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Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
Published on: August 28, 2018
Pericoronary Adipose Tissue Radiomic Features and Quantitative Plaque Analysis in Coronary Artery Disease: Insights
Konstantin V Zavadovsky1, Alexey V Kalinovsky1, Alina N Maltseva1
1Department of Radiology and Tomography, Cardiology Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk 634012, Russia.
Abstract:
Background/Objectives: Coronary computed tomography angiography (CCTA) is a modern method for assessing the total burden of atherosclerotic lesions. The perivascular fat attenuation index (PFAI) is a reliable predictor of major adverse cardiovascular events (MACE). Radiomics extracts substantially more information from images than visual assessment by radiologists. However, the relationships between quantitative parameters of coronary atherosclerosis, the PFAI, and radiomic features of pericoronary adipose tissue (PCAT) in patients with coronary artery disease (CAD) remain unclear. The study aimed to evaluate the associations between PCAT characteristics, including radiomic features, and quantitative parameters of coronary atherosclerosis in stable CAD patients. Methods: The study included 79 patients with stable CAD who underwent CCTA. The patients were divided into two groups: nonobstructive CAD (NOCAD, stenosis < 50%; n = 61) and obstructive CAD (OCAD, stenosis ≥ 50%; n = 18). The CCTA data were analyzed to quantify coronary atherosclerosis parameters (plaque volume and burden), the PFAI, PCAT volume, and radiomic features of PCAT in the proximal segments of major coronary arteries. Results: The study included 79 patients: NOCAD group = 61 patients (age 57.00 (50.00-65.00) years) and OCAD group = 18 patients (age 60.5 (55.75-65.75) years). The OCAD patients exhibited higher plaque volume and burden across all components. No significant between-group differences were observed in PFAI or PCAT volume for any vessel. However, 50% (46/92) of PCAT radiomic features in the proximal right coronary artery (RCA) differed significantly between groups, 42 of which were textural. The PFAI correlated most strongly with soft tissue (ST) plaque volume (ρ = -0.22), and burden (ρ = -0.21) of the soft tissue component of plaques (p < 0.001). The PCAT volume significantly correlated (p < 0.001) with plaque volume (ρ = 0.30) and with individual components-soft tissue (ρ = 0.30), fibrous-fatty (ρ = 0.27), fibrous (ρ = 0.30), calcified (ρ = 0.22), and non-calcified (ρ = 0.30)-as well as with the burden of the soft tissue component (ρ = 0.26). Conclusions: The radiomic features of RCA PCAT differed significantly between the NOCAD and OCAD groups. Quantitative coronary atherosclerosis parameters showed significant associations with the PCAT radiomic features in CAD patients, potentially serving as independent predictors of the MACE risk. In contrast, the PFAI values did not differ between groups and neither PFAI nor PCAT volume associated with atherosclerosis parameters.
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