title: Epicardial fat from echocardiography: a new method for visceral adipose tissue prediction.
abstract: OBJECTIVE
  To validate transthoracic echocardiography as an easy and reliable imaging method for visceral adipose tissue (VAT) prediction. VAT is recognized as an important indicator of high cardiovascular and metabolic risk. Several methods are applied to estimate VAT, with different results.
  
  
  METHODS
  We selected 60 healthy subjects (29 women, 31 men, 49.5 +/- 16.2 years) with a wide range of body mass indexes. Each subject underwent transthoracic echocardiogram and magnetic resonance imaging (MRI) to measure epicardial fat thickness on the right ventricle. Measurements of epicardial adipose tissue thickness were obtained from the same echocardiographic and MRI views and points. MRI was also used to measure VAT cross-sectional areas at the level of L4 to L5. Anthropometric indexes were also measured.
  
  
  RESULTS
  Subjects with predominant visceral fat accumulation showed higher epicardial adipose tissue thickness than subjects with predominant peripheral fat distribution: 9.97 +/- 2.88 vs. 4.34 +/- 1.98 (p = 0.005) and 7.19 +/- 2.74 vs. 3.43 +/- 1.64 (p = 0.004) in men and women, respectively. Simple linear regression analysis showed an excellent correlation between epicardial adipose tissue and waist circumference (r = 0.895, p = 0.01) and MRI abdominal VAT (r = 0.864, p = 0.01). Multiple regression analysis showed that epicardial adipose tissue thickness (r(2) = 0.442, p = 0.02) was the strongest independent variable correlated to MRI VAT. Bland test confirmed the good agreement between the two methods.
  
  
  CONCLUSIONS
  Epicardial adipose tissue showed a strong correlation with anthropometric and imaging measurements of VAT. Hence, transthoracic echocardiography could be an easy and reliable imaging method for VAT prediction.
authors.affiliation: Endocrinology, Department of Clinical Sciences, "La Sapienza" University, Rome Italy. gianluca.iaco@tin.it
authors.forename: Gianluca
authors.initials: G
authors.lastname: Iacobellis
authors.forename: Filippo
authors.initials: F
authors.lastname: Assael
authors.forename: Maria Cristina
authors.initials: MC
authors.lastname: Ribaudo
authors.forename: Alessandra
authors.initials: A
authors.lastname: Zappaterreno
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Alessi
authors.forename: Umberto
authors.initials: U
authors.lastname: Di Mario
authors.forename: Frida
authors.initials: F
authors.lastname: Leonetti
mesh_terms: D000273:Adipose Tissue / Q000000981:diagnostic imaging*; D000328:Adult; D000368:Aged; D001823:Body Composition; D001824:Body Constitution; D004452:Echocardiography; D005260:Female; D006801:Humans; D016014:Linear Models; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D010496:Pericardium / Q000000981:diagnostic imaging*; D012044:Regression Analysis; D014781:Viscera