Liang Jianhua, Lin Congcong, Qi Hongliang, Lin Yongkai, Deng Liwei, Wu Jieyao, Yang Chunyang, He Zhiyuan, Li Jiaqing, Li Hanwei, Hu Debin, Chen Hongwen, Li Yuanzhang
The Fifth Affiliated Hospital, Southern Medical University, Guangzhou, China (J.L., C.L., Y.L., L.D., J.W., C.Y., Z.H., J.L., Y.L.).
Nanfang Hospital, Southern Medical University, Guangzhou, China (H.Q., H.L., D.H., H.C.).
Acad Radiol. 2025 Mar;32(3):1344-1352. doi: 10.1016/j.acra.2024.11.063. Epub 2024 Dec 18.
Patients with a low Agatston score often present with clinical signs and symptoms suggestive of coronary artery disease, despite having minimal calcium deposits. This study aimed to compare the efficacy of low-dose non-contrast cardiac CT with coronary computed tomography angiography (CCTA) in pericoronary adipose tissue (PCAT) radiomics for predicting coronary artery plaques, using CCTA as the reference standard.
This retrospective study analyzed 459 patients with suspected coronary artery disease and a coronary artery calcium score < 100 Agatston units, who were treated between June 2021 and December 2023 at a tertiary hospital. Three predictive models for coronary artery plaques were developed: (1) a clinical factor model, (2) a hybrid model integrating clinical factors and CT PCAT radiomics, and (3) a hybrid model integrating clinical factors and CCTA PCAT radiomics. Multivariable logistic regression and receiver operating characteristic curve evaluations were performed to develop and validate predictive models.
Both hybrid models showed significant correlations in the training set (r = 0.890, P < 0.001) and the validation set (r = 0.920, P < 0.001). The mean agreement in the training set is 0, with 3.42% (11/322) of the data points outside the 95% CI (-0.18-0.18, P < 0.001). The mean agreement in the validation set is -0.244, with 6.57% (9/137) of the data points outside the 95% CI (-0.443-0.045, P < 0.001).
Non-contract CT PCAT radiomics showed comparable efficacy to CCTA PCAT radiomics in predicting coronary artery plaques among patients with low Agatston scores.
尽管阿加斯顿积分较低、钙沉积极少,但此类患者常出现提示冠状动脉疾病的临床体征和症状。本研究旨在以冠状动脉计算机断层扫描血管造影(CCTA)为参考标准,比较低剂量非增强心脏CT与CCTA在冠状动脉周围脂肪组织(PCAT)放射组学中预测冠状动脉斑块的疗效。
本回顾性研究分析了2021年6月至2023年12月在一家三级医院接受治疗的459例疑似冠状动脉疾病且冠状动脉钙积分<100阿加斯顿单位的患者。建立了三种冠状动脉斑块预测模型:(1)临床因素模型;(2)整合临床因素与CT PCAT放射组学的混合模型;(3)整合临床因素与CCTA PCAT放射组学的混合模型。进行多变量逻辑回归和受试者操作特征曲线评估以建立和验证预测模型。
两种混合模型在训练集(r = 0.890,P < 0.001)和验证集(r = 0.920,P < 0.001)中均显示出显著相关性。训练集中的平均一致性为0,95%置信区间(-0.18 - 0.18,P < 0.001)外的数据点占3.42%(11/322)。验证集中的平均一致性为 -0.244,95%置信区间(-0.443 - 0.045,P < 0.001)外的数据点占6.57%(9/137)。
在阿加斯顿积分较低的患者中,非增强CT PCAT放射组学在预测冠状动脉斑块方面显示出与CCTA PCAT放射组学相当的疗效。