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Epicardial fat volume measured on nongated chest CT is a predictor of coronary artery disease

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A Correction to this article was published on 05 July 2019

This article has been updated

Abstract

Objective

To investigate whether epicardial fat volume (EFV) quantified on ECG-nongated noncontrast CT (nongated-NCCT) could be used as a reliable and reproducible predictor for coronary artery disease (CAD).

Methods

One hundred seventeen subjects (65 men, mean age 66.6 ± 11.9 years) underwent coronary CT angiography (CCTA) and nongated-NCCT during a single session because of symptoms suggestive of CAD. Two observers independently quantified EFV on both images. Correlation between CCTA-EFV and nongated-NCCT-EFV was assessed using Pearson’s correlation coefficient and Bland–Altman plots. Inter-observer agreement was analyzed using concordance correlation coefficients (CCC). Coronary risk factors including EFV were compared between CAD-positive (> 50% stenosis) and CAD-negative groups. The association between EFV and CAD was analyzed using multivariate logistic regression. ROC analysis was performed, and AUC was compared with DeLong’s method.

Results

Seventy-four subjects were diagnosed with CAD. An excellent correlation was noted between CCTA-EFV and nongated-NCCT-EFV (r = 0.948, p < 0.001), despite the systematic difference between both measurements (mean bias, 1.26). Inter-observer agreement was nearly perfect (CCC, 0.988 and 0.985 for CCTA and nongated-NCCT, respectively, p < 0.001). Significant differences were noted between subjects with versus without CAD in age, hypertension, and EFV on both types of images (p ≤ 0.026). Multivariate analysis revealed that increased EFV on CCTA (odds ratio 1.185, p = 0.003) and nongated-NCCT (odds ratio 1.20, p = 0.015) was independently associated with CAD. There was no significant difference between CCTA-EFV and nongated-NCCT-EFV in AUC for the prediction of CAD (0.659 vs 0.665, p = 0.706).

Conclusions

Despite the absence of ECG gating, EFV measured on NCCT may serve as a reproducible predictor for CAD with accuracy equivalent to EFV measured on CCTA.

Key Points

• Despite the absence of ECG gating, the EFV on NCCT provides nearly perfect inter-observer reproducibility and shows excellent correlation with measurements on gated CCTA.

• EFV on nongated-NCCT may serve as an independent biomarker for predicting coronary artery disease with accuracy equivalent to that of EFV on gated CCTA.

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Change history

  • 05 July 2019

    The original version of this article, published on 11 March 2019, unfortunately contained a mistake. The following correction has therefore been made in the original: the presentation of Fig. 5 was incorrect. The corrected figure is given below.

  • 05 July 2019

    The original version of this article, published on 11 March 2019, unfortunately contained a mistake. The following correction has therefore been made in the original: the presentation of Fig.��5 was incorrect. The corrected figure is given below.

Abbreviations

CAD:

Coronary artery disease

CCTA:

Coronary CT angiography

EF:

Epicardial fat

EFV:

Epicardial fat volume

NCCT:

Noncontrast CT

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Funding

The authors state that this work has not received any funding.

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Authors and Affiliations

  1. Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto, 860-8556, Japan

    Yasunori Nagayama, Seitaro Oda, Takeshi Nakaura & Yasuyuki Yamashita

  2. Department of Radiology, Minamata City General Hospital and Medical Center, 1-2-1, Tenjin-cho, Minamata, 867-0041, Japan

    Naoki Nakamura, Ryo Itatani, Shinichiro Kusunoki & Hideo Takahashi

  3. Department of Diagnostic Radiology, Yokohama City University Hospital, 3-9 Fukuura, Kanazawa-ku, Yokohama, 236-0004, Japan

    Daisuke Utsunomiya

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  1. Yasunori Nagayama
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Correspondence to Yasunori Nagayama.

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Nagayama, Y., Nakamura, N., Itatani, R. et al. Epicardial fat volume measured on nongated chest CT is a predictor of coronary artery disease. Eur Radiol 29, 3638–3646 (2019). https://doi.org/10.1007/s00330-019-06079-x

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  • DOI: https://doi.org/10.1007/s00330-019-06079-x

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