An artificial intelligence algorithm demonstrated 88.76% agreement with cardiologist interpretation in detecting and semi-quantitating coronary artery calcium on non-gated, non-contrast chest CT scans.
Observational (n=527)
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No
Does an AI algorithm accurately detect and semi-quantitate coronary artery calcium on non-gated, non-contrast CT scans obtained for non-cardiac indications?
AI can accurately detect and semi-quantitate coronary artery calcium on routine non-gated, non-contrast chest CTs, identifying a significant proportion of patients with previously undiagnosed ASCVD who may benefit from preventive therapies.
INTRODUCTION: Non-gated, non-contrast computed tomography (CT) scans are commonly ordered for a variety of non-cardiac indications, but do not routinely comment on the presence of coronary artery calcium (CAC)/atherosclerotic cardiovascular disease (ASCVD) which is known to correlate with increased cardiovascular risk. Artificial intelligence (AI) algorithms can help detect and quantify CAC/ASCVD which can lead to early treatment and improved outcomes. METHODS: Using an FDA-approved algorithm (NANOX AI) to measure coronary artery calcium (CAC) on non-gated, non-contrast CT chest, 536 serial scans were evaluated in this single-center retrospective study. Scans were categorized by Agatston scores as normal-mild (<100), moderate (100-399), or severe (≥400). AI results were validated by cardiologist's overread. Patient charts were retrospectively analyzed for clinical characteristics. RESULTS: Of the 527 patients included in this analysis, a total of 258 (48.96%) had moderate-severe disease; of these, 164 patients (63.57%, p< 0.001) had no previous diagnosis of CAD. Of those with moderate-severe disease 135 of 258 (52.33% p=0.006) were not on aspirin and 96 (37.21% p=0.093) were not on statin therapy. Cardiologist interpretation demonstrated 88.76% agreement with AI classification. DISCUSSION/CONCLUSION: Machine learning utilized in CT scans obtained for non-cardiac indications can detect and semi-quantitate CAC accurately. Artificial intelligence algorithms can accurately be applied to non-gated, non-contrast CT scans to identify CAC/ASCVD allowing for early medical intervention and improved clinical outcomes.
Kerndt et al. (Tue,) conducted a observational in Coronary artery calcium (CAC) (n=527). Artificial intelligence algorithm (NANOX AI) vs. Cardiologist interpretation was evaluated on Agreement between AI classification and cardiologist interpretation for CAC severity. An artificial intelligence algorithm demonstrated 88.76% agreement with cardiologist interpretation in detecting and semi-quantitating coronary artery calcium on non-gated, non-contrast chest CT scans.