Threshold for the upper normal limit of indexed epicardial fat volume: Derivation in a healthy population and validation in an outcome-based study Academic Article uri icon


MeSH Major

  • Adipose Tissue
  • Coronary Artery Disease
  • Pericardium
  • Tomography, X-Ray Computed


  • Epicardial fat volume (EFV) quantified on noncontrast cardiac computed tomography relates to cardiovascular prognosis. We sought to define the upper normal limit of body surface area (BSA)-indexed EFV (EFVi) in a healthy population and to validate it as a predictor of major adverse cardiovascular events (MACE). We analyzed noncontrast cardiac computed tomography scans of 226 healthy subjects with a low Framingham Risk Score (FRS; ≤6%) performed for coronary calcium scoring (CCS). EFV was quantified using validated software and indexed to BSA. We defined the 95th percentile as the upper normal limit. Subsequently, we reanalyzed a separate cohort of 232 participants from a previously published case-control study with 4-year follow-up and 58 cases of MACE to test the additive value of an abnormally high EFVi for predicting MACE. Of the 226 healthy participants 51% were men (mean age 52 ± 9 years). EFV correlated to BSA (r = 0.373, p <0.0001). Median, range, and 25th and 75th percentiles of the non-normally distributed EFVi were 33.3, 10.8 to 96.6, and 24.5 and 45.5 cm(3)/m(2). The 95th percentile definition of the upper normal limit of EFVi was 68.1 cm(3)/m(2). For prediction of MACE, EFVi values higher than the newly defined threshold emerged as a significant and independent predictor after controlling for confounders (odds ratio 2.8, 95% confidence interval 1.3 to 6.4, p = 0.012) and trended in its additive value to the combination of CCS ≥400 and FRS (area under the receiver operating characteristic curve 0.714 vs 0.675, p = 0.1277). In conclusion, in a healthy population we determined 68.1 cm(3)/m(2) as the 95th percentile threshold for abnormally high EFVi. EFVi exceeding this value independently predicted MACE and trended to add to CCS and FRS in this prediction.

publication date

  • December 2011



  • Academic Article



  • eng

PubMed Central ID

  • PMC3215795

Digital Object Identifier (DOI)

  • 10.1016/j.amjcard.2011.07.031

PubMed ID

  • 21880291

Additional Document Info

start page

  • 1680

end page

  • 5


  • 108


  • 11