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Automated quantification of epicardial adipose tissue (EAT) in coronary CT angiography; comparison with manual assessment and correlation with coronary artery disease.

Abstract：

BACKGROUND:Epicardial adipose tissue (EAT) is emerging as a risk factor for coronary artery disease (CAD). OBJECTIVE:The aim of this study was to determine the applicability and efficiency of automated EAT quantification. METHODS:EAT volume was assessed both manually and automatically in 157 patients undergoing coronary CT angiography. Manual assessment consisted of a short-axis-based manual measurement, whereas automated assessment on both contrast and non-contrast-enhanced data sets was achieved through novel prototype software. Duration of both quantification methods was recorded, and EAT volumes were compared with paired samples t test. Correlation of volumes was determined with intraclass correlation coefficient; agreement was tested with Bland-Altman analysis. The association between EAT and CAD was estimated with logistic regression. RESULTS:Automated quantification was significantly less time consuming than automated quantification (17 ± 2 seconds vs 280 ± 78 seconds; P < .0001). Although manual EAT volume differed significantly from automated EAT volume (75 ± 33 cm(³) vs 95 ± 45 cm(³); P < .001), a good correlation between both assessments was found (r = 0.76; P < .001). For all methods, EAT volume was positively associated with the presence of CAD. Stronger predictive value for the severity of CAD was achieved through automated quantification on both contrast-enhanced and non-contrast-enhanced data sets. CONCLUSION:Automated EAT quantification is a quick method to estimate EAT and may serve as a predictor for CAD presence and severity.

journal_name

J Cardiovasc Comput Tomogr

journal_title

Journal of cardiovascular computed tomography

authors

Mihl C,Loeffen D,Versteylen MO,Takx RA,Nelemans PJ,Nijssen EC,Vega-Higuera F,Wildberger JE,Das M

doi

10.1016/j.jcct.2014.04.003

subject

Has Abstract

pub_date

2014-05-01 00:00:00

pages

215-21

issue

eissn

1934-5925

issn

1876-861X

pii

S1934-5925(14)00096-3

journal_volume

pub_type

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Automated quantification of epicardial adipose tissue (EAT) in coronary CT angiography; comparison with manual assessment and correlation with coronary artery disease.