Perivascular fat attenuation for predicting adverse cardiac events in stable patients undergoing invasive coronary angiography

Abstract

Background: Inflammation surrounding the coronary arteries can be non-invasively assessed using pericoronary adipose tissue attenuation (PCAT). While PCAT holds promise for further risk stratification of patients with low coronary artery disease (CAD) prevalence, its value in higher risk populations remains unknown.

Methods: CORE320 enrolled patients referred for invasive coronary angiography with known or suspected CAD. Coronary computed tomography angiography (CCTA) images were collected for 381 patients for whom clinical outcomes were assessed 5 years after enrollment. Using semi-automated image analysis software, PCAT was obtained and normalized for the right coronary (RCA), left anterior descending (LAD), and left circumflex arteries (LCx). The association between PCAT and major adverse cardiovascular events (MACE) during follow up was assessed using Cox regression models.

Results: Thirty-seven patients were excluded due to technical failure. For the remaining 344 patients, median age was 62 (interquartile range, 55-68) with 59% having ≥1 coronary artery stenosis of ≥50% by quantitative coronary angiography. Mean attenuation values for PCAT in RCA, LAD, and LCx were -74.9, -74.2, and -71.2, respectively. Hazard ratios and 95% confidence intervals (CI) for normalized PCAT in the RCA, LAD, and LCx for MACE were 0.96 (CI: 0.75-1.22, p ​= ​0.71), 1.31 (95% CI: 0.96-1.78, p ​= ​0.09), and 0.98 (95% CI: 0.78-1.22, p ​= ​0.84), respectively. For death, stroke, or myocardial infarction only, hazard ratios were 0.68 (0.44-1.07), 0.85 (0.56-1.29), and 0.57 (0.41-0.80), respectively.

Conclusions: In patients referred for invasive coronary angiography with suspected CAD, PCAT did not predict MACE during long term follow up. Further studies are needed to understand the relationship of PCAT with CAD risk.

Keywords: Coronary artery disease; Coronary computed tomography angiography; Coronary heart disease; Multidetector computed tomography; Perivascular fat attenuation.

Figure 1.

An example of computer-aided segmentation of a right coronary artery with traced lumen and vessel contours and pericoronary adipose attenuation. The left panel (1A) shows a three-dimensional reconstruction of CT images with the proximal right coronary artery highlighted (red rectangle) which is shown below in a straightened curved multi-planar reformatted CT image along with lumen and vessel border tracing. The right upper panel shows a cross-sectional view of the red rectangle with an 1mm perivascular shell closest to vessel wall analyzed for X-ray attenuation. The right lower panel depicts all 5 shells out to 5mm beyond the outer vessel wall. Panels 1B and C depict PCAT analysis out to 1- and 5-mm shells, respectively, with 1D and 1E being the grayscale equivalents. Blue highlights the perivascular region within −30 to 337 Hounsfield units [HU], while red highlights perivascular fat within −190 to −31 HU. Green highlights the lumen, which was excluded from PCAT analysis. Green circle indicates inner vessel wall; yellow circle presents outer vessel wall; purple circle represents region of PCAT analysis.

Figure 2.

Exemplar images of patients with (3A) low and (3B) high PCAT values out to 2mm beyond the vessel wall, with panels 3C and 3D being the corresponding grayscale images. Blue highlights the perivascular region within −30 to 337 Hounsfield units [HU], while red highlights perivascular fat within −190 to −31 HU. In panels 2B and 2D, yellow circles present the inner and outer vessel wall, while the green line represents the region of PCAT analysis (in this example, 2mm from outer vessel wall).

Figure 3.

Distribution of pericoronary adipose tissue attenuation values for those with and without MACE (3A) and hard events (3B). RCA: right coronary artery; LAD: left anterior descending artery; LCx: left circumflex artery.

Figure 4.

Receiver operator characteristics (ROC) curves for multivariable models predictive of MACE (4A, P=0.70 for ΔAUC) or hard events (4B, P=0.18 for ΔAUC). Red line represents model with variables of age, male sex, hypertension, dyslipidemia, diabetes, smoking status, and previous MI, while green line represents a model with the above variables in addition to PCAT of the right coronary artery (RCA).