AI Article Synopsis

  • PCAT is linked to inflammation and coronary atherosclerosis, prompting a study on its relationship with coronary artery disease (CAD) severity using advanced CT imaging techniques.
  • The study involved 403 patients with chest pain, measuring various PCAT quality indicators (like the fat attenuation index) and epicardial adipose tissue attenuation to assess CAD presence and severity.
  • Results revealed that the fat attenuation index was the most effective and independent predictor of CAD, with a diagnostic accuracy of 80.6%, indicating its potential as a useful marker for tracking PCAT changes related to the disease.

Article Abstract

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. 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) and spectral virtual mono-energetic images at 40 keV (FAI), slope of spectral HU curve (λ), 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. FAI, λ, Eff-Z, and FAI 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 was the most powerful independent indicator (odds ratio 1.058, 95% CI 1.044-1.073; < 0.001) of CAD among these parameters. Using an optimal cut-off (-131.8 HU), FAI showed higher diagnostic accuracy of 80.6% compared with the other parameters. These preliminary findings suggest that FAI on SDCT may be an appealing surrogate maker to allow monitoring of PCAT changes in the development of CAD.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8514719PMC
http://dx.doi.org/10.3389/fcvm.2021.720127DOI Listing

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