医学
冠状动脉疾病
内科学
接收机工作特性
糖尿病
曲线下面积
无线电技术
逻辑回归
计算机辅助设计
单变量
单变量分析
心脏病学
放射科
核医学
多元分析
多元统计
机器学习
内分泌学
工程制图
工程类
计算机科学
作者
Meng Chen,Jiang Hu,Can Chen,Guangyu Hao,Su Hu,Jialiang Xu,Chunhong Hu
标识
DOI:10.1177/02841851231189998
摘要
Background Type 2 diabetes mellitus (T2DM) is associated with a markedly increased prevalence of coronary artery disease (CAD). Radiomics features of pericoronary adipose tissue (PCAT) were correlated with inflammation, which may have potential value in the prediction of CAD. Purpose To determine whether radiomics analysis of PCAT captured by plain computed tomography (CT) could predict obstructive CAD in patients with T2DM. Material and Methods The study included 155 patients with T2DM with suspected CAD between January 2020 and December 2021. Volumes of right coronary artery of 10–50 mm were delineated in the plain CT to extract radiomics features and PCAT CT attenuation (PCATa). Least absolute shrinkage and selection operator was used to select the useful radiomics features to calculate the radiomics score (Rad-score). Univariate and multivariable logistic regression were applied to select independent predictors. The predictive performance was evaluated by the area under the receiver operating characteristics curve (AUC). Results Rad-score (per 0.1 increments: odds ratio [OR] = 1.297; P < 0.001), coronary artery calcium score (CACS) (OR = 1.003; P = 0.037), and sex (OR = 3.245; P = 0.026) were identified as independent predictors for obstructive CAD. Rad-score (AUC = 0.835) outperformed CACS (AUC = 0.780), sex (AUC = 0.665), and PCATa (AUC = 0.550) in predicting obstructive CAD ( P = 0.017 and 0.003 for Rad-score vs. sex and PCATa, respectively); however, the improvement between Rad-score and CACS had no statistical significance ( P = 0.490). Conclusion Plain CT-derived Rad-score may be used as a preliminary screening tool for obstructive CAD in patients with T2DM.
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