The Role of Quantitative Assessment of Visceral Adipose Tissue of the Heart as a Predictor for Cardiovascular Events

Chernina, Valeria; Морозов, С. П.; Низовцова, Л. А.; Blokhin, Ivan; Sitdikov, D.; Гомболевский, В. А.

doi:10.20862/0042-4676-2019-100-6-387-394

Cited by 4 publications

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References 30 publications

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“…Объем ЭЖТ с высокой точностью может быть измерен с помощью КТ (ручной, полуавтоматической и автоматической методиками) [12][13][14][15]. Ручная и полуавтоматическая методики достаточно трудоемки и времязатратны, что препятствует их внедрению в повседневную практику.…”

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Epicardial fat Tissue Volumetry: Comparison of Semi-Automatic Measurement and the Machine Learning Algorithm

et al. 2020

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Aim To compare assessments of epicardial adipose tissue (EAT) volumes obtained with a semi-automatic, physician-performed analysis and an automatic analysis using a machine-learning algorithm by data of low-dose (LDCT) and standard computed tomography (CT) of chest organs.Material and methods This analytical, retrospective, transversal study randomly included 100 patients from a database of a united radiological informational service (URIS). The patients underwent LDCT as a part of the project “Low-dose chest computed tomography as a screening method for detection of lung cancer and other diseases of chest organs” (n=50) and chest CT according to a standard protocol (n=50) in outpatient clinics of Moscow. Each image was read by two radiologists on a Syngo. via VB20 workstation. In addition, each image was evaluated with a developed machine-learning algorithm, which provides a completely automatic measurement of EAT.Results Comparison of EAT volumes obtained with chest LDCT and CT showed highly consistent results both for the expert-performed semi-automatic analyses (correlation coefficient >98 %) and between the expert layout and the machine-learning algorithm (correlation coefficient >95 %). Time of performing segmentation and volumetry on one image with the machine-learning algorithm was not longer than 40 sec, which was 30 times faster than the quantitative analysis performed by an expert and potentially facilitated quantification of the EAT volume in the clinical conditions.Conclusion The proposed method of automatic volumetry will expedite the analysis of EAT for predicting the risk of ischemic heart disease.

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Epicardial fat Tissue Volumetry: Comparison of Semi-Automatic Measurement and the Machine Learning Algorithm

et al. 2020

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Clinical significance of epicardial fat assessment in hypertensive patients with non-alcoholic fatty liver disease

Стаценко

2022

Arter. gipertenz.

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Objective. To study the relationship between the thickness of epicardial adipose tissue (EAT) and indicators of the structural and functional heart characteristics and cardiovascular risk in hypertensive patients with nonalcoholic fatty liver disease (NAFLD).Design and methods. A comparative cross-sectional study was conducted involved 120 patients, aged 45 to 65 years, with hypertension (HTN) of I–II stages, degrees 1–2, with NAFLD (Fatty Liver Index (FLI > 60)) and without NAFLD. A clinical examination was carried out: history, physical examination, measurement of “office” blood pressure and heart rate, anthropometric parameters (height, weight, body mass index). The indicators of carbohydrate and lipid metabolism, chronic low-intensity inflammation (C-reactive protein (CRP), tumor necrosis factor alpha (TNF-α)) were determined, insulin resistance indices were calculated. The structural and functional state of the liver and heart was assessed by ultrasound, and the thickness of the EAT was determined. The SCORE scale was used to assess the 10-year fatal risk.Results. Indicators characterizing chronic low-intensity systemic inflammation (CRP, TNF-α) and insulin resistance (HOMA-IR metabolic index (MI), triglycerides (TG) / high-density lipoproteins (HDL)) were higher in patients with HTN and NAFLD than in patients with isolated HTN. Echocardiography showed that patients with comorbid pathology had greater EAT thickness (p < 0,001) and more profound left ventricular myocardial hypertrophy (thickness of the left ventricular posterior wall (LVPW) (p = 0,019), interventricular septum (IVS) (p = 0,012), left ventricular myocardial mass (LVMM) (p = 0,029)). In the group of patients with HTN and NAFLD, the correlation analysis showed direct moderate-strong relationships between EAT thickness and TPWLV (r = 0,345, p < 0,001), IVS (r = 0,344, p < 0,001), LVMM (r = 0,372, p < 0,001), index LVMM (r = 0,221, p = 0,015), FLI (r = 0,722, p < 0,001), TNF-α (r = 0,495, p < 0,001), HOMA-IR (r = 0,38, p < 0,001), MI (r = 0,374, p < 0.001), TG/HDL (r = 0,354, p < 0,001), CRP (r = 0,30, p = 0,002), TG (r = 0,305, p = 0,001), very low density lipoprotein cholesterol (r = 0,306, p = 0,001) and medium strength inverse relationship with HDL (r = 0,30, p = 0,008). A multiple regression analysis was performed to assess the relationship between EAT thickness and the severity of chronic systemic inflammation and insulin resistance in patients with HTN and NAFLD: with an increase in TNF-α by 1 pg/ml and TG/HDL by 1, an increase in EAT thickness by 0,15 and 0,68 mm, respectively, should be expected. An increase in EAT thickness by 1 mm was accompanied by an increase in LVMM by 12,8 g. Logistic regression analysis showed a direct relation between EAT thickness and the probability of cardiovascular 10-year risk increase by 5,0% or more.Conclusions. This study showed that in patients with HTN and NAFLD, the EAT thickness was significantly higher, which strongly correlates with indicators of left ventricular hypertrophy, the severity of liver steatosis (FLI), chronic low-intensity systemic inflammation, and insulin resistance. With an increase in TNF-α and TG/HDL, an increase in the EAT thickness should be expected. EAT thickness was significantly associated with an increase in LVMM and increased chance of high and very high risk of cardiovascular complications in patients with HTN and NAFLD.

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Cardiac visceral fat volume estimation from low-dose chest computed tomography: a study with a designed beating heart phantom

Chernina

Kulberg

Aleshina

et al. 2021

Almanac of Clinical Medicine

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Background: Since 2017, a pilot project for lung cancer screening by chest low dose computed tomography (LDCT) has been implemented in Moscow. Patients to be included into the screening have risk factors for ischemic heart disease (IHD). The association between epicardial adipose tissue (EAT) volume and coronary artery atherosclerosis, IHD, and atrial fibrillation has been demonstrated previously.Aim: To demonstrate the feasibility of LDCTbased EAT volumetry using a dynamic (contracting) heart phantom.Materials and methods: The study was performed with the designed dynamic heart phantom and chest phantom in two stages. At stage I, two adipose tissue pieces were scanned inside and outside the chest phantom using CT and LDCT. At stage II, the dynamic heart phantom was scanned outside and inside the chest phantom. In addition, we scanned the heart phantom with a coronary calcium phantom. The contracting heart phantom was developed within three months. All scans of the phantom were performed within one day. We determined the adipose tissue thresholds in LDCT and the EAT volumetric error with both chest CT and LDCT. Measurements of the adipose tissue volumes were performed by the radiologist twice with semi-automatic software.Results: The results of stage I helped to identify optimal density thresholds for LDCT-based adipose tissue volumetry in lung cancer screening, ranging from -250 HU to -30 HU. The stage II results showed that for all heart phantom scanning variants, the average EAT volumetry error did not exceed 5%, except for the case of contracting heart phantom with added coronary calcium in a chest phantom with body mass index (BMI) 29 (-5.92%). Adding the coronary calcium phantom to the heart phantom in LDCT increased the error by an average of 4% in BMI 23 and BMI 29 chest phantoms.Conclusion: LDCT-based EAT volumetry with fat density threshold from -250 HU to -30 HU is feasible in lung cancer screening, including patients with coronary calcium. However, considering the phantom design, further patient studies, and correlation of EAT volumes between LDCT for lung cancer screening and сoronary CT angiography are required.

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The Role of Quantitative Assessment of Visceral Adipose Tissue of the Heart as a Predictor for Cardiovascular Events

Cited by 4 publications

References 30 publications

Epicardial fat Tissue Volumetry: Comparison of Semi-Automatic Measurement and the Machine Learning Algorithm

Epicardial fat Tissue Volumetry: Comparison of Semi-Automatic Measurement and the Machine Learning Algorithm

Clinical significance of epicardial fat assessment in hypertensive patients with non-alcoholic fatty liver disease

Cardiac visceral fat volume estimation from low-dose chest computed tomography: a study with a designed beating heart phantom

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