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Imagine your body is a car, and your health is tracked by an odometer. For most of us, that odometer ticks up slowly and steadily. We might drive for 50 or 60 years before the engine starts to show significant wear and tear. But for some children, the odometer is spinning wildly out of control from the moment they are born. This is the reality of Homozygous Familial Hypercholesterolemia, or HoFH.
Atherosclerotic cardiovascular disease (ASCVD) remains the leading global cause of mortality despite major advances in acute care. Modern preventive cardiology increasingly recognizes apolipoprotein B (ApoB)–containing lipoproteins as the necessary and causal drivers of atherosclerosis.
For decades, the public has viewed heart disease as a “late-life accident”—a sudden collision of age and lifestyle that strikes in the golden years.
Cardiovascular medicine is undergoing a substantive paradigm shift, moving from a predominantly reactive, symptom-driven model toward a preventive framework grounded in early detection and individualized risk assessment. At the center of this transition is the integration of artificial intelligence (AI) with coronary computed tomography angiography (CCTA), particularly through the development of atherosclerosis imaging–quantitative computed tomography (AI-QCT).
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