Ascending Aortic Calcium Identifies Patients at Risk Despite Normal Myocardial Flow, Perfusion and Coronary Calcium: A 13-Site Cohort Study

Background Patients with normal perfusion, normal myocardial flow reserve (MFR) and no coronary artery calcium (CAC) on myocardial perfusion imaging are considered low risk. Yet, adverse events still occur and no routinely reported imaging marker stratifies residual risk. This study aims to determine whether fully automated ascending aortic calcification (AAC) from the attenuation correction CT stratifies risk in these patients. Methods In the multicenter REFINE-PET registry, AAC was quantified from non-contrast CT using deep learning aortic segmentation and Agatston scoring. Triple-normal was defined as stress total perfusion deficit (TPD) <5%, MFR >2 and CAC 0. The primary endpoint was cardiovascular death, myocardial infarction or heart failure admission, with heart failure admission as key secondary endpoint. Cox models were adjusted for clinical confounders. Results Of 21,923 patients, 3,580 (16.3%) were triple-normal, of whom 1,322 (36.9%) had AAC (median Agatston 65, IQR 22-212). Agreement with three blinded readers was good to excellent (Intraclass correlation coefficient 0.87-0.90). Over a median follow-up of 52 months (IQR 26-69), 194 primary events occurred. Per standard deviation, AAC was independently associated with the primary endpoint (adjusted HR 1.24, 95% CI 1.09-1.40; p<0.001), heart failure admission (adjusted HR 1.30, 95% CI 1.10-1.55; p=0.003) and all-cause mortality (adjusted HR 1.17, 95% CI 1.04-1.32; p=0.009). AAC improved model fit beyond clinical factors, MFR and TPD (p< or =0.009), with modest gains in discrimination ({Delta}C 0.007-0.009). Conclusions In patients with normal PET readouts, automated AAC was independently associated with adverse outcomes, most strongly heart failure admission, beyond clinical risk factors, perfusion and flow.