The coronary artery calcium (CAC) score, a well-validated quantitative marker, is widely recommended for coronary artery disease (CAD) screening and predicting future cardiovascular events, especially in asymptomatic individuals. In contrast, for symptomatic patients, coronary computed tomography angiography (CCTA) is the preferred diagnostic tool due to its high sensitivity and negative predictive value in detecting CAD. The increased utilization of CCTA has led to the development of the Coronary Artery Disease Reporting and Data System (CAD-RADS), which standardizes CCTA reporting and interpretations across clinicians, thereby enhancing communication and facilitating more informed patient management decisions. Furthermore, CCTA has the capability to visualize plaques surrounding luminal stenosis. Numerous studies emphasize its ability to detect vulnerable or high-risk plaques, demonstrating significant prognostic value even in subclinical atherosclerosis, which is predominantly asymptomatic. At this juncture, quantitative plaque imaging becomes vital for precisely measuring plaque volume and burden, including the assessment of high-risk plaque components, while minimizing operator variability. Although integrating this technology into clinical practice is currently challenging, the advent of artificial intelligence and future CT machine advancements are expected to enable its clinical implementation, paving the way for personalized patient care in the near future.