Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu Province, China.
BMC Med Imaging. 2023 Jul 28;23(1):99. doi: 10.1186/s12880-023-01051-0.
Type 2 diabetes mellitus (T2DM) patients have a higher incidence of coronary artery disease than the general population. The aim of this study was to develop a radiomics nomogram of pericoronary adipose tissue (PCAT) based on non-contrast CT to predict haemodynamically significant coronary stenosis in T2DM patients.
The study enrolled 215 T2DM patients who underwent non-contrast CT and coronary computed tomography angiography (CCTA). CCTA derived fractional flow reserve (FFR) ≤ 0.80 was defined as hemodynamically significant stenosis.1691 radiomics features were extracted from PCAT on non-contrast CT. Minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) were used to select useful radiomics features to construct Radscore. Logistic regression was applied to select significant factors among Radscore, fat attenuation index (FAI) and coronary artery calcium score (CACS) to construct radiomics nomogram.
Radscore [odds ratio (OR) = 2.84; P < 0.001] and CACS (OR = 1.00; P = 0.023) were identified as independent predictors to construct the radiomics nomogram. The radiomics nomogram showed excellent performance [training cohort: area under the curve (AUC) = 0.81; 95% CI: 0.76-0.86; validation cohort: AUC = 0.83; 95%CI: 0.76-0.90] to predict haemodynamically significant coronary stenosis in patients with T2DM. Decision curve analysis demonstrated high clinical value of the radiomics nomogram.
The non-contrast CT-based radiomics nomogram of PCAT could effectively predict haemodynamically significant coronary stenosis in patients with T2DM, which might be a potential noninvasive tool for screening of high-risk patients.
2 型糖尿病（T2DM）患者发生冠状动脉疾病的几率高于普通人群。本研究旨在基于非增强 CT 构建冠状动脉旁脂肪组织（PCAT）的放射组学列线图，以预测 T2DM 患者的血流动力学意义重大的冠状动脉狭窄。
本研究纳入了 215 例接受非增强 CT 和冠状动脉计算机断层血管造影（CCTA）检查的 T2DM 患者。将 CCTA 得出的血流储备分数（FFR）≤0.80 定义为血流动力学意义重大的狭窄。从非增强 CT 上的 PCAT 中提取了 1691 个放射组学特征。采用最小冗余最大相关（mRMR）和最小绝对值收缩和选择算子（LASSO）选择有用的放射组学特征构建 Radscore。Logistic 回归用于在 Radscore、脂肪衰减指数（FAI）和冠状动脉钙评分（CACS）中选择显著因素构建放射组学列线图。
Radscore[比值比（OR）=2.84；P<0.001]和 CACS（OR=1.00；P=0.023）被确定为独立预测因子以构建放射组学列线图。放射组学列线图显示出良好的性能[训练队列：曲线下面积（AUC）=0.81；95%可信区间：0.76-0.86；验证队列：AUC=0.83；95%可信区间：0.76-0.90]，可用于预测 T2DM 患者血流动力学意义重大的冠状动脉狭窄。决策曲线分析表明放射组学列线图具有较高的临床价值。
基于非增强 CT 的 PCAT 放射组学列线图可有效预测 T2DM 患者血流动力学意义重大的冠状动脉狭窄，可能是筛查高危患者的一种潜在非侵入性工具。
