Search

Purpose of the study. A comprehensive quantification of ectopic fat depots using modern methods of radiation diagnosis in patients with ischemic heart disease.Patients and methods. The study included 76 patients with a verified diagnosis of ischemic heart disease (IHD). The control group consisted of 32 people without clinical manifestations of IHD. All patients to assess the area and volume of visceral adipose tissue, as well as measuring the volume of paraaortic adipose tissue at the level of the abdominal aorta were performed multispiral computed tomography (MSCT) at the level of L3–L5 vertebrae. In order to visualize and morphometry pericoronary and paraaortic adipose tissue at the level of the thoracic aorta, patients in both groups were performed MSCT angiography of the coronary arteries with ECG synchronization. To visualize the epicardial fat depot with an assessment of the thickness of the adipose tissue layer, magnetic resonance imaging (MRI) of the heart was performed.Results. During the comparative analysis, significantly higher values of quantitative indicators of the main ectopic fat depots were noted in patients with coronary artery disease. Estimation of the prevalence of obesity according to BMI data in the compared groups showed no significant differences. Considering the standard values of the area and volume of visceral adipose tissue, the prevalence of obesity was significantly higher in the group of patients with IHD. Conducted correlation analysis showed the relationship of quantitative indicators of ectopic visceral, para-aortic and epicardial fat depots. Moreover, in the group of patients with IHD, stronger correlations were found between the fat depots of different localization (r = 0,71, p = 0,013 in group with IHD and r = 0,59, p = 0,039 in group without IND).Conclusion. Modern tomographic methods allow for a comprehensive quantification of ectopic fat depots. Significantly higher morphometry indices of the studied fat depots in patients with coronary artery disease demonstrate the need to develop a unified diagnostic algorithm for reliable stratification of cardiometabolic risk.