Why the study?
Pericoronary adipose tissue is considered a source of inflammatory mediators driving coronary atherosclerosis, but the correlation between dual-layer spectral detector CT-derived PCAT quality and CAD severity was unknown.
Does pericoronary adipose tissue quality determined by dual-layer spectral detector CT correlate with the presence and severity of coronary artery disease?
Does pericoronary adipose tissue quality determined by dual-layer spectral detector CT correlate with the presence and severity of coronary artery disease?
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FAI40keV derived from dual-layer spectral detector CT is a promising surrogate imaging marker for detecting pericoronary adipose tissue changes and identifying the presence of coronary artery disease.
Background: Pericoronary adipose tissue (PCAT) is considered as a source of inflammatory mediators, leading to the development of coronary atherosclerosis. The study aimed to investigate the correlation between PCAT quality derived from dual-layer spectral detector CT (SDCT) and the severity of coronary artery disease (CAD), and whether PCAT parameters were independently associated with the presence of CAD. Materials and Methods: A total of 403 patients with symptoms of chest pain who underwent SDCT were included. PCAT quality including fat attenuation index (FAI) measured from conventional polychromatic CT images (FAI 120kvp ) and spectral virtual mono-energetic images at 40 keV (FAI 40keV ), slope of spectral HU curve (λ HU ), and effective atomic number (Eff-Z) were measured around the lesions representing the maximal degree of vascular stenosis in each patient. Meanwhile, overall epicardial adipose tissue (EAT) attenuation was acquired in the conventional polychromatic energy imaging. Results: FAI 40keV , λ HU , Eff-Z, and FAI 120kvp increased along with the degree of CAD in general and were superior to the overall EAT attenuation for detecting the presence of CAD. Multivariate logistic regression analysis indicated that FAI 40keV was the most powerful independent indicator (odds ratio 1.058, 95% CI 1.044–1.073; p < 0.001) of CAD among these parameters. Using an optimal cut-off (−131.8 HU), FAI 40keV showed higher diagnostic accuracy of 80.6% compared with the other parameters. Conclusions: These preliminary findings suggest that FAI 40keV on SDCT may be an appealing surrogate maker to allow monitoring of PCAT changes in the development of CAD.
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Dang et al. (2021) studied this question.
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