Aims Coronary CT angiography (CCTA) is a first-line modality in the investigation of suspected coronary artery disease (CAD). Mapping of perivascular Fat Attenuation Index (FAI) on routine CCTA enables the non-invasive detection of coronary artery inflammation by quantifying spatial changes in perivascular fat composition. We now report the performance of a new medical device, CaRi-Heart®, which integrates standardised FAI mapping together with clinical risk factors and plaque metrics to provide individualised cardiovascular risk prediction. Methods and Results The study included 3912 consecutive patients undergoing CCTA as part of clinical care in the United States (n = 2040) and Europe (n = 1872). These cohorts were used to generate age-specific nomograms and percentile curves as reference maps for the standardised interpretation of FAI. The first output of CaRi-Heart® is the FAI-Score of each coronary artery, which provides a measure of coronary inflammation adjusted for technical, biological and anatomical characteristics. FAI-Score is then incorporated into a risk prediction algorithm together with clinical risk factors and CCTA-derived coronary plaque metrics to generate the CaRi-Heart® Risk that predicts the likelihood of a fatal cardiac event at 8 years. CaRi-Heart® Risk was trained in the US population and its performance was validated externally in the European population. It improved risk discrimination over a clinical risk factor-based model (Δ[C-statistic] of 0.085, P = 0.01 in the US Cohort and 0.149, P < 0.001 in the European cohort) and had a consistent net clinical benefit on decision curve analysis above a baseline traditional risk factor-based model across the spectrum of cardiac risk. Conclusion CaRi-Heart® reliably improves cardiovascular risk prediction by incorporating traditional cardiovascular risk factors along with comprehensive CCTA coronary plaque and perivascular adipose tissue phenotyping. This integration advances the prognostic utility of CCTA for individual patients and paves the way for its use as a screening tool among patients referred for CCTA. Translational Perspective Mapping of perivascular Fat Attenuation Index (FAI) on coronary computed tomography angiography (CCTA) enables the non-invasive detection of coronary artery inflammation by quantifying spatial changes in perivascular fat composition. We now report the performance of a new medical device, CaRi-Heart®, which integrates standardised FAI mapping together with clinical risk factors and plaque metrics to provide age-standardised reference maps and individualised cardiovascular risk prediction. This integration advances the prognostic value of CCTA and paves the way for its use as a screening tool among patients referred for CCTA.
Coronary CT angiography (CCTA) has evolved into a first-line diagnostic test for the investigation of chest pain. Despite advances toward standardizing the reporting of CCTA through the Coronary Artery Disease Reporting and Data System (or CAD-RADS) tool, the prognostic value of CCTA in the earliest stages of atherosclerosis remains limited. Translational work on the bidirectional interplay between the coronary arteries and the perivascular adipose tissue (PVAT) has highlighted PVAT as an in vivo molecular sensor of coronary inflammation. Coronary inflammation is dynamically associated with phenotypic changes in its adjacent PVAT, which can now be detected as perivascular attenuation gradients at CCTA. These gradients are captured and quantified through the fat attenuation index (FAI), a CCTA-based biomarker of coronary inflammation. FAI carries significant prognostic value in both primary and secondary prevention (patients with and without established coronary artery disease) and offers a significant improvement in cardiac risk discrimination beyond traditional risk factors, such as coronary calcium, high-risk plaque features, or the extent of coronary atherosclerosis. Thanks to its dynamic nature, FAI may be used as a marker of disease activity, with observational studies further suggesting that it tracks the response to anti-inflammatory interventions. Finally, radiotranscriptomic studies have revealed complementary radiomic patterns of PVAT, which detect more permanent adverse fibrotic and vascular PVAT remodeling, further expanding the value of PVAT phenotyping as an important readout in modern CCTA analysis.
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