Computed tomography angiography (CTA) has validated the use of pericoronary adipose tissue (PCAT) attenuation as a credible indicator of coronary inflammation, playing a crucial role in coronary artery disease (CAD). This study aimed to evaluate the long-term effects of high-dose statins on PCAT attenuation at coronary lesion sites and changes in plaque distribution. Our prospective observational study included 52 patients (mean age 60.43) with chest pain, a low-to-intermediate likelihood of CAD, who had documented atheromatous plaque through CTA, performed approximately 1 year and 3 years after inclusion. We utilized the advanced features of the CaRi-Heart^® and syngo.via Frontier^® systems to assess coronary plaques and changes in PCAT attenuation. The investigation of changes in plaque morphology revealed significant alterations. Notably, in mixed plaques, calcified portions increased (p < 0.0001), while non-calcified plaque volume (NCPV) decreased (p = 0.0209). PCAT attenuation generally decreased after one year and remained low, indicating reduced inflammation in the following arteries: left anterior descending artery (LAD) (p = 0.0142), left circumflex artery (LCX) (p = 0.0513), and right coronary artery (RCA) (p = 0.1249). The CaRi-Heart^® risk also decreased significantly (p = 0.0041). Linear regression analysis demonstrated a correlation between increased PCAT attenuation and higher volumes of NCPV (p < 0.0001, r = 0.3032) and lipid-rich plaque volume (p < 0.0001, r = 0.3281). Our study provides evidence that high-dose statin therapy significantly reduces CAD risk factors, inflammation, and plaque vulnerability, as evidenced by the notable decrease in PCAT attenuation, a critical indicator of plaque progression.

Inflammation is a key factor in the development of atherosclerosis, a disease characterized by the buildup of plaque in the arteries. COVID-19 infection is known to cause systemic inflammation, but its impact on local plaque vulnerability is unclear. Our study aimed to investigate the impact of COVID-19 infection on coronary artery disease (CAD) in patients who underwent computed tomography angiography (CCTA) for chest pain in the early stages after infection, using an AI-powered solution called CaRi-Heart^®. The study included 158 patients (mean age was 61.63 ± 10.14 years) with angina and low to intermediate clinical likelihood of CAD, with 75 having a previous COVID-19 infection and 83 without infection. The results showed that patients who had a previous COVID-19 infection had higher levels of pericoronary inflammation than those who did not have a COVID-19 infection, suggesting that COVID-19 may increase the risk of coronary plaque destabilization. This study highlights the potential long-term impact of COVID-19 on cardiovascular health, and the importance of monitoring and managing cardiovascular risk factors in patients recovering from COVID-19 infection. The AI-powered CaRi-Heart^® technology may offer a non-invasive way to detect coronary artery inflammation and plaque instability in patients with COVID-19.

Background: Coronary artery calcium (CAC) scores are a widely used surrogate marker for atherosclerotic burden, but they do not fully reflect plaque vulnerability or coronary inflammation. This study aimed to evaluate the relationship between CACs, coronary plaque characteristics, and perivascular inflammatory activity using advanced CCTA and CaRi-Heart^® analysis. Methods: A total of 250 patients with no prior cardiovascular disease were retrospectively evaluated and stratified by CACs into three groups: 0 (n = 28), 1–100 (n = 121), and >100 (n = 101). Coronary plaque morphology, high-risk plaque (HRP) features, CAD-RADS scores, and AI-derived fat attenuation index (FAI) centiles were assessed. Results: Significant differences across CAC categories were observed for several key parameters. The number of diseased coronary segments increased markedly (from 1.39 ± 1.10 vs. 2.97 ± 1.57 vs. 3.94 ± 2.10; p < 0.0001, one-way ANOVA). A similar upward trend was seen for segment involvement scores, HRP prevalence, and the proportions of mixed and calcified plaque components. Regression analysis demonstrated that CACs correlated significantly with segment burden (r² = 0.2520), CAD-RADS (r² = 0.1352), and the FAI score centile (r² = 0.0568). Conclusions: This study highlights the limitations of CACs as a standalone risk stratification tool. Vulnerable and inflamed plaques may already be present in patients with low or zero CACs. Integrating CCTA with perivascular FAI mapping enables earlier detection of biologically active atherosclerosis and supports more precise clinical decision-making.

Introduction: The pericoronary fat attenuation index (FAI) is an emerging computed tomography-derived marker for measuring vascular inflammation at coronary vessels. It holds prognostic significance for major cardiovascular events and enhances cardiac risk assessment, complementing traditional risk factors and coronary artery calcium scores. However, the impact of local coronary circulation factors on pericoronary inflammation development in right versus left coronary arteries has not been clearly understood. Objective: This study aimed to investigate the regional differences in inflammation levels between the right and left coronary arteries in four clinical scenarios: acute coronary event in the follow-up period, post-COVID patients, recent percutaneous intervention, and unstable angina with significant lesions on native coronary arteries. Methods: The study included 153 patients (mean age 62 years, 70.5% male) who underwent clinically indicated coronary computed tomography angiography (CCTA). Vulnerable plaque features were analyzed to identify high-risk plaques. FAI and the FAI score, a score integrating risk factors and age, were calculated for each case at the left anterior descending artery (LAD), circumflex artery (LCX), and right coronary artery (RCA). Results: A total of 459 coronary arteries were analyzed. Both FAI and FAI scores were higher in the RCA (15.23 ± 11.97) compared to the LAD (10.55 ± 6.78) and (11.48 ± 6.5) LCX (p = 0.02). FAI values showed a significantly higher level at the RCA (−71.25 ± 7.47 HU) compared to the LCX (−76 ± 7.68 HU) and the LAD (−73.04 ± 8.9 HU, p <0.0001). This trend persisted across all subgroups, including post-COVID CT scans (−75.49 ± 7.62 HU for RCA vs. −72.89 ± 9.40 HU for the LCX vs. −71.28 ± 7.82 HU for the LAD, p = 0.01) and patients with high-risk plaques (20.98 ± 16.29 for the RCA vs. 11.77 ± 7.68 for the LCX vs. 12.83 ± 6.47 for the LAD, p = 0.03). Conclusion: Plaques in different coronary areas show varied vulnerability and inflammation levels. The RCA, in particular, demonstrates greater inflammation susceptibility, with higher inflammation scores in areas surrounding the coronary plaques.

Cardiovascular emergencies most frequently arise from the sudden destabilization of atherosclerotic plaques. Conventional diagnostic strategies predominantly focus on luminal stenosis, despite the fact that most acute coronary events originate from non-obstructive lesions with high inflammatory activity. Recent advances in cardiac computed tomography (CCT) enable visualization of plaque morphology and surrounding perivascular fat, offering a unique window into coronary inflammation. The fat attenuation index (FAI), derived from pericoronary adipose tissue (PCAT) radiodensity, has emerged as a dynamic imaging biomarker capable of detecting vascular inflammation before clinical events occur. This review summarizes current evidence on the role of PCAT inflammation in plaque vulnerability, its implications for acute cardiovascular presentations, and recent technological innovations—including AI-enhanced analysis and photon-counting CT—that advance risk prediction. Inflammation-based imaging derived from CCT, including PCAT-FAI, has emerged as a promising research tool that may enhance risk stratification in patients presenting with chest pain. These developments signify a shift from purely anatomical assessment toward biological characterization of CAD, potentially transforming prevention and acute care.

Background/Objectives: Atrial fibrillation (AF) is associated with increased epicardial adipose tissue (EAT), atrial dilation, and coronary inflammation, though causality remains unclear. Cardiac computed tomography (CCT) allows for precise quantification of EAT volume and the left atrial volume index (LAVI), along with the calculation of the fat attenuation index (FAI), indicating coronary inflammation. Combined with the Coronary Artery Disease-Reporting and Data System (CAD-RADS), these imaging markers may improve AF risk stratification. This study evaluates the association between peri-atrial EAT volumes, LAVI, CAD-RADS, and FAI scores in AF patients using advanced AI platforms. Methods: This retrospective study analyzed 122 patients presenting with angina-type pain and a low-to-intermediate likelihood of CAD, who underwent CCT. Patients were divided into two groups based on rhythm status: 42 with AF and 80 without AF. Total EAT, left atrial (LA-EAT), and bi-atrial EAT (BA-EAT) volumes were assessed, along with LAV, CAD-RADS classification, and FAI scores measured using CaRi-Heart^® and syngo.via Frontier^®. Results: AF patients exhibited significantly higher EAT volumes (total EAT: 231.8 ± 45.85 vs. 153.2 ± 54.14 mL, p < 0.0001; LA-EAT: 23.55 ± 6.44 vs. 15.54 ± 8.49 mL, p < 0.0001; BA-EAT: 50.24 ± 12.69 vs. 39.84 ± 15.70 mL, p = 0.0002) and elevated LAVI values (57.7 ± 11.44 vs. 45.9 ± 12.58 mL/m², p < 0.0001). ROC analyses confirmed strong diagnostic performance of total EAT (AUC = 0.869), LA-EAT (AUC = 0.776), BA-EAT (AUC = 0.703), and the LAVI (AUC = 0.756). Higher CAD-RADS categories (2–5) were more frequent in AF, although significant differences were observed only in the lowest category (0–1; 26.2% AF vs. 47.8% non-AF, p = 0.032). Total FAI scores were also higher in AF patients (14.83 ± 10.16 vs. 12.37 ± 7.89, p = 0.044). Conclusions: Increased EAT volumes, an elevated LAVI, and higher FAI scores are significantly associated with AF, suggesting a combined structural and inflammatory substrate. EAT, the LAVI, the FAI, and CAD-RADS collectively represent valuable non-invasive imaging biomarkers for early AF risk assessment.