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.

The locally adapted workflow for the identification of high-risk atherosclerotic plaques that may cause Acute Coronary Syndrome (ACS) based on the integration of CCT and CFD is carried out systematically. These are the steps in the presented methodology, namely, the patient cohort, imaging, data handling and analysis, CFD simulation, and clinical implementation.

Firstly, select patients based on symptoms of coronary artery disease (CAD), high-risk factors (e.g., family history, hypertension, diabetes), or those requiring further evaluation after preliminary tests and then Preparation: Give drugs to achieve a proper rate of heartbeat. The order includes checking the patient's habits for proper hydration and contraindications to the use of contrast media. If investigators read this, then follow CCT imaging protocol. Conduct CCT with the help of a multi-detector CT scanner only. Take detailed images of the coronary arteries. Plan to administer iodinated contrast material to improve the visual display of coronary arteries. Moreover, electrocardiographic gating ensures the timely exposure of the patient's heart to radiation during the cardiac cycle to minimize motion. All the above processes have to be accomplished then the remaining work is taken care of by Mimics and Ansys Simulation software. Create reconstructions of the coronary arteries using Ansys software and out of the CCT data that was acquired. Grasp positive remodeling, low attenuation plaque, napkin ring sign, and spotty calcification in atherosclerotic plaques. Document the features that were noticed about the plaques that are in the identified places; the sizes and the shapes and the location certainly. The working process is, to a large extent, sequential. When one of them is absent the other does not work, or does not operate within the protocol, we do not discover our result. Following that, ''Cut out' the coronary artery regions of interest from the reconstructed 3D images. Develop a mesh based on the segmented coronary artery regions. This entails the segmentation of the artery into small parts that are useful in making a CFD analysis. CFD Simulation has some conditions that are important for the results of the research.

Boundary Conditions: Define physiological boundary conditions, such as blood flow rates, pressure, and velocity, based on patient-specific data.

Simulation: Configure the CFD software with the segmented geometry and boundary conditions. Run the CFD simulations to calculate hemodynamic parameters, including wall shear stress (WSS), and flow velocity profiles.

Data Analysis: Analyze the CFD results to understand the hemodynamic environment within the coronary arteries and identify regions with abnormal hemodynamic forces.

After Completing the above processes, Integrate anatomical data from CCT (plaque characteristics) with hemodynamic data from CFD (WSS). Identify high-risk plaques based on combined criteria, including anatomical vulnerability and hemodynamic stress. Then, the investigators Generate a detailed report summarizing the findings from CCT and CFD analysis. The investigators Stratify patients into different risk categories (low, moderate, high) based on the comprehensive assessment. Finally, the investigators will adjust the treatment plan based on the findings and analysis of the patient's response.

Inclusion Criteria:

• Adults aged 40-70 years.
• Presenting with symptoms of CAD (e.g., chest pain, shortness of breath) or having multiple risk factors (e.g., hypertension, diabetes, smoking).
• Able to provide informed consent.

Exclusion Criteria:

• Severe renal impairment (due to contrast media risk).
• Previous allergic reaction to iodinated contrast media.
• Pregnant or lactating women.

The study population includes patients diagnosed with atherosclerosis, identified through CT angiography (CTA). High-resolution CT scan data reconstruct patient-specific vascular geometries, focusing on regions of clinical interest, such as arterial bifurcations and stenotic segments. Key parameters include Curvature, Surface Roughness, stenosis severity and bifurcation angles, allowing for a detailed computational fluid dynamics (CFD) analysis of hemodynamic forces contributing to endothelial dysfunction and plaque progression.