An automated quantification method for the Agatston coronary artery calcium score on coronary computed tomography angiography

被引:9
|
作者
Wang, Wenjia [1 ]
Yang, Lin [2 ]
Wang, Sicong [1 ]
Wang, Qiong [2 ]
Xu, Lei [2 ]
机构
[1] GE Healthcare China, Beijing, Peoples R China
[2] Capital Med Univ, Beijing Anzhen Hosp, Dept Radiol, Beijing 100029, Peoples R China
基金
中国国家自然科学基金;
关键词
Coronary artery calcium (CAC); coronary computed tomography angiography (CCTA); non-contrast cardiac computed tomography (CT); CARDIOVASCULAR RISK-ASSESSMENT; DIAGNOSTIC PERFORMANCE; RADIATION-EXPOSURE; CARDIAC CT; PREDICTION; PLAQUE; CLASSIFICATION; CALCIFICATION; DENSITY;
D O I
10.21037/qims-21-775
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Background: A coronary artery calcium (CAC) score can provide supplementary information for predicting the risk of cardiovascular disease (CVD). Although CAC is clinically measured with non-contrast cardiac computed tomography (CT), coronary CT angiography (CCTA) may also be used, allowing for the simultaneous evaluation of coronary artery vessels and calcified plaques. This study proposes a method for the automated quantification of the Agatston CAC score from CCTA and compares our method's performance with that of non-contrast cardiac CT. Methods: Sixty-two patients were selected from a clinical registry and divided into four CAC categories. They underwent both non-contrast cardiac CT and CCTA. The Agatston CAC score derived from non-contrast cardiac CT (standard Agatston CAC score) was used as the reference standard. Calcifications were automatically identified and quantified using different thresholds after a deep learning-based coronary artery segmentation model pretrained on CCTA images. Comparisons were made between the standard Agatston CAC score and the CCTA-based Agatston CAC score (CCTA-CAC score) on a per-patient and per-vessel basis. Spearman's rank-order correlation coefficient (R) and intra-class correlation (ICC) values were used to calculate the correlation between the two methods. Results: After comparison, the optimal lower threshold in CCTA-CAC score calculations was found to be 650 Hounsfield units (HU). Using this threshold on a per-patient basis, the automatically computed CCTA-CAC score showed a high correlation (R =0.959; P<0.01) and ICC (R =0.8219; P<0.01) with the standard Agatston CAC score. On a per-vessel basis, the standard Agatston CAC score was also highly correlated with the CCTA-CAC score (R =0.889; P<0.01 and ICC =0.717; P<0.01). Of the 62 patients enrolled, 47 (76%) were classified into the same cardiovascular risk category using the CCTA-CAC score quantification method as when the standard Agatston CAC score was used. Agreement within the CAC categories was also good (kappa =0.7560). Conclusions: Fully automated quantification of the Agatston CAC score on CCTA images is feasible and shows a high correlation with the reference standard. This method could simplify the quantification procedure and has the potential to reduce the radiation dose and save time by eliminating the non-contrast cardiac CT stage.
引用
收藏
页码:1787 / 1799
页数:13
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