Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto, 860-8556, Japan.
Department of Radiology, Minamata City General Hospital and Medical Center, 1-2-1, Tenjin-cho, Minamata, 867-0041, Japan.
Eur Radiol. 2019 Jul;29(7):3638-3646. doi: 10.1007/s00330-019-06079-x. Epub 2019 Mar 11.
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).
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.
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).
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.
• 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.
探讨心电图门控非对比 CT(nongated-NCCT)上测量的心外膜脂肪体积(EFV)是否可作为冠状动脉疾病(CAD)的可靠且可重复的预测指标。
117 例因疑似 CAD 症状而在单次就诊时接受冠状动脉 CT 血管造影(CCTA)和 nongated-NCCT 的患者入选。两名观察者分别在两种图像上独立定量 EFV。使用 Pearson 相关系数和 Bland-Altman 图评估 CCTA-EFV 和 nongated-NCCT-EFV 之间的相关性。使用一致性相关系数(CCC)分析观察者间的一致性。比较 CAD 阳性(>50%狭窄)和 CAD 阴性组之间的冠心病危险因素,包括 EFV。使用多变量逻辑回归分析 EFV 与 CAD 的关系。进行 ROC 分析,并比较 AUC 和 DeLong 方法。
74 例患者被诊断为 CAD。尽管两种测量值之间存在系统差异(平均偏差,1.26),但 CCTA-EFV 和 nongated-NCCT-EFV 之间存在极好的相关性(r=0.948,p<0.001)。观察者间的一致性几乎完美(CCTA 和 nongated-NCCT 的 CCC 分别为 0.988 和 0.985,p<0.001)。在两种图像上,有 CAD 与无 CAD 的患者之间在年龄、高血压和 EFV 方面存在显著差异(p≤0.026)。多变量分析显示,CCTA 上的 EFV 增加(优势比 1.185,p=0.003)和 nongated-NCCT 上的 EFV 增加(优势比 1.20,p=0.015)与 CAD 独立相关。CCTA-EFV 和 nongated-NCCT-EFV 对 CAD 的预测 AUC 之间无显著差异(0.659 对 0.665,p=0.706)。
尽管没有心电图门控,NCCT 上测量的 EFV 仍可作为 CAD 的一种可重复的预测指标,其准确性与 CCTA 上测量的 EFV 相当。
• 尽管没有心电图门控,NCCT 上的 EFV 提供了近乎完美的观察者间可重复性,并与门控 CCTA 上的测量结果显示出极好的相关性。• nongated-NCCT 上的 EFV 可作为预测冠状动脉疾病的独立生物标志物,其准确性与门控 CCTA 上的 EFV 相当。