Prediction of angiographic coronary disease and mortality with a cadmium-zinc-telluride camera: a comparison of upright and supine ejection fractions and left ventricular volumes - Walker, Jackson; Christianson, Annette; Athar, Muhammad; Waqar, Fahad; Gerson, Myron (Frontiers in Nuclear Medicine, 2023)
Introduction: Perfusion imaging strongly predicts coronary artery disease (CAD), while cardiac volumes and left ventricular ejection fraction (LVEF) strongly predicts mortality. Compared to traditional Anger single photon emission computed tomography (SPECT) cameras, cadmium-zinc-telluride cameras provide higher resolution resulting in different left ventricular volumes. The D-SPECT cadmium-zinc-telluride camera is commonly used to image in the upright position, introducing changes in left ventricular loading conditions, potentially altering left ventricular volumes. Yet, little or no data exist concerning the predictive value of left ventricular volumes and ejection fraction when acquired in the upright position. We explored models for predicting CAD and mortality, comparing upright versus supine imaging. Methods: Retrospective study of patients with upright/supine stress and rest imaging and coronary angiography within 3 months. Univariate and multivariable analyses were performed to predict abnormal angiogram and all-cause mortality. Results: 210/392 (53.6%) patients had significant angiographic CAD. 78/392 (19.9%) died over 75 months. Best multivariable model for CAD included supine summed stress score and supine stress LVEF, with AUROC of 0.862, sensitivity 76.7%, specificity 82.4%, but this model was not statistically superior to the best upright model. Best multivariable models for mortality included age, diabetes, history of cardiovascular disease, and end-systolic volume, with upright and supine models being equivalent. Discussion: Angiographic CAD was best predicted by 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 upright and supine images.