The study investigates the use of advanced imaging techniques and computational methods to identify high-risk plaques in coronary arteries. These plaques are significant because they have the potential to cause acute coronary syndrome (ACS), a condition that includes heart attacks and unstable angina. The research focuses on integrating Coronary Computed Tomography (CCT) with Computational Fluid Dynamics (CFD) to provide detailed insights into plaque characteristics and their hemodynamic environment. The study's primary aim is to enhance the early detection and characterization of high-risk coronary plaques that could lead to ACS. By combining CCT, a non-invasive imaging technique, with CFD, which stimulates blood flow dynamics, the study seeks to: Identify High-Risk Plaques, Apply CFD to analyze the blood flow around these plaques, Improve Prediction of ACS, Inform Clinical Decision-Making. Computational fluid dynamics (CFD) analysis of CCT data can also provide a non-invasive hemodynamic assessment to identify high-risk plaques destined to cause acute coronary syndrome. Patients with adverse plaque characteristics like positive remodeling or low-attenuation plaque have a greater risk of future coronary events.