Inflammatory risk quantification in systemic inflammatory disease using coronary CT angiography

Immune-mediated Inflammatory Diseases (IMIDs) are associated with increased cardiovascular risk, including atherosclerosis and myocardial infarction. Inflammation is a key risk factor for the development and progression of coronary atherosclerosis. Tracking attenuation changes in perivascular adipose tissue driven by inflammatory signals secreted from the adjacent artery has been introduced as a new way to non-invasively quantify inflammation using routine coronary computed tomography angiography (CCTA). The fat attenuation index (FAI) and the standardized metric, FAI Score, enable quantification of these changes, and have recently been shown to provide useful estimates of coronary artery inflammation in a longitudinal multicenter cohort.1 However, the performance of these metrics among individuals with IMIDs has yet to be elucidated. This study aimed to evaluate the presence of coronary inflammation imaging via FAI analysis among individuals with IMIDs to determine the relationship with incident adverse cardiovascular outcomes. This study evaluated 909 patients with IMIDs, including 558 (61.4%) patients with psoriatic disease, 277 (30.5%) with rheumatoid arthritis, and 111 (12.5%) with systemic lupus erythematosus, who were clinically referred for CCTA at two academic medical centres from 2006 to 2021. IMIDs were identified through ICD9/10 codes before the CCTA. CAD severity was categorized using the CAD-RADS (Coronary Artery Disease Reporting and Data System) classification: no plaque or stenosis (CAD-RADS 0), non-obstructive CAD (CAD-RADS 1–2, 1–49% stenosis), and obstructive CAD (CAD-RADS 3–5, ≥50% stenosis), as previously reported.2 Baseline prescription anti-inflammatory therapies were identified when present at the time of CCTA. Coronary inflammation was measured using the perivascular FAI Score, an established quantitative metric of coronary inflammation (adjusted for age, sex, and technical parameters)1 in each major coronary artery and averaged to create a single FAI Score per scan. FAI Score was measured using CaRi-Research and a fully automated, unsupervised deep learning model. The primary outcome was a composite of all-cause death, non-fatal myocardial infarction, or hospitalization for heart failure. The secondary outcome was a composite of all-cause death, non-fatal myocardial infarction, or non-fatal stroke. Time-to-first-event analyses were performed with the use of Kaplan–Meier curves and hazard ratios with 95% confidence intervals were calculated with the use of a Cox proportional-hazards model comparing patients with low (1st-74th percentile) vs. high (75th-100th percentile) FAI Scores and adjusted for traditional cardiovascular risk factors (hypertension, hyperlipidemia, diabetes mellitus, current smoking status) and CAD severity. This retrospective study was approved by MGB IRB (Mass General Brigham Institutional Review Boards), and informed written consent was waived. The investigation conformed to the principles outlined in the Declaration of Helsinki.