Association of Coronary Artery Calcium Detected by Routine Ungated CT Imaging With Cardiovascular Outcomes

Background: Coronary artery calcium (CAC) is a strong predictor of cardiovascular events across all racial and ethnic groups. CAC can be quantified on non-ECG-gated CTs performed for other reasons, allowing for opportunistic screening for subclinical atherosclerosis. Objectives: We investigated whether incidental CAC quantified on routine non-ECG-gated CTs using a deep-learning (DL) algorithm provided cardiovascular risk stratification beyond traditional risk prediction methods. Methods: Incidental CAC was quantified using a DL algorithm (DL-CAC) on non-ECG-gated chest CTs performed for routine care in all settings at a large academic medical center from 2014–2019. We measured the association between DL-CAC (0, 1–99, or ≥100) with all-cause death (primary outcome), and the secondary composite outcomes of death/myocardial infarction (MI)/stroke and death/MI/stroke/revascularization using Cox regression. We adjusted for age, sex, race, ethnicity, comorbidities, systolic blood pressure, lipid levels, smoking status, and anti-hypertensive use. Ten-year atherosclerotic cardiovascular disease risk was calculated using the pooled cohort equations. Results: Out of 5,678 adults without ASCVD (51% women, 18% Asian, 13% Hispanic/Latinx), 52% had DL-CAC>0. Those with DL-CAC≥100 had an average PCE risk of 24%, yet only 26% were on statins. After adjustment, patients with DL-CAC≥100 had increased risk of death [HR 1.51 (1.28–1.79)], death/MI/stroke [HR 1.57 (1.33–1.84)] and death/MI/stroke/revascularization [HR 1.69 (1.45–1.98)] compared with DL-CAC=0. Conclusion: Incidental CAC≥100 was associated with an increased risk of all-cause death and adverse cardiovascular outcomes, beyond traditional risk factors. DL-CAC from routine non-ECG-gated CTs identifies patients at increased cardiovascular risk and holds promise as a tool for opportunistic screening to facilitate earlier intervention.