Body mass components affecting low-attenuation noncalcified coronary plaque burden

Abstract

Abstract Funding Acknowledgements Type of funding sources: Public hospital(s). Main funding source(s): National Institute of Cardiology in Warsaw, Poland Background Weight control is a major risk modifier for coronary artery disease. However, the effect exerted by individual body mass components on coronary plaque may not be uniform. Low-attenuation noncalcified plaque (LAP) has been recently identified as an independent predictor of cardiovascular outcomes [1]. Purpose To determine the relationship between changes in body mass composition and LAP burden. Methods 89 participants of Dietary Intervention to Stop Coronary Atherosclerosis in Computed Tomography (DISCO-CT) were enrolled into the analysis (40% women, mean age 60±7.7 years). Patients with non-obstructive (stenosis<70%) coronary atherosclerosis confirmed in coronary computed tomography angiography (CCTA) and qualified to conservative treatment were randomized (1:1) to intensive diet and lifestyle intervention atop optimal medical therapy (OMT) versus OMT alone over 66.8±13.7 months [2]. Body mass (BM) and body mass components including total body fat (TBF), skeletal muscle mass (SMM), visceral cell mass (VCM), and extracellular mass (ECM) were measured at baseline and follow-up (InBody S10 analyser, South Korea). LAP burden was defined as the volume of coronary plaque <30 Hounsfield units divided by the vessel volume, and expressed in %. Changes in body components were compared with changes in LAP measured in serial CCTA scans (QAngioCT, Medis Medical Imaging Systems, the Netherlands). Results Reduction in BM was significantly higher in the experimental (∆BM=-3.6±4.9 kg) vs control arm (∆BM=-1.4±2.9 kg; p = 0.016) and so was the reduction in TBF (∆TBF=-4.2±5.3 kg vs ∆TBF=0.2±4.3 kg, respectively; p<0.001). SMM increased by 0.4±2.6 kg in the experimental arm and decreased by 1.0±2.1 kg in the control arm (p = 0.006). No significant interarm differences were observed for changes in VCM and ECM. Reduction in LAP was higher in the experimental vs control arm (∆LAP=-0.42±1.4% vs ∆LAP=-0.03±0.45%, respectively; p = 0.078). In the entire study population, a significant positive correlation between LAP reduction and BM reduction was revealed (r=0.45, p<0.001). Multivariate regression model incorporating the investigated body mass components identified TBF as the only component associated with LAP reduction (table). Conclusions Body mass reduction may decrease LAP burden due to body fat reduction.