index had lower GLS than those in lower EATV index (−19.4±1.2% vs. −18.8±1.3%, p=0.002). However, there were no significant difference between two groups regarding to the CS and RS. Linear regression analysis showed that there was strong correlation between EATV index and GLS (R=0.216, p=0.004); whereas, both RS and CS were strongly associated with the interventricular septum thickness (RS: R=0.248, p=0.003; CS: R= −0.192, p=0.023) and relative wall thickness (RS: R=0.178, p=0.036; CS: R= −0.184, p=0.030) but not with EATV; on multiple regression analysis, EATV was a predictor of GLS independent of age, male gender, BMI, diabetes, hyperlipidemia, hypertension and CAD (Adjusted R2=0.238, p<0.001).

Conclusion

EATV is independently associated with GLS despite the preserved LVEF and lacking of obstructive CAD, and may play a significant role in estimating impaired longitudinal LV performance.

P5304Adipose tissue surrounding the kidney and its impact on coronary artery disease

Background

Growing evidence suggests that visceral adipose tissue has systemic and local impact for the development of cardiovascular disease. Previously, we reported that epicardial adipose tissue, as one of visceral fat, was a risk factor for the development of coronary artery disease (CAD). However, the association between another visceral adiposity kidney fat and CAD remains unclear.

Purpose

In this study we aimed to clarify whether there exists link between adipose tissue surrounding the kidney and CAD among patients.

Method

The study population consisted of 201 consecutive patients who underwent 320-slice multi-detector computed tomography (MDCT) coronary angiography. Study subjects were divided into the CAD (≥1 coronary artery stenosis of ≥50%) and non-CAD groups. Adipose tissue surrounding the kidney were quantified by the computed tomography and peri-renal fat volumetric measurements were performed on axial views by manually placing the Region of Interest (ROI) on the renal fascia. The peri-renal fat area of each slice was summed and multiplied by the slice thickness and number of slices to determine the total peri-renal fat volume. Adipose tissue was determined as the density range was −190 to −30 Hounsfield unit. Peri-renal fat volume were indexed by body surface area (BSA).

Results

The mean age was higher in CAD group than those in non-CAD (66±11 vs. 71±10 years, p=0.005). The diabetes, hypertension and hyperlipidemia were significantly prevalent in CAD comparing to non-CAD group. BSA adjusted Peri-renal fat volume was significantly larger in CAD than those in non-CAD (43±27 vs. 60±39 ml/m2). Linear regression analysis showed that BSA adjusted peri-renal fat volume was significantly correlated with visceral fat area (VFA) (R=0.729, p<0.001). Multiple regression analysis for estimating CAD showed that BSA adjusted peri-renal fat volume was a predictor of CAD after adjusting for confounding factors which including age, gender, body mass index, smoking, hypertension, hyperlipidemia, diabetes and VFA (Adjusted R2=0.201, p<0.001); In addition, in the above traditional risk factors model even when the VFA was replaced by the eGFR<60 ml/min/1.73m2, the BSA adjusted peri-renal fat volume still keep a significance for predicting the CAD in the multivariate analysis (Adjusted R2=0.198, p<0.001).

Conclusion

Peri-renal fat volume might be a predictor of CAD. Kidney fat at least partially may contributes to the development of CAD by impaired kidney function.