Fig. 2: Paradigm shift towards individualized treatment recommendations based on artificial intelligence-supported evaluation of atherosclerotic plaque.

Conventional treatment strategies for coronary artery disease include treat to target (adjusting therapy to achieve specific goals), risk-factor-based treatment (focusing on managing overall cardiovascular risk by addressing multiple risk factors) and fire-and-forget (prescribing fixed doses of drugs without monitoring specific targets). These strategies often overlook the complexity of pathology, ignoring the benefits of individualized therapy. Artificial intelligence (AI)-supported evaluation of atherosclerotic plaque could improve patient management by revealing the extent and nature of disease-regulating coronary atherosclerosis in each patient and by informing individualized treatment recommendations based on age-adjusted and gender-adjusted coronary total plaque volume (TPV) percentiles. The percentile curves depicted are for illustrative purposes only and do not represent real data. On the basis of the Delphi consensus process conducted after the third meeting of the Quantitative Cardiovascular Imaging Study Group, the initiation of lipid-lowering medication is recommended if the presence of any coronary atherosclerotic plaque is detected, and treatment escalation to high-intensity regimens (Table 1) is advised when the 70th percentile TPV threshold is reached on coronary CT angiography.