Coronary artery disease (CAD) is accountable for a substantial portion of cardiovascular morbidity and mortality worldwide. Although traditional risk prediction algorithms to determine individuals at risk of future ACS have been used, these approaches are still considered less precise for estimating individual risk, and can misclassify a large proportion of definite acute myocardial infarction (AMI) as low-risk individuals for future AMI. Moreover, current risk evaluation has focused primarily on identifying individuals with high-grade stenosis, yet, the majority of ACS tend to occur without prior high-grade coronary stenosis in the culprit event-causing plaques. Notably, in relation to gender disparity, these findings are more apparent, with prognosis appearing considerably worse for women, with greater morbidity and mortality in the post-AMI period. Although autopsy examinations and invasive modalities such as intravascular ultrasound (IVUS) have revealed characteristics of vulnerable plaque with high ACS risk, these modalities have assessed patients only after rather than before the occurrence of an ACS, which may impede on determining a cause-effect relationship.