Predicting coronary atherosclerosis heart disease with pericoronary adipose tissue attenuation parameters based on dual-layer spectral detector computed tomography: a preliminary exploration

Lei Zou; Xigang Xiao; Yulin Jia; Feng Yin; Jing Zhu; Qi Gao; Ming Xue; Shushan Dong

doi:10.21037/qims-22-1019

Predicting coronary atherosclerosis heart disease with pericoronary adipose tissue attenuation parameters based on dual-layer spectral detector computed tomography: a preliminary exploration

Quant Imaging Med Surg. 2023 May 1;13(5):2975-2988. doi: 10.21037/qims-22-1019. Epub 2023 Apr 3.

Authors

Lei Zou¹, Xigang Xiao¹, Yulin Jia¹, Feng Yin¹, Jing Zhu¹, Qi Gao¹, Ming Xue¹, Shushan Dong²

Affiliations

¹ Radiology Department, the First Affiliated Hospital of Harbin Medical University, Harbin, China.
² Clinical Science, Philips Healthcare, Beijing, China.

Abstract

Background: Coronary atherosclerosis is a chronic inflammatory condition. Pericoronary adipose tissue (PCAT) attenuation is closely related to coronary inflammation. This study aimed to investigate the relationship between PCAT attenuation parameters and coronary atherosclerotic heart disease (CAD) using dual-layer spectral detector computed tomography (SDCT).

Methods: This cross-sectional study included eligible patients who underwent coronary computed tomography angiography using SDCT at the First Affiliated Hospital of Harbin Medical University between April 2021 and September 2021. Patients were classified as CAD (with coronary artery atherosclerotic plaque) or non-CAD (without coronary artery atherosclerotic plaque). Propensity score matching was used to match the two groups. The fat attenuation index (FAI) was used to quantify PCAT attenuation. The FAI was measured on conventional images (120 kVp) and virtual monoenergetic images (VMI) by semiautomatic software. The slope of the spectral attenuation curve (λ) was calculated. Regression models were established to evaluate the predictive value of PCAT attenuation parameters for CAD.

Results: A total of 45 patients with CAD and 45 patients without CAD were enrolled. The PCAT attenuation parameters in the CAD group were significantly higher than those in the non-CAD group (all P values <0.05). The PCAT attenuation parameters of vessels with or without plaques in the CAD group were higher than those of vessels without plaques in the non-CAD group (all P values <0.05). In the CAD group, the PCAT attenuation parameters of vessels with plaques were slightly higher than those of vessels without plaques (all P values >0.05). In receiver operating characteristic curve analysis, the FAIVMI model achieved an area under the curve (AUC) of 0.8123 for discriminating between patients with and without CAD, which was higher than those of the FAI_{120 kVp} model (AUC =0.7444) and the λ model (AUC =0.7230). However, the combined model of FAIVMI, FAI_{120 kVp}, and λ obtained the best performance (AUC =0.8296) of all the models.

Conclusions: PCAT attenuation parameters obtained using dual-layer SDCT can aid in distinguishing patients with and without CAD. By detecting increases in PCAT attenuation parameters, it might be possible to predict the formation of atherosclerotic plaques before they appear.

Keywords: Pericoronary adipose tissue attenuation; atherosclerotic plaque; coronary atherosclerosis heart disease; coronary computed tomography angiography; dual-layer spectral detector computed tomography.