Abstract 4135636: Age- and Sex-Related Coronary Atherosclerosis by Artificial Intelligence Quantitative Coronary CT Angiography from the INVICTUS Registry

Background: Coronary plaque analysis using artificial intelligence quantitative coronary CT (AI-QCT) is a promising tool to identify coronary atherosclerosis. However, there is insufficient data on coronary atherosclerosis volume and morphology using AI-QCT in patients who are at high risk of atherosclerosis. The purpose of this study is to clarify the differences in the volume and phenotypes of coronary atherosclerosis by age and gender using AI-QCT. Methods: The INVICTUS Registry is a multi-center registry enrolling patients who clinically underwent coronary CT angiography and invasive coronary angiography with invasive imaging modalities in Japan. Patients with a history of percutaneous coronary intervention or coronary artery bypass graft were excluded in this study. Using AI-QCT, the volume, and phenotypes (calcified, non-calcified, low-density non-calcified plaque [LD-NCP]) of coronary atherosclerosis were analyzed and assessed by age (<55, 55-64, 65-74, and 75 and older) and gender. Results: A total of 982 patients were enrolled in the study. The mean age was 70.3 ± 10.8 years, 71.9% were male. Approximately two-thirds of patients had hypertension (73.3%) and dyslipidemia (71.5%), and 36.7% had diabetes. Mean total plaque volume (PV), calcified PV, non-calcified PV, and low-density PV were 745.5±529.8 mm 3 , 248.3±302.0 mm 3 , 482.2±340.6 mm 3 , and 15.0±29.4 mm 3 , respectively. The results of plaque volume and phenotypes by age are shown in the figure. Compared to those under 55 years of age, total PV increased gradually and significantly by about 10% for every 10 years of age (p=0.022). Though no significant difference was observed in non-calcified PV between the age groups (p=0.379), calcified PV progressively and significantly increases approximately 70% for every 10 years of age (p<0.001). In contrast, the low-density plaque volume showed a trend toward a significant decrease with increasing age (p=0.073). These trends did not differ by gender. Conclusion: In a large cohort of patients at high risk for atherosclerosis analyzed by AI-QCT, total coronary PV increased with age, primarily calcified PV. While no change in non-calcified PV between the age groups, LD-NCPV was likely to decrease with increasing age. These findings may contribute to the guidance for the prevention of coronary artery diseases based on coronary atherosclerosis phenotype by age and gender.