Key result
Epicardial adipose tissue volume independently correlates with changes in low attenuation plaque burden, unlike calcium scoring.
Why the study?
Non-contrast calcium scoring has limited utility for monitoring high-risk plaque, creating a need for novel non-contrast imaging biomarkers able to track vulnerable plaque.
Do changes in epicardial and pericardial adipose tissue volumes correlate with changes in low attenuation plaque burden in patients with non-obstructive coronary atherosclerosis?
Do changes in epicardial and pericardial adipose tissue volumes correlate with changes in low attenuation plaque burden in patients with non-obstructive coronary atherosclerosis?
Changes in epicardial and pericardial fat volumes correlate with low attenuation plaque burden dynamics, suggesting non-contrast CT assessment of epicardial fat may help monitor high-risk plaque.
EAT volume may track LAP changes on serial CCTA; hypothesis-generating and requires prospective validation before clinical use.
Background Coronary computed tomography angiography (CCTA) is a viable method for monitoring high-risk plaque, however, non-contrast calcium scoring (CAS) has a limited utility in this context. The search for novel non-contrast imaging biomarkers able to track vulnerable plaque is necessary. Purpose To investigate correlations between low attenuation plaque (LAP) identified through CCTA and non-contrast CAS, pericardial adipose tissue (PEAT), and epicardial adipose tissue (EAT) in patients with non-obstructive coronary atherosclerosis undergoing serial CCTA. Methods We analyzed data from 89 participants (40% women, 60±7.7 years) of the Dietary Intervention to Stop Coronary Atherosclerosis in the Computed Tomography (DISCO-CT) study. This single-center, randomized study enrolled patients with non-obstructive coronary atherosclerosis (stenosis <70%) confirmed in CCTA to assess the effect of intensive diet and lifestyle intervention atop optimal medical therapy versus optimal medical therapy alone (1:1) on coronary plaque regression. CCTA was performed at baseline and repeated at mean follow-up of 66.8±13.7 weeks (2x192 row scanner, temporal resolution 66 ms). CAS and coronary fat were measured in non-contrast sequences using a dedicated software and analysed in relation to contrast-derived LAP, defined as the volume of coronary plaque <30 HU divided by the volume of the vessel and expressed in %. Results Mean LAP burden decreased by 0.23±1.0% (p=0.041), mean PEAT volume decreased by 17.8±44.1 cm³ (p<0.001), and mean EAT volume decreased by 5.4±19.3 cm³ (p=0.01), while median CAS increased by 21.2 (IQR, 1.7; 71.7) Agatston units (p<0.001), Figure 1. Positive correlations were found between changes (∆) in LAP burden and changes in both PEAT and EAT volumes (r=0.349, p=0.001, Figure 2A, and r=0.490, p<0.001, Figure 2B, respectively), but not with change in CAS (Figure 2C). Multivariate linear regression analysis identified EAT as an independent predictor of LAP regression (95% CI, 0.007; 0.032; p=0.003). Conclusions Pericardial and epicardial fat volumes and their dynamics positively correlate with LAP burden, while CAS does not. Monitoring EAT volume using non-contrast computed tomography may facilitate the assessment of high-risk plaque progression or regression, overcoming the limitations of CAS.Figure 1 Figure 2
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Henzel et al. (2025) studied this question. Epicardial adipose tissue volume independently correlates with changes in low attenuation plaque burden (r=0.49, p<0.001), while calcium scoring does not.
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