Razipour Aryabod, Grodecki Kajetan, Manral Nipun, Geers Jolien, Gransar Heidi, Shanbhag Aakash, Miller Robert J H, Rozanski Alan, Berman Daniel S, Slomka Piotr J, Dey Damini
Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA; First Department of Cardiology, Medical University of Warsaw, Warsaw, Poland.
Atherosclerosis. 2025 Feb;401:119098. doi: 10.1016/j.atherosclerosis.2024.119098. Epub 2024 Dec 22.
The significance of left ventricular mass and chamber volumes from non-contrast computed tomography (CT) for predicting major adverse cardiovascular events (MACE) has not been studied. Our objective was to evaluate the role of artificial intelligence-enabled multi-chamber cardiac volumetry from non-contrast CT for long-term risk stratification in asymptomatic subjects without known coronary artery disease.
Our study included 2022 asymptomatic individuals (55.6 ± 9.0 years; 59.2 % male) from the EISNER (Early Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research) trial. Multi-chamber cardiac volumetry was performed using deep-learning algorithms from routine non-contrast CT scans for coronary artery calcium scoring. MACE was defined as cardiac death, acute coronary syndrome, and late (>180 days) revascularization.
A total of 215 individuals (11 %) suffered MACE at a mean follow-up of 13.9 ± 3 years. Individuals with MACE had higher left ventricular mass (115.1g vs. 105.2g, p < 0.001). In a multivariable analysis adjusted for cardiovascular risk factors and medications, left ventricular mass (HR 2.76, p<0.001) and coronary artery calcium score (HR 1.34, p<0.001) were independent predictors of long-term MACE. Adding left ventricular mass to the coronary calcium score improved the Receiver Operating Characteristic Area Under the Curve (AUC 0.753 vs 0.767, p=0.031) with continuous net reclassification index of 18 % (p=0.011). Left ventricular mass (HR 3.89, p<0.001), but not the coronary artery calcium score predicted cardiovascular death.
Left ventricular mass quantified automatically by AI from routine non-contrast CT independently predicted long-term MACE over and above the coronary calcium score in asymptomatic participants without known coronary artery disease.
非增强计算机断层扫描（CT）测得的左心室质量和腔室容积对预测主要不良心血管事件（MACE）的意义尚未得到研究。我们的目的是评估基于人工智能的非增强CT多腔室心脏容积测量在无症状且无已知冠状动脉疾病的受试者长期风险分层中的作用。
我们的研究纳入了EISNER（通过无创成像研究早期识别亚临床动脉粥样硬化）试验中的2022名无症状个体（55.6±9.0岁；59.2%为男性）。使用深度学习算法对常规非增强CT扫描进行冠状动脉钙化评分的同时进行多腔室心脏容积测量。MACE定义为心源性死亡、急性冠状动脉综合征和晚期（>180天）血运重建。
在平均13.9±3年的随访中，共有215名个体（11%）发生了MACE。发生MACE的个体左心室质量更高（115.1g对105.2g，p<0.001）。在针对心血管危险因素和药物进行调整的多变量分析中，左心室质量（HR 2.76，p<0.001）和冠状动脉钙化评分（HR 1.34，p<0.001）是长期MACE的独立预测因素。将左心室质量添加到冠状动脉钙化评分中可改善曲线下受试者工作特征面积（AUC 0.753对0.767，p=0.031），连续净重新分类指数为18%（p=0.011）。左心室质量（HR 3.89，p<0.001）而非冠状动脉钙化评分可预测心血管死亡。
在无已知冠状动脉疾病的无症状参与者中，通过人工智能从常规非增强CT自动量化的左心室质量在冠状动脉钙化评分之外独立预测了长期MACE。
