Walker Jackson, Christianson Annette, Athar Muhammad, Waqar Fahad, Gerson Myron
Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, United States.
Division of Statistics and Data Science, University of Cincinnati College of Medicine, Cincinnati, OH, United States.
Front Nucl Med. 2023 Apr 28;3:1162784. doi: 10.3389/fnume.2023.1162784. eCollection 2023.
Perfusion imaging strongly predicts coronary artery disease (CAD), whereas cardiac volumes and left ventricular ejection fraction (LVEF) strongly predict mortality. Compared to conventional Anger single-photon emission computed tomography (SPECT) cameras, cadmium-zinc-telluride (CZT) cameras provide higher resolution, resulting in different left ventricular volumes. The cadmium-zinc-telluride D-SPECT camera is commonly used to image in the upright position, which introduces changes in left ventricular loading conditions and potentially alters left ventricular volumes. However, little or no data exist on the predictive value of left ventricular volumes and ejection fraction when acquired in the upright position. We investigated models for the prediction of CAD and mortality, comparing upright and supine imaging.
A retrospective study of patients with upright/supine stress and rest imaging and coronary angiography within 3 months was performed. Univariate and multivariable analyses were performed to predict abnormal angiograms and all-cause mortality.
Of the 392 patients, 210 (53.6%) had significant angiographic CAD; 78 (19.9%) patients died over 75 months. The best multivariable model for CAD included the supine summed stress score and supine stress LVEF, with an area under the receiver operating characteristic of 0.862, a sensitivity of 76.7%, and a specificity of 82.4%, but this model was not statistically superior to the best upright model. The best multivariable models for mortality included age, diabetes, history of cardiovascular disease, and end-systolic volume, with the upright and supine models being equivalent.
Angiographic CAD was best predicted by the supine summed stress score and LVEF but was not statistically superior to the next-best upright model. Mortality was best predicted by end-systolic volume in combination with age, diabetes status, and cardiovascular disease status, with equivalent results from the upright and supine images.
灌注成像能有力地预测冠状动脉疾病（CAD），而心脏容积和左心室射血分数（LVEF）能有力地预测死亡率。与传统的安杰尔单光子发射计算机断层扫描（SPECT）相机相比，碲化镉锌（CZT）相机具有更高的分辨率，这会导致左心室容积不同。碲化镉锌D-SPECT相机通常用于直立位成像，这会引起左心室负荷条件的变化，并可能改变左心室容积。然而，关于在直立位获取左心室容积和射血分数的预测价值的数据很少或几乎没有。我们研究了预测CAD和死亡率的模型，比较了直立位和仰卧位成像。
对在3个月内进行直立/仰卧位负荷和静息成像及冠状动脉造影的患者进行回顾性研究。进行单变量和多变量分析以预测异常血管造影和全因死亡率。
在392例患者中，210例（53.6%）有显著的血管造影CAD；78例（19.9%）患者在75个月内死亡。预测CAD的最佳多变量模型包括仰卧位总负荷评分和仰卧位负荷LVEF，受试者操作特征曲线下面积为0.862，敏感性为76.7%，特异性为82.4%，但该模型在统计学上并不优于最佳直立位模型。预测死亡率的最佳多变量模型包括年龄、糖尿病、心血管疾病史和收缩末期容积，直立位和仰卧位模型相当。
仰卧位总负荷评分和LVEF对血管造影CAD的预测效果最佳，但在统计学上并不优于次佳的直立位模型。收缩末期容积结合年龄、糖尿病状态和心血管疾病状态对死亡率的预测效果最佳，直立位和仰卧位图像的结果相当。
